|
14927
|
671
|
3
|
2026-05-11T06:06:29.394073+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778479589394_m2.jpg...
|
iTerm2
|
screenpipe"
|
True
|
NULL
|
monitor_2
|
NULL
|
NULL
|
NULL
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NULL
|
whisper_init_state: kv cross size = 9.44 MB
whi whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-10T23:27:31.985285Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-10T23:27:41.489329Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected
2026-05-10T23:27:42.161846Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)
2026-05-10T23:27:42.163527Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-10T23:27:42.164408Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)
2026-05-10T23:27:42.164471Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-10T23:27:42.164492Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)
2026-05-10T23:27:42.881174Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)
2026-05-10T23:27:43.285854Z INFO screenpipe_audio::transcription::handle_new_transcript: device soundcore AeroClip (input) skipping duplicate transcript (entire content overlaps with previous)
2026-05-10T23:27:58.189174Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: soundcore AeroClip (input)
2026-05-10T23:27:58.190264Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)
2026-05-10T23:27:58.190299Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: soundcore AeroClip (input)
2026-05-10T23:27:58.190324Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)
2026-05-10T23:27:58.190332Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for soundcore AeroClip (input)
2026-05-10T23:27:58.203316Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for MacBook Pro Microphone (input)
2026-05-10T23:28:32.063312Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected
2026-05-10T23:28:32.531328Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)
2026-05-10T23:28:32.531913Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-10T23:28:32.531933Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)
2026-05-10T23:28:32.532003Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)
2026-05-10T23:28:32.708770Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-10T23:28:32.708807Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-10T23:51:42.401532Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: sign in for higher AI quotas + cloud sync:
screenpipe login
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T02:54:23.501609Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: get the screenpipe desktop app for the full experience
[URL_WITH_CREDENTIALS] ~/.screenpipe/data $ 2026-05-11T07:55:11.700985Z INFO screenpipe_engine::ui_recorder: UI recording session ended: 851f2de1-d8f5-4b4a-b008-420703e8e4b2
2026-05-11T07:55:11.701373Z INFO screenpipe: shutdown complete
ggml_metal_free: deallocating
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T07:55:27.408897Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)
2026-05-11T07:55:32.412685Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T08:08:48.291500Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)
2026-05-11T09:04:13.378932Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ cd ..
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ du -sh
2.9G .
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ alias sp-start
sp-start='npx screenpipe@latest record --disable-audio --ignored-windows "Boosteroid"'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-05-11T09:06:14.511481Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store
checking permissions...
screen recording: ok
microphone: ok
accessibility: ok
2026-05-11T09:06:14.591827Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-05-11T09:06:16.007353Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-05-11T09:06:16.008982Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-05-11T09:06:16.009480Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-05-11T09:06:16.029339Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true
2026-05-11T09:06:16.029396Z INFO screenpipe: meeting detector enabled — independent of transcription mode
2026-05-11T09:06:16.402389Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)
2026-05-11T09:06:16.402461Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)
2026-05-11T09:06:16.402480Z INFO screenpipe: API server listening on [IP_ADDRESS]:3030 (localhost only)
2026-05-11T09:06:16.402564Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key
2026-05-11T09:06:16.402590Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager
2026-05-11T09:06:16.405899Z INFO screenpipe_core::pipes: loaded pipe: day-recap
2026-05-11T09:06:16.406247Z INFO screenpipe_core::pipes: loaded pipe: standup-update
2026-05-11T09:06:16.406815Z INFO screenpipe_core::pipes: loaded pipe: ai-habits
2026-05-11T09:06:16.406896Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown
2026-05-11T09:06:16.406969Z INFO screenpipe_core::pipes: loaded pipe: video-export
2026-05-11T09:06:16.407056Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary
2026-0...
|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"whisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-10T23:27:31.985285Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-10T23:27:41.489329Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected\n2026-05-10T23:27:42.161846Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)\n2026-05-10T23:27:42.163527Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-10T23:27:42.164408Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)\n2026-05-10T23:27:42.164471Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-10T23:27:42.164492Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)\n2026-05-10T23:27:42.881174Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)\n2026-05-10T23:27:43.285854Z INFO screenpipe_audio::transcription::handle_new_transcript: device soundcore AeroClip (input) skipping duplicate transcript (entire content overlaps with previous)\n2026-05-10T23:27:58.189174Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: soundcore AeroClip (input)\n2026-05-10T23:27:58.190264Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-10T23:27:58.190299Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: soundcore AeroClip (input)\n2026-05-10T23:27:58.190324Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n2026-05-10T23:27:58.190332Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for soundcore AeroClip (input)\n2026-05-10T23:27:58.203316Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for MacBook Pro Microphone (input)\n2026-05-10T23:28:32.063312Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected\n2026-05-10T23:28:32.531328Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)\n2026-05-10T23:28:32.531913Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-10T23:28:32.531933Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)\n2026-05-10T23:28:32.532003Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)\n2026-05-10T23:28:32.708770Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-10T23:28:32.708807Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-10T23:51:42.401532Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T02:54:23.501609Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\n2026-05-11T07:21:22.702849Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: soundcore AeroClip (input)\n2026-05-11T07:21:22.703351Z ERROR screenpipe_audio::audio_manager::device_monitor: failed to start new default input soundcore AeroClip (input): device soundcore AeroClip (input) not found (will back off)\n2026-05-11T07:21:22.704671Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 1), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:22.704693Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] failed to start input device soundcore AeroClip (input) (attempt 1): device soundcore AeroClip (input) not found\n2026-05-11T07:21:23.587900Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for MacBook Pro Microphone (input)\n2026-05-11T07:21:24.708381Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 2), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:24.708451Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] failed to start input device soundcore AeroClip (input) (attempt 2): device soundcore AeroClip (input) not found\n2026-05-11T07:21:26.711922Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 3), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:26.712001Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] failed to start input device soundcore AeroClip (input) (attempt 3): device soundcore AeroClip (input) not found\n2026-05-11T07:21:28.723900Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 4), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:28.726974Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-11T07:21:28.727134Z INFO screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] input device restored, device=soundcore AeroClip (input)\n2026-05-11T07:21:28.972503Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n2026-05-11T07:21:28.972538Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for soundcore AeroClip (input)\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\n2026-05-11T07:54:37.325769Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T07:54:37.395897Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-11T07:54:37.716552Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for soundcore AeroClip (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-11T07:54:37.848027Z WARN screenpipe_audio::audio_manager::manager: recording for device soundcore AeroClip (input) exited with error: stream rebuild required after screen unlock for soundcore AeroClip (input) (recovery is automatic via device_monitor)\n2026-05-11T07:54:38.122040Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for soundcore AeroClip (input), cleaning up for restart\n2026-05-11T07:54:38.122133Z INFO screenpipe_audio::device::device_manager: Stopping device: soundcore AeroClip (input)\n2026-05-11T07:54:38.359253Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-11T07:54:38.359387Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: soundcore AeroClip (input)\n2026-05-11T07:54:38.359454Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-11T07:54:38.859645Z INFO screenpipe_engine::vision_manager::monitor_watcher: Monitor 2 disconnected, stopping recording\n2026-05-11T07:54:38.859753Z INFO screenpipe_engine::vision_manager::manager: Stopping vision recording for monitor 2\n2026-05-11T07:54:39.562590Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-11T07:54:43.369378Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-11T07:54:44.338317Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-11T07:54:44.740316Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: day rollover (130 -> 131), clearing cache\n2026-05-11T07:55:08.874809Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-7753641314521957899, trigger=click)\n^C2026-05-11T07:55:11.501876Z INFO screenpipe: received ctrl+c, initiating shutdown\n2026-05-11T07:55:11.502778Z INFO screenpipe_audio::device::device_manager: Stopping device: soundcore AeroClip (input)\n2026-05-11T07:55:11.502929Z INFO screenpipe_audio::device::device_manager: Stopping device: System Audio (output)\n\n2026-05-11T07:55:11.529908Z INFO screenpipe_audio::audio_manager::manager: audio manager stopped \n2026-05-11T07:55:11.530005Z INFO screenpipe: stopping UI event capture\n2026-05-11T07:55:11.530067Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker shutting down\n2026-05-11T07:55:11.530084Z INFO screenpipe_engine::meeting_detector: meeting v2: shutdown received, exiting detection loop\n2026-05-11T07:55:11.530309Z INFO screenpipe: received shutdown signal for VisionManager\n2026-05-11T07:55:11.530497Z INFO screenpipe_engine::vision_manager::manager: Shutting down VisionManager\n2026-05-11T07:55:11.530534Z INFO screenpipe_engine::vision_manager::manager: Stopping VisionManager\n2026-05-11T07:55:11.530559Z INFO screenpipe_engine::vision_manager::manager: Stopping vision recording for monitor 1\n2026-05-11T07:55:11.535166Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T07:55:11.700985Z INFO screenpipe_engine::ui_recorder: UI recording session ended: 851f2de1-d8f5-4b4a-b008-420703e8e4b2\n2026-05-11T07:55:11.701373Z INFO screenpipe: shutdown complete\nggml_metal_free: deallocating\n\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status \nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T07:55:27.408897Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\n2026-05-11T07:55:32.412685Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T08:08:48.291500Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\n2026-05-11T09:04:13.378932Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ cd ..\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ du -sh\n2.9G\u0000\u0000\u0000\t.\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ alias sp-start\nsp-start='npx screenpipe@latest record --disable-audio --ignored-windows \"Boosteroid\"'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-05-11T09:06:14.511481Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store\nchecking permissions...\n screen recording: ok\n microphone: ok\n accessibility: ok\n2026-05-11T09:06:14.591827Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-05-11T09:06:16.007353Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-05-11T09:06:16.008982Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-05-11T09:06:16.009480Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-05-11T09:06:16.029339Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true\n2026-05-11T09:06:16.029396Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-05-11T09:06:16.402389Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-05-11T09:06:16.402461Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-05-11T09:06:16.402480Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-05-11T09:06:16.402564Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-05-11T09:06:16.402590Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-05-11T09:06:16.405899Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-05-11T09:06:16.406247Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-05-11T09:06:16.406815Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-05-11T09:06:16.406896Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-05-11T09:06:16.406969Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-05-11T09:06:16.407056Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-05-11T09:06:16.407076Z INFO screenpipe_core::pipes: loaded 6 pipes from \"/Users/lukas/.screenpipe/pipes\"\n\n\n\n _ \n __________________ ___ ____ ____ (_____ ___ \n / ___/ ___/ ___/ _ \\/ _ \\/ __ \\ / __ \\/ / __ \\/ _ \\\n (__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/\n/____/\\___/_/ \\___/\\___/_/ /_/ / .___/_/ .___/\\___/ \n /_/ /_/ \n\n\n\npower AI by everything you've seen, said or heard\nopen source | runs locally | developer friendly\n\n\n┌────────────────────────┬────────────────────────────────────┐\n│ setting │ value │\n├────────────────────────┼────────────────────────────────────┤\n│ audio chunk duration │ 30 seconds │\n│ port │ 3030 │\n│ audio disabled │ false │\n│ vision disabled │ false │\n│ pause on DRM content │ false │\n│ audio engine │ Parakeet │\n│ vad engine │ Silero │\n│ data directory │ /Users/lukas/.screenpipe │\n│ debug mode │ false │\n│ telemetry │ true │\n│ use pii removal │ true │\n│ use all monitors │ true │\n│ ignored windows │ [] │\n│ included windows │ [] │\n│ cloud sync │ disabled │\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n│ retention mode │ media-only (keep transcripts) │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ soundcore AeroClip (input) │\n│ │ System Audio (output) │\n└────────────────────────┴────────────────────────────────────┘\nyou are using local processing. all your data stays on your computer.\n\nwarning: telemetry is enabled. only error-level data will be sent.\nto disable, use the --disable-telemetry flag.\n\ncheck latest changes here: https://github.com/screenpipe/screenpipe/releases\n2026-05-11T09:06:16.409138Z INFO screenpipe: starting UI event capture\n2026-05-11T09:06:16.408692Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\n2026-05-11T09:06:16.413613Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n2026-05-11T09:06:16.415157Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-05-11T09:06:16.423358Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-05-11T09:06:16.437722Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-05-11T09:06:16.437713Z INFO screenpipe_engine::ui_recorder: UI recording session started: d42b8b31-1886-4817-bb21-01c53354434e\n2026-05-11T09:06:16.437981Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-10 06:06:16.437979 UTC to 2026-05-11 06:06:16.437979 UTC)\n2026-05-11T09:06:16.438357Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-05-11T09:06:16.446170Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-05-11T09:06:16.450650Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-05-11T09:06:16.763530Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 380 frame entries, coverage from 2026-05-10 06:06:16.437979 UTC\n2026-05-11T09:06:18.890147Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-05-11T09:06:18.890201Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-05-11T09:06:18.890230Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-05-11T09:06:19.779724Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)\n2026-05-11T09:06:19.779774Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-05-11T09:06:19.779785Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)\n2026-05-11T09:06:19.779792Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)\n2026-05-11T09:06:19.779831Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-05-11T09:06:21.291749Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-11T09:06:22.220403Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 1: frame_id=14920, dur=692ms\n2026-05-11T09:06:23.611887Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-11T09:06:24.399905Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 2: frame_id=14921, dur=352ms\n2026-05-11T09:06:26.412219Z INFO screenpipe_audio::transcription::engine: whisper model available: \"/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin\"\n2026-05-11T09:06:26.412338Z INFO screenpipe_audio::transcription::whisper::model: whisper context: gpu acceleration enabled (Metal on macOS, Vulkan on Windows)\n2026-05-11T09:06:26.412358Z INFO screenpipe_audio::transcription::engine: loading whisper model with GPU acceleration...\nwhisper_init_from_file_with_params_no_state: loading model from '/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin'\nwhisper_init_with_params_no_state: use gpu = 1\nwhisper_init_with_params_no_state: flash attn = 0\nwhisper_init_with_params_no_state: gpu_device = 0\nwhisper_init_with_params_no_state: dtw = 0\nggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices\nggml_metal_library_init: using embedded metal library\n2026-05-11T09:06:28.494279Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=8847004055550803395, trigger=visual_change)","depth":4,"on_screen":true,"value":"whisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-10T23:27:31.985285Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-10T23:27:41.489329Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected\n2026-05-10T23:27:42.161846Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)\n2026-05-10T23:27:42.163527Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-10T23:27:42.164408Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)\n2026-05-10T23:27:42.164471Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-10T23:27:42.164492Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)\n2026-05-10T23:27:42.881174Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)\n2026-05-10T23:27:43.285854Z INFO screenpipe_audio::transcription::handle_new_transcript: device soundcore AeroClip (input) skipping duplicate transcript (entire content overlaps with previous)\n2026-05-10T23:27:58.189174Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: soundcore AeroClip (input)\n2026-05-10T23:27:58.190264Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-10T23:27:58.190299Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: soundcore AeroClip (input)\n2026-05-10T23:27:58.190324Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n2026-05-10T23:27:58.190332Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for soundcore AeroClip (input)\n2026-05-10T23:27:58.203316Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for MacBook Pro Microphone (input)\n2026-05-10T23:28:32.063312Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected\n2026-05-10T23:28:32.531328Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)\n2026-05-10T23:28:32.531913Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-10T23:28:32.531933Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)\n2026-05-10T23:28:32.532003Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)\n2026-05-10T23:28:32.708770Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-10T23:28:32.708807Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-10T23:51:42.401532Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T02:54:23.501609Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\n2026-05-11T07:21:22.702849Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: soundcore AeroClip (input)\n2026-05-11T07:21:22.703351Z ERROR screenpipe_audio::audio_manager::device_monitor: failed to start new default input soundcore AeroClip (input): device soundcore AeroClip (input) not found (will back off)\n2026-05-11T07:21:22.704671Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 1), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:22.704693Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] failed to start input device soundcore AeroClip (input) (attempt 1): device soundcore AeroClip (input) not found\n2026-05-11T07:21:23.587900Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for MacBook Pro Microphone (input)\n2026-05-11T07:21:24.708381Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 2), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:24.708451Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] failed to start input device soundcore AeroClip (input) (attempt 2): device soundcore AeroClip (input) not found\n2026-05-11T07:21:26.711922Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 3), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:26.712001Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] failed to start input device soundcore AeroClip (input) (attempt 3): device soundcore AeroClip (input) not found\n2026-05-11T07:21:28.723900Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 4), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:28.726974Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-11T07:21:28.727134Z INFO screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] input device restored, device=soundcore AeroClip (input)\n2026-05-11T07:21:28.972503Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n2026-05-11T07:21:28.972538Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for soundcore AeroClip (input)\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\n2026-05-11T07:54:37.325769Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T07:54:37.395897Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-11T07:54:37.716552Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for soundcore AeroClip (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-11T07:54:37.848027Z WARN screenpipe_audio::audio_manager::manager: recording for device soundcore AeroClip (input) exited with error: stream rebuild required after screen unlock for soundcore AeroClip (input) (recovery is automatic via device_monitor)\n2026-05-11T07:54:38.122040Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for soundcore AeroClip (input), cleaning up for restart\n2026-05-11T07:54:38.122133Z INFO screenpipe_audio::device::device_manager: Stopping device: soundcore AeroClip (input)\n2026-05-11T07:54:38.359253Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-11T07:54:38.359387Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: soundcore AeroClip (input)\n2026-05-11T07:54:38.359454Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-11T07:54:38.859645Z INFO screenpipe_engine::vision_manager::monitor_watcher: Monitor 2 disconnected, stopping recording\n2026-05-11T07:54:38.859753Z INFO screenpipe_engine::vision_manager::manager: Stopping vision recording for monitor 2\n2026-05-11T07:54:39.562590Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-11T07:54:43.369378Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-11T07:54:44.338317Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-11T07:54:44.740316Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: day rollover (130 -> 131), clearing cache\n2026-05-11T07:55:08.874809Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-7753641314521957899, trigger=click)\n^C2026-05-11T07:55:11.501876Z INFO screenpipe: received ctrl+c, initiating shutdown\n2026-05-11T07:55:11.502778Z INFO screenpipe_audio::device::device_manager: Stopping device: soundcore AeroClip (input)\n2026-05-11T07:55:11.502929Z INFO screenpipe_audio::device::device_manager: Stopping device: System Audio (output)\n\n2026-05-11T07:55:11.529908Z INFO screenpipe_audio::audio_manager::manager: audio manager stopped \n2026-05-11T07:55:11.530005Z INFO screenpipe: stopping UI event capture\n2026-05-11T07:55:11.530067Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker shutting down\n2026-05-11T07:55:11.530084Z INFO screenpipe_engine::meeting_detector: meeting v2: shutdown received, exiting detection loop\n2026-05-11T07:55:11.530309Z INFO screenpipe: received shutdown signal for VisionManager\n2026-05-11T07:55:11.530497Z INFO screenpipe_engine::vision_manager::manager: Shutting down VisionManager\n2026-05-11T07:55:11.530534Z INFO screenpipe_engine::vision_manager::manager: Stopping VisionManager\n2026-05-11T07:55:11.530559Z INFO screenpipe_engine::vision_manager::manager: Stopping vision recording for monitor 1\n2026-05-11T07:55:11.535166Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T07:55:11.700985Z INFO screenpipe_engine::ui_recorder: UI recording session ended: 851f2de1-d8f5-4b4a-b008-420703e8e4b2\n2026-05-11T07:55:11.701373Z INFO screenpipe: shutdown complete\nggml_metal_free: deallocating\n\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status \nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T07:55:27.408897Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\n2026-05-11T07:55:32.412685Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T08:08:48.291500Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\n2026-05-11T09:04:13.378932Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ cd ..\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ du -sh\n2.9G\u0000\u0000\u0000\t.\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ alias sp-start\nsp-start='npx screenpipe@latest record --disable-audio --ignored-windows \"Boosteroid\"'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-05-11T09:06:14.511481Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store\nchecking permissions...\n screen recording: ok\n microphone: ok\n accessibility: ok\n2026-05-11T09:06:14.591827Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-05-11T09:06:16.007353Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-05-11T09:06:16.008982Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-05-11T09:06:16.009480Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-05-11T09:06:16.029339Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true\n2026-05-11T09:06:16.029396Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-05-11T09:06:16.402389Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-05-11T09:06:16.402461Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-05-11T09:06:16.402480Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-05-11T09:06:16.402564Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-05-11T09:06:16.402590Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-05-11T09:06:16.405899Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-05-11T09:06:16.406247Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-05-11T09:06:16.406815Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-05-11T09:06:16.406896Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-05-11T09:06:16.406969Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-05-11T09:06:16.407056Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-05-11T09:06:16.407076Z INFO screenpipe_core::pipes: loaded 6 pipes from \"/Users/lukas/.screenpipe/pipes\"\n\n\n\n _ \n __________________ ___ ____ ____ (_____ ___ \n / ___/ ___/ ___/ _ \\/ _ \\/ __ \\ / __ \\/ / __ \\/ _ \\\n (__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/\n/____/\\___/_/ \\___/\\___/_/ /_/ / .___/_/ .___/\\___/ \n /_/ /_/ \n\n\n\npower AI by everything you've seen, said or heard\nopen source | runs locally | developer friendly\n\n\n┌────────────────────────┬────────────────────────────────────┐\n│ setting │ value │\n├────────────────────────┼────────────────────────────────────┤\n│ audio chunk duration │ 30 seconds │\n│ port │ 3030 │\n│ audio disabled │ false │\n│ vision disabled │ false │\n│ pause on DRM content │ false │\n│ audio engine │ Parakeet │\n│ vad engine │ Silero │\n│ data directory │ /Users/lukas/.screenpipe │\n│ debug mode │ false │\n│ telemetry │ true │\n│ use pii removal │ true │\n│ use all monitors │ true │\n│ ignored windows │ [] │\n│ included windows │ [] │\n│ cloud sync │ disabled │\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n│ retention mode │ media-only (keep transcripts) │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ soundcore AeroClip (input) │\n│ │ System Audio (output) │\n└────────────────────────┴────────────────────────────────────┘\nyou are using local processing. all your data stays on your computer.\n\nwarning: telemetry is enabled. only error-level data will be sent.\nto disable, use the --disable-telemetry flag.\n\ncheck latest changes here: https://github.com/screenpipe/screenpipe/releases\n2026-05-11T09:06:16.409138Z INFO screenpipe: starting UI event capture\n2026-05-11T09:06:16.408692Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\n2026-05-11T09:06:16.413613Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n2026-05-11T09:06:16.415157Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-05-11T09:06:16.423358Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-05-11T09:06:16.437722Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-05-11T09:06:16.437713Z INFO screenpipe_engine::ui_recorder: UI recording session started: d42b8b31-1886-4817-bb21-01c53354434e\n2026-05-11T09:06:16.437981Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-10 06:06:16.437979 UTC to 2026-05-11 06:06:16.437979 UTC)\n2026-05-11T09:06:16.438357Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-05-11T09:06:16.446170Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-05-11T09:06:16.450650Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-05-11T09:06:16.763530Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 380 frame entries, coverage from 2026-05-10 06:06:16.437979 UTC\n2026-05-11T09:06:18.890147Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-05-11T09:06:18.890201Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-05-11T09:06:18.890230Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-05-11T09:06:19.779724Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)\n2026-05-11T09:06:19.779774Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-05-11T09:06:19.779785Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)\n2026-05-11T09:06:19.779792Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)\n2026-05-11T09:06:19.779831Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-05-11T09:06:21.291749Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-11T09:06:22.220403Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 1: frame_id=14920, dur=692ms\n2026-05-11T09:06:23.611887Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-11T09:06:24.399905Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 2: frame_id=14921, dur=352ms\n2026-05-11T09:06:26.412219Z INFO screenpipe_audio::transcription::engine: whisper model available: \"/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin\"\n2026-05-11T09:06:26.412338Z INFO screenpipe_audio::transcription::whisper::model: whisper context: gpu acceleration enabled (Metal on macOS, Vulkan on Windows)\n2026-05-11T09:06:26.412358Z INFO screenpipe_audio::transcription::engine: loading whisper model with GPU acceleration...\nwhisper_init_from_file_with_params_no_state: loading model from '/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin'\nwhisper_init_with_params_no_state: use gpu = 1\nwhisper_init_with_params_no_state: flash attn = 0\nwhisper_init_with_params_no_state: gpu_device = 0\nwhisper_init_with_params_no_state: dtw = 0\nggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices\nggml_metal_library_init: using embedded metal library\n2026-05-11T09:06:28.494279Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=8847004055550803395, trigger=visual_change)","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.27027926,"top":1.0,"width":0.058843084,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.27227393,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (-zsh)","depth":2,"bounds":{"left":0.32912233,"top":1.0,"width":0.058843084,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.33111703,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.3879654,"top":1.0,"width":0.058843084,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.3899601,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.44680852,"top":1.0,"width":0.058843084,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.4488032,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.5056516,"top":1.0,"width":0.058843084,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.50764626,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.56449467,"top":1.0,"width":0.058843084,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.56648934,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.62333775,"top":1.0,"width":0.058843084,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.6253325,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.6821808,"top":1.0,"width":0.058843084,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.68417555,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.7273936,"top":1.0,"width":0.01861702,"height":-0.023144484},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"screenpipe\"","depth":1,"bounds":{"left":0.4956782,"top":1.0,"width":0.027925532,"height":-0.02394259},"on_screen":true,"role_description":"text"}]...
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7226862535680594261
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-816202915870083616
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click
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accessibility
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NULL
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whisper_init_state: kv cross size = 9.44 MB
whi whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-10T23:27:31.985285Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-10T23:27:41.489329Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected
2026-05-10T23:27:42.161846Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)
2026-05-10T23:27:42.163527Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-10T23:27:42.164408Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)
2026-05-10T23:27:42.164471Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-10T23:27:42.164492Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)
2026-05-10T23:27:42.881174Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)
2026-05-10T23:27:43.285854Z INFO screenpipe_audio::transcription::handle_new_transcript: device soundcore AeroClip (input) skipping duplicate transcript (entire content overlaps with previous)
2026-05-10T23:27:58.189174Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: soundcore AeroClip (input)
2026-05-10T23:27:58.190264Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)
2026-05-10T23:27:58.190299Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: soundcore AeroClip (input)
2026-05-10T23:27:58.190324Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)
2026-05-10T23:27:58.190332Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for soundcore AeroClip (input)
2026-05-10T23:27:58.203316Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for MacBook Pro Microphone (input)
2026-05-10T23:28:32.063312Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected
2026-05-10T23:28:32.531328Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)
2026-05-10T23:28:32.531913Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-10T23:28:32.531933Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)
2026-05-10T23:28:32.532003Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)
2026-05-10T23:28:32.708770Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-10T23:28:32.708807Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-10T23:51:42.401532Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
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whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T02:54:23.501609Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: get the screenpipe desktop app for the full experience
[URL_WITH_CREDENTIALS] ~/.screenpipe/data $ 2026-05-11T07:55:11.700985Z INFO screenpipe_engine::ui_recorder: UI recording session ended: 851f2de1-d8f5-4b4a-b008-420703e8e4b2
2026-05-11T07:55:11.701373Z INFO screenpipe: shutdown complete
ggml_metal_free: deallocating
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T07:55:27.408897Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)
2026-05-11T07:55:32.412685Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T08:08:48.291500Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)
2026-05-11T09:04:13.378932Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ cd ..
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ du -sh
2.9G .
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ alias sp-start
sp-start='npx screenpipe@latest record --disable-audio --ignored-windows "Boosteroid"'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-05-11T09:06:14.511481Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store
checking permissions...
screen recording: ok
microphone: ok
accessibility: ok
2026-05-11T09:06:14.591827Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-05-11T09:06:16.007353Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-05-11T09:06:16.008982Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-05-11T09:06:16.009480Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-05-11T09:06:16.029339Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true
2026-05-11T09:06:16.029396Z INFO screenpipe: meeting detector enabled — independent of transcription mode
2026-05-11T09:06:16.402389Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)
2026-05-11T09:06:16.402461Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)
2026-05-11T09:06:16.402480Z INFO screenpipe: API server listening on [IP_ADDRESS]:3030 (localhost only)
2026-05-11T09:06:16.402564Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key
2026-05-11T09:06:16.402590Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager
2026-05-11T09:06:16.405899Z INFO screenpipe_core::pipes: loaded pipe: day-recap
2026-05-11T09:06:16.406247Z INFO screenpipe_core::pipes: loaded pipe: standup-update
2026-05-11T09:06:16.406815Z INFO screenpipe_core::pipes: loaded pipe: ai-habits
2026-05-11T09:06:16.406896Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown
2026-05-11T09:06:16.406969Z INFO screenpipe_core::pipes: loaded pipe: video-export
2026-05-11T09:06:16.407056Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary
2026-0...
|
14925
|
NULL
|
NULL
|
NULL
|
|
14932
|
671
|
6
|
2026-05-11T06:06:34.803322+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778479594803_m2.jpg...
|
iTerm2
|
screenpipe"
|
True
|
NULL
|
monitor_2
|
NULL
|
NULL
|
NULL
|
NULL
|
whisper_init_state: kv cross size = 9.44 MB
whi whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-10T23:27:31.985285Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-10T23:27:41.489329Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected
2026-05-10T23:27:42.161846Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)
2026-05-10T23:27:42.163527Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-10T23:27:42.164408Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)
2026-05-10T23:27:42.164471Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-10T23:27:42.164492Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)
2026-05-10T23:27:42.881174Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)
2026-05-10T23:27:43.285854Z INFO screenpipe_audio::transcription::handle_new_transcript: device soundcore AeroClip (input) skipping duplicate transcript (entire content overlaps with previous)
2026-05-10T23:27:58.189174Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: soundcore AeroClip (input)
2026-05-10T23:27:58.190264Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)
2026-05-10T23:27:58.190299Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: soundcore AeroClip (input)
2026-05-10T23:27:58.190324Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)
2026-05-10T23:27:58.190332Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for soundcore AeroClip (input)
2026-05-10T23:27:58.203316Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for MacBook Pro Microphone (input)
2026-05-10T23:28:32.063312Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected
2026-05-10T23:28:32.531328Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)
2026-05-10T23:28:32.531913Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-10T23:28:32.531933Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)
2026-05-10T23:28:32.532003Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)
2026-05-10T23:28:32.708770Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-10T23:28:32.708807Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-10T23:51:42.401532Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: sign in for higher AI quotas + cloud sync:
screenpipe login
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T02:54:23.501609Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: get the screenpipe desktop app for the full experience
[URL_WITH_CREDENTIALS] ~/.screenpipe/data $ 2026-05-11T07:55:11.700985Z INFO screenpipe_engine::ui_recorder: UI recording session ended: 851f2de1-d8f5-4b4a-b008-420703e8e4b2
2026-05-11T07:55:11.701373Z INFO screenpipe: shutdown complete
ggml_metal_free: deallocating
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T07:55:27.408897Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)
2026-05-11T07:55:32.412685Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T08:08:48.291500Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)
2026-05-11T09:04:13.378932Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ cd ..
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ du -sh
2.9G .
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ alias sp-start
sp-start='npx screenpipe@latest record --disable-audio --ignored-windows "Boosteroid"'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-05-11T09:06:14.511481Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store
checking permissions...
screen recording: ok
microphone: ok
accessibility: ok
2026-05-11T09:06:14.591827Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-05-11T09:06:16.007353Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-05-11T09:06:16.008982Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-05-11T09:06:16.009480Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-05-11T09:06:16.029339Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true
2026-05-11T09:06:16.029396Z INFO screenpipe: meeting detector enabled — independent of transcription mode
2026-05-11T09:06:16.402389Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)
2026-05-11T09:06:16.402461Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)
2026-05-11T09:06:16.402480Z INFO screenpipe: API server listening on [IP_ADDRESS]:3030 (localhost only)
2026-05-11T09:06:16.402564Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key
2026-05-11T09:06:16.402590Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager
2026-05-11T09:06:16.405899Z INFO screenpipe_core::pipes: loaded pipe: day-recap
2026-05-11T09:06:16.406247Z INFO screenpipe_core::pipes: loaded pipe: standup-update
2026-05-11T09:06:16.406815Z INFO screenpipe_core::pipes: loaded pipe: ai-habits
2026-05-11T09:06:16.406896Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown
2026-05-11T09:06:16.406969Z INFO screenpipe_core::pipes: loaded pipe: video-export
2026-05-11T09:06:16.407056Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary
2026-0...
|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"whisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-10T23:27:31.985285Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-10T23:27:41.489329Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected\n2026-05-10T23:27:42.161846Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)\n2026-05-10T23:27:42.163527Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-10T23:27:42.164408Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)\n2026-05-10T23:27:42.164471Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-10T23:27:42.164492Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)\n2026-05-10T23:27:42.881174Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)\n2026-05-10T23:27:43.285854Z INFO screenpipe_audio::transcription::handle_new_transcript: device soundcore AeroClip (input) skipping duplicate transcript (entire content overlaps with previous)\n2026-05-10T23:27:58.189174Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: soundcore AeroClip (input)\n2026-05-10T23:27:58.190264Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-10T23:27:58.190299Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: soundcore AeroClip (input)\n2026-05-10T23:27:58.190324Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n2026-05-10T23:27:58.190332Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for soundcore AeroClip (input)\n2026-05-10T23:27:58.203316Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for MacBook Pro Microphone (input)\n2026-05-10T23:28:32.063312Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected\n2026-05-10T23:28:32.531328Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)\n2026-05-10T23:28:32.531913Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-10T23:28:32.531933Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)\n2026-05-10T23:28:32.532003Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)\n2026-05-10T23:28:32.708770Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-10T23:28:32.708807Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-10T23:51:42.401532Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T02:54:23.501609Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\n2026-05-11T07:21:22.702849Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: soundcore AeroClip (input)\n2026-05-11T07:21:22.703351Z ERROR screenpipe_audio::audio_manager::device_monitor: failed to start new default input soundcore AeroClip (input): device soundcore AeroClip (input) not found (will back off)\n2026-05-11T07:21:22.704671Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 1), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:22.704693Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] failed to start input device soundcore AeroClip (input) (attempt 1): device soundcore AeroClip (input) not found\n2026-05-11T07:21:23.587900Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for MacBook Pro Microphone (input)\n2026-05-11T07:21:24.708381Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 2), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:24.708451Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] failed to start input device soundcore AeroClip (input) (attempt 2): device soundcore AeroClip (input) not found\n2026-05-11T07:21:26.711922Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 3), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:26.712001Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] failed to start input device soundcore AeroClip (input) (attempt 3): device soundcore AeroClip (input) not found\n2026-05-11T07:21:28.723900Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 4), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:28.726974Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-11T07:21:28.727134Z INFO screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] input device restored, device=soundcore AeroClip (input)\n2026-05-11T07:21:28.972503Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n2026-05-11T07:21:28.972538Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for soundcore AeroClip (input)\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\n2026-05-11T07:54:37.325769Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T07:54:37.395897Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-11T07:54:37.716552Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for soundcore AeroClip (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-11T07:54:37.848027Z WARN screenpipe_audio::audio_manager::manager: recording for device soundcore AeroClip (input) exited with error: stream rebuild required after screen unlock for soundcore AeroClip (input) (recovery is automatic via device_monitor)\n2026-05-11T07:54:38.122040Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for soundcore AeroClip (input), cleaning up for restart\n2026-05-11T07:54:38.122133Z INFO screenpipe_audio::device::device_manager: Stopping device: soundcore AeroClip (input)\n2026-05-11T07:54:38.359253Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-11T07:54:38.359387Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: soundcore AeroClip (input)\n2026-05-11T07:54:38.359454Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-11T07:54:38.859645Z INFO screenpipe_engine::vision_manager::monitor_watcher: Monitor 2 disconnected, stopping recording\n2026-05-11T07:54:38.859753Z INFO screenpipe_engine::vision_manager::manager: Stopping vision recording for monitor 2\n2026-05-11T07:54:39.562590Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-11T07:54:43.369378Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-11T07:54:44.338317Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-11T07:54:44.740316Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: day rollover (130 -> 131), clearing cache\n2026-05-11T07:55:08.874809Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-7753641314521957899, trigger=click)\n^C2026-05-11T07:55:11.501876Z INFO screenpipe: received ctrl+c, initiating shutdown\n2026-05-11T07:55:11.502778Z INFO screenpipe_audio::device::device_manager: Stopping device: soundcore AeroClip (input)\n2026-05-11T07:55:11.502929Z INFO screenpipe_audio::device::device_manager: Stopping device: System Audio (output)\n\n2026-05-11T07:55:11.529908Z INFO screenpipe_audio::audio_manager::manager: audio manager stopped \n2026-05-11T07:55:11.530005Z INFO screenpipe: stopping UI event capture\n2026-05-11T07:55:11.530067Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker shutting down\n2026-05-11T07:55:11.530084Z INFO screenpipe_engine::meeting_detector: meeting v2: shutdown received, exiting detection loop\n2026-05-11T07:55:11.530309Z INFO screenpipe: received shutdown signal for VisionManager\n2026-05-11T07:55:11.530497Z INFO screenpipe_engine::vision_manager::manager: Shutting down VisionManager\n2026-05-11T07:55:11.530534Z INFO screenpipe_engine::vision_manager::manager: Stopping VisionManager\n2026-05-11T07:55:11.530559Z INFO screenpipe_engine::vision_manager::manager: Stopping vision recording for monitor 1\n2026-05-11T07:55:11.535166Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T07:55:11.700985Z INFO screenpipe_engine::ui_recorder: UI recording session ended: 851f2de1-d8f5-4b4a-b008-420703e8e4b2\n2026-05-11T07:55:11.701373Z INFO screenpipe: shutdown complete\nggml_metal_free: deallocating\n\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status \nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T07:55:27.408897Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\n2026-05-11T07:55:32.412685Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T08:08:48.291500Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\n2026-05-11T09:04:13.378932Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ cd ..\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ du -sh\n2.9G\u0000\u0000\u0000\t.\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ alias sp-start\nsp-start='npx screenpipe@latest record --disable-audio --ignored-windows \"Boosteroid\"'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-05-11T09:06:14.511481Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store\nchecking permissions...\n screen recording: ok\n microphone: ok\n accessibility: ok\n2026-05-11T09:06:14.591827Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-05-11T09:06:16.007353Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-05-11T09:06:16.008982Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-05-11T09:06:16.009480Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-05-11T09:06:16.029339Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true\n2026-05-11T09:06:16.029396Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-05-11T09:06:16.402389Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-05-11T09:06:16.402461Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-05-11T09:06:16.402480Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-05-11T09:06:16.402564Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-05-11T09:06:16.402590Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-05-11T09:06:16.405899Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-05-11T09:06:16.406247Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-05-11T09:06:16.406815Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-05-11T09:06:16.406896Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-05-11T09:06:16.406969Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-05-11T09:06:16.407056Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-05-11T09:06:16.407076Z INFO screenpipe_core::pipes: loaded 6 pipes from \"/Users/lukas/.screenpipe/pipes\"\n\n\n\n _ \n __________________ ___ ____ ____ (_____ ___ \n / ___/ ___/ ___/ _ \\/ _ \\/ __ \\ / __ \\/ / __ \\/ _ \\\n (__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/\n/____/\\___/_/ \\___/\\___/_/ /_/ / .___/_/ .___/\\___/ \n /_/ /_/ \n\n\n\npower AI by everything you've seen, said or heard\nopen source | runs locally | developer friendly\n\n\n┌────────────────────────┬────────────────────────────────────┐\n│ setting │ value │\n├────────────────────────┼────────────────────────────────────┤\n│ audio chunk duration │ 30 seconds │\n│ port │ 3030 │\n│ audio disabled │ false │\n│ vision disabled │ false │\n│ pause on DRM content │ false │\n│ audio engine │ Parakeet │\n│ vad engine │ Silero │\n│ data directory │ /Users/lukas/.screenpipe │\n│ debug mode │ false │\n│ telemetry │ true │\n│ use pii removal │ true │\n│ use all monitors │ true │\n│ ignored windows │ [] │\n│ included windows │ [] │\n│ cloud sync │ disabled │\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n│ retention mode │ media-only (keep transcripts) │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ soundcore AeroClip (input) │\n│ │ System Audio (output) │\n└────────────────────────┴────────────────────────────────────┘\nyou are using local processing. all your data stays on your computer.\n\nwarning: telemetry is enabled. only error-level data will be sent.\nto disable, use the --disable-telemetry flag.\n\ncheck latest changes here: https://github.com/screenpipe/screenpipe/releases\n2026-05-11T09:06:16.409138Z INFO screenpipe: starting UI event capture\n2026-05-11T09:06:16.408692Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\n2026-05-11T09:06:16.413613Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n2026-05-11T09:06:16.415157Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-05-11T09:06:16.423358Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-05-11T09:06:16.437722Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-05-11T09:06:16.437713Z INFO screenpipe_engine::ui_recorder: UI recording session started: d42b8b31-1886-4817-bb21-01c53354434e\n2026-05-11T09:06:16.437981Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-10 06:06:16.437979 UTC to 2026-05-11 06:06:16.437979 UTC)\n2026-05-11T09:06:16.438357Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-05-11T09:06:16.446170Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-05-11T09:06:16.450650Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-05-11T09:06:16.763530Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 380 frame entries, coverage from 2026-05-10 06:06:16.437979 UTC\n2026-05-11T09:06:18.890147Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-05-11T09:06:18.890201Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-05-11T09:06:18.890230Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-05-11T09:06:19.779724Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)\n2026-05-11T09:06:19.779774Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-05-11T09:06:19.779785Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)\n2026-05-11T09:06:19.779792Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)\n2026-05-11T09:06:19.779831Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-05-11T09:06:21.291749Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-11T09:06:22.220403Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 1: frame_id=14920, dur=692ms\n2026-05-11T09:06:23.611887Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-11T09:06:24.399905Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 2: frame_id=14921, dur=352ms\n2026-05-11T09:06:26.412219Z INFO screenpipe_audio::transcription::engine: whisper model available: \"/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin\"\n2026-05-11T09:06:26.412338Z INFO screenpipe_audio::transcription::whisper::model: whisper context: gpu acceleration enabled (Metal on macOS, Vulkan on Windows)\n2026-05-11T09:06:26.412358Z INFO screenpipe_audio::transcription::engine: loading whisper model with GPU acceleration...\nwhisper_init_from_file_with_params_no_state: loading model from '/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin'\nwhisper_init_with_params_no_state: use gpu = 1\nwhisper_init_with_params_no_state: flash attn = 0\nwhisper_init_with_params_no_state: gpu_device = 0\nwhisper_init_with_params_no_state: dtw = 0\nggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices\nggml_metal_library_init: using embedded metal library\n2026-05-11T09:06:28.494279Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=8847004055550803395, trigger=visual_change)","depth":4,"on_screen":true,"value":"whisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-10T23:27:31.985285Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-10T23:27:41.489329Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected\n2026-05-10T23:27:42.161846Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)\n2026-05-10T23:27:42.163527Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-10T23:27:42.164408Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)\n2026-05-10T23:27:42.164471Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-10T23:27:42.164492Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)\n2026-05-10T23:27:42.881174Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)\n2026-05-10T23:27:43.285854Z INFO screenpipe_audio::transcription::handle_new_transcript: device soundcore AeroClip (input) skipping duplicate transcript (entire content overlaps with previous)\n2026-05-10T23:27:58.189174Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: soundcore AeroClip (input)\n2026-05-10T23:27:58.190264Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-10T23:27:58.190299Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: soundcore AeroClip (input)\n2026-05-10T23:27:58.190324Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n2026-05-10T23:27:58.190332Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for soundcore AeroClip (input)\n2026-05-10T23:27:58.203316Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for MacBook Pro Microphone (input)\n2026-05-10T23:28:32.063312Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected\n2026-05-10T23:28:32.531328Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)\n2026-05-10T23:28:32.531913Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-10T23:28:32.531933Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)\n2026-05-10T23:28:32.532003Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)\n2026-05-10T23:28:32.708770Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-10T23:28:32.708807Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-10T23:51:42.401532Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T02:54:23.501609Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\n2026-05-11T07:21:22.702849Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: soundcore AeroClip (input)\n2026-05-11T07:21:22.703351Z ERROR screenpipe_audio::audio_manager::device_monitor: failed to start new default input soundcore AeroClip (input): device soundcore AeroClip (input) not found (will back off)\n2026-05-11T07:21:22.704671Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 1), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:22.704693Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] failed to start input device soundcore AeroClip (input) (attempt 1): device soundcore AeroClip (input) not found\n2026-05-11T07:21:23.587900Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for MacBook Pro Microphone (input)\n2026-05-11T07:21:24.708381Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 2), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:24.708451Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] failed to start input device soundcore AeroClip (input) (attempt 2): device soundcore AeroClip (input) not found\n2026-05-11T07:21:26.711922Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 3), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:26.712001Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] failed to start input device soundcore AeroClip (input) (attempt 3): device soundcore AeroClip (input) not found\n2026-05-11T07:21:28.723900Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 4), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:28.726974Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-11T07:21:28.727134Z INFO screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] input device restored, device=soundcore AeroClip (input)\n2026-05-11T07:21:28.972503Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n2026-05-11T07:21:28.972538Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for soundcore AeroClip (input)\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\n2026-05-11T07:54:37.325769Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T07:54:37.395897Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-11T07:54:37.716552Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for soundcore AeroClip (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-11T07:54:37.848027Z WARN screenpipe_audio::audio_manager::manager: recording for device soundcore AeroClip (input) exited with error: stream rebuild required after screen unlock for soundcore AeroClip (input) (recovery is automatic via device_monitor)\n2026-05-11T07:54:38.122040Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for soundcore AeroClip (input), cleaning up for restart\n2026-05-11T07:54:38.122133Z INFO screenpipe_audio::device::device_manager: Stopping device: soundcore AeroClip (input)\n2026-05-11T07:54:38.359253Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-11T07:54:38.359387Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: soundcore AeroClip (input)\n2026-05-11T07:54:38.359454Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-11T07:54:38.859645Z INFO screenpipe_engine::vision_manager::monitor_watcher: Monitor 2 disconnected, stopping recording\n2026-05-11T07:54:38.859753Z INFO screenpipe_engine::vision_manager::manager: Stopping vision recording for monitor 2\n2026-05-11T07:54:39.562590Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-11T07:54:43.369378Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-11T07:54:44.338317Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-11T07:54:44.740316Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: day rollover (130 -> 131), clearing cache\n2026-05-11T07:55:08.874809Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-7753641314521957899, trigger=click)\n^C2026-05-11T07:55:11.501876Z INFO screenpipe: received ctrl+c, initiating shutdown\n2026-05-11T07:55:11.502778Z INFO screenpipe_audio::device::device_manager: Stopping device: soundcore AeroClip (input)\n2026-05-11T07:55:11.502929Z INFO screenpipe_audio::device::device_manager: Stopping device: System Audio (output)\n\n2026-05-11T07:55:11.529908Z INFO screenpipe_audio::audio_manager::manager: audio manager stopped \n2026-05-11T07:55:11.530005Z INFO screenpipe: stopping UI event capture\n2026-05-11T07:55:11.530067Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker shutting down\n2026-05-11T07:55:11.530084Z INFO screenpipe_engine::meeting_detector: meeting v2: shutdown received, exiting detection loop\n2026-05-11T07:55:11.530309Z INFO screenpipe: received shutdown signal for VisionManager\n2026-05-11T07:55:11.530497Z INFO screenpipe_engine::vision_manager::manager: Shutting down VisionManager\n2026-05-11T07:55:11.530534Z INFO screenpipe_engine::vision_manager::manager: Stopping VisionManager\n2026-05-11T07:55:11.530559Z INFO screenpipe_engine::vision_manager::manager: Stopping vision recording for monitor 1\n2026-05-11T07:55:11.535166Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T07:55:11.700985Z INFO screenpipe_engine::ui_recorder: UI recording session ended: 851f2de1-d8f5-4b4a-b008-420703e8e4b2\n2026-05-11T07:55:11.701373Z INFO screenpipe: shutdown complete\nggml_metal_free: deallocating\n\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status \nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T07:55:27.408897Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\n2026-05-11T07:55:32.412685Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T08:08:48.291500Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\n2026-05-11T09:04:13.378932Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ cd ..\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ du -sh\n2.9G\u0000\u0000\u0000\t.\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ alias sp-start\nsp-start='npx screenpipe@latest record --disable-audio --ignored-windows \"Boosteroid\"'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-05-11T09:06:14.511481Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store\nchecking permissions...\n screen recording: ok\n microphone: ok\n accessibility: ok\n2026-05-11T09:06:14.591827Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-05-11T09:06:16.007353Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-05-11T09:06:16.008982Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-05-11T09:06:16.009480Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-05-11T09:06:16.029339Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true\n2026-05-11T09:06:16.029396Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-05-11T09:06:16.402389Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-05-11T09:06:16.402461Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-05-11T09:06:16.402480Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-05-11T09:06:16.402564Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-05-11T09:06:16.402590Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-05-11T09:06:16.405899Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-05-11T09:06:16.406247Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-05-11T09:06:16.406815Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-05-11T09:06:16.406896Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-05-11T09:06:16.406969Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-05-11T09:06:16.407056Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-05-11T09:06:16.407076Z INFO screenpipe_core::pipes: loaded 6 pipes from \"/Users/lukas/.screenpipe/pipes\"\n\n\n\n _ \n __________________ ___ ____ ____ (_____ ___ \n / ___/ ___/ ___/ _ \\/ _ \\/ __ \\ / __ \\/ / __ \\/ _ \\\n (__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/\n/____/\\___/_/ \\___/\\___/_/ /_/ / .___/_/ .___/\\___/ \n /_/ /_/ \n\n\n\npower AI by everything you've seen, said or heard\nopen source | runs locally | developer friendly\n\n\n┌────────────────────────┬────────────────────────────────────┐\n│ setting │ value │\n├────────────────────────┼────────────────────────────────────┤\n│ audio chunk duration │ 30 seconds │\n│ port │ 3030 │\n│ audio disabled │ false │\n│ vision disabled │ false │\n│ pause on DRM content │ false │\n│ audio engine │ Parakeet │\n│ vad engine │ Silero │\n│ data directory │ /Users/lukas/.screenpipe │\n│ debug mode │ false │\n│ telemetry │ true │\n│ use pii removal │ true │\n│ use all monitors │ true │\n│ ignored windows │ [] │\n│ included windows │ [] │\n│ cloud sync │ disabled │\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n│ retention mode │ media-only (keep transcripts) │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ soundcore AeroClip (input) │\n│ │ System Audio (output) │\n└────────────────────────┴────────────────────────────────────┘\nyou are using local processing. all your data stays on your computer.\n\nwarning: telemetry is enabled. only error-level data will be sent.\nto disable, use the --disable-telemetry flag.\n\ncheck latest changes here: https://github.com/screenpipe/screenpipe/releases\n2026-05-11T09:06:16.409138Z INFO screenpipe: starting UI event capture\n2026-05-11T09:06:16.408692Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\n2026-05-11T09:06:16.413613Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n2026-05-11T09:06:16.415157Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-05-11T09:06:16.423358Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-05-11T09:06:16.437722Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-05-11T09:06:16.437713Z INFO screenpipe_engine::ui_recorder: UI recording session started: d42b8b31-1886-4817-bb21-01c53354434e\n2026-05-11T09:06:16.437981Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-10 06:06:16.437979 UTC to 2026-05-11 06:06:16.437979 UTC)\n2026-05-11T09:06:16.438357Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-05-11T09:06:16.446170Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-05-11T09:06:16.450650Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-05-11T09:06:16.763530Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 380 frame entries, coverage from 2026-05-10 06:06:16.437979 UTC\n2026-05-11T09:06:18.890147Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-05-11T09:06:18.890201Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-05-11T09:06:18.890230Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-05-11T09:06:19.779724Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)\n2026-05-11T09:06:19.779774Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-05-11T09:06:19.779785Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)\n2026-05-11T09:06:19.779792Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)\n2026-05-11T09:06:19.779831Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-05-11T09:06:21.291749Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-11T09:06:22.220403Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 1: frame_id=14920, dur=692ms\n2026-05-11T09:06:23.611887Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-11T09:06:24.399905Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 2: frame_id=14921, dur=352ms\n2026-05-11T09:06:26.412219Z INFO screenpipe_audio::transcription::engine: whisper model available: \"/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin\"\n2026-05-11T09:06:26.412338Z INFO screenpipe_audio::transcription::whisper::model: whisper context: gpu acceleration enabled (Metal on macOS, Vulkan on Windows)\n2026-05-11T09:06:26.412358Z INFO screenpipe_audio::transcription::engine: loading whisper model with GPU acceleration...\nwhisper_init_from_file_with_params_no_state: loading model from '/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin'\nwhisper_init_with_params_no_state: use gpu = 1\nwhisper_init_with_params_no_state: flash attn = 0\nwhisper_init_with_params_no_state: gpu_device = 0\nwhisper_init_with_params_no_state: dtw = 0\nggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices\nggml_metal_library_init: using embedded metal library\n2026-05-11T09:06:28.494279Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=8847004055550803395, trigger=visual_change)","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.27027926,"top":1.0,"width":0.058843084,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.27227393,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (-zsh)","depth":2,"bounds":{"left":0.32912233,"top":1.0,"width":0.058843084,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.33111703,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.3879654,"top":1.0,"width":0.058843084,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.3899601,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.44680852,"top":1.0,"width":0.058843084,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.4488032,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.5056516,"top":1.0,"width":0.058843084,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.50764626,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.56449467,"top":1.0,"width":0.058843084,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.56648934,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.62333775,"top":1.0,"width":0.058843084,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.6253325,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.6821808,"top":1.0,"width":0.058843084,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.68417555,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.7273936,"top":1.0,"width":0.01861702,"height":-0.023144484},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"screenpipe\"","depth":1,"bounds":{"left":0.4956782,"top":1.0,"width":0.027925532,"height":-0.02394259},"on_screen":true,"role_description":"text"}]...
|
7226862535680594261
|
-816202915870083616
|
click
|
accessibility
|
NULL
|
whisper_init_state: kv cross size = 9.44 MB
whi whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-10T23:27:31.985285Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-10T23:27:41.489329Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected
2026-05-10T23:27:42.161846Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)
2026-05-10T23:27:42.163527Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-10T23:27:42.164408Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)
2026-05-10T23:27:42.164471Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-10T23:27:42.164492Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)
2026-05-10T23:27:42.881174Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)
2026-05-10T23:27:43.285854Z INFO screenpipe_audio::transcription::handle_new_transcript: device soundcore AeroClip (input) skipping duplicate transcript (entire content overlaps with previous)
2026-05-10T23:27:58.189174Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: soundcore AeroClip (input)
2026-05-10T23:27:58.190264Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)
2026-05-10T23:27:58.190299Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: soundcore AeroClip (input)
2026-05-10T23:27:58.190324Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)
2026-05-10T23:27:58.190332Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for soundcore AeroClip (input)
2026-05-10T23:27:58.203316Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for MacBook Pro Microphone (input)
2026-05-10T23:28:32.063312Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected
2026-05-10T23:28:32.531328Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)
2026-05-10T23:28:32.531913Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-10T23:28:32.531933Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)
2026-05-10T23:28:32.532003Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)
2026-05-10T23:28:32.708770Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-10T23:28:32.708807Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-10T23:51:42.401532Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: sign in for higher AI quotas + cloud sync:
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whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T02:54:23.501609Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: get the screenpipe desktop app for the full experience
[URL_WITH_CREDENTIALS] ~/.screenpipe/data $ 2026-05-11T07:55:11.700985Z INFO screenpipe_engine::ui_recorder: UI recording session ended: 851f2de1-d8f5-4b4a-b008-420703e8e4b2
2026-05-11T07:55:11.701373Z INFO screenpipe: shutdown complete
ggml_metal_free: deallocating
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T07:55:27.408897Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)
2026-05-11T07:55:32.412685Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T08:08:48.291500Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)
2026-05-11T09:04:13.378932Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ cd ..
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ du -sh
2.9G .
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ alias sp-start
sp-start='npx screenpipe@latest record --disable-audio --ignored-windows "Boosteroid"'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-05-11T09:06:14.511481Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store
checking permissions...
screen recording: ok
microphone: ok
accessibility: ok
2026-05-11T09:06:14.591827Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-05-11T09:06:16.007353Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-05-11T09:06:16.008982Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-05-11T09:06:16.009480Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-05-11T09:06:16.029339Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true
2026-05-11T09:06:16.029396Z INFO screenpipe: meeting detector enabled — independent of transcription mode
2026-05-11T09:06:16.402389Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)
2026-05-11T09:06:16.402461Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)
2026-05-11T09:06:16.402480Z INFO screenpipe: API server listening on [IP_ADDRESS]:3030 (localhost only)
2026-05-11T09:06:16.402564Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key
2026-05-11T09:06:16.402590Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager
2026-05-11T09:06:16.405899Z INFO screenpipe_core::pipes: loaded pipe: day-recap
2026-05-11T09:06:16.406247Z INFO screenpipe_core::pipes: loaded pipe: standup-update
2026-05-11T09:06:16.406815Z INFO screenpipe_core::pipes: loaded pipe: ai-habits
2026-05-11T09:06:16.406896Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown
2026-05-11T09:06:16.406969Z INFO screenpipe_core::pipes: loaded pipe: video-export
2026-05-11T09:06:16.407056Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary
2026-0...
|
NULL
|
NULL
|
NULL
|
NULL
|
|
14939
|
670
|
10
|
2026-05-11T06:06:43.375835+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778479603375_m1.jpg...
|
iTerm2
|
screenpipe"
|
True
|
NULL
|
monitor_1
|
NULL
|
NULL
|
NULL
|
NULL
|
whisper_init_state: compute buffer (cross) = 8 whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-10T23:27:31.985285Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-10T23:27:41.489329Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected
2026-05-10T23:27:42.161846Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)
2026-05-10T23:27:42.163527Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-10T23:27:42.164408Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)
2026-05-10T23:27:42.164471Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-10T23:27:42.164492Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)
2026-05-10T23:27:42.881174Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)
2026-05-10T23:27:43.285854Z INFO screenpipe_audio::transcription::handle_new_transcript: device soundcore AeroClip (input) skipping duplicate transcript (entire content overlaps with previous)
2026-05-10T23:27:58.189174Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: soundcore AeroClip (input)
2026-05-10T23:27:58.190264Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)
2026-05-10T23:27:58.190299Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: soundcore AeroClip (input)
2026-05-10T23:27:58.190324Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)
2026-05-10T23:27:58.190332Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for soundcore AeroClip (input)
2026-05-10T23:27:58.203316Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for MacBook Pro Microphone (input)
2026-05-10T23:28:32.063312Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected
2026-05-10T23:28:32.531328Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)
2026-05-10T23:28:32.531913Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-10T23:28:32.531933Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)
2026-05-10T23:28:32.532003Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)
2026-05-10T23:28:32.708770Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-10T23:28:32.708807Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-10T23:51:42.401532Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
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whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T02:54:23.501609Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: get the screenpipe desktop app for the full experience
[URL_WITH_CREDENTIALS] ~/.screenpipe/data $ 2026-05-11T07:55:11.700985Z INFO screenpipe_engine::ui_recorder: UI recording session ended: 851f2de1-d8f5-4b4a-b008-420703e8e4b2
2026-05-11T07:55:11.701373Z INFO screenpipe: shutdown complete
ggml_metal_free: deallocating
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T07:55:27.408897Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)
2026-05-11T07:55:32.412685Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T08:08:48.291500Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)
2026-05-11T09:04:13.378932Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ cd ..
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ du -sh
2.9G .
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ alias sp-start
sp-start='npx screenpipe@latest record --disable-audio --ignored-windows "Boosteroid"'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-05-11T09:06:14.511481Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store
checking permissions...
screen recording: ok
microphone: ok
accessibility: ok
2026-05-11T09:06:14.591827Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-05-11T09:06:16.007353Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-05-11T09:06:16.008982Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-05-11T09:06:16.009480Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-05-11T09:06:16.029339Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true
2026-05-11T09:06:16.029396Z INFO screenpipe: meeting detector enabled — independent of transcription mode
2026-05-11T09:06:16.402389Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)
2026-05-11T09:06:16.402461Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)
2026-05-11T09:06:16.402480Z INFO screenpipe: API server listening on [IP_ADDRESS]:3030 (localhost only)
2026-05-11T09:06:16.402564Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key
2026-05-11T09:06:16.402590Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager
2026-05-11T09:06:16.405899Z INFO screenpipe_core::pipes: loaded pipe: day-recap
2026-05-11T09:06:16.406247Z INFO screenpipe_core::pipes: loaded pipe: standup-update
2026-05-11T09:06:16.406815Z INFO screenpipe_core::pipes: loaded pipe: ai-habits
2026-05-11T09:06:16.406896Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown
2026-05-11T09:06:16.406969Z INFO screenpipe_core::pipes: loaded pipe: video-export
2026-05-11T09:06:16.407056Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary
2026-05-11T09:06:16.407076Z INFO screenpipe_core::pipes: loaded 6 pipes from "/Users/lukas/.screenpipe/pipes"
_
__________________ ___ ____ ____ (...
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[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"whisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-10T23:27:31.985285Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-10T23:27:41.489329Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected\n2026-05-10T23:27:42.161846Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)\n2026-05-10T23:27:42.163527Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-10T23:27:42.164408Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)\n2026-05-10T23:27:42.164471Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-10T23:27:42.164492Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)\n2026-05-10T23:27:42.881174Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)\n2026-05-10T23:27:43.285854Z INFO screenpipe_audio::transcription::handle_new_transcript: device soundcore AeroClip (input) skipping duplicate transcript (entire content overlaps with previous)\n2026-05-10T23:27:58.189174Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: soundcore AeroClip (input)\n2026-05-10T23:27:58.190264Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-10T23:27:58.190299Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: soundcore AeroClip (input)\n2026-05-10T23:27:58.190324Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n2026-05-10T23:27:58.190332Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for soundcore AeroClip (input)\n2026-05-10T23:27:58.203316Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for MacBook Pro Microphone (input)\n2026-05-10T23:28:32.063312Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected\n2026-05-10T23:28:32.531328Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)\n2026-05-10T23:28:32.531913Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-10T23:28:32.531933Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)\n2026-05-10T23:28:32.532003Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)\n2026-05-10T23:28:32.708770Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-10T23:28:32.708807Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-10T23:51:42.401532Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T02:54:23.501609Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\n2026-05-11T07:21:22.702849Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: soundcore AeroClip (input)\n2026-05-11T07:21:22.703351Z ERROR screenpipe_audio::audio_manager::device_monitor: failed to start new default input soundcore AeroClip (input): device soundcore AeroClip (input) not found (will back off)\n2026-05-11T07:21:22.704671Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 1), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:22.704693Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] failed to start input device soundcore AeroClip (input) (attempt 1): device soundcore AeroClip (input) not found\n2026-05-11T07:21:23.587900Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for MacBook Pro Microphone (input)\n2026-05-11T07:21:24.708381Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 2), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:24.708451Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] failed to start input device soundcore AeroClip (input) (attempt 2): device soundcore AeroClip (input) not found\n2026-05-11T07:21:26.711922Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 3), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:26.712001Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] failed to start input device soundcore AeroClip (input) (attempt 3): device soundcore AeroClip (input) not found\n2026-05-11T07:21:28.723900Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 4), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:28.726974Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-11T07:21:28.727134Z INFO screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] input device restored, device=soundcore AeroClip (input)\n2026-05-11T07:21:28.972503Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n2026-05-11T07:21:28.972538Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for soundcore AeroClip (input)\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\n2026-05-11T07:54:37.325769Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T07:54:37.395897Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-11T07:54:37.716552Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for soundcore AeroClip (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-11T07:54:37.848027Z WARN screenpipe_audio::audio_manager::manager: recording for device soundcore AeroClip (input) exited with error: stream rebuild required after screen unlock for soundcore AeroClip (input) (recovery is automatic via device_monitor)\n2026-05-11T07:54:38.122040Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for soundcore AeroClip (input), cleaning up for restart\n2026-05-11T07:54:38.122133Z INFO screenpipe_audio::device::device_manager: Stopping device: soundcore AeroClip (input)\n2026-05-11T07:54:38.359253Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-11T07:54:38.359387Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: soundcore AeroClip (input)\n2026-05-11T07:54:38.359454Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-11T07:54:38.859645Z INFO screenpipe_engine::vision_manager::monitor_watcher: Monitor 2 disconnected, stopping recording\n2026-05-11T07:54:38.859753Z INFO screenpipe_engine::vision_manager::manager: Stopping vision recording for monitor 2\n2026-05-11T07:54:39.562590Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-11T07:54:43.369378Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-11T07:54:44.338317Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-11T07:54:44.740316Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: day rollover (130 -> 131), clearing cache\n2026-05-11T07:55:08.874809Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-7753641314521957899, trigger=click)\n^C2026-05-11T07:55:11.501876Z INFO screenpipe: received ctrl+c, initiating shutdown\n2026-05-11T07:55:11.502778Z INFO screenpipe_audio::device::device_manager: Stopping device: soundcore AeroClip (input)\n2026-05-11T07:55:11.502929Z INFO screenpipe_audio::device::device_manager: Stopping device: System Audio (output)\n\n2026-05-11T07:55:11.529908Z INFO screenpipe_audio::audio_manager::manager: audio manager stopped \n2026-05-11T07:55:11.530005Z INFO screenpipe: stopping UI event capture\n2026-05-11T07:55:11.530067Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker shutting down\n2026-05-11T07:55:11.530084Z INFO screenpipe_engine::meeting_detector: meeting v2: shutdown received, exiting detection loop\n2026-05-11T07:55:11.530309Z INFO screenpipe: received shutdown signal for VisionManager\n2026-05-11T07:55:11.530497Z INFO screenpipe_engine::vision_manager::manager: Shutting down VisionManager\n2026-05-11T07:55:11.530534Z INFO screenpipe_engine::vision_manager::manager: Stopping VisionManager\n2026-05-11T07:55:11.530559Z INFO screenpipe_engine::vision_manager::manager: Stopping vision recording for monitor 1\n2026-05-11T07:55:11.535166Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T07:55:11.700985Z INFO screenpipe_engine::ui_recorder: UI recording session ended: 851f2de1-d8f5-4b4a-b008-420703e8e4b2\n2026-05-11T07:55:11.701373Z INFO screenpipe: shutdown complete\nggml_metal_free: deallocating\n\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status \nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T07:55:27.408897Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\n2026-05-11T07:55:32.412685Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T08:08:48.291500Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\n2026-05-11T09:04:13.378932Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ cd ..\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ du -sh\n2.9G\u0000\u0000\u0000\t.\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ alias sp-start\nsp-start='npx screenpipe@latest record --disable-audio --ignored-windows \"Boosteroid\"'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-05-11T09:06:14.511481Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store\nchecking permissions...\n screen recording: ok\n microphone: ok\n accessibility: ok\n2026-05-11T09:06:14.591827Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-05-11T09:06:16.007353Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-05-11T09:06:16.008982Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-05-11T09:06:16.009480Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-05-11T09:06:16.029339Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true\n2026-05-11T09:06:16.029396Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-05-11T09:06:16.402389Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-05-11T09:06:16.402461Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-05-11T09:06:16.402480Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-05-11T09:06:16.402564Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-05-11T09:06:16.402590Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-05-11T09:06:16.405899Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-05-11T09:06:16.406247Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-05-11T09:06:16.406815Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-05-11T09:06:16.406896Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-05-11T09:06:16.406969Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-05-11T09:06:16.407056Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-05-11T09:06:16.407076Z INFO screenpipe_core::pipes: loaded 6 pipes from \"/Users/lukas/.screenpipe/pipes\"\n\n\n\n _ \n __________________ ___ ____ ____ (_____ ___ \n / ___/ ___/ ___/ _ \\/ _ \\/ __ \\ / __ \\/ / __ \\/ _ \\\n (__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/\n/____/\\___/_/ \\___/\\___/_/ /_/ / .___/_/ .___/\\___/ \n /_/ /_/ \n\n\n\npower AI by everything you've seen, said or heard\nopen source | runs locally | developer friendly\n\n\n┌────────────────────────┬────────────────────────────────────┐\n│ setting │ value │\n├────────────────────────┼────────────────────────────────────┤\n│ audio chunk duration │ 30 seconds │\n│ port │ 3030 │\n│ audio disabled │ false │\n│ vision disabled │ false │\n│ pause on DRM content │ false │\n│ audio engine │ Parakeet │\n│ vad engine │ Silero │\n│ data directory │ /Users/lukas/.screenpipe │\n│ debug mode │ false │\n│ telemetry │ true │\n│ use pii removal │ true │\n│ use all monitors │ true │\n│ ignored windows │ [] │\n│ included windows │ [] │\n│ cloud sync │ disabled │\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n│ retention mode │ media-only (keep transcripts) │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ soundcore AeroClip (input) │\n│ │ System Audio (output) │\n└────────────────────────┴────────────────────────────────────┘\nyou are using local processing. all your data stays on your computer.\n\nwarning: telemetry is enabled. only error-level data will be sent.\nto disable, use the --disable-telemetry flag.\n\ncheck latest changes here: https://github.com/screenpipe/screenpipe/releases\n2026-05-11T09:06:16.409138Z INFO screenpipe: starting UI event capture\n2026-05-11T09:06:16.408692Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\n2026-05-11T09:06:16.413613Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n2026-05-11T09:06:16.415157Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-05-11T09:06:16.423358Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-05-11T09:06:16.437722Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-05-11T09:06:16.437713Z INFO screenpipe_engine::ui_recorder: UI recording session started: d42b8b31-1886-4817-bb21-01c53354434e\n2026-05-11T09:06:16.437981Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-10 06:06:16.437979 UTC to 2026-05-11 06:06:16.437979 UTC)\n2026-05-11T09:06:16.438357Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-05-11T09:06:16.446170Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-05-11T09:06:16.450650Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-05-11T09:06:16.763530Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 380 frame entries, coverage from 2026-05-10 06:06:16.437979 UTC\n2026-05-11T09:06:18.890147Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-05-11T09:06:18.890201Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-05-11T09:06:18.890230Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-05-11T09:06:19.779724Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)\n2026-05-11T09:06:19.779774Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-05-11T09:06:19.779785Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)\n2026-05-11T09:06:19.779792Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)\n2026-05-11T09:06:19.779831Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-05-11T09:06:21.291749Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-11T09:06:22.220403Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 1: frame_id=14920, dur=692ms\n2026-05-11T09:06:23.611887Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-11T09:06:24.399905Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 2: frame_id=14921, dur=352ms\n2026-05-11T09:06:26.412219Z INFO screenpipe_audio::transcription::engine: whisper model available: \"/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin\"\n2026-05-11T09:06:26.412338Z INFO screenpipe_audio::transcription::whisper::model: whisper context: gpu acceleration enabled (Metal on macOS, Vulkan on Windows)\n2026-05-11T09:06:26.412358Z INFO screenpipe_audio::transcription::engine: loading whisper model with GPU acceleration...\nwhisper_init_from_file_with_params_no_state: loading model from '/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin'\nwhisper_init_with_params_no_state: use gpu = 1\nwhisper_init_with_params_no_state: flash attn = 0\nwhisper_init_with_params_no_state: gpu_device = 0\nwhisper_init_with_params_no_state: dtw = 0\nggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices\nggml_metal_library_init: using embedded metal library\n2026-05-11T09:06:28.494279Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=8847004055550803395, trigger=visual_change)\n2026-05-11T09:06:37.351240Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=5134103372534729140, trigger=visual_change)\n2026-05-11T09:06:37.622550Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=5134103372534729140, trigger=click)\n2026-05-11T09:06:37.645003Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=5134103372534729140, trigger=click)\n2026-05-11T09:06:41.080867Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=4385064071004619482, trigger=click)","depth":4,"on_screen":true,"value":"whisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-10T23:27:31.985285Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-10T23:27:41.489329Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected\n2026-05-10T23:27:42.161846Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)\n2026-05-10T23:27:42.163527Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-10T23:27:42.164408Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)\n2026-05-10T23:27:42.164471Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-10T23:27:42.164492Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)\n2026-05-10T23:27:42.881174Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)\n2026-05-10T23:27:43.285854Z INFO screenpipe_audio::transcription::handle_new_transcript: device soundcore AeroClip (input) skipping duplicate transcript (entire content overlaps with previous)\n2026-05-10T23:27:58.189174Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: soundcore AeroClip (input)\n2026-05-10T23:27:58.190264Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-10T23:27:58.190299Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: soundcore AeroClip (input)\n2026-05-10T23:27:58.190324Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n2026-05-10T23:27:58.190332Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for soundcore AeroClip (input)\n2026-05-10T23:27:58.203316Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for MacBook Pro Microphone (input)\n2026-05-10T23:28:32.063312Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected\n2026-05-10T23:28:32.531328Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)\n2026-05-10T23:28:32.531913Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-10T23:28:32.531933Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)\n2026-05-10T23:28:32.532003Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)\n2026-05-10T23:28:32.708770Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-10T23:28:32.708807Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-10T23:51:42.401532Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T02:54:23.501609Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\n2026-05-11T07:21:22.702849Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: soundcore AeroClip (input)\n2026-05-11T07:21:22.703351Z ERROR screenpipe_audio::audio_manager::device_monitor: failed to start new default input soundcore AeroClip (input): device soundcore AeroClip (input) not found (will back off)\n2026-05-11T07:21:22.704671Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 1), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:22.704693Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] failed to start input device soundcore AeroClip (input) (attempt 1): device soundcore AeroClip (input) not found\n2026-05-11T07:21:23.587900Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for MacBook Pro Microphone (input)\n2026-05-11T07:21:24.708381Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 2), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:24.708451Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] failed to start input device soundcore AeroClip (input) (attempt 2): device soundcore AeroClip (input) not found\n2026-05-11T07:21:26.711922Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 3), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:26.712001Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] failed to start input device soundcore AeroClip (input) (attempt 3): device soundcore AeroClip (input) not found\n2026-05-11T07:21:28.723900Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] no input device running (attempt 4), starting default: soundcore AeroClip (input)\n2026-05-11T07:21:28.726974Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-11T07:21:28.727134Z INFO screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] input device restored, device=soundcore AeroClip (input)\n2026-05-11T07:21:28.972503Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n2026-05-11T07:21:28.972538Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for soundcore AeroClip (input)\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\n2026-05-11T07:54:37.325769Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T07:54:37.395897Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-11T07:54:37.716552Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for soundcore AeroClip (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-11T07:54:37.848027Z WARN screenpipe_audio::audio_manager::manager: recording for device soundcore AeroClip (input) exited with error: stream rebuild required after screen unlock for soundcore AeroClip (input) (recovery is automatic via device_monitor)\n2026-05-11T07:54:38.122040Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for soundcore AeroClip (input), cleaning up for restart\n2026-05-11T07:54:38.122133Z INFO screenpipe_audio::device::device_manager: Stopping device: soundcore AeroClip (input)\n2026-05-11T07:54:38.359253Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-11T07:54:38.359387Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: soundcore AeroClip (input)\n2026-05-11T07:54:38.359454Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-11T07:54:38.859645Z INFO screenpipe_engine::vision_manager::monitor_watcher: Monitor 2 disconnected, stopping recording\n2026-05-11T07:54:38.859753Z INFO screenpipe_engine::vision_manager::manager: Stopping vision recording for monitor 2\n2026-05-11T07:54:39.562590Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-11T07:54:43.369378Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-11T07:54:44.338317Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-11T07:54:44.740316Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: day rollover (130 -> 131), clearing cache\n2026-05-11T07:55:08.874809Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-7753641314521957899, trigger=click)\n^C2026-05-11T07:55:11.501876Z INFO screenpipe: received ctrl+c, initiating shutdown\n2026-05-11T07:55:11.502778Z INFO screenpipe_audio::device::device_manager: Stopping device: soundcore AeroClip (input)\n2026-05-11T07:55:11.502929Z INFO screenpipe_audio::device::device_manager: Stopping device: System Audio (output)\n\n2026-05-11T07:55:11.529908Z INFO screenpipe_audio::audio_manager::manager: audio manager stopped \n2026-05-11T07:55:11.530005Z INFO screenpipe: stopping UI event capture\n2026-05-11T07:55:11.530067Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker shutting down\n2026-05-11T07:55:11.530084Z INFO screenpipe_engine::meeting_detector: meeting v2: shutdown received, exiting detection loop\n2026-05-11T07:55:11.530309Z INFO screenpipe: received shutdown signal for VisionManager\n2026-05-11T07:55:11.530497Z INFO screenpipe_engine::vision_manager::manager: Shutting down VisionManager\n2026-05-11T07:55:11.530534Z INFO screenpipe_engine::vision_manager::manager: Stopping VisionManager\n2026-05-11T07:55:11.530559Z INFO screenpipe_engine::vision_manager::manager: Stopping vision recording for monitor 1\n2026-05-11T07:55:11.535166Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T07:55:11.700985Z INFO screenpipe_engine::ui_recorder: UI recording session ended: 851f2de1-d8f5-4b4a-b008-420703e8e4b2\n2026-05-11T07:55:11.701373Z INFO screenpipe: shutdown complete\nggml_metal_free: deallocating\n\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status \nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T07:55:27.408897Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\n2026-05-11T07:55:32.412685Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T08:08:48.291500Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)\n2026-05-11T09:04:13.378932Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ cd ..\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ du -sh\n2.9G\u0000\u0000\u0000\t.\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ alias sp-start\nsp-start='npx screenpipe@latest record --disable-audio --ignored-windows \"Boosteroid\"'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-05-11T09:06:14.511481Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store\nchecking permissions...\n screen recording: ok\n microphone: ok\n accessibility: ok\n2026-05-11T09:06:14.591827Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-05-11T09:06:16.007353Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-05-11T09:06:16.008982Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-05-11T09:06:16.009480Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-05-11T09:06:16.029339Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true\n2026-05-11T09:06:16.029396Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-05-11T09:06:16.402389Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-05-11T09:06:16.402461Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-05-11T09:06:16.402480Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-05-11T09:06:16.402564Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-05-11T09:06:16.402590Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-05-11T09:06:16.405899Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-05-11T09:06:16.406247Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-05-11T09:06:16.406815Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-05-11T09:06:16.406896Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-05-11T09:06:16.406969Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-05-11T09:06:16.407056Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-05-11T09:06:16.407076Z INFO screenpipe_core::pipes: loaded 6 pipes from \"/Users/lukas/.screenpipe/pipes\"\n\n\n\n _ \n __________________ ___ ____ ____ (_____ ___ \n / ___/ ___/ ___/ _ \\/ _ \\/ __ \\ / __ \\/ / __ \\/ _ \\\n (__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/\n/____/\\___/_/ \\___/\\___/_/ /_/ / .___/_/ .___/\\___/ \n /_/ /_/ \n\n\n\npower AI by everything you've seen, said or heard\nopen source | runs locally | developer friendly\n\n\n┌────────────────────────┬────────────────────────────────────┐\n│ setting │ value │\n├────────────────────────┼────────────────────────────────────┤\n│ audio chunk duration │ 30 seconds │\n│ port │ 3030 │\n│ audio disabled │ false │\n│ vision disabled │ false │\n│ pause on DRM content │ false │\n│ audio engine │ Parakeet │\n│ vad engine │ Silero │\n│ data directory │ /Users/lukas/.screenpipe │\n│ debug mode │ false │\n│ telemetry │ true │\n│ use pii removal │ true │\n│ use all monitors │ true │\n│ ignored windows │ [] │\n│ included windows │ [] │\n│ cloud sync │ disabled │\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n│ retention mode │ media-only (keep transcripts) │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ soundcore AeroClip (input) │\n│ │ System Audio (output) │\n└────────────────────────┴────────────────────────────────────┘\nyou are using local processing. all your data stays on your computer.\n\nwarning: telemetry is enabled. only error-level data will be sent.\nto disable, use the --disable-telemetry flag.\n\ncheck latest changes here: https://github.com/screenpipe/screenpipe/releases\n2026-05-11T09:06:16.409138Z INFO screenpipe: starting UI event capture\n2026-05-11T09:06:16.408692Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\n2026-05-11T09:06:16.413613Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n2026-05-11T09:06:16.415157Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-05-11T09:06:16.423358Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-05-11T09:06:16.437722Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-05-11T09:06:16.437713Z INFO screenpipe_engine::ui_recorder: UI recording session started: d42b8b31-1886-4817-bb21-01c53354434e\n2026-05-11T09:06:16.437981Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-10 06:06:16.437979 UTC to 2026-05-11 06:06:16.437979 UTC)\n2026-05-11T09:06:16.438357Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-05-11T09:06:16.446170Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-05-11T09:06:16.450650Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-05-11T09:06:16.763530Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 380 frame entries, coverage from 2026-05-10 06:06:16.437979 UTC\n2026-05-11T09:06:18.890147Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-05-11T09:06:18.890201Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-05-11T09:06:18.890230Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-05-11T09:06:19.779724Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)\n2026-05-11T09:06:19.779774Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-05-11T09:06:19.779785Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)\n2026-05-11T09:06:19.779792Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)\n2026-05-11T09:06:19.779831Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-05-11T09:06:21.291749Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-11T09:06:22.220403Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 1: frame_id=14920, dur=692ms\n2026-05-11T09:06:23.611887Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-11T09:06:24.399905Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 2: frame_id=14921, dur=352ms\n2026-05-11T09:06:26.412219Z INFO screenpipe_audio::transcription::engine: whisper model available: \"/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin\"\n2026-05-11T09:06:26.412338Z INFO screenpipe_audio::transcription::whisper::model: whisper context: gpu acceleration enabled (Metal on macOS, Vulkan on Windows)\n2026-05-11T09:06:26.412358Z INFO screenpipe_audio::transcription::engine: loading whisper model with GPU acceleration...\nwhisper_init_from_file_with_params_no_state: loading model from '/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin'\nwhisper_init_with_params_no_state: use gpu = 1\nwhisper_init_with_params_no_state: flash attn = 0\nwhisper_init_with_params_no_state: gpu_device = 0\nwhisper_init_with_params_no_state: dtw = 0\nggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices\nggml_metal_library_init: using embedded metal library\n2026-05-11T09:06:28.494279Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=8847004055550803395, trigger=visual_change)\n2026-05-11T09:06:37.351240Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=5134103372534729140, trigger=visual_change)\n2026-05-11T09:06:37.622550Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=5134103372534729140, trigger=click)\n2026-05-11T09:06:37.645003Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=5134103372534729140, trigger=click)\n2026-05-11T09:06:41.080867Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=4385064071004619482, trigger=click)","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.0,"top":0.05888889,"width":0.16388889,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.004166667,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (-zsh)","depth":2,"bounds":{"left":0.16388889,"top":0.05888889,"width":0.16388889,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.16805555,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.32777777,"top":0.05888889,"width":0.16388889,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.33194444,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.49166667,"top":0.05888889,"width":0.16388889,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.49583334,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.65555555,"top":0.05888889,"width":0.16388889,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.6597222,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.8194444,"top":0.05888889,"width":0.16388889,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.82361114,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.9548611,"top":0.032222223,"width":0.03888889,"height":0.018888889},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"screenpipe\"","depth":1,"bounds":{"left":0.47083333,"top":0.033333335,"width":0.058333334,"height":0.017777778},"on_screen":true,"role_description":"text"}]...
|
3919767619690102304
|
-816202915870083616
|
visual_change
|
accessibility
|
NULL
|
whisper_init_state: compute buffer (cross) = 8 whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-10T23:27:31.985285Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-10T23:27:41.489329Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected
2026-05-10T23:27:42.161846Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)
2026-05-10T23:27:42.163527Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-10T23:27:42.164408Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)
2026-05-10T23:27:42.164471Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-10T23:27:42.164492Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)
2026-05-10T23:27:42.881174Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)
2026-05-10T23:27:43.285854Z INFO screenpipe_audio::transcription::handle_new_transcript: device soundcore AeroClip (input) skipping duplicate transcript (entire content overlaps with previous)
2026-05-10T23:27:58.189174Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: soundcore AeroClip (input)
2026-05-10T23:27:58.190264Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)
2026-05-10T23:27:58.190299Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: soundcore AeroClip (input)
2026-05-10T23:27:58.190324Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)
2026-05-10T23:27:58.190332Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for soundcore AeroClip (input)
2026-05-10T23:27:58.203316Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for MacBook Pro Microphone (input)
2026-05-10T23:28:32.063312Z ERROR screenpipe_audio::core::stream: an error occurred on the audio stream: device disconnected
2026-05-10T23:28:32.531328Z INFO screenpipe_audio::audio_manager::device_monitor: system default input changed to: MacBook Pro Microphone (input)
2026-05-10T23:28:32.531913Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-10T23:28:32.531933Z INFO screenpipe_audio::audio_manager::device_monitor: switched to new system default input: MacBook Pro Microphone (input)
2026-05-10T23:28:32.532003Z INFO screenpipe_audio::core::run_record_and_transcribe: stopped recording for soundcore AeroClip (input)
2026-05-10T23:28:32.708770Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-10T23:28:32.708807Z INFO screenpipe_audio::core::run_record_and_transcribe: screen locked, pausing audio recording for MacBook Pro Microphone (input)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-10T23:51:42.401532Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: sign in for higher AI quotas + cloud sync:
screenpipe login
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T02:54:23.501609Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: get the screenpipe desktop app for the full experience
[URL_WITH_CREDENTIALS] ~/.screenpipe/data $ 2026-05-11T07:55:11.700985Z INFO screenpipe_engine::ui_recorder: UI recording session ended: 851f2de1-d8f5-4b4a-b008-420703e8e4b2
2026-05-11T07:55:11.701373Z INFO screenpipe: shutdown complete
ggml_metal_free: deallocating
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T07:55:27.408897Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)
2026-05-11T07:55:32.412685Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ sp-status
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ 2026-05-11T08:08:48.291500Z INFO screenpipe_engine::sleep_monitor: Screen locked (CGSession safety-net poll)
2026-05-11T09:04:13.378932Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe/data $ cd ..
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ du -sh
2.9G .
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ alias sp-start
sp-start='npx screenpipe@latest record --disable-audio --ignored-windows "Boosteroid"'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-05-11T09:06:14.511481Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store
checking permissions...
screen recording: ok
microphone: ok
accessibility: ok
2026-05-11T09:06:14.591827Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-05-11T09:06:16.007353Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-05-11T09:06:16.008982Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-05-11T09:06:16.009480Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-05-11T09:06:16.029339Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true
2026-05-11T09:06:16.029396Z INFO screenpipe: meeting detector enabled — independent of transcription mode
2026-05-11T09:06:16.402389Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)
2026-05-11T09:06:16.402461Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)
2026-05-11T09:06:16.402480Z INFO screenpipe: API server listening on [IP_ADDRESS]:3030 (localhost only)
2026-05-11T09:06:16.402564Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key
2026-05-11T09:06:16.402590Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager
2026-05-11T09:06:16.405899Z INFO screenpipe_core::pipes: loaded pipe: day-recap
2026-05-11T09:06:16.406247Z INFO screenpipe_core::pipes: loaded pipe: standup-update
2026-05-11T09:06:16.406815Z INFO screenpipe_core::pipes: loaded pipe: ai-habits
2026-05-11T09:06:16.406896Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown
2026-05-11T09:06:16.406969Z INFO screenpipe_core::pipes: loaded pipe: video-export
2026-05-11T09:06:16.407056Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary
2026-05-11T09:06:16.407076Z INFO screenpipe_core::pipes: loaded 6 pipes from "/Users/lukas/.screenpipe/pipes"
_
__________________ ___ ____ ____ (...
|
NULL
|
NULL
|
NULL
|
NULL
|
|
21087
|
922
|
4
|
2026-05-11T17:11:18.942726+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519478942_m1.jpg...
|
iTerm2
|
screenpipe"
|
True
|
NULL
|
monitor_1
|
NULL
|
NULL
|
NULL
|
NULL
|
2026-05-11T19:55:41.050300Z INFO screenpipe_engin 2026-05-11T19:55:41.050300Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.2MB → 0.4MB (6.1x), 10 JPEGs deleted
2026-05-11T19:55:41.940193Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T19:56:35.278909Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T19:58:37.834427Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:00:40.424221Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:00:42.183237Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames
2026-05-11T20:00:43.461244Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.2MB → 0.4MB (6.1x), 10 JPEGs deleted
2026-05-11T20:00:44.432338Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted
tip: install a starter bundle of pipes:
screenpipe install https://screenpi.pe/start.json
2026-05-11T20:02:18.870768Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
2026-05-11T20:02:18.927472Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)
2026-05-11T20:02:18.981757Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)
2026-05-11T20:02:20.964004Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart
2026-05-11T20:02:20.964175Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)
2026-05-11T20:02:21.415539Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-11T20:02:21.415697Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)
2026-05-11T20:02:21.415980Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-11T20:02:21.813264Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
2026-05-11T20:02:24.656924Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1
2026-05-11T20:02:24.684324Z WARN sqlx::query: summary="SELECT DISTINCT app_name, window_name, …" db.statement="\n\nSELECT\n DISTINCT app_name,\n window_name,\n browser_url\nFROM\n frames\nWHERE\n timestamp > datetime('now', '-30 seconds')\n AND app_name IS NOT NULL\n AND window_name IS NOT NULL\n" rows_affected=1 rows_returned=197 elapsed=5.061547s
2026-05-11T20:02:26.657137Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)
2026-05-11T20:02:30.621870Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)
2026-05-11T20:02:34.637496Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:02:44.001643Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:03:30.479471Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-5826347064466025141, trigger=visual_change)
2026-05-11T20:03:52.131531Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-5425790139218707027, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:04:45.978554Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:05:05.168645Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 89.5ms elapsed (expected 5.3ms) → inserting 84.2ms silence (8080 samples)
2026-05-11T20:05:16.224790Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=4930168029133975798, trigger=click)
2026-05-11T20:05:27.444659Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 187.9ms elapsed (expected 5.3ms) → inserting 182.6ms silence (17527 samples)
2026-05-11T20:05:46.190016Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=1 rows_returned=18 elapsed=1.745995375s
2026-05-11T20:05:46.191257Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 18 eligible frames
2026-05-11T20:05:47.142521Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.8MB → 0.4MB (4.9x), 8 JPEGs deleted
2026-05-11T20:05:48.203203Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.5MB → 0.3MB (5.1x), 8 JPEGs deleted
tip: sign in for higher AI quotas + cloud sync:
screenpipe login
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:06:48.489458Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:08:50.983819Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:10:48.583599Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found d...
|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"2026-05-11T19:55:41.050300Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.2MB → 0.4MB (6.1x), 10 JPEGs deleted\n2026-05-11T19:55:41.940193Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T19:56:35.278909Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T19:58:37.834427Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:00:40.424221Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:00:42.183237Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames\n2026-05-11T20:00:43.461244Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.2MB → 0.4MB (6.1x), 10 JPEGs deleted\n2026-05-11T20:00:44.432338Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-11T20:02:18.870768Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T20:02:18.927472Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-11T20:02:18.981757Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)\n2026-05-11T20:02:20.964004Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart\n2026-05-11T20:02:20.964175Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)\n2026-05-11T20:02:21.415539Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-11T20:02:21.415697Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)\n2026-05-11T20:02:21.415980Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-11T20:02:21.813264Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T20:02:24.656924Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-11T20:02:24.684324Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=197 elapsed=5.061547s\n2026-05-11T20:02:26.657137Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-11T20:02:30.621870Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-11T20:02:34.637496Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:02:44.001643Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:03:30.479471Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-5826347064466025141, trigger=visual_change)\n2026-05-11T20:03:52.131531Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-5425790139218707027, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:04:45.978554Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:05:05.168645Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 89.5ms elapsed (expected 5.3ms) → inserting 84.2ms silence (8080 samples)\n2026-05-11T20:05:16.224790Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=4930168029133975798, trigger=click)\n2026-05-11T20:05:27.444659Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 187.9ms elapsed (expected 5.3ms) → inserting 182.6ms silence (17527 samples)\n2026-05-11T20:05:46.190016Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=18 elapsed=1.745995375s\n2026-05-11T20:05:46.191257Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 18 eligible frames\n2026-05-11T20:05:47.142521Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.8MB → 0.4MB (4.9x), 8 JPEGs deleted\n2026-05-11T20:05:48.203203Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.5MB → 0.3MB (5.1x), 8 JPEGs deleted\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:06:48.489458Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:08:50.983819Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:10:48.583599Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:10:54.062636Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe","depth":4,"on_screen":true,"value":"2026-05-11T19:55:41.050300Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.2MB → 0.4MB (6.1x), 10 JPEGs deleted\n2026-05-11T19:55:41.940193Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T19:56:35.278909Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T19:58:37.834427Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:00:40.424221Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:00:42.183237Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames\n2026-05-11T20:00:43.461244Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.2MB → 0.4MB (6.1x), 10 JPEGs deleted\n2026-05-11T20:00:44.432338Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-11T20:02:18.870768Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T20:02:18.927472Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-11T20:02:18.981757Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)\n2026-05-11T20:02:20.964004Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart\n2026-05-11T20:02:20.964175Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)\n2026-05-11T20:02:21.415539Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-11T20:02:21.415697Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)\n2026-05-11T20:02:21.415980Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-11T20:02:21.813264Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T20:02:24.656924Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-11T20:02:24.684324Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=197 elapsed=5.061547s\n2026-05-11T20:02:26.657137Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-11T20:02:30.621870Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-11T20:02:34.637496Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:02:44.001643Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:03:30.479471Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-5826347064466025141, trigger=visual_change)\n2026-05-11T20:03:52.131531Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-5425790139218707027, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:04:45.978554Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:05:05.168645Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 89.5ms elapsed (expected 5.3ms) → inserting 84.2ms silence (8080 samples)\n2026-05-11T20:05:16.224790Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=4930168029133975798, trigger=click)\n2026-05-11T20:05:27.444659Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 187.9ms elapsed (expected 5.3ms) → inserting 182.6ms silence (17527 samples)\n2026-05-11T20:05:46.190016Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=18 elapsed=1.745995375s\n2026-05-11T20:05:46.191257Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 18 eligible frames\n2026-05-11T20:05:47.142521Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.8MB → 0.4MB (4.9x), 8 JPEGs deleted\n2026-05-11T20:05:48.203203Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.5MB → 0.3MB (5.1x), 8 JPEGs deleted\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:06:48.489458Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:08:50.983819Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:10:48.583599Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:10:54.062636Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.0,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.004166667,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (docker)","depth":2,"bounds":{"left":0.140625,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.14479166,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.28125,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.28541666,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.421875,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.42604166,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.5625,"top":0.05888889,"width":0.14027777,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.56666666,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.7027778,"top":0.05888889,"width":0.14027777,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.70694447,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.84305555,"top":0.05888889,"width":0.14027777,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.8472222,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.9548611,"top":0.032222223,"width":0.03888889,"height":0.018888889},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"screenpipe\"","depth":1,"bounds":{"left":0.47083333,"top":0.033333335,"width":0.058333334,"height":0.017777778},"on_screen":true,"role_description":"text"}]...
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1557952319796948289
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-852231723626465824
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click
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accessibility
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NULL
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2026-05-11T19:55:41.050300Z INFO screenpipe_engin 2026-05-11T19:55:41.050300Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.2MB → 0.4MB (6.1x), 10 JPEGs deleted
2026-05-11T19:55:41.940193Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T19:56:35.278909Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T19:58:37.834427Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:00:40.424221Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:00:42.183237Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames
2026-05-11T20:00:43.461244Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.2MB → 0.4MB (6.1x), 10 JPEGs deleted
2026-05-11T20:00:44.432338Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted
tip: install a starter bundle of pipes:
screenpipe install https://screenpi.pe/start.json
2026-05-11T20:02:18.870768Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
2026-05-11T20:02:18.927472Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)
2026-05-11T20:02:18.981757Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)
2026-05-11T20:02:20.964004Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart
2026-05-11T20:02:20.964175Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)
2026-05-11T20:02:21.415539Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-11T20:02:21.415697Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)
2026-05-11T20:02:21.415980Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-11T20:02:21.813264Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
2026-05-11T20:02:24.656924Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1
2026-05-11T20:02:24.684324Z WARN sqlx::query: summary="SELECT DISTINCT app_name, window_name, …" db.statement="\n\nSELECT\n DISTINCT app_name,\n window_name,\n browser_url\nFROM\n frames\nWHERE\n timestamp > datetime('now', '-30 seconds')\n AND app_name IS NOT NULL\n AND window_name IS NOT NULL\n" rows_affected=1 rows_returned=197 elapsed=5.061547s
2026-05-11T20:02:26.657137Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)
2026-05-11T20:02:30.621870Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)
2026-05-11T20:02:34.637496Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:02:44.001643Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:03:30.479471Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-5826347064466025141, trigger=visual_change)
2026-05-11T20:03:52.131531Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-5425790139218707027, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:04:45.978554Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:05:05.168645Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 89.5ms elapsed (expected 5.3ms) → inserting 84.2ms silence (8080 samples)
2026-05-11T20:05:16.224790Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=4930168029133975798, trigger=click)
2026-05-11T20:05:27.444659Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 187.9ms elapsed (expected 5.3ms) → inserting 182.6ms silence (17527 samples)
2026-05-11T20:05:46.190016Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=1 rows_returned=18 elapsed=1.745995375s
2026-05-11T20:05:46.191257Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 18 eligible frames
2026-05-11T20:05:47.142521Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.8MB → 0.4MB (4.9x), 8 JPEGs deleted
2026-05-11T20:05:48.203203Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.5MB → 0.3MB (5.1x), 8 JPEGs deleted
tip: sign in for higher AI quotas + cloud sync:
screenpipe login
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:06:48.489458Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:08:50.983819Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:10:48.583599Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found d...
|
21086
|
NULL
|
NULL
|
NULL
|
|
21088
|
923
|
4
|
2026-05-11T17:11:18.941542+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519478941_m2.jpg...
|
iTerm2
|
screenpipe"
|
True
|
NULL
|
monitor_2
|
NULL
|
NULL
|
NULL
|
NULL
|
2026-05-11T19:55:41.050300Z INFO screenpipe_engin 2026-05-11T19:55:41.050300Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.2MB → 0.4MB (6.1x), 10 JPEGs deleted
2026-05-11T19:55:41.940193Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T19:56:35.278909Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T19:58:37.834427Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:00:40.424221Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:00:42.183237Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames
2026-05-11T20:00:43.461244Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.2MB → 0.4MB (6.1x), 10 JPEGs deleted
2026-05-11T20:00:44.432338Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted
tip: install a starter bundle of pipes:
screenpipe install https://screenpi.pe/start.json
2026-05-11T20:02:18.870768Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
2026-05-11T20:02:18.927472Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)
2026-05-11T20:02:18.981757Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)
2026-05-11T20:02:20.964004Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart
2026-05-11T20:02:20.964175Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)
2026-05-11T20:02:21.415539Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-11T20:02:21.415697Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)
2026-05-11T20:02:21.415980Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-11T20:02:21.813264Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
2026-05-11T20:02:24.656924Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1
2026-05-11T20:02:24.684324Z WARN sqlx::query: summary="SELECT DISTINCT app_name, window_name, …" db.statement="\n\nSELECT\n DISTINCT app_name,\n window_name,\n browser_url\nFROM\n frames\nWHERE\n timestamp > datetime('now', '-30 seconds')\n AND app_name IS NOT NULL\n AND window_name IS NOT NULL\n" rows_affected=1 rows_returned=197 elapsed=5.061547s
2026-05-11T20:02:26.657137Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)
2026-05-11T20:02:30.621870Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)
2026-05-11T20:02:34.637496Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:02:44.001643Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:03:30.479471Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-5826347064466025141, trigger=visual_change)
2026-05-11T20:03:52.131531Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-5425790139218707027, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:04:45.978554Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:05:05.168645Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 89.5ms elapsed (expected 5.3ms) → inserting 84.2ms silence (8080 samples)
2026-05-11T20:05:16.224790Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=4930168029133975798, trigger=click)
2026-05-11T20:05:27.444659Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 187.9ms elapsed (expected 5.3ms) → inserting 182.6ms silence (17527 samples)
2026-05-11T20:05:46.190016Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=1 rows_returned=18 elapsed=1.745995375s
2026-05-11T20:05:46.191257Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 18 eligible frames
2026-05-11T20:05:47.142521Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.8MB → 0.4MB (4.9x), 8 JPEGs deleted
2026-05-11T20:05:48.203203Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.5MB → 0.3MB (5.1x), 8 JPEGs deleted
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whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:06:48.489458Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:08:50.983819Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:10:48.583599Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found d...
|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"2026-05-11T19:55:41.050300Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.2MB → 0.4MB (6.1x), 10 JPEGs deleted\n2026-05-11T19:55:41.940193Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T19:56:35.278909Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T19:58:37.834427Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:00:40.424221Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:00:42.183237Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames\n2026-05-11T20:00:43.461244Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.2MB → 0.4MB (6.1x), 10 JPEGs deleted\n2026-05-11T20:00:44.432338Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-11T20:02:18.870768Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T20:02:18.927472Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-11T20:02:18.981757Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)\n2026-05-11T20:02:20.964004Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart\n2026-05-11T20:02:20.964175Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)\n2026-05-11T20:02:21.415539Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-11T20:02:21.415697Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)\n2026-05-11T20:02:21.415980Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-11T20:02:21.813264Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T20:02:24.656924Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-11T20:02:24.684324Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=197 elapsed=5.061547s\n2026-05-11T20:02:26.657137Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-11T20:02:30.621870Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-11T20:02:34.637496Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:02:44.001643Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:03:30.479471Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-5826347064466025141, trigger=visual_change)\n2026-05-11T20:03:52.131531Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-5425790139218707027, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:04:45.978554Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:05:05.168645Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 89.5ms elapsed (expected 5.3ms) → inserting 84.2ms silence (8080 samples)\n2026-05-11T20:05:16.224790Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=4930168029133975798, trigger=click)\n2026-05-11T20:05:27.444659Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 187.9ms elapsed (expected 5.3ms) → inserting 182.6ms silence (17527 samples)\n2026-05-11T20:05:46.190016Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=18 elapsed=1.745995375s\n2026-05-11T20:05:46.191257Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 18 eligible frames\n2026-05-11T20:05:47.142521Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.8MB → 0.4MB (4.9x), 8 JPEGs deleted\n2026-05-11T20:05:48.203203Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.5MB → 0.3MB (5.1x), 8 JPEGs deleted\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:06:48.489458Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:08:50.983819Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:10:48.583599Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:10:54.062636Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe","depth":4,"on_screen":true,"value":"2026-05-11T19:55:41.050300Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.2MB → 0.4MB (6.1x), 10 JPEGs deleted\n2026-05-11T19:55:41.940193Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T19:56:35.278909Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T19:58:37.834427Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:00:40.424221Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:00:42.183237Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames\n2026-05-11T20:00:43.461244Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.2MB → 0.4MB (6.1x), 10 JPEGs deleted\n2026-05-11T20:00:44.432338Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-11T20:02:18.870768Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T20:02:18.927472Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-11T20:02:18.981757Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)\n2026-05-11T20:02:20.964004Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart\n2026-05-11T20:02:20.964175Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)\n2026-05-11T20:02:21.415539Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-11T20:02:21.415697Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)\n2026-05-11T20:02:21.415980Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-11T20:02:21.813264Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T20:02:24.656924Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-11T20:02:24.684324Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=197 elapsed=5.061547s\n2026-05-11T20:02:26.657137Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-11T20:02:30.621870Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-11T20:02:34.637496Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:02:44.001643Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:03:30.479471Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-5826347064466025141, trigger=visual_change)\n2026-05-11T20:03:52.131531Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-5425790139218707027, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:04:45.978554Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:05:05.168645Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 89.5ms elapsed (expected 5.3ms) → inserting 84.2ms silence (8080 samples)\n2026-05-11T20:05:16.224790Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=4930168029133975798, trigger=click)\n2026-05-11T20:05:27.444659Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 187.9ms elapsed (expected 5.3ms) → inserting 182.6ms silence (17527 samples)\n2026-05-11T20:05:46.190016Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=18 elapsed=1.745995375s\n2026-05-11T20:05:46.191257Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 18 eligible frames\n2026-05-11T20:05:47.142521Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.8MB → 0.4MB (4.9x), 8 JPEGs deleted\n2026-05-11T20:05:48.203203Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.5MB → 0.3MB (5.1x), 8 JPEGs deleted\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:06:48.489458Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:08:50.983819Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:10:48.583599Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:10:54.062636Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.27027926,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.27227393,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (docker)","depth":2,"bounds":{"left":0.33759972,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.33959442,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.40492022,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.4069149,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.4722407,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.4742354,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.53956115,"top":1.0,"width":0.06715426,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.5415558,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.60671544,"top":1.0,"width":0.06715426,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.6087101,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.67386967,"top":1.0,"width":0.06715426,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.67586434,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.7273936,"top":1.0,"width":0.01861702,"height":-0.023144484},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"screenpipe\"","depth":1,"bounds":{"left":0.4956782,"top":1.0,"width":0.027925532,"height":-0.02394259},"on_screen":true,"role_description":"text"}]...
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1557952319796948289
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-852231723626465824
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click
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accessibility
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NULL
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2026-05-11T19:55:41.050300Z INFO screenpipe_engin 2026-05-11T19:55:41.050300Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.2MB → 0.4MB (6.1x), 10 JPEGs deleted
2026-05-11T19:55:41.940193Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T19:56:35.278909Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T19:58:37.834427Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:00:40.424221Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:00:42.183237Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames
2026-05-11T20:00:43.461244Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.2MB → 0.4MB (6.1x), 10 JPEGs deleted
2026-05-11T20:00:44.432338Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted
tip: install a starter bundle of pipes:
screenpipe install https://screenpi.pe/start.json
2026-05-11T20:02:18.870768Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
2026-05-11T20:02:18.927472Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)
2026-05-11T20:02:18.981757Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)
2026-05-11T20:02:20.964004Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart
2026-05-11T20:02:20.964175Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)
2026-05-11T20:02:21.415539Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-11T20:02:21.415697Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)
2026-05-11T20:02:21.415980Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-11T20:02:21.813264Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
2026-05-11T20:02:24.656924Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1
2026-05-11T20:02:24.684324Z WARN sqlx::query: summary="SELECT DISTINCT app_name, window_name, …" db.statement="\n\nSELECT\n DISTINCT app_name,\n window_name,\n browser_url\nFROM\n frames\nWHERE\n timestamp > datetime('now', '-30 seconds')\n AND app_name IS NOT NULL\n AND window_name IS NOT NULL\n" rows_affected=1 rows_returned=197 elapsed=5.061547s
2026-05-11T20:02:26.657137Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)
2026-05-11T20:02:30.621870Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)
2026-05-11T20:02:34.637496Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:02:44.001643Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:03:30.479471Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-5826347064466025141, trigger=visual_change)
2026-05-11T20:03:52.131531Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-5425790139218707027, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:04:45.978554Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:05:05.168645Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 89.5ms elapsed (expected 5.3ms) → inserting 84.2ms silence (8080 samples)
2026-05-11T20:05:16.224790Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=4930168029133975798, trigger=click)
2026-05-11T20:05:27.444659Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 187.9ms elapsed (expected 5.3ms) → inserting 182.6ms silence (17527 samples)
2026-05-11T20:05:46.190016Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=1 rows_returned=18 elapsed=1.745995375s
2026-05-11T20:05:46.191257Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 18 eligible frames
2026-05-11T20:05:47.142521Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.8MB → 0.4MB (4.9x), 8 JPEGs deleted
2026-05-11T20:05:48.203203Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.5MB → 0.3MB (5.1x), 8 JPEGs deleted
tip: sign in for higher AI quotas + cloud sync:
screenpipe login
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:06:48.489458Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:08:50.983819Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:10:48.583599Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found d...
|
NULL
|
NULL
|
NULL
|
NULL
|
|
21089
|
922
|
5
|
2026-05-11T17:11:24.165600+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519484165_m1.jpg...
|
iTerm2
|
screenpipe"
|
True
|
NULL
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monitor_1
|
NULL
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NULL
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NULL
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NULL
|
2026-05-11T19:55:41.940193Z INFO screenpipe_engin 2026-05-11T19:55:41.940193Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T19:56:35.278909Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T19:58:37.834427Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:00:40.424221Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:00:42.183237Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames
2026-05-11T20:00:43.461244Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.2MB → 0.4MB (6.1x), 10 JPEGs deleted
2026-05-11T20:00:44.432338Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted
tip: install a starter bundle of pipes:
screenpipe install https://screenpi.pe/start.json
2026-05-11T20:02:18.870768Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
2026-05-11T20:02:18.927472Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)
2026-05-11T20:02:18.981757Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)
2026-05-11T20:02:20.964004Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart
2026-05-11T20:02:20.964175Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)
2026-05-11T20:02:21.415539Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-11T20:02:21.415697Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)
2026-05-11T20:02:21.415980Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-11T20:02:21.813264Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
2026-05-11T20:02:24.656924Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1
2026-05-11T20:02:24.684324Z WARN sqlx::query: summary="SELECT DISTINCT app_name, window_name, …" db.statement="\n\nSELECT\n DISTINCT app_name,\n window_name,\n browser_url\nFROM\n frames\nWHERE\n timestamp > datetime('now', '-30 seconds')\n AND app_name IS NOT NULL\n AND window_name IS NOT NULL\n" rows_affected=1 rows_returned=197 elapsed=5.061547s
2026-05-11T20:02:26.657137Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)
2026-05-11T20:02:30.621870Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)
2026-05-11T20:02:34.637496Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:02:44.001643Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:03:30.479471Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-5826347064466025141, trigger=visual_change)
2026-05-11T20:03:52.131531Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-5425790139218707027, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:04:45.978554Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:05:05.168645Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 89.5ms elapsed (expected 5.3ms) → inserting 84.2ms silence (8080 samples)
2026-05-11T20:05:16.224790Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=4930168029133975798, trigger=click)
2026-05-11T20:05:27.444659Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 187.9ms elapsed (expected 5.3ms) → inserting 182.6ms silence (17527 samples)
2026-05-11T20:05:46.190016Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=1 rows_returned=18 elapsed=1.745995375s
2026-05-11T20:05:46.191257Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 18 eligible frames
2026-05-11T20:05:47.142521Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.8MB → 0.4MB (4.9x), 8 JPEGs deleted
2026-05-11T20:05:48.203203Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.5MB → 0.3MB (5.1x), 8 JPEGs deleted
tip: sign in for higher AI quotas + cloud sync:
screenpipe login
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:06:48.489458Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:08:50.983819Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:10:48.583599Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = ...
|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"2026-05-11T19:55:41.940193Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T19:56:35.278909Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T19:58:37.834427Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:00:40.424221Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:00:42.183237Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames\n2026-05-11T20:00:43.461244Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.2MB → 0.4MB (6.1x), 10 JPEGs deleted\n2026-05-11T20:00:44.432338Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-11T20:02:18.870768Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T20:02:18.927472Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-11T20:02:18.981757Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)\n2026-05-11T20:02:20.964004Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart\n2026-05-11T20:02:20.964175Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)\n2026-05-11T20:02:21.415539Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-11T20:02:21.415697Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)\n2026-05-11T20:02:21.415980Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-11T20:02:21.813264Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T20:02:24.656924Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-11T20:02:24.684324Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=197 elapsed=5.061547s\n2026-05-11T20:02:26.657137Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-11T20:02:30.621870Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-11T20:02:34.637496Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:02:44.001643Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:03:30.479471Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-5826347064466025141, trigger=visual_change)\n2026-05-11T20:03:52.131531Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-5425790139218707027, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:04:45.978554Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:05:05.168645Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 89.5ms elapsed (expected 5.3ms) → inserting 84.2ms silence (8080 samples)\n2026-05-11T20:05:16.224790Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=4930168029133975798, trigger=click)\n2026-05-11T20:05:27.444659Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 187.9ms elapsed (expected 5.3ms) → inserting 182.6ms silence (17527 samples)\n2026-05-11T20:05:46.190016Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=18 elapsed=1.745995375s\n2026-05-11T20:05:46.191257Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 18 eligible frames\n2026-05-11T20:05:47.142521Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.8MB → 0.4MB (4.9x), 8 JPEGs deleted\n2026-05-11T20:05:48.203203Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.5MB → 0.3MB (5.1x), 8 JPEGs deleted\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:06:48.489458Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:08:50.983819Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:10:48.583599Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:10:54.062636Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\n2026-05-11T20:11:21.171912Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=1557952319796948289, trigger=visual_change)","depth":4,"on_screen":true,"value":"2026-05-11T19:55:41.940193Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T19:56:35.278909Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T19:58:37.834427Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:00:40.424221Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:00:42.183237Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames\n2026-05-11T20:00:43.461244Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.2MB → 0.4MB (6.1x), 10 JPEGs deleted\n2026-05-11T20:00:44.432338Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-11T20:02:18.870768Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T20:02:18.927472Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-11T20:02:18.981757Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)\n2026-05-11T20:02:20.964004Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart\n2026-05-11T20:02:20.964175Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)\n2026-05-11T20:02:21.415539Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-11T20:02:21.415697Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)\n2026-05-11T20:02:21.415980Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-11T20:02:21.813264Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T20:02:24.656924Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-11T20:02:24.684324Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=1 rows_returned=197 elapsed=5.061547s\n2026-05-11T20:02:26.657137Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-11T20:02:30.621870Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-11T20:02:34.637496Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:02:44.001643Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:03:30.479471Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-5826347064466025141, trigger=visual_change)\n2026-05-11T20:03:52.131531Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-5425790139218707027, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:04:45.978554Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:05:05.168645Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 89.5ms elapsed (expected 5.3ms) → inserting 84.2ms silence (8080 samples)\n2026-05-11T20:05:16.224790Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=4930168029133975798, trigger=click)\n2026-05-11T20:05:27.444659Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 187.9ms elapsed (expected 5.3ms) → inserting 182.6ms silence (17527 samples)\n2026-05-11T20:05:46.190016Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=18 elapsed=1.745995375s\n2026-05-11T20:05:46.191257Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 18 eligible frames\n2026-05-11T20:05:47.142521Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.8MB → 0.4MB (4.9x), 8 JPEGs deleted\n2026-05-11T20:05:48.203203Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.5MB → 0.3MB (5.1x), 8 JPEGs deleted\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:06:48.489458Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:08:50.983819Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T20:10:48.583599Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T20:10:54.062636Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\n2026-05-11T20:11:21.171912Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=1557952319796948289, trigger=visual_change)","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.0,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.004166667,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (docker)","depth":2,"bounds":{"left":0.140625,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.14479166,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.28125,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.28541666,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.421875,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.42604166,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.5625,"top":0.05888889,"width":0.14027777,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.56666666,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.7027778,"top":0.05888889,"width":0.14027777,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.70694447,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.84305555,"top":0.05888889,"width":0.14027777,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.8472222,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.9548611,"top":0.032222223,"width":0.03888889,"height":0.018888889},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"screenpipe\"","depth":1,"bounds":{"left":0.47083333,"top":0.033333335,"width":0.058333334,"height":0.017777778},"on_screen":true,"role_description":"text"}]...
|
-456339702770083891
|
-852231723626465824
|
visual_change
|
accessibility
|
NULL
|
2026-05-11T19:55:41.940193Z INFO screenpipe_engin 2026-05-11T19:55:41.940193Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T19:56:35.278909Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T19:58:37.834427Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:00:40.424221Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:00:42.183237Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 22 eligible frames
2026-05-11T20:00:43.461244Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 2.2MB → 0.4MB (6.1x), 10 JPEGs deleted
2026-05-11T20:00:44.432338Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 10 frames, 1.9MB → 0.3MB (6.4x), 10 JPEGs deleted
tip: install a starter bundle of pipes:
screenpipe install https://screenpi.pe/start.json
2026-05-11T20:02:18.870768Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
2026-05-11T20:02:18.927472Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for MacBook Pro Microphone (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)
2026-05-11T20:02:18.981757Z WARN screenpipe_audio::audio_manager::manager: recording for device MacBook Pro Microphone (input) exited with error: stream rebuild required after screen unlock for MacBook Pro Microphone (input) (recovery is automatic via device_monitor)
2026-05-11T20:02:20.964004Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for MacBook Pro Microphone (input), cleaning up for restart
2026-05-11T20:02:20.964175Z INFO screenpipe_audio::device::device_manager: Stopping device: MacBook Pro Microphone (input)
2026-05-11T20:02:21.415539Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-11T20:02:21.415697Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: MacBook Pro Microphone (input)
2026-05-11T20:02:21.415980Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-11T20:02:21.813264Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)
2026-05-11T20:02:24.656924Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1
2026-05-11T20:02:24.684324Z WARN sqlx::query: summary="SELECT DISTINCT app_name, window_name, …" db.statement="\n\nSELECT\n DISTINCT app_name,\n window_name,\n browser_url\nFROM\n frames\nWHERE\n timestamp > datetime('now', '-30 seconds')\n AND app_name IS NOT NULL\n AND window_name IS NOT NULL\n" rows_affected=1 rows_returned=197 elapsed=5.061547s
2026-05-11T20:02:26.657137Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)
2026-05-11T20:02:30.621870Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)
2026-05-11T20:02:34.637496Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:02:44.001643Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:03:30.479471Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-5826347064466025141, trigger=visual_change)
2026-05-11T20:03:52.131531Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-5425790139218707027, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:04:45.978554Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:05:05.168645Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 89.5ms elapsed (expected 5.3ms) → inserting 84.2ms silence (8080 samples)
2026-05-11T20:05:16.224790Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=4930168029133975798, trigger=click)
2026-05-11T20:05:27.444659Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 187.9ms elapsed (expected 5.3ms) → inserting 182.6ms silence (17527 samples)
2026-05-11T20:05:46.190016Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=1 rows_returned=18 elapsed=1.745995375s
2026-05-11T20:05:46.191257Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 18 eligible frames
2026-05-11T20:05:47.142521Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.8MB → 0.4MB (4.9x), 8 JPEGs deleted
2026-05-11T20:05:48.203203Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 8 frames, 1.5MB → 0.3MB (5.1x), 8 JPEGs deleted
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whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:06:48.489458Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T20:08:50.983819Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-11T20:10:48.583599Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = ...
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NULL
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NULL
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NULL
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NULL
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|
21773
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952
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0
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2026-05-12T06:21:17.052235+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-12/1778 /Users/lukas/.screenpipe/data/data/2026-05-12/1778566877052_m1.jpg...
|
iTerm2
|
screenpipe"
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True
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NULL
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monitor_1
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NULL
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NULL
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NULL
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NULL
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ggml_metal_init: allocating
ggml_metal_init: found ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:27:49.369341Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:29:51.512607Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: get the screenpipe desktop app for the full experience
[URL_WITH_CREDENTIALS] record
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-05-12T09:21:07.201625Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store
checking permissions...
screen recording: ok
microphone: ok
accessibility: ok
2026-05-12T09:21:07.328817Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-05-12T09:21:10.020463Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-05-12T09:21:10.024711Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-05-12T09:21:10.025571Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-05-12T09:21:10.055207Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true
2026-05-12T09:21:10.055275Z INFO screenpipe: meeting detector enabled — independent of transcription mode
2026-05-12T09:21:10.666779Z INFO screenpipe: API server listening on [IP_ADDRESS]:3030 (localhost only)
2026-05-12T09:21:10.666832Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key
2026-05-12T09:21:10.666681Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)
2026-05-12T09:21:10.666983Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager
2026-05-12T09:21:10.666647Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)
2026-05-12T09:21:10.673969Z INFO screenpipe_core::pipes: loaded pipe: day-recap
2026-05-12T09:21:10.675449Z INFO screenpipe_core::pipes: loaded pipe: standup-update
2026-05-12T09:21:10.676236Z INFO screenpipe_core::pipes: loaded pipe: ai-habits
2026-05-12T09:21:10.676638Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown
2026-05-12T09:21:10.677056Z INFO screenpipe_core::pipes: loaded pipe: video-export
2026-05-12T09:21:10.677293Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary
2026-05-12T09:21:10.677398Z INFO screenpipe_core::pipes: loaded 6 pipes from "/Users/lukas/.screenpipe/pipes"
_
__________________ ___ ____ ____ (_____ ___
/ ___/ ___/ ___/ _ \/ _ \/ __ \ / __ \/ / __ \/ _ \
(__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/
/____/\___/_/ \___/\___/_/ /_/ / .___/_/ .___/\___/
/_/ /_/
power AI by everything you've seen, said or heard
open source | runs locally | developer friendly
┌────────────────────────┬────────────────────────────────────┐
│ setting │ value │
├────────────────────────┼────────────────────────────────────┤
│ audio chunk duration │ 30 seconds │
│ port │ 3030 │
│ audio disabled │ false │
│ vision disabled │ false │
│ pause on DRM content │ false │
│ audio engine │ Parakeet │
│ vad engine │ Silero │
│ data directory │ /Users/lukas/.screenpipe │
│ debug mode │ false │
│ telemetry │ true │
│ use pii removal │ true │
│ use all monitors │ true │
│ ignored windows │ [] │
│ included windows │ [] │
│ cloud sync │ disabled │
│ auto-destruct pid │ 0 │
│ deepgram key │ not set │
│ api auth │ enabled │
│ encrypt secrets │ disabled │
│ retention days │ 14 │
│ retention mode │ media-only (keep transcripts) │
├────────────────────────┼────────────────────────────────────┤
│ languages │ │
│ │ all languages │
├────────────────────────┼────────────────────────────────────┤
│ monitors │ │
│ │ id: 1 │
│ │ id: 2 │
├────────────────────────┼────────────────────────────────────┤
│ audio devices │ │
│ │ MacBook Pro Microphone (input) │
│ │ System Audio (output) │
└────────────────────────┴────────────────────────────────────┘
you are using local processing. all your data stays on your computer.
warning: telemetry is enabled. only error-level data will be sent.
to disable, use the --disable-telemetry flag.
check latest changes here: https://github.com/screenpipe/screenpipe/releases
2026-05-12T09:21:10.684547Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)
2026-05-12T09:21:10.686111Z INFO screenpipe: starting UI event capture
2026-05-12T09:21:10.696691Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh
2026-05-12T09:21:10.705742Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))
2026-05-12T09:21:10.712331Z INFO screenpipe_engine::ui_recorder: Starting UI event capture
2026-05-12T09:21:10.753596Z INFO screenpipe_engine::ui_recorder: UI recording session started: eee53fe6-52d6-4c4e-a7e5-11ede410f444
2026-05-12T09:21:10.753638Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)
2026-05-12T09:21:10.753679Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-11 06:21:10.753677 UTC to 2026-05-12 06:21:10.753677 UTC)
2026-05-12T09:21:10.754945Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)
2026-05-12T09:21:10.764596Z INFO screenpipe_engine::server: Server listening on [IP_ADDRESS]:3030
2026-05-12T09:21:10.771437Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030
2026-05-12T09:21:15.451981Z WARN sqlx::query: summary="SELECT f.id, f.timestamp, f.offset_index, …" db.statement="\n\nSELECT\n f.id,\n f.timestamp,\n f.offset_index,\n COALESCE(\n SUBSTR(f.full_text, 1, 200),\n SUBSTR(f.accessibility_text, 1, 200),\n (\n SELECT\n SUBSTR(ot.text, 1, 200)\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as text,\n COALESCE(\n f.app_name,\n (\n SELECT\n ot.app_name\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as app_name,\n COALESCE(\n f.window_name,\n (\n SELECT\n ot.window_name\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as window_name,\n COALESCE(vc.device_name, f.device_name) as screen_device,\n COALESCE(vc.file_path, f.snapshot_path) as video_path,\n COALESCE(vc.fps, 0.033) as chunk_fps,\n f.browser_url,\n f.machine_id\nFROM\n ...
|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"ggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:27:49.369341Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:29:51.512607Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:31:53.426255Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:33:55.437876Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:35:57.413206Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\n2026-05-11T22:37:14.870936Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=0 elapsed=1.714129166s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:37:59.603705Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:40:02.174925Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:42:04.809914Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T22:42:16.957748Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=0 elapsed=1.95758825s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:44:07.738461Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:46:10.863483Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:48:13.767660Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:50:16.132089Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:52:18.678586Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T22:52:18.727748Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=0 elapsed=1.378493375s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:54:20.840336Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T22:54:38.134704Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T22:54:38.619890Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for soundcore AeroClip (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-11T22:54:38.630348Z WARN screenpipe_audio::audio_manager::manager: recording for device soundcore AeroClip (input) exited with error: stream rebuild required after screen unlock for soundcore AeroClip (input) (recovery is automatic via device_monitor)\n2026-05-11T22:54:38.810449Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T22:54:40.719100Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for soundcore AeroClip (input), cleaning up for restart\n2026-05-11T22:54:40.719269Z INFO screenpipe_audio::device::device_manager: Stopping device: soundcore AeroClip (input)\n2026-05-11T22:54:41.038928Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-11T22:54:41.039052Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: soundcore AeroClip (input)\n2026-05-11T22:54:41.039131Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n2026-05-11T22:54:42.005620Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-11T22:54:44.076894Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-11T22:54:48.213325Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=0 rows_returned=234 elapsed=1.275494791s\n2026-05-11T22:54:48.379801Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\nzsh: terminated npx screenpipe@latest record\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-05-12T09:21:07.201625Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store\nchecking permissions...\n screen recording: ok\n microphone: ok\n accessibility: ok\n2026-05-12T09:21:07.328817Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-05-12T09:21:10.020463Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-05-12T09:21:10.024711Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-05-12T09:21:10.025571Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-05-12T09:21:10.055207Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true\n2026-05-12T09:21:10.055275Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-05-12T09:21:10.666779Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-05-12T09:21:10.666832Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-05-12T09:21:10.666681Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-05-12T09:21:10.666983Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-05-12T09:21:10.666647Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-05-12T09:21:10.673969Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-05-12T09:21:10.675449Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-05-12T09:21:10.676236Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-05-12T09:21:10.676638Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-05-12T09:21:10.677056Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-05-12T09:21:10.677293Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-05-12T09:21:10.677398Z INFO screenpipe_core::pipes: loaded 6 pipes from \"/Users/lukas/.screenpipe/pipes\"\n\n\n\n _ \n __________________ ___ ____ ____ (_____ ___ \n / ___/ ___/ ___/ _ \\/ _ \\/ __ \\ / __ \\/ / __ \\/ _ \\\n (__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/\n/____/\\___/_/ \\___/\\___/_/ /_/ / .___/_/ .___/\\___/ \n /_/ /_/ \n\n\n\npower AI by everything you've seen, said or heard\nopen source | runs locally | developer friendly\n\n\n┌────────────────────────┬────────────────────────────────────┐\n│ setting │ value │\n├────────────────────────┼────────────────────────────────────┤\n│ audio chunk duration │ 30 seconds │\n│ port │ 3030 │\n│ audio disabled │ false │\n│ vision disabled │ false │\n│ pause on DRM content │ false │\n│ audio engine │ Parakeet │\n│ vad engine │ Silero │\n│ data directory │ /Users/lukas/.screenpipe │\n│ debug mode │ false │\n│ telemetry │ true │\n│ use pii removal │ true │\n│ use all monitors │ true │\n│ ignored windows │ [] │\n│ included windows │ [] │\n│ cloud sync │ disabled │\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n│ retention mode │ media-only (keep transcripts) │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ MacBook Pro Microphone (input) │\n│ │ System Audio (output) │\n└────────────────────────┴────────────────────────────────────┘\nyou are using local processing. all your data stays on your computer.\n\nwarning: telemetry is enabled. only error-level data will be sent.\nto disable, use the --disable-telemetry flag.\n\ncheck latest changes here: https://github.com/screenpipe/screenpipe/releases\n2026-05-12T09:21:10.684547Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\n2026-05-12T09:21:10.686111Z INFO screenpipe: starting UI event capture\n2026-05-12T09:21:10.696691Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n2026-05-12T09:21:10.705742Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-05-12T09:21:10.712331Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-05-12T09:21:10.753596Z INFO screenpipe_engine::ui_recorder: UI recording session started: eee53fe6-52d6-4c4e-a7e5-11ede410f444\n2026-05-12T09:21:10.753638Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-05-12T09:21:10.753679Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-11 06:21:10.753677 UTC to 2026-05-12 06:21:10.753677 UTC)\n2026-05-12T09:21:10.754945Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-05-12T09:21:10.764596Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-05-12T09:21:10.771437Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-05-12T09:21:15.451981Z WARN sqlx::query: summary=\"SELECT f.id, f.timestamp, f.offset_index, …\" db.statement=\"\\n\\nSELECT\\n f.id,\\n f.timestamp,\\n f.offset_index,\\n COALESCE(\\n SUBSTR(f.full_text, 1, 200),\\n SUBSTR(f.accessibility_text, 1, 200),\\n (\\n SELECT\\n SUBSTR(ot.text, 1, 200)\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as text,\\n COALESCE(\\n f.app_name,\\n (\\n SELECT\\n ot.app_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as app_name,\\n COALESCE(\\n f.window_name,\\n (\\n SELECT\\n ot.window_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as window_name,\\n COALESCE(vc.device_name, f.device_name) as screen_device,\\n COALESCE(vc.file_path, f.snapshot_path) as video_path,\\n COALESCE(vc.fps, 0.033) as chunk_fps,\\n f.browser_url,\\n f.machine_id\\nFROM\\n frames f\\n LEFT JOIN video_chunks vc ON f.video_chunk_id = vc.id\\nWHERE\\n f.timestamp >= ?1\\n AND f.timestamp <= ?2\\n AND COALESCE(vc.file_path, f.snapshot_path, '') NOT LIKE 'cloud://%'\\nORDER BY\\n f.timestamp DESC,\\n f.offset_index DESC\\nLIMIT\\n 10000\\n\" rows_affected=0 rows_returned=6633 elapsed=4.697616625s\n2026-05-12T09:21:15.476188Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 6633 frame entries, coverage from 2026-05-11 06:21:10.753677 UTC\n2026-05-12T09:21:16.549935Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-05-12T09:21:16.550139Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-05-12T09:21:16.550184Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-05-12T09:21:19.459497Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)\n2026-05-12T09:21:19.463986Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-05-12T09:21:19.465573Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)\n2026-05-12T09:21:19.467110Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)\n2026-05-12T09:21:19.468420Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-05-12T09:21:20.691544Z INFO screenpipe_audio::transcription::engine: whisper model available: \"/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin\"\n2026-05-12T09:21:20.692520Z INFO screenpipe_audio::transcription::whisper::model: whisper context: gpu acceleration enabled (Metal on macOS, Vulkan on Windows)\n2026-05-12T09:21:20.692565Z INFO screenpipe_audio::transcription::engine: loading whisper model with GPU acceleration...\nwhisper_init_from_file_with_params_no_state: loading model from '/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin'\nwhisper_init_with_params_no_state: use gpu = 1\nwhisper_init_with_params_no_state: flash attn = 0\nwhisper_init_with_params_no_state: gpu_device = 0\nwhisper_init_with_params_no_state: dtw = 0\nggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices\nggml_metal_library_init: using embedded metal library\nggml_metal_library_init: loaded in 0.036 sec\nggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)\nggml_metal_device_init: GPU name: Apple M1\nggml_metal_device_init: GPU family: MTLGPUFamilyApple7 (1007)\nggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)\nggml_metal_device_init: GPU family: MTLGPUFamilyMetal3 (5001)\nggml_metal_device_init: simdgroup reduction = true\nggml_metal_device_init: simdgroup matrix mul. = true\nggml_metal_device_init: has unified memory = true\nggml_metal_device_init: has bfloat = true\nggml_metal_device_init: has tensor = false\nggml_metal_device_init: use residency sets = true\nggml_metal_device_init: use shared buffers = true\nggml_metal_device_init: recommendedMaxWorkingSetSize = 11453.25 MB\nwhisper_init_with_params_no_state: devices = 3\nwhisper_init_with_params_no_state: backends = 3\nwhisper_model_load: loading model\nwhisper_model_load: n_vocab = 51865\nwhisper_model_load: n_audio_ctx = 1500\nwhisper_model_load: n_audio_state = 384\nwhisper_model_load: n_audio_head = 6\nwhisper_model_load: n_audio_layer = 4\nwhisper_model_load: n_text_ctx = 448\nwhisper_model_load: n_text_state = 384\nwhisper_model_load: n_text_head = 6\nwhisper_model_load: n_text_layer = 4\nwhisper_model_load: n_mels = 80\nwhisper_model_load: ftype = 1\nwhisper_model_load: qntvr = 0\nwhisper_model_load: type = 1 (tiny)\nwhisper_model_load: adding 1608 extra tokens\nwhisper_model_load: n_langs = 99\nwhisper_model_load: Metal total size = 77.11 MB\nwhisper_model_load: model size = 77.11 MB\n2026-05-12T09:21:20.866406Z INFO screenpipe_audio::transcription::engine: whisper model loaded successfully\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\n2026-05-12T09:21:20.896976Z INFO screenpipe_audio::audio_manager::manager: transcription session created (will be reused across segments)\n2026-05-12T09:21:20.928794Z INFO screenpipe_audio::audio_manager::manager: seeded 14 speakers (named + unnamed) from DB into embedding manager\n2026-05-12T09:21:20.929372Z INFO screenpipe_audio::audio_manager::manager: audio manager started\n2026-05-12T09:21:20.930136Z INFO screenpipe_audio::audio_manager::manager: calendar-assisted speaker diarization: listening for meeting events\n2026-05-12T09:21:21.212480Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-12T09:21:22.112224Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)","depth":4,"on_screen":true,"value":"ggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:27:49.369341Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:29:51.512607Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:31:53.426255Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:33:55.437876Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:35:57.413206Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\n2026-05-11T22:37:14.870936Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=0 elapsed=1.714129166s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:37:59.603705Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:40:02.174925Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:42:04.809914Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T22:42:16.957748Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=0 elapsed=1.95758825s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:44:07.738461Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:46:10.863483Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:48:13.767660Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:50:16.132089Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:52:18.678586Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T22:52:18.727748Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=0 elapsed=1.378493375s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:54:20.840336Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T22:54:38.134704Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T22:54:38.619890Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for soundcore AeroClip (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-11T22:54:38.630348Z WARN screenpipe_audio::audio_manager::manager: recording for device soundcore AeroClip (input) exited with error: stream rebuild required after screen unlock for soundcore AeroClip (input) (recovery is automatic via device_monitor)\n2026-05-11T22:54:38.810449Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T22:54:40.719100Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for soundcore AeroClip (input), cleaning up for restart\n2026-05-11T22:54:40.719269Z INFO screenpipe_audio::device::device_manager: Stopping device: soundcore AeroClip (input)\n2026-05-11T22:54:41.038928Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-11T22:54:41.039052Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: soundcore AeroClip (input)\n2026-05-11T22:54:41.039131Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n2026-05-11T22:54:42.005620Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-11T22:54:44.076894Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-11T22:54:48.213325Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=0 rows_returned=234 elapsed=1.275494791s\n2026-05-11T22:54:48.379801Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\nzsh: terminated npx screenpipe@latest record\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-05-12T09:21:07.201625Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store\nchecking permissions...\n screen recording: ok\n microphone: ok\n accessibility: ok\n2026-05-12T09:21:07.328817Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-05-12T09:21:10.020463Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-05-12T09:21:10.024711Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-05-12T09:21:10.025571Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-05-12T09:21:10.055207Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true\n2026-05-12T09:21:10.055275Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-05-12T09:21:10.666779Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-05-12T09:21:10.666832Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-05-12T09:21:10.666681Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-05-12T09:21:10.666983Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-05-12T09:21:10.666647Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-05-12T09:21:10.673969Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-05-12T09:21:10.675449Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-05-12T09:21:10.676236Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-05-12T09:21:10.676638Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-05-12T09:21:10.677056Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-05-12T09:21:10.677293Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-05-12T09:21:10.677398Z INFO screenpipe_core::pipes: loaded 6 pipes from \"/Users/lukas/.screenpipe/pipes\"\n\n\n\n _ \n __________________ ___ ____ ____ (_____ ___ \n / ___/ ___/ ___/ _ \\/ _ \\/ __ \\ / __ \\/ / __ \\/ _ \\\n (__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/\n/____/\\___/_/ \\___/\\___/_/ /_/ / .___/_/ .___/\\___/ \n /_/ /_/ \n\n\n\npower AI by everything you've seen, said or heard\nopen source | runs locally | developer friendly\n\n\n┌────────────────────────┬────────────────────────────────────┐\n│ setting │ value │\n├────────────────────────┼────────────────────────────────────┤\n│ audio chunk duration │ 30 seconds │\n│ port │ 3030 │\n│ audio disabled │ false │\n│ vision disabled │ false │\n│ pause on DRM content │ false │\n│ audio engine │ Parakeet │\n│ vad engine │ Silero │\n│ data directory │ /Users/lukas/.screenpipe │\n│ debug mode │ false │\n│ telemetry │ true │\n│ use pii removal │ true │\n│ use all monitors │ true │\n│ ignored windows │ [] │\n│ included windows │ [] │\n│ cloud sync │ disabled │\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n│ retention mode │ media-only (keep transcripts) │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ MacBook Pro Microphone (input) │\n│ │ System Audio (output) │\n└────────────────────────┴────────────────────────────────────┘\nyou are using local processing. all your data stays on your computer.\n\nwarning: telemetry is enabled. only error-level data will be sent.\nto disable, use the --disable-telemetry flag.\n\ncheck latest changes here: https://github.com/screenpipe/screenpipe/releases\n2026-05-12T09:21:10.684547Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\n2026-05-12T09:21:10.686111Z INFO screenpipe: starting UI event capture\n2026-05-12T09:21:10.696691Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n2026-05-12T09:21:10.705742Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-05-12T09:21:10.712331Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-05-12T09:21:10.753596Z INFO screenpipe_engine::ui_recorder: UI recording session started: eee53fe6-52d6-4c4e-a7e5-11ede410f444\n2026-05-12T09:21:10.753638Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-05-12T09:21:10.753679Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-11 06:21:10.753677 UTC to 2026-05-12 06:21:10.753677 UTC)\n2026-05-12T09:21:10.754945Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-05-12T09:21:10.764596Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-05-12T09:21:10.771437Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-05-12T09:21:15.451981Z WARN sqlx::query: summary=\"SELECT f.id, f.timestamp, f.offset_index, …\" db.statement=\"\\n\\nSELECT\\n f.id,\\n f.timestamp,\\n f.offset_index,\\n COALESCE(\\n SUBSTR(f.full_text, 1, 200),\\n SUBSTR(f.accessibility_text, 1, 200),\\n (\\n SELECT\\n SUBSTR(ot.text, 1, 200)\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as text,\\n COALESCE(\\n f.app_name,\\n (\\n SELECT\\n ot.app_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as app_name,\\n COALESCE(\\n f.window_name,\\n (\\n SELECT\\n ot.window_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as window_name,\\n COALESCE(vc.device_name, f.device_name) as screen_device,\\n COALESCE(vc.file_path, f.snapshot_path) as video_path,\\n COALESCE(vc.fps, 0.033) as chunk_fps,\\n f.browser_url,\\n f.machine_id\\nFROM\\n frames f\\n LEFT JOIN video_chunks vc ON f.video_chunk_id = vc.id\\nWHERE\\n f.timestamp >= ?1\\n AND f.timestamp <= ?2\\n AND COALESCE(vc.file_path, f.snapshot_path, '') NOT LIKE 'cloud://%'\\nORDER BY\\n f.timestamp DESC,\\n f.offset_index DESC\\nLIMIT\\n 10000\\n\" rows_affected=0 rows_returned=6633 elapsed=4.697616625s\n2026-05-12T09:21:15.476188Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 6633 frame entries, coverage from 2026-05-11 06:21:10.753677 UTC\n2026-05-12T09:21:16.549935Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-05-12T09:21:16.550139Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-05-12T09:21:16.550184Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-05-12T09:21:19.459497Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)\n2026-05-12T09:21:19.463986Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-05-12T09:21:19.465573Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)\n2026-05-12T09:21:19.467110Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)\n2026-05-12T09:21:19.468420Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-05-12T09:21:20.691544Z INFO screenpipe_audio::transcription::engine: whisper model available: \"/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin\"\n2026-05-12T09:21:20.692520Z INFO screenpipe_audio::transcription::whisper::model: whisper context: gpu acceleration enabled (Metal on macOS, Vulkan on Windows)\n2026-05-12T09:21:20.692565Z INFO screenpipe_audio::transcription::engine: loading whisper model with GPU acceleration...\nwhisper_init_from_file_with_params_no_state: loading model from '/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin'\nwhisper_init_with_params_no_state: use gpu = 1\nwhisper_init_with_params_no_state: flash attn = 0\nwhisper_init_with_params_no_state: gpu_device = 0\nwhisper_init_with_params_no_state: dtw = 0\nggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices\nggml_metal_library_init: using embedded metal library\nggml_metal_library_init: loaded in 0.036 sec\nggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)\nggml_metal_device_init: GPU name: Apple M1\nggml_metal_device_init: GPU family: MTLGPUFamilyApple7 (1007)\nggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)\nggml_metal_device_init: GPU family: MTLGPUFamilyMetal3 (5001)\nggml_metal_device_init: simdgroup reduction = true\nggml_metal_device_init: simdgroup matrix mul. = true\nggml_metal_device_init: has unified memory = true\nggml_metal_device_init: has bfloat = true\nggml_metal_device_init: has tensor = false\nggml_metal_device_init: use residency sets = true\nggml_metal_device_init: use shared buffers = true\nggml_metal_device_init: recommendedMaxWorkingSetSize = 11453.25 MB\nwhisper_init_with_params_no_state: devices = 3\nwhisper_init_with_params_no_state: backends = 3\nwhisper_model_load: loading model\nwhisper_model_load: n_vocab = 51865\nwhisper_model_load: n_audio_ctx = 1500\nwhisper_model_load: n_audio_state = 384\nwhisper_model_load: n_audio_head = 6\nwhisper_model_load: n_audio_layer = 4\nwhisper_model_load: n_text_ctx = 448\nwhisper_model_load: n_text_state = 384\nwhisper_model_load: n_text_head = 6\nwhisper_model_load: n_text_layer = 4\nwhisper_model_load: n_mels = 80\nwhisper_model_load: ftype = 1\nwhisper_model_load: qntvr = 0\nwhisper_model_load: type = 1 (tiny)\nwhisper_model_load: adding 1608 extra tokens\nwhisper_model_load: n_langs = 99\nwhisper_model_load: Metal total size = 77.11 MB\nwhisper_model_load: model size = 77.11 MB\n2026-05-12T09:21:20.866406Z INFO screenpipe_audio::transcription::engine: whisper model loaded successfully\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\n2026-05-12T09:21:20.896976Z INFO screenpipe_audio::audio_manager::manager: transcription session created (will be reused across segments)\n2026-05-12T09:21:20.928794Z INFO screenpipe_audio::audio_manager::manager: seeded 14 speakers (named + unnamed) from DB into embedding manager\n2026-05-12T09:21:20.929372Z INFO screenpipe_audio::audio_manager::manager: audio manager started\n2026-05-12T09:21:20.930136Z INFO screenpipe_audio::audio_manager::manager: calendar-assisted speaker diarization: listening for meeting events\n2026-05-12T09:21:21.212480Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-12T09:21:22.112224Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.0,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.004166667,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (-zsh)","depth":2,"bounds":{"left":0.140625,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.14479166,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.28125,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.28541666,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.421875,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.42604166,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.5625,"top":0.05888889,"width":0.14027777,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.56666666,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.7027778,"top":0.05888889,"width":0.14027777,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.70694447,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.84305555,"top":0.05888889,"width":0.14027777,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.8472222,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.9548611,"top":0.032222223,"width":0.03888889,"height":0.018888889},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"screenpipe\"","depth":1,"bounds":{"left":0.47083333,"top":0.033333335,"width":0.058333334,"height":0.017777778},"on_screen":true,"role_description":"text"}]...
|
-8051471798226442119
|
-852231715036531232
|
manual
|
accessibility
|
NULL
|
ggml_metal_init: allocating
ggml_metal_init: found ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:27:49.369341Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:29:51.512607Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: get the screenpipe desktop app for the full experience
[URL_WITH_CREDENTIALS] record
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-05-12T09:21:07.201625Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store
checking permissions...
screen recording: ok
microphone: ok
accessibility: ok
2026-05-12T09:21:07.328817Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-05-12T09:21:10.020463Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-05-12T09:21:10.024711Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-05-12T09:21:10.025571Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-05-12T09:21:10.055207Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true
2026-05-12T09:21:10.055275Z INFO screenpipe: meeting detector enabled — independent of transcription mode
2026-05-12T09:21:10.666779Z INFO screenpipe: API server listening on [IP_ADDRESS]:3030 (localhost only)
2026-05-12T09:21:10.666832Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key
2026-05-12T09:21:10.666681Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)
2026-05-12T09:21:10.666983Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager
2026-05-12T09:21:10.666647Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)
2026-05-12T09:21:10.673969Z INFO screenpipe_core::pipes: loaded pipe: day-recap
2026-05-12T09:21:10.675449Z INFO screenpipe_core::pipes: loaded pipe: standup-update
2026-05-12T09:21:10.676236Z INFO screenpipe_core::pipes: loaded pipe: ai-habits
2026-05-12T09:21:10.676638Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown
2026-05-12T09:21:10.677056Z INFO screenpipe_core::pipes: loaded pipe: video-export
2026-05-12T09:21:10.677293Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary
2026-05-12T09:21:10.677398Z INFO screenpipe_core::pipes: loaded 6 pipes from "/Users/lukas/.screenpipe/pipes"
_
__________________ ___ ____ ____ (_____ ___
/ ___/ ___/ ___/ _ \/ _ \/ __ \ / __ \/ / __ \/ _ \
(__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/
/____/\___/_/ \___/\___/_/ /_/ / .___/_/ .___/\___/
/_/ /_/
power AI by everything you've seen, said or heard
open source | runs locally | developer friendly
┌────────────────────────┬────────────────────────────────────┐
│ setting │ value │
├────────────────────────┼────────────────────────────────────┤
│ audio chunk duration │ 30 seconds │
│ port │ 3030 │
│ audio disabled │ false │
│ vision disabled │ false │
│ pause on DRM content │ false │
│ audio engine │ Parakeet │
│ vad engine │ Silero │
│ data directory │ /Users/lukas/.screenpipe │
│ debug mode │ false │
│ telemetry │ true │
│ use pii removal │ true │
│ use all monitors │ true │
│ ignored windows │ [] │
│ included windows │ [] │
│ cloud sync │ disabled │
│ auto-destruct pid │ 0 │
│ deepgram key │ not set │
│ api auth │ enabled │
│ encrypt secrets │ disabled │
│ retention days │ 14 │
│ retention mode │ media-only (keep transcripts) │
├────────────────────────┼────────────────────────────────────┤
│ languages │ │
│ │ all languages │
├────────────────────────┼────────────────────────────────────┤
│ monitors │ │
│ │ id: 1 │
│ │ id: 2 │
├────────────────────────┼────────────────────────────────────┤
│ audio devices │ │
│ │ MacBook Pro Microphone (input) │
│ │ System Audio (output) │
└────────────────────────┴────────────────────────────────────┘
you are using local processing. all your data stays on your computer.
warning: telemetry is enabled. only error-level data will be sent.
to disable, use the --disable-telemetry flag.
check latest changes here: https://github.com/screenpipe/screenpipe/releases
2026-05-12T09:21:10.684547Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)
2026-05-12T09:21:10.686111Z INFO screenpipe: starting UI event capture
2026-05-12T09:21:10.696691Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh
2026-05-12T09:21:10.705742Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))
2026-05-12T09:21:10.712331Z INFO screenpipe_engine::ui_recorder: Starting UI event capture
2026-05-12T09:21:10.753596Z INFO screenpipe_engine::ui_recorder: UI recording session started: eee53fe6-52d6-4c4e-a7e5-11ede410f444
2026-05-12T09:21:10.753638Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)
2026-05-12T09:21:10.753679Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-11 06:21:10.753677 UTC to 2026-05-12 06:21:10.753677 UTC)
2026-05-12T09:21:10.754945Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)
2026-05-12T09:21:10.764596Z INFO screenpipe_engine::server: Server listening on [IP_ADDRESS]:3030
2026-05-12T09:21:10.771437Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030
2026-05-12T09:21:15.451981Z WARN sqlx::query: summary="SELECT f.id, f.timestamp, f.offset_index, …" db.statement="\n\nSELECT\n f.id,\n f.timestamp,\n f.offset_index,\n COALESCE(\n SUBSTR(f.full_text, 1, 200),\n SUBSTR(f.accessibility_text, 1, 200),\n (\n SELECT\n SUBSTR(ot.text, 1, 200)\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as text,\n COALESCE(\n f.app_name,\n (\n SELECT\n ot.app_name\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as app_name,\n COALESCE(\n f.window_name,\n (\n SELECT\n ot.window_name\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as window_name,\n COALESCE(vc.device_name, f.device_name) as screen_device,\n COALESCE(vc.file_path, f.snapshot_path) as video_path,\n COALESCE(vc.fps, 0.033) as chunk_fps,\n f.browser_url,\n f.machine_id\nFROM\n ...
|
NULL
|
NULL
|
NULL
|
NULL
|
|
21798
|
954
|
9
|
2026-05-12T06:24:15.428810+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-12/1778 /Users/lukas/.screenpipe/data/data/2026-05-12/1778567055428_m1.jpg...
|
iTerm2
|
screenpipe"
|
True
|
NULL
|
monitor_1
|
NULL
|
NULL
|
NULL
|
NULL
|
whisper_init_state: kv pad size = 2.36 MB
whi whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:33:55.437876Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:35:57.413206Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
2026-05-11T22:37:14.870936Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=0 elapsed=1.714129166s
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:37:59.603705Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:40:02.174925Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: install a starter bundle of pipes:
screenpipe install [URL_WITH_CREDENTIALS] record
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-05-12T09:21:07.201625Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store
checking permissions...
screen recording: ok
microphone: ok
accessibility: ok
2026-05-12T09:21:07.328817Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-05-12T09:21:10.020463Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-05-12T09:21:10.024711Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-05-12T09:21:10.025571Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-05-12T09:21:10.055207Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true
2026-05-12T09:21:10.055275Z INFO screenpipe: meeting detector enabled — independent of transcription mode
2026-05-12T09:21:10.666779Z INFO screenpipe: API server listening on [IP_ADDRESS]:3030 (localhost only)
2026-05-12T09:21:10.666832Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key
2026-05-12T09:21:10.666681Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)
2026-05-12T09:21:10.666983Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager
2026-05-12T09:21:10.666647Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)
2026-05-12T09:21:10.673969Z INFO screenpipe_core::pipes: loaded pipe: day-recap
2026-05-12T09:21:10.675449Z INFO screenpipe_core::pipes: loaded pipe: standup-update
2026-05-12T09:21:10.676236Z INFO screenpipe_core::pipes: loaded pipe: ai-habits
2026-05-12T09:21:10.676638Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown
2026-05-12T09:21:10.677056Z INFO screenpipe_core::pipes: loaded pipe: video-export
2026-05-12T09:21:10.677293Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary
2026-05-12T09:21:10.677398Z INFO screenpipe_core::pipes: loaded 6 pipes from "/Users/lukas/.screenpipe/pipes"
_
__________________ ___ ____ ____ (_____ ___
/ ___/ ___/ ___/ _ \/ _ \/ __ \ / __ \/ / __ \/ _ \
(__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/
/____/\___/_/ \___/\___/_/ /_/ / .___/_/ .___/\___/
/_/ /_/
power AI by everything you've seen, said or heard
open source | runs locally | developer friendly
┌────────────────────────┬────────────────────────────────────┐
│ setting │ value │
├────────────────────────┼────────────────────────────────────┤
│ audio chunk duration │ 30 seconds │
│ port │ 3030 │
│ audio disabled │ false │
│ vision disabled │ false │
│ pause on DRM content │ false │
│ audio engine │ Parakeet │
│ vad engine │ Silero │
│ data directory │ /Users/lukas/.screenpipe │
│ debug mode │ false │
│ telemetry │ true │
│ use pii removal │ true │
│ use all monitors │ true │
│ ignored windows │ [] │
│ included windows │ [] │
│ cloud sync │ disabled │
│ auto-destruct pid │ 0 │
│ deepgram key │ not set │
│ api auth │ enabled │
│ encrypt secrets │ disabled │
│ retention days │ 14 │
│ retention mode │ media-only (keep transcripts) │
├────────────────────────┼────────────────────────────────────┤
│ languages │ │
│ │ all languages │
├────────────────────────┼────────────────────────────────────┤
│ monitors │ │
│ │ id: 1 │
│ │ id: 2 │
├────────────────────────┼────────────────────────────────────┤
│ audio devices │ │
│ │ MacBook Pro Microphone (input) │
│ │ System Audio (output) │
└────────────────────────┴────────────────────────────────────┘
you are using local processing. all your data stays on your computer.
warning: telemetry is enabled. only error-level data will be sent.
to disable, use the --disable-telemetry flag.
check latest changes here: https://github.com/screenpipe/screenpipe/releases
2026-05-12T09:21:10.684547Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)
2026-05-12T09:21:10.686111Z INFO screenpipe: starting UI event capture
2026-05-12T09:21:10.696691Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh
2026-05-12T09:21:10.705742Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))
2026-05-12T09:21:10.712331Z INFO screenpipe_engine::ui_recorder: Starting UI event capture
2026-05-12T09:21:10.753596Z INFO screenpipe_engine::ui_recorder: UI recording session started: eee53fe6-52d6-4c4e-a7e5-11ede410f444
2026-05-12T09:21:10.753638Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)
2026-05-12T09:21:10.753679Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-11 06:21:10.753677 UTC to 2026-05-12 06:21:10.753677 UTC)
2026-05-12T09:21:10.754945Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)
2026-05-12T09:21:10.764596Z INFO screenpipe_engine::server: Server listening on [IP_ADDRESS]:3030
2026-05-12T09:21:10.771437Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030
2026-05-12T09:21:15.451981Z WARN sqlx::query: summary="SELECT f.id, f.timestamp, f.offset_index, …" db.statement="\n\nSELECT\n f.id,\n f.timestamp,\n f.offset_index,\n COALESCE(\n SUBSTR(f.full_text, 1, 200),\n SUBSTR(f.accessibility_text, 1, 200),\n (\n SELECT\n SUBSTR(ot.text, 1, 200)\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as text,\n COALESCE(\n f.app_name,\n (\n SELECT\n ot.app_name\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as app_name,\n COALESCE(\n f.window_name,\n (\n SELECT\n ot.window_name\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as window_name,\n COALESCE(vc.device_name, f.device_name) as screen_device,\n COALESCE(vc.file_path, f.snapshot_path) as video_path,\n COALESCE(vc.fps, 0.033) as chunk_fps,\n f.browser_url,\n f.machine_id\nFROM\n frames f\n LEFT JOIN video_chunks vc ON f.video_chunk_id = vc.id\nWHERE\n f.timestamp >= ?1\n AND f.timestamp <= ?2\n AND COALESCE(vc.file_path, f.snapshot_path, '') NOT LIKE 'cloud://%'\nORDER BY\n f.timestamp DESC,\n f.offset_index DESC\nLIMIT\n 10000\n" rows_affected=0 rows_returned=6633 elapsed=4.697616625s
2026-05-12T09:21:15.476188Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 6633 frame entries, coverage from 2026-05-11 06:21:10.753677 UTC
2026-05-12T09:21:16.549935Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)
2026-05-12T09:21:16.550139Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)
2026-05-12T09:21:16.550184Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)
2026-05-12T09:21:19.459497Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)
2026-05-12T09:21:19.463986Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)
2026-05-12T09:21:19.465573Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)
2026-05-12T09:21:19.467110Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)
2026-05-12T09:21:19.468420Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)
2026-05-12T09:21:20.691544Z INFO screenpipe_audio::transcription::engine: whisper model available: "/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin"
2026-05-12T09:21:20.692520Z INFO screenpipe_audio::transcription::whisper::model: whisper context: gpu acceleration enabled (Metal on macOS, Vulkan on Windows)
2026-05-12T09:21:20.692565Z INFO screenpipe_audio::transcription::engine: loading whisper model with GPU acceleration...
whisper_init_from_file_with_params_no_state: loading model from '/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin'
whisper_init_with_params_no_state: use gpu = 1
whisper_init_with_params_no_state: flash attn = 0
whisper_init_with_params_no_state: gpu_device = 0
whisper_init_with_params_no_state: dtw = 0
ggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices
ggml_metal_library_init: using embedded metal library
ggml_metal_library_init: loaded in 0.036 sec
ggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)
ggml_metal_device_init: GPU name: Apple M1
ggml_metal_device_init: GPU family: MTLGPUFamilyApple7 (1007)
ggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)
ggml_metal_device_init: GPU family: MTLGPUFamilyMetal3 (5001)
ggml_metal_device_init: simdgroup reduction = true
ggml_metal_device_init: simdgroup matrix mul. = true
ggml_metal_device_init: has unified memory = true
ggml_metal_device_init: has bfloat = true
ggml_metal_device_init: has tensor = false
ggml_metal_device_init: use residency sets = true
ggml_metal_device_init: use shared buffers = true
ggml_metal_device_init: recommendedMaxWorkingSetSize = 11453.25 MB
whisper_init_with_params_no_state: devices = 3
whisper_init_with_params_no_state: backends = 3
whisper_model_load: loading model
whisper_model_load: n_vocab = 51865
whisper_model_load: n_audio_ctx = 1500
whisper_model_load: n_audio_state = 384
whisper_model_load: n_audio_head = 6
whisper_model_load: n_audio_layer = 4
whisper_model_load: n_text_ctx = 448
whisper_model_load: n_text_state = 384
whisper_model_load: n_text_head = 6
whisper_model_load: n_text_layer = 4
whisper_model_load: n_mels = 80
whisper_model_load: ftype = 1
whisper_model_load: qntvr = 0
whisper_model_load: type = 1 (tiny)
whisper_model_load: adding 1608 extra tokens
whisper_model_load: n_langs = 99
whisper_model_load: Metal total size = 77.11 MB
whisper_model_load: model size = 77.11 MB
2026-05-12T09:21:20.866406Z INFO screenpipe_audio::transcription::engine: whisper model loaded successfully
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
2026-05-12T09:21:20.896976Z INFO screenpipe_audio::audio_manager::manager: transcription session created (will be reused across segments)
2026-05-12T09:21:20.928794Z INFO screenpipe_audio::audio_manager::manager: seeded 14 speakers (named + unnamed) from DB into embedding manager
2026-05-12T09:21:20.929372Z INFO screenpipe_audio::audio_manager::manager: audio manager started
2026-05-12T09:21:20.930136Z INFO screenpipe_audio::audio_manager::manager: calendar-assisted speaker diarization: listening for meeting events
2026-05-12T09:21:21.212480Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-12T09:21:22.112224Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)
2026-05-12T09:21:22.697027Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 1: frame_id=21773, dur=116ms
2026-05-12T09:21:23.853614Z INFO screenpipe_audio::device::device_manager: starting recording for device: System Audio (output)
2026-05-12T09:21:23.854499Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for System Audio (output) (unknown / 30s segments)
2026-05-12T09:21:23.854491Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-12T09:21:28.046940Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)
2026-05-12T09:21:28.381213Z WARN screenpipe_a11y::tree::macos_lines: lines: AXUIElementCopyParameterizedAttributeValue(AXLineForIndex) failed status=os::Status { raw: -25212, fcc: "....", help: "https://www.osstatus.com?search=-25212" } — first failure (further failures suppressed); search highlights will fall back to paragraph bbox on this app
2026-05-12T09:21:28.684461Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 2: frame_id=21775, dur=90ms
2026-05-12T09:22:12.427026Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=2 elapsed=1.759127041s
2026-05-12T09:22:12.427274Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames
2026-05-12T09:22:12.869213Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.2MB → 0.3MB (0.9x), 1 JPEGs deleted
2026-05-12T09:22:13.304558Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.3MB → 0.4MB (0.9x), 1 JPEGs deleted
2026-05-12T09:22:39.009649Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-1944753676112650055, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency...
|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"whisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:33:55.437876Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:35:57.413206Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\n2026-05-11T22:37:14.870936Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=0 elapsed=1.714129166s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:37:59.603705Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:40:02.174925Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:42:04.809914Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T22:42:16.957748Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=0 elapsed=1.95758825s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:44:07.738461Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:46:10.863483Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:48:13.767660Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:50:16.132089Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:52:18.678586Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T22:52:18.727748Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=0 elapsed=1.378493375s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:54:20.840336Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T22:54:38.134704Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T22:54:38.619890Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for soundcore AeroClip (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-11T22:54:38.630348Z WARN screenpipe_audio::audio_manager::manager: recording for device soundcore AeroClip (input) exited with error: stream rebuild required after screen unlock for soundcore AeroClip (input) (recovery is automatic via device_monitor)\n2026-05-11T22:54:38.810449Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T22:54:40.719100Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for soundcore AeroClip (input), cleaning up for restart\n2026-05-11T22:54:40.719269Z INFO screenpipe_audio::device::device_manager: Stopping device: soundcore AeroClip (input)\n2026-05-11T22:54:41.038928Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-11T22:54:41.039052Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: soundcore AeroClip (input)\n2026-05-11T22:54:41.039131Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n2026-05-11T22:54:42.005620Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-11T22:54:44.076894Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-11T22:54:48.213325Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=0 rows_returned=234 elapsed=1.275494791s\n2026-05-11T22:54:48.379801Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\nzsh: terminated npx screenpipe@latest record\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-05-12T09:21:07.201625Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store\nchecking permissions...\n screen recording: ok\n microphone: ok\n accessibility: ok\n2026-05-12T09:21:07.328817Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-05-12T09:21:10.020463Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-05-12T09:21:10.024711Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-05-12T09:21:10.025571Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-05-12T09:21:10.055207Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true\n2026-05-12T09:21:10.055275Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-05-12T09:21:10.666779Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-05-12T09:21:10.666832Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-05-12T09:21:10.666681Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-05-12T09:21:10.666983Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-05-12T09:21:10.666647Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-05-12T09:21:10.673969Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-05-12T09:21:10.675449Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-05-12T09:21:10.676236Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-05-12T09:21:10.676638Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-05-12T09:21:10.677056Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-05-12T09:21:10.677293Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-05-12T09:21:10.677398Z INFO screenpipe_core::pipes: loaded 6 pipes from \"/Users/lukas/.screenpipe/pipes\"\n\n\n\n _ \n __________________ ___ ____ ____ (_____ ___ \n / ___/ ___/ ___/ _ \\/ _ \\/ __ \\ / __ \\/ / __ \\/ _ \\\n (__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/\n/____/\\___/_/ \\___/\\___/_/ /_/ / .___/_/ .___/\\___/ \n /_/ /_/ \n\n\n\npower AI by everything you've seen, said or heard\nopen source | runs locally | developer friendly\n\n\n┌────────────────────────┬────────────────────────────────────┐\n│ setting │ value │\n├────────────────────────┼────────────────────────────────────┤\n│ audio chunk duration │ 30 seconds │\n│ port │ 3030 │\n│ audio disabled │ false │\n│ vision disabled │ false │\n│ pause on DRM content │ false │\n│ audio engine │ Parakeet │\n│ vad engine │ Silero │\n│ data directory │ /Users/lukas/.screenpipe │\n│ debug mode │ false │\n│ telemetry │ true │\n│ use pii removal │ true │\n│ use all monitors │ true │\n│ ignored windows │ [] │\n│ included windows │ [] │\n│ cloud sync │ disabled │\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n│ retention mode │ media-only (keep transcripts) │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ MacBook Pro Microphone (input) │\n│ │ System Audio (output) │\n└────────────────────────┴────────────────────────────────────┘\nyou are using local processing. all your data stays on your computer.\n\nwarning: telemetry is enabled. only error-level data will be sent.\nto disable, use the --disable-telemetry flag.\n\ncheck latest changes here: https://github.com/screenpipe/screenpipe/releases\n2026-05-12T09:21:10.684547Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\n2026-05-12T09:21:10.686111Z INFO screenpipe: starting UI event capture\n2026-05-12T09:21:10.696691Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n2026-05-12T09:21:10.705742Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-05-12T09:21:10.712331Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-05-12T09:21:10.753596Z INFO screenpipe_engine::ui_recorder: UI recording session started: eee53fe6-52d6-4c4e-a7e5-11ede410f444\n2026-05-12T09:21:10.753638Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-05-12T09:21:10.753679Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-11 06:21:10.753677 UTC to 2026-05-12 06:21:10.753677 UTC)\n2026-05-12T09:21:10.754945Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-05-12T09:21:10.764596Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-05-12T09:21:10.771437Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-05-12T09:21:15.451981Z WARN sqlx::query: summary=\"SELECT f.id, f.timestamp, f.offset_index, …\" db.statement=\"\\n\\nSELECT\\n f.id,\\n f.timestamp,\\n f.offset_index,\\n COALESCE(\\n SUBSTR(f.full_text, 1, 200),\\n SUBSTR(f.accessibility_text, 1, 200),\\n (\\n SELECT\\n SUBSTR(ot.text, 1, 200)\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as text,\\n COALESCE(\\n f.app_name,\\n (\\n SELECT\\n ot.app_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as app_name,\\n COALESCE(\\n f.window_name,\\n (\\n SELECT\\n ot.window_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as window_name,\\n COALESCE(vc.device_name, f.device_name) as screen_device,\\n COALESCE(vc.file_path, f.snapshot_path) as video_path,\\n COALESCE(vc.fps, 0.033) as chunk_fps,\\n f.browser_url,\\n f.machine_id\\nFROM\\n frames f\\n LEFT JOIN video_chunks vc ON f.video_chunk_id = vc.id\\nWHERE\\n f.timestamp >= ?1\\n AND f.timestamp <= ?2\\n AND COALESCE(vc.file_path, f.snapshot_path, '') NOT LIKE 'cloud://%'\\nORDER BY\\n f.timestamp DESC,\\n f.offset_index DESC\\nLIMIT\\n 10000\\n\" rows_affected=0 rows_returned=6633 elapsed=4.697616625s\n2026-05-12T09:21:15.476188Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 6633 frame entries, coverage from 2026-05-11 06:21:10.753677 UTC\n2026-05-12T09:21:16.549935Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-05-12T09:21:16.550139Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-05-12T09:21:16.550184Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-05-12T09:21:19.459497Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)\n2026-05-12T09:21:19.463986Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-05-12T09:21:19.465573Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)\n2026-05-12T09:21:19.467110Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)\n2026-05-12T09:21:19.468420Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-05-12T09:21:20.691544Z INFO screenpipe_audio::transcription::engine: whisper model available: \"/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin\"\n2026-05-12T09:21:20.692520Z INFO screenpipe_audio::transcription::whisper::model: whisper context: gpu acceleration enabled (Metal on macOS, Vulkan on Windows)\n2026-05-12T09:21:20.692565Z INFO screenpipe_audio::transcription::engine: loading whisper model with GPU acceleration...\nwhisper_init_from_file_with_params_no_state: loading model from '/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin'\nwhisper_init_with_params_no_state: use gpu = 1\nwhisper_init_with_params_no_state: flash attn = 0\nwhisper_init_with_params_no_state: gpu_device = 0\nwhisper_init_with_params_no_state: dtw = 0\nggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices\nggml_metal_library_init: using embedded metal library\nggml_metal_library_init: loaded in 0.036 sec\nggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)\nggml_metal_device_init: GPU name: Apple M1\nggml_metal_device_init: GPU family: MTLGPUFamilyApple7 (1007)\nggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)\nggml_metal_device_init: GPU family: MTLGPUFamilyMetal3 (5001)\nggml_metal_device_init: simdgroup reduction = true\nggml_metal_device_init: simdgroup matrix mul. = true\nggml_metal_device_init: has unified memory = true\nggml_metal_device_init: has bfloat = true\nggml_metal_device_init: has tensor = false\nggml_metal_device_init: use residency sets = true\nggml_metal_device_init: use shared buffers = true\nggml_metal_device_init: recommendedMaxWorkingSetSize = 11453.25 MB\nwhisper_init_with_params_no_state: devices = 3\nwhisper_init_with_params_no_state: backends = 3\nwhisper_model_load: loading model\nwhisper_model_load: n_vocab = 51865\nwhisper_model_load: n_audio_ctx = 1500\nwhisper_model_load: n_audio_state = 384\nwhisper_model_load: n_audio_head = 6\nwhisper_model_load: n_audio_layer = 4\nwhisper_model_load: n_text_ctx = 448\nwhisper_model_load: n_text_state = 384\nwhisper_model_load: n_text_head = 6\nwhisper_model_load: n_text_layer = 4\nwhisper_model_load: n_mels = 80\nwhisper_model_load: ftype = 1\nwhisper_model_load: qntvr = 0\nwhisper_model_load: type = 1 (tiny)\nwhisper_model_load: adding 1608 extra tokens\nwhisper_model_load: n_langs = 99\nwhisper_model_load: Metal total size = 77.11 MB\nwhisper_model_load: model size = 77.11 MB\n2026-05-12T09:21:20.866406Z INFO screenpipe_audio::transcription::engine: whisper model loaded successfully\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\n2026-05-12T09:21:20.896976Z INFO screenpipe_audio::audio_manager::manager: transcription session created (will be reused across segments)\n2026-05-12T09:21:20.928794Z INFO screenpipe_audio::audio_manager::manager: seeded 14 speakers (named + unnamed) from DB into embedding manager\n2026-05-12T09:21:20.929372Z INFO screenpipe_audio::audio_manager::manager: audio manager started\n2026-05-12T09:21:20.930136Z INFO screenpipe_audio::audio_manager::manager: calendar-assisted speaker diarization: listening for meeting events\n2026-05-12T09:21:21.212480Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-12T09:21:22.112224Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-12T09:21:22.697027Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 1: frame_id=21773, dur=116ms\n2026-05-12T09:21:23.853614Z INFO screenpipe_audio::device::device_manager: starting recording for device: System Audio (output)\n2026-05-12T09:21:23.854499Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for System Audio (output) (unknown / 30s segments)\n2026-05-12T09:21:23.854491Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-12T09:21:28.046940Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-12T09:21:28.381213Z WARN screenpipe_a11y::tree::macos_lines: lines: AXUIElementCopyParameterizedAttributeValue(AXLineForIndex) failed status=os::Status { raw: -25212, fcc: \"....\", help: \"https://www.osstatus.com?search=-25212\" } — first failure (further failures suppressed); search highlights will fall back to paragraph bbox on this app\n2026-05-12T09:21:28.684461Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 2: frame_id=21775, dur=90ms\n2026-05-12T09:22:12.427026Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=2 elapsed=1.759127041s\n2026-05-12T09:22:12.427274Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames\n2026-05-12T09:22:12.869213Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.2MB → 0.3MB (0.9x), 1 JPEGs deleted\n2026-05-12T09:22:13.304558Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.3MB → 0.4MB (0.9x), 1 JPEGs deleted\n2026-05-12T09:22:39.009649Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-1944753676112650055, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T09:23:23.041658Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks","depth":4,"on_screen":true,"value":"whisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:33:55.437876Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:35:57.413206Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\n2026-05-11T22:37:14.870936Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=0 elapsed=1.714129166s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:37:59.603705Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:40:02.174925Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:42:04.809914Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T22:42:16.957748Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=0 elapsed=1.95758825s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:44:07.738461Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:46:10.863483Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:48:13.767660Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:50:16.132089Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:52:18.678586Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T22:52:18.727748Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=0 elapsed=1.378493375s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:54:20.840336Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T22:54:38.134704Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T22:54:38.619890Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for soundcore AeroClip (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-11T22:54:38.630348Z WARN screenpipe_audio::audio_manager::manager: recording for device soundcore AeroClip (input) exited with error: stream rebuild required after screen unlock for soundcore AeroClip (input) (recovery is automatic via device_monitor)\n2026-05-11T22:54:38.810449Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T22:54:40.719100Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for soundcore AeroClip (input), cleaning up for restart\n2026-05-11T22:54:40.719269Z INFO screenpipe_audio::device::device_manager: Stopping device: soundcore AeroClip (input)\n2026-05-11T22:54:41.038928Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-11T22:54:41.039052Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: soundcore AeroClip (input)\n2026-05-11T22:54:41.039131Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n2026-05-11T22:54:42.005620Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-11T22:54:44.076894Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-11T22:54:48.213325Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=0 rows_returned=234 elapsed=1.275494791s\n2026-05-11T22:54:48.379801Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\nzsh: terminated npx screenpipe@latest record\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-05-12T09:21:07.201625Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store\nchecking permissions...\n screen recording: ok\n microphone: ok\n accessibility: ok\n2026-05-12T09:21:07.328817Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-05-12T09:21:10.020463Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-05-12T09:21:10.024711Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-05-12T09:21:10.025571Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-05-12T09:21:10.055207Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true\n2026-05-12T09:21:10.055275Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-05-12T09:21:10.666779Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-05-12T09:21:10.666832Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-05-12T09:21:10.666681Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-05-12T09:21:10.666983Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-05-12T09:21:10.666647Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-05-12T09:21:10.673969Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-05-12T09:21:10.675449Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-05-12T09:21:10.676236Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-05-12T09:21:10.676638Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-05-12T09:21:10.677056Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-05-12T09:21:10.677293Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-05-12T09:21:10.677398Z INFO screenpipe_core::pipes: loaded 6 pipes from \"/Users/lukas/.screenpipe/pipes\"\n\n\n\n _ \n __________________ ___ ____ ____ (_____ ___ \n / ___/ ___/ ___/ _ \\/ _ \\/ __ \\ / __ \\/ / __ \\/ _ \\\n (__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/\n/____/\\___/_/ \\___/\\___/_/ /_/ / .___/_/ .___/\\___/ \n /_/ /_/ \n\n\n\npower AI by everything you've seen, said or heard\nopen source | runs locally | developer friendly\n\n\n┌────────────────────────┬────────────────────────────────────┐\n│ setting │ value │\n├────────────────────────┼────────────────────────────────────┤\n│ audio chunk duration │ 30 seconds │\n│ port │ 3030 │\n│ audio disabled │ false │\n│ vision disabled │ false │\n│ pause on DRM content │ false │\n│ audio engine │ Parakeet │\n│ vad engine │ Silero │\n│ data directory │ /Users/lukas/.screenpipe │\n│ debug mode │ false │\n│ telemetry │ true │\n│ use pii removal │ true │\n│ use all monitors │ true │\n│ ignored windows │ [] │\n│ included windows │ [] │\n│ cloud sync │ disabled │\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n│ retention mode │ media-only (keep transcripts) │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ MacBook Pro Microphone (input) │\n│ │ System Audio (output) │\n└────────────────────────┴────────────────────────────────────┘\nyou are using local processing. all your data stays on your computer.\n\nwarning: telemetry is enabled. only error-level data will be sent.\nto disable, use the --disable-telemetry flag.\n\ncheck latest changes here: https://github.com/screenpipe/screenpipe/releases\n2026-05-12T09:21:10.684547Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\n2026-05-12T09:21:10.686111Z INFO screenpipe: starting UI event capture\n2026-05-12T09:21:10.696691Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n2026-05-12T09:21:10.705742Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-05-12T09:21:10.712331Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-05-12T09:21:10.753596Z INFO screenpipe_engine::ui_recorder: UI recording session started: eee53fe6-52d6-4c4e-a7e5-11ede410f444\n2026-05-12T09:21:10.753638Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-05-12T09:21:10.753679Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-11 06:21:10.753677 UTC to 2026-05-12 06:21:10.753677 UTC)\n2026-05-12T09:21:10.754945Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-05-12T09:21:10.764596Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-05-12T09:21:10.771437Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-05-12T09:21:15.451981Z WARN sqlx::query: summary=\"SELECT f.id, f.timestamp, f.offset_index, …\" db.statement=\"\\n\\nSELECT\\n f.id,\\n f.timestamp,\\n f.offset_index,\\n COALESCE(\\n SUBSTR(f.full_text, 1, 200),\\n SUBSTR(f.accessibility_text, 1, 200),\\n (\\n SELECT\\n SUBSTR(ot.text, 1, 200)\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as text,\\n COALESCE(\\n f.app_name,\\n (\\n SELECT\\n ot.app_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as app_name,\\n COALESCE(\\n f.window_name,\\n (\\n SELECT\\n ot.window_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as window_name,\\n COALESCE(vc.device_name, f.device_name) as screen_device,\\n COALESCE(vc.file_path, f.snapshot_path) as video_path,\\n COALESCE(vc.fps, 0.033) as chunk_fps,\\n f.browser_url,\\n f.machine_id\\nFROM\\n frames f\\n LEFT JOIN video_chunks vc ON f.video_chunk_id = vc.id\\nWHERE\\n f.timestamp >= ?1\\n AND f.timestamp <= ?2\\n AND COALESCE(vc.file_path, f.snapshot_path, '') NOT LIKE 'cloud://%'\\nORDER BY\\n f.timestamp DESC,\\n f.offset_index DESC\\nLIMIT\\n 10000\\n\" rows_affected=0 rows_returned=6633 elapsed=4.697616625s\n2026-05-12T09:21:15.476188Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 6633 frame entries, coverage from 2026-05-11 06:21:10.753677 UTC\n2026-05-12T09:21:16.549935Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-05-12T09:21:16.550139Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-05-12T09:21:16.550184Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-05-12T09:21:19.459497Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)\n2026-05-12T09:21:19.463986Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-05-12T09:21:19.465573Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)\n2026-05-12T09:21:19.467110Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)\n2026-05-12T09:21:19.468420Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-05-12T09:21:20.691544Z INFO screenpipe_audio::transcription::engine: whisper model available: \"/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin\"\n2026-05-12T09:21:20.692520Z INFO screenpipe_audio::transcription::whisper::model: whisper context: gpu acceleration enabled (Metal on macOS, Vulkan on Windows)\n2026-05-12T09:21:20.692565Z INFO screenpipe_audio::transcription::engine: loading whisper model with GPU acceleration...\nwhisper_init_from_file_with_params_no_state: loading model from '/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin'\nwhisper_init_with_params_no_state: use gpu = 1\nwhisper_init_with_params_no_state: flash attn = 0\nwhisper_init_with_params_no_state: gpu_device = 0\nwhisper_init_with_params_no_state: dtw = 0\nggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices\nggml_metal_library_init: using embedded metal library\nggml_metal_library_init: loaded in 0.036 sec\nggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)\nggml_metal_device_init: GPU name: Apple M1\nggml_metal_device_init: GPU family: MTLGPUFamilyApple7 (1007)\nggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)\nggml_metal_device_init: GPU family: MTLGPUFamilyMetal3 (5001)\nggml_metal_device_init: simdgroup reduction = true\nggml_metal_device_init: simdgroup matrix mul. = true\nggml_metal_device_init: has unified memory = true\nggml_metal_device_init: has bfloat = true\nggml_metal_device_init: has tensor = false\nggml_metal_device_init: use residency sets = true\nggml_metal_device_init: use shared buffers = true\nggml_metal_device_init: recommendedMaxWorkingSetSize = 11453.25 MB\nwhisper_init_with_params_no_state: devices = 3\nwhisper_init_with_params_no_state: backends = 3\nwhisper_model_load: loading model\nwhisper_model_load: n_vocab = 51865\nwhisper_model_load: n_audio_ctx = 1500\nwhisper_model_load: n_audio_state = 384\nwhisper_model_load: n_audio_head = 6\nwhisper_model_load: n_audio_layer = 4\nwhisper_model_load: n_text_ctx = 448\nwhisper_model_load: n_text_state = 384\nwhisper_model_load: n_text_head = 6\nwhisper_model_load: n_text_layer = 4\nwhisper_model_load: n_mels = 80\nwhisper_model_load: ftype = 1\nwhisper_model_load: qntvr = 0\nwhisper_model_load: type = 1 (tiny)\nwhisper_model_load: adding 1608 extra tokens\nwhisper_model_load: n_langs = 99\nwhisper_model_load: Metal total size = 77.11 MB\nwhisper_model_load: model size = 77.11 MB\n2026-05-12T09:21:20.866406Z INFO screenpipe_audio::transcription::engine: whisper model loaded successfully\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\n2026-05-12T09:21:20.896976Z INFO screenpipe_audio::audio_manager::manager: transcription session created (will be reused across segments)\n2026-05-12T09:21:20.928794Z INFO screenpipe_audio::audio_manager::manager: seeded 14 speakers (named + unnamed) from DB into embedding manager\n2026-05-12T09:21:20.929372Z INFO screenpipe_audio::audio_manager::manager: audio manager started\n2026-05-12T09:21:20.930136Z INFO screenpipe_audio::audio_manager::manager: calendar-assisted speaker diarization: listening for meeting events\n2026-05-12T09:21:21.212480Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-12T09:21:22.112224Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-12T09:21:22.697027Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 1: frame_id=21773, dur=116ms\n2026-05-12T09:21:23.853614Z INFO screenpipe_audio::device::device_manager: starting recording for device: System Audio (output)\n2026-05-12T09:21:23.854499Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for System Audio (output) (unknown / 30s segments)\n2026-05-12T09:21:23.854491Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-12T09:21:28.046940Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-12T09:21:28.381213Z WARN screenpipe_a11y::tree::macos_lines: lines: AXUIElementCopyParameterizedAttributeValue(AXLineForIndex) failed status=os::Status { raw: -25212, fcc: \"....\", help: \"https://www.osstatus.com?search=-25212\" } — first failure (further failures suppressed); search highlights will fall back to paragraph bbox on this app\n2026-05-12T09:21:28.684461Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 2: frame_id=21775, dur=90ms\n2026-05-12T09:22:12.427026Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=2 elapsed=1.759127041s\n2026-05-12T09:22:12.427274Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames\n2026-05-12T09:22:12.869213Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.2MB → 0.3MB (0.9x), 1 JPEGs deleted\n2026-05-12T09:22:13.304558Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.3MB → 0.4MB (0.9x), 1 JPEGs deleted\n2026-05-12T09:22:39.009649Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-1944753676112650055, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T09:23:23.041658Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.0,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.004166667,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (-zsh)","depth":2,"bounds":{"left":0.140625,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.14479166,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.28125,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.28541666,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.421875,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.42604166,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.5625,"top":0.05888889,"width":0.14027777,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.56666666,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.7027778,"top":0.05888889,"width":0.14027777,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.70694447,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.84305555,"top":0.05888889,"width":0.14027777,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.8472222,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.9548611,"top":0.032222223,"width":0.03888889,"height":0.018888889},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"screenpipe\"","depth":1,"bounds":{"left":0.47083333,"top":0.033333335,"width":0.058333334,"height":0.017777778},"on_screen":true,"role_description":"text"}]...
|
4600003808199063888
|
-852231712889047584
|
app_switch
|
accessibility
|
NULL
|
whisper_init_state: kv pad size = 2.36 MB
whi whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:33:55.437876Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:35:57.413206Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
2026-05-11T22:37:14.870936Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=0 elapsed=1.714129166s
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:37:59.603705Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:40:02.174925Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: install a starter bundle of pipes:
screenpipe install [URL_WITH_CREDENTIALS] record
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-05-12T09:21:07.201625Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store
checking permissions...
screen recording: ok
microphone: ok
accessibility: ok
2026-05-12T09:21:07.328817Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-05-12T09:21:10.020463Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-05-12T09:21:10.024711Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-05-12T09:21:10.025571Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-05-12T09:21:10.055207Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true
2026-05-12T09:21:10.055275Z INFO screenpipe: meeting detector enabled — independent of transcription mode
2026-05-12T09:21:10.666779Z INFO screenpipe: API server listening on [IP_ADDRESS]:3030 (localhost only)
2026-05-12T09:21:10.666832Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key
2026-05-12T09:21:10.666681Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)
2026-05-12T09:21:10.666983Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager
2026-05-12T09:21:10.666647Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)
2026-05-12T09:21:10.673969Z INFO screenpipe_core::pipes: loaded pipe: day-recap
2026-05-12T09:21:10.675449Z INFO screenpipe_core::pipes: loaded pipe: standup-update
2026-05-12T09:21:10.676236Z INFO screenpipe_core::pipes: loaded pipe: ai-habits
2026-05-12T09:21:10.676638Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown
2026-05-12T09:21:10.677056Z INFO screenpipe_core::pipes: loaded pipe: video-export
2026-05-12T09:21:10.677293Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary
2026-05-12T09:21:10.677398Z INFO screenpipe_core::pipes: loaded 6 pipes from "/Users/lukas/.screenpipe/pipes"
_
__________________ ___ ____ ____ (_____ ___
/ ___/ ___/ ___/ _ \/ _ \/ __ \ / __ \/ / __ \/ _ \
(__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/
/____/\___/_/ \___/\___/_/ /_/ / .___/_/ .___/\___/
/_/ /_/
power AI by everything you've seen, said or heard
open source | runs locally | developer friendly
┌────────────────────────┬────────────────────────────────────┐
│ setting │ value │
├────────────────────────┼────────────────────────────────────┤
│ audio chunk duration │ 30 seconds │
│ port │ 3030 │
│ audio disabled │ false │
│ vision disabled │ false │
│ pause on DRM content │ false │
│ audio engine │ Parakeet │
│ vad engine │ Silero │
│ data directory │ /Users/lukas/.screenpipe │
│ debug mode │ false │
│ telemetry │ true │
│ use pii removal │ true │
│ use all monitors │ true │
│ ignored windows │ [] │
│ included windows │ [] │
│ cloud sync │ disabled │
│ auto-destruct pid │ 0 │
│ deepgram key │ not set │
│ api auth │ enabled │
│ encrypt secrets │ disabled │
│ retention days │ 14 │
│ retention mode │ media-only (keep transcripts) │
├────────────────────────┼────────────────────────────────────┤
│ languages │ │
│ │ all languages │
├────────────────────────┼────────────────────────────────────┤
│ monitors │ │
│ │ id: 1 │
│ │ id: 2 │
├────────────────────────┼────────────────────────────────────┤
│ audio devices │ │
│ │ MacBook Pro Microphone (input) │
│ │ System Audio (output) │
└────────────────────────┴────────────────────────────────────┘
you are using local processing. all your data stays on your computer.
warning: telemetry is enabled. only error-level data will be sent.
to disable, use the --disable-telemetry flag.
check latest changes here: https://github.com/screenpipe/screenpipe/releases
2026-05-12T09:21:10.684547Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)
2026-05-12T09:21:10.686111Z INFO screenpipe: starting UI event capture
2026-05-12T09:21:10.696691Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh
2026-05-12T09:21:10.705742Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))
2026-05-12T09:21:10.712331Z INFO screenpipe_engine::ui_recorder: Starting UI event capture
2026-05-12T09:21:10.753596Z INFO screenpipe_engine::ui_recorder: UI recording session started: eee53fe6-52d6-4c4e-a7e5-11ede410f444
2026-05-12T09:21:10.753638Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)
2026-05-12T09:21:10.753679Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-11 06:21:10.753677 UTC to 2026-05-12 06:21:10.753677 UTC)
2026-05-12T09:21:10.754945Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)
2026-05-12T09:21:10.764596Z INFO screenpipe_engine::server: Server listening on [IP_ADDRESS]:3030
2026-05-12T09:21:10.771437Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030
2026-05-12T09:21:15.451981Z WARN sqlx::query: summary="SELECT f.id, f.timestamp, f.offset_index, …" db.statement="\n\nSELECT\n f.id,\n f.timestamp,\n f.offset_index,\n COALESCE(\n SUBSTR(f.full_text, 1, 200),\n SUBSTR(f.accessibility_text, 1, 200),\n (\n SELECT\n SUBSTR(ot.text, 1, 200)\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as text,\n COALESCE(\n f.app_name,\n (\n SELECT\n ot.app_name\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as app_name,\n COALESCE(\n f.window_name,\n (\n SELECT\n ot.window_name\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as window_name,\n COALESCE(vc.device_name, f.device_name) as screen_device,\n COALESCE(vc.file_path, f.snapshot_path) as video_path,\n COALESCE(vc.fps, 0.033) as chunk_fps,\n f.browser_url,\n f.machine_id\nFROM\n frames f\n LEFT JOIN video_chunks vc ON f.video_chunk_id = vc.id\nWHERE\n f.timestamp >= ?1\n AND f.timestamp <= ?2\n AND COALESCE(vc.file_path, f.snapshot_path, '') NOT LIKE 'cloud://%'\nORDER BY\n f.timestamp DESC,\n f.offset_index DESC\nLIMIT\n 10000\n" rows_affected=0 rows_returned=6633 elapsed=4.697616625s
2026-05-12T09:21:15.476188Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 6633 frame entries, coverage from 2026-05-11 06:21:10.753677 UTC
2026-05-12T09:21:16.549935Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)
2026-05-12T09:21:16.550139Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)
2026-05-12T09:21:16.550184Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)
2026-05-12T09:21:19.459497Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)
2026-05-12T09:21:19.463986Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)
2026-05-12T09:21:19.465573Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)
2026-05-12T09:21:19.467110Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)
2026-05-12T09:21:19.468420Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)
2026-05-12T09:21:20.691544Z INFO screenpipe_audio::transcription::engine: whisper model available: "/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin"
2026-05-12T09:21:20.692520Z INFO screenpipe_audio::transcription::whisper::model: whisper context: gpu acceleration enabled (Metal on macOS, Vulkan on Windows)
2026-05-12T09:21:20.692565Z INFO screenpipe_audio::transcription::engine: loading whisper model with GPU acceleration...
whisper_init_from_file_with_params_no_state: loading model from '/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin'
whisper_init_with_params_no_state: use gpu = 1
whisper_init_with_params_no_state: flash attn = 0
whisper_init_with_params_no_state: gpu_device = 0
whisper_init_with_params_no_state: dtw = 0
ggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices
ggml_metal_library_init: using embedded metal library
ggml_metal_library_init: loaded in 0.036 sec
ggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)
ggml_metal_device_init: GPU name: Apple M1
ggml_metal_device_init: GPU family: MTLGPUFamilyApple7 (1007)
ggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)
ggml_metal_device_init: GPU family: MTLGPUFamilyMetal3 (5001)
ggml_metal_device_init: simdgroup reduction = true
ggml_metal_device_init: simdgroup matrix mul. = true
ggml_metal_device_init: has unified memory = true
ggml_metal_device_init: has bfloat = true
ggml_metal_device_init: has tensor = false
ggml_metal_device_init: use residency sets = true
ggml_metal_device_init: use shared buffers = true
ggml_metal_device_init: recommendedMaxWorkingSetSize = 11453.25 MB
whisper_init_with_params_no_state: devices = 3
whisper_init_with_params_no_state: backends = 3
whisper_model_load: loading model
whisper_model_load: n_vocab = 51865
whisper_model_load: n_audio_ctx = 1500
whisper_model_load: n_audio_state = 384
whisper_model_load: n_audio_head = 6
whisper_model_load: n_audio_layer = 4
whisper_model_load: n_text_ctx = 448
whisper_model_load: n_text_state = 384
whisper_model_load: n_text_head = 6
whisper_model_load: n_text_layer = 4
whisper_model_load: n_mels = 80
whisper_model_load: ftype = 1
whisper_model_load: qntvr = 0
whisper_model_load: type = 1 (tiny)
whisper_model_load: adding 1608 extra tokens
whisper_model_load: n_langs = 99
whisper_model_load: Metal total size = 77.11 MB
whisper_model_load: model size = 77.11 MB
2026-05-12T09:21:20.866406Z INFO screenpipe_audio::transcription::engine: whisper model loaded successfully
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
2026-05-12T09:21:20.896976Z INFO screenpipe_audio::audio_manager::manager: transcription session created (will be reused across segments)
2026-05-12T09:21:20.928794Z INFO screenpipe_audio::audio_manager::manager: seeded 14 speakers (named + unnamed) from DB into embedding manager
2026-05-12T09:21:20.929372Z INFO screenpipe_audio::audio_manager::manager: audio manager started
2026-05-12T09:21:20.930136Z INFO screenpipe_audio::audio_manager::manager: calendar-assisted speaker diarization: listening for meeting events
2026-05-12T09:21:21.212480Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-12T09:21:22.112224Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)
2026-05-12T09:21:22.697027Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 1: frame_id=21773, dur=116ms
2026-05-12T09:21:23.853614Z INFO screenpipe_audio::device::device_manager: starting recording for device: System Audio (output)
2026-05-12T09:21:23.854499Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for System Audio (output) (unknown / 30s segments)
2026-05-12T09:21:23.854491Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-12T09:21:28.046940Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)
2026-05-12T09:21:28.381213Z WARN screenpipe_a11y::tree::macos_lines: lines: AXUIElementCopyParameterizedAttributeValue(AXLineForIndex) failed status=os::Status { raw: -25212, fcc: "....", help: "https://www.osstatus.com?search=-25212" } — first failure (further failures suppressed); search highlights will fall back to paragraph bbox on this app
2026-05-12T09:21:28.684461Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 2: frame_id=21775, dur=90ms
2026-05-12T09:22:12.427026Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=2 elapsed=1.759127041s
2026-05-12T09:22:12.427274Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames
2026-05-12T09:22:12.869213Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.2MB → 0.3MB (0.9x), 1 JPEGs deleted
2026-05-12T09:22:13.304558Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.3MB → 0.4MB (0.9x), 1 JPEGs deleted
2026-05-12T09:22:39.009649Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-1944753676112650055, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency...
|
NULL
|
NULL
|
NULL
|
NULL
|
|
21799
|
955
|
11
|
2026-05-12T06:24:15.455864+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-12/1778 /Users/lukas/.screenpipe/data/data/2026-05-12/1778567055455_m2.jpg...
|
iTerm2
|
screenpipe"
|
True
|
NULL
|
monitor_2
|
NULL
|
NULL
|
NULL
|
NULL
|
whisper_init_state: kv pad size = 2.36 MB
whi whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:33:55.437876Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:35:57.413206Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
2026-05-11T22:37:14.870936Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=0 elapsed=1.714129166s
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:37:59.603705Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:40:02.174925Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: install a starter bundle of pipes:
screenpipe install [URL_WITH_CREDENTIALS] record
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-05-12T09:21:07.201625Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store
checking permissions...
screen recording: ok
microphone: ok
accessibility: ok
2026-05-12T09:21:07.328817Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-05-12T09:21:10.020463Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-05-12T09:21:10.024711Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-05-12T09:21:10.025571Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-05-12T09:21:10.055207Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true
2026-05-12T09:21:10.055275Z INFO screenpipe: meeting detector enabled — independent of transcription mode
2026-05-12T09:21:10.666779Z INFO screenpipe: API server listening on [IP_ADDRESS]:3030 (localhost only)
2026-05-12T09:21:10.666832Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key
2026-05-12T09:21:10.666681Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)
2026-05-12T09:21:10.666983Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager
2026-05-12T09:21:10.666647Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)
2026-05-12T09:21:10.673969Z INFO screenpipe_core::pipes: loaded pipe: day-recap
2026-05-12T09:21:10.675449Z INFO screenpipe_core::pipes: loaded pipe: standup-update
2026-05-12T09:21:10.676236Z INFO screenpipe_core::pipes: loaded pipe: ai-habits
2026-05-12T09:21:10.676638Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown
2026-05-12T09:21:10.677056Z INFO screenpipe_core::pipes: loaded pipe: video-export
2026-05-12T09:21:10.677293Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary
2026-05-12T09:21:10.677398Z INFO screenpipe_core::pipes: loaded 6 pipes from "/Users/lukas/.screenpipe/pipes"
_
__________________ ___ ____ ____ (_____ ___
/ ___/ ___/ ___/ _ \/ _ \/ __ \ / __ \/ / __ \/ _ \
(__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/
/____/\___/_/ \___/\___/_/ /_/ / .___/_/ .___/\___/
/_/ /_/
power AI by everything you've seen, said or heard
open source | runs locally | developer friendly
┌────────────────────────┬────────────────────────────────────┐
│ setting │ value │
├────────────────────────┼────────────────────────────────────┤
│ audio chunk duration │ 30 seconds │
│ port │ 3030 │
│ audio disabled │ false │
│ vision disabled │ false │
│ pause on DRM content │ false │
│ audio engine │ Parakeet │
│ vad engine │ Silero │
│ data directory │ /Users/lukas/.screenpipe │
│ debug mode │ false │
│ telemetry │ true │
│ use pii removal │ true │
│ use all monitors │ true │
│ ignored windows │ [] │
│ included windows │ [] │
│ cloud sync │ disabled │
│ auto-destruct pid │ 0 │
│ deepgram key │ not set │
│ api auth │ enabled │
│ encrypt secrets │ disabled │
│ retention days │ 14 │
│ retention mode │ media-only (keep transcripts) │
├────────────────────────┼────────────────────────────────────┤
│ languages │ │
│ │ all languages │
├────────────────────────┼────────────────────────────────────┤
│ monitors │ │
│ │ id: 1 │
│ │ id: 2 │
├────────────────────────┼────────────────────────────────────┤
│ audio devices │ │
│ │ MacBook Pro Microphone (input) │
│ │ System Audio (output) │
└────────────────────────┴────────────────────────────────────┘
you are using local processing. all your data stays on your computer.
warning: telemetry is enabled. only error-level data will be sent.
to disable, use the --disable-telemetry flag.
check latest changes here: https://github.com/screenpipe/screenpipe/releases
2026-05-12T09:21:10.684547Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)
2026-05-12T09:21:10.686111Z INFO screenpipe: starting UI event capture
2026-05-12T09:21:10.696691Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh
2026-05-12T09:21:10.705742Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))
2026-05-12T09:21:10.712331Z INFO screenpipe_engine::ui_recorder: Starting UI event capture
2026-05-12T09:21:10.753596Z INFO screenpipe_engine::ui_recorder: UI recording session started: eee53fe6-52d6-4c4e-a7e5-11ede410f444
2026-05-12T09:21:10.753638Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)
2026-05-12T09:21:10.753679Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-11 06:21:10.753677 UTC to 2026-05-12 06:21:10.753677 UTC)
2026-05-12T09:21:10.754945Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)
2026-05-12T09:21:10.764596Z INFO screenpipe_engine::server: Server listening on [IP_ADDRESS]:3030
2026-05-12T09:21:10.771437Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030
2026-05-12T09:21:15.451981Z WARN sqlx::query: summary="SELECT f.id, f.timestamp, f.offset_index, …" db.statement="\n\nSELECT\n f.id,\n f.timestamp,\n f.offset_index,\n COALESCE(\n SUBSTR(f.full_text, 1, 200),\n SUBSTR(f.accessibility_text, 1, 200),\n (\n SELECT\n SUBSTR(ot.text, 1, 200)\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as text,\n COALESCE(\n f.app_name,\n (\n SELECT\n ot.app_name\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as app_name,\n COALESCE(\n f.window_name,\n (\n SELECT\n ot.window_name\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as window_name,\n COALESCE(vc.device_name, f.device_name) as screen_device,\n COALESCE(vc.file_path, f.snapshot_path) as video_path,\n COALESCE(vc.fps, 0.033) as chunk_fps,\n f.browser_url,\n f.machine_id\nFROM\n frames f\n LEFT JOIN video_chunks vc ON f.video_chunk_id = vc.id\nWHERE\n f.timestamp >= ?1\n AND f.timestamp <= ?2\n AND COALESCE(vc.file_path, f.snapshot_path, '') NOT LIKE 'cloud://%'\nORDER BY\n f.timestamp DESC,\n f.offset_index DESC\nLIMIT\n 10000\n" rows_affected=0 rows_returned=6633 elapsed=4.697616625s
2026-05-12T09:21:15.476188Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 6633 frame entries, coverage from 2026-05-11 06:21:10.753677 UTC
2026-05-12T09:21:16.549935Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)
2026-05-12T09:21:16.550139Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)
2026-05-12T09:21:16.550184Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)
2026-05-12T09:21:19.459497Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)
2026-05-12T09:21:19.463986Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)
2026-05-12T09:21:19.465573Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)
2026-05-12T09:21:19.467110Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)
2026-05-12T09:21:19.468420Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)
2026-05-12T09:21:20.691544Z INFO screenpipe_audio::transcription::engine: whisper model available: "/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin"
2026-05-12T09:21:20.692520Z INFO screenpipe_audio::transcription::whisper::model: whisper context: gpu acceleration enabled (Metal on macOS, Vulkan on Windows)
2026-05-12T09:21:20.692565Z INFO screenpipe_audio::transcription::engine: loading whisper model with GPU acceleration...
whisper_init_from_file_with_params_no_state: loading model from '/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin'
whisper_init_with_params_no_state: use gpu = 1
whisper_init_with_params_no_state: flash attn = 0
whisper_init_with_params_no_state: gpu_device = 0
whisper_init_with_params_no_state: dtw = 0
ggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices
ggml_metal_library_init: using embedded metal library
ggml_metal_library_init: loaded in 0.036 sec
ggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)
ggml_metal_device_init: GPU name: Apple M1
ggml_metal_device_init: GPU family: MTLGPUFamilyApple7 (1007)
ggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)
ggml_metal_device_init: GPU family: MTLGPUFamilyMetal3 (5001)
ggml_metal_device_init: simdgroup reduction = true
ggml_metal_device_init: simdgroup matrix mul. = true
ggml_metal_device_init: has unified memory = true
ggml_metal_device_init: has bfloat = true
ggml_metal_device_init: has tensor = false
ggml_metal_device_init: use residency sets = true
ggml_metal_device_init: use shared buffers = true
ggml_metal_device_init: recommendedMaxWorkingSetSize = 11453.25 MB
whisper_init_with_params_no_state: devices = 3
whisper_init_with_params_no_state: backends = 3
whisper_model_load: loading model
whisper_model_load: n_vocab = 51865
whisper_model_load: n_audio_ctx = 1500
whisper_model_load: n_audio_state = 384
whisper_model_load: n_audio_head = 6
whisper_model_load: n_audio_layer = 4
whisper_model_load: n_text_ctx = 448
whisper_model_load: n_text_state = 384
whisper_model_load: n_text_head = 6
whisper_model_load: n_text_layer = 4
whisper_model_load: n_mels = 80
whisper_model_load: ftype = 1
whisper_model_load: qntvr = 0
whisper_model_load: type = 1 (tiny)
whisper_model_load: adding 1608 extra tokens
whisper_model_load: n_langs = 99
whisper_model_load: Metal total size = 77.11 MB
whisper_model_load: model size = 77.11 MB
2026-05-12T09:21:20.866406Z INFO screenpipe_audio::transcription::engine: whisper model loaded successfully
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
2026-05-12T09:21:20.896976Z INFO screenpipe_audio::audio_manager::manager: transcription session created (will be reused across segments)
2026-05-12T09:21:20.928794Z INFO screenpipe_audio::audio_manager::manager: seeded 14 speakers (named + unnamed) from DB into embedding manager
2026-05-12T09:21:20.929372Z INFO screenpipe_audio::audio_manager::manager: audio manager started
2026-05-12T09:21:20.930136Z INFO screenpipe_audio::audio_manager::manager: calendar-assisted speaker diarization: listening for meeting events
2026-05-12T09:21:21.212480Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-12T09:21:22.112224Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)
2026-05-12T09:21:22.697027Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 1: frame_id=21773, dur=116ms
2026-05-12T09:21:23.853614Z INFO screenpipe_audio::device::device_manager: starting recording for device: System Audio (output)
2026-05-12T09:21:23.854499Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for System Audio (output) (unknown / 30s segments)
2026-05-12T09:21:23.854491Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-12T09:21:28.046940Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)
2026-05-12T09:21:28.381213Z WARN screenpipe_a11y::tree::macos_lines: lines: AXUIElementCopyParameterizedAttributeValue(AXLineForIndex) failed status=os::Status { raw: -25212, fcc: "....", help: "https://www.osstatus.com?search=-25212" } — first failure (further failures suppressed); search highlights will fall back to paragraph bbox on this app
2026-05-12T09:21:28.684461Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 2: frame_id=21775, dur=90ms
2026-05-12T09:22:12.427026Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=2 elapsed=1.759127041s
2026-05-12T09:22:12.427274Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames
2026-05-12T09:22:12.869213Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.2MB → 0.3MB (0.9x), 1 JPEGs deleted
2026-05-12T09:22:13.304558Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.3MB → 0.4MB (0.9x), 1 JPEGs deleted
2026-05-12T09:22:39.009649Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-1944753676112650055, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency...
|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"whisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:33:55.437876Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:35:57.413206Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\n2026-05-11T22:37:14.870936Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=0 elapsed=1.714129166s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:37:59.603705Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:40:02.174925Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:42:04.809914Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T22:42:16.957748Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=0 elapsed=1.95758825s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:44:07.738461Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:46:10.863483Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:48:13.767660Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:50:16.132089Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:52:18.678586Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T22:52:18.727748Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=0 elapsed=1.378493375s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:54:20.840336Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T22:54:38.134704Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T22:54:38.619890Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for soundcore AeroClip (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-11T22:54:38.630348Z WARN screenpipe_audio::audio_manager::manager: recording for device soundcore AeroClip (input) exited with error: stream rebuild required after screen unlock for soundcore AeroClip (input) (recovery is automatic via device_monitor)\n2026-05-11T22:54:38.810449Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T22:54:40.719100Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for soundcore AeroClip (input), cleaning up for restart\n2026-05-11T22:54:40.719269Z INFO screenpipe_audio::device::device_manager: Stopping device: soundcore AeroClip (input)\n2026-05-11T22:54:41.038928Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-11T22:54:41.039052Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: soundcore AeroClip (input)\n2026-05-11T22:54:41.039131Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n2026-05-11T22:54:42.005620Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-11T22:54:44.076894Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-11T22:54:48.213325Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=0 rows_returned=234 elapsed=1.275494791s\n2026-05-11T22:54:48.379801Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\nzsh: terminated npx screenpipe@latest record\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-05-12T09:21:07.201625Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store\nchecking permissions...\n screen recording: ok\n microphone: ok\n accessibility: ok\n2026-05-12T09:21:07.328817Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-05-12T09:21:10.020463Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-05-12T09:21:10.024711Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-05-12T09:21:10.025571Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-05-12T09:21:10.055207Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true\n2026-05-12T09:21:10.055275Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-05-12T09:21:10.666779Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-05-12T09:21:10.666832Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-05-12T09:21:10.666681Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-05-12T09:21:10.666983Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-05-12T09:21:10.666647Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-05-12T09:21:10.673969Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-05-12T09:21:10.675449Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-05-12T09:21:10.676236Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-05-12T09:21:10.676638Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-05-12T09:21:10.677056Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-05-12T09:21:10.677293Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-05-12T09:21:10.677398Z INFO screenpipe_core::pipes: loaded 6 pipes from \"/Users/lukas/.screenpipe/pipes\"\n\n\n\n _ \n __________________ ___ ____ ____ (_____ ___ \n / ___/ ___/ ___/ _ \\/ _ \\/ __ \\ / __ \\/ / __ \\/ _ \\\n (__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/\n/____/\\___/_/ \\___/\\___/_/ /_/ / .___/_/ .___/\\___/ \n /_/ /_/ \n\n\n\npower AI by everything you've seen, said or heard\nopen source | runs locally | developer friendly\n\n\n┌────────────────────────┬────────────────────────────────────┐\n│ setting │ value │\n├────────────────────────┼────────────────────────────────────┤\n│ audio chunk duration │ 30 seconds │\n│ port │ 3030 │\n│ audio disabled │ false │\n│ vision disabled │ false │\n│ pause on DRM content │ false │\n│ audio engine │ Parakeet │\n│ vad engine │ Silero │\n│ data directory │ /Users/lukas/.screenpipe │\n│ debug mode │ false │\n│ telemetry │ true │\n│ use pii removal │ true │\n│ use all monitors │ true │\n│ ignored windows │ [] │\n│ included windows │ [] │\n│ cloud sync │ disabled │\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n│ retention mode │ media-only (keep transcripts) │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ MacBook Pro Microphone (input) │\n│ │ System Audio (output) │\n└────────────────────────┴────────────────────────────────────┘\nyou are using local processing. all your data stays on your computer.\n\nwarning: telemetry is enabled. only error-level data will be sent.\nto disable, use the --disable-telemetry flag.\n\ncheck latest changes here: https://github.com/screenpipe/screenpipe/releases\n2026-05-12T09:21:10.684547Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\n2026-05-12T09:21:10.686111Z INFO screenpipe: starting UI event capture\n2026-05-12T09:21:10.696691Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n2026-05-12T09:21:10.705742Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-05-12T09:21:10.712331Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-05-12T09:21:10.753596Z INFO screenpipe_engine::ui_recorder: UI recording session started: eee53fe6-52d6-4c4e-a7e5-11ede410f444\n2026-05-12T09:21:10.753638Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-05-12T09:21:10.753679Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-11 06:21:10.753677 UTC to 2026-05-12 06:21:10.753677 UTC)\n2026-05-12T09:21:10.754945Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-05-12T09:21:10.764596Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-05-12T09:21:10.771437Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-05-12T09:21:15.451981Z WARN sqlx::query: summary=\"SELECT f.id, f.timestamp, f.offset_index, …\" db.statement=\"\\n\\nSELECT\\n f.id,\\n f.timestamp,\\n f.offset_index,\\n COALESCE(\\n SUBSTR(f.full_text, 1, 200),\\n SUBSTR(f.accessibility_text, 1, 200),\\n (\\n SELECT\\n SUBSTR(ot.text, 1, 200)\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as text,\\n COALESCE(\\n f.app_name,\\n (\\n SELECT\\n ot.app_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as app_name,\\n COALESCE(\\n f.window_name,\\n (\\n SELECT\\n ot.window_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as window_name,\\n COALESCE(vc.device_name, f.device_name) as screen_device,\\n COALESCE(vc.file_path, f.snapshot_path) as video_path,\\n COALESCE(vc.fps, 0.033) as chunk_fps,\\n f.browser_url,\\n f.machine_id\\nFROM\\n frames f\\n LEFT JOIN video_chunks vc ON f.video_chunk_id = vc.id\\nWHERE\\n f.timestamp >= ?1\\n AND f.timestamp <= ?2\\n AND COALESCE(vc.file_path, f.snapshot_path, '') NOT LIKE 'cloud://%'\\nORDER BY\\n f.timestamp DESC,\\n f.offset_index DESC\\nLIMIT\\n 10000\\n\" rows_affected=0 rows_returned=6633 elapsed=4.697616625s\n2026-05-12T09:21:15.476188Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 6633 frame entries, coverage from 2026-05-11 06:21:10.753677 UTC\n2026-05-12T09:21:16.549935Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-05-12T09:21:16.550139Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-05-12T09:21:16.550184Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-05-12T09:21:19.459497Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)\n2026-05-12T09:21:19.463986Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-05-12T09:21:19.465573Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)\n2026-05-12T09:21:19.467110Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)\n2026-05-12T09:21:19.468420Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-05-12T09:21:20.691544Z INFO screenpipe_audio::transcription::engine: whisper model available: \"/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin\"\n2026-05-12T09:21:20.692520Z INFO screenpipe_audio::transcription::whisper::model: whisper context: gpu acceleration enabled (Metal on macOS, Vulkan on Windows)\n2026-05-12T09:21:20.692565Z INFO screenpipe_audio::transcription::engine: loading whisper model with GPU acceleration...\nwhisper_init_from_file_with_params_no_state: loading model from '/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin'\nwhisper_init_with_params_no_state: use gpu = 1\nwhisper_init_with_params_no_state: flash attn = 0\nwhisper_init_with_params_no_state: gpu_device = 0\nwhisper_init_with_params_no_state: dtw = 0\nggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices\nggml_metal_library_init: using embedded metal library\nggml_metal_library_init: loaded in 0.036 sec\nggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)\nggml_metal_device_init: GPU name: Apple M1\nggml_metal_device_init: GPU family: MTLGPUFamilyApple7 (1007)\nggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)\nggml_metal_device_init: GPU family: MTLGPUFamilyMetal3 (5001)\nggml_metal_device_init: simdgroup reduction = true\nggml_metal_device_init: simdgroup matrix mul. = true\nggml_metal_device_init: has unified memory = true\nggml_metal_device_init: has bfloat = true\nggml_metal_device_init: has tensor = false\nggml_metal_device_init: use residency sets = true\nggml_metal_device_init: use shared buffers = true\nggml_metal_device_init: recommendedMaxWorkingSetSize = 11453.25 MB\nwhisper_init_with_params_no_state: devices = 3\nwhisper_init_with_params_no_state: backends = 3\nwhisper_model_load: loading model\nwhisper_model_load: n_vocab = 51865\nwhisper_model_load: n_audio_ctx = 1500\nwhisper_model_load: n_audio_state = 384\nwhisper_model_load: n_audio_head = 6\nwhisper_model_load: n_audio_layer = 4\nwhisper_model_load: n_text_ctx = 448\nwhisper_model_load: n_text_state = 384\nwhisper_model_load: n_text_head = 6\nwhisper_model_load: n_text_layer = 4\nwhisper_model_load: n_mels = 80\nwhisper_model_load: ftype = 1\nwhisper_model_load: qntvr = 0\nwhisper_model_load: type = 1 (tiny)\nwhisper_model_load: adding 1608 extra tokens\nwhisper_model_load: n_langs = 99\nwhisper_model_load: Metal total size = 77.11 MB\nwhisper_model_load: model size = 77.11 MB\n2026-05-12T09:21:20.866406Z INFO screenpipe_audio::transcription::engine: whisper model loaded successfully\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\n2026-05-12T09:21:20.896976Z INFO screenpipe_audio::audio_manager::manager: transcription session created (will be reused across segments)\n2026-05-12T09:21:20.928794Z INFO screenpipe_audio::audio_manager::manager: seeded 14 speakers (named + unnamed) from DB into embedding manager\n2026-05-12T09:21:20.929372Z INFO screenpipe_audio::audio_manager::manager: audio manager started\n2026-05-12T09:21:20.930136Z INFO screenpipe_audio::audio_manager::manager: calendar-assisted speaker diarization: listening for meeting events\n2026-05-12T09:21:21.212480Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-12T09:21:22.112224Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-12T09:21:22.697027Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 1: frame_id=21773, dur=116ms\n2026-05-12T09:21:23.853614Z INFO screenpipe_audio::device::device_manager: starting recording for device: System Audio (output)\n2026-05-12T09:21:23.854499Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for System Audio (output) (unknown / 30s segments)\n2026-05-12T09:21:23.854491Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-12T09:21:28.046940Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-12T09:21:28.381213Z WARN screenpipe_a11y::tree::macos_lines: lines: AXUIElementCopyParameterizedAttributeValue(AXLineForIndex) failed status=os::Status { raw: -25212, fcc: \"....\", help: \"https://www.osstatus.com?search=-25212\" } — first failure (further failures suppressed); search highlights will fall back to paragraph bbox on this app\n2026-05-12T09:21:28.684461Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 2: frame_id=21775, dur=90ms\n2026-05-12T09:22:12.427026Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=2 elapsed=1.759127041s\n2026-05-12T09:22:12.427274Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames\n2026-05-12T09:22:12.869213Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.2MB → 0.3MB (0.9x), 1 JPEGs deleted\n2026-05-12T09:22:13.304558Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.3MB → 0.4MB (0.9x), 1 JPEGs deleted\n2026-05-12T09:22:39.009649Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-1944753676112650055, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T09:23:23.041658Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks","depth":4,"on_screen":true,"value":"whisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:33:55.437876Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:35:57.413206Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\n2026-05-11T22:37:14.870936Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=0 elapsed=1.714129166s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:37:59.603705Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:40:02.174925Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:42:04.809914Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T22:42:16.957748Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=0 elapsed=1.95758825s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:44:07.738461Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:46:10.863483Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:48:13.767660Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:50:16.132089Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:52:18.678586Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T22:52:18.727748Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=0 elapsed=1.378493375s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:54:20.840336Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T22:54:38.134704Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T22:54:38.619890Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for soundcore AeroClip (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-11T22:54:38.630348Z WARN screenpipe_audio::audio_manager::manager: recording for device soundcore AeroClip (input) exited with error: stream rebuild required after screen unlock for soundcore AeroClip (input) (recovery is automatic via device_monitor)\n2026-05-11T22:54:38.810449Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T22:54:40.719100Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for soundcore AeroClip (input), cleaning up for restart\n2026-05-11T22:54:40.719269Z INFO screenpipe_audio::device::device_manager: Stopping device: soundcore AeroClip (input)\n2026-05-11T22:54:41.038928Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-11T22:54:41.039052Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: soundcore AeroClip (input)\n2026-05-11T22:54:41.039131Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n2026-05-11T22:54:42.005620Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-11T22:54:44.076894Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-11T22:54:48.213325Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=0 rows_returned=234 elapsed=1.275494791s\n2026-05-11T22:54:48.379801Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\nzsh: terminated npx screenpipe@latest record\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-05-12T09:21:07.201625Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store\nchecking permissions...\n screen recording: ok\n microphone: ok\n accessibility: ok\n2026-05-12T09:21:07.328817Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-05-12T09:21:10.020463Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-05-12T09:21:10.024711Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-05-12T09:21:10.025571Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-05-12T09:21:10.055207Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true\n2026-05-12T09:21:10.055275Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-05-12T09:21:10.666779Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-05-12T09:21:10.666832Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-05-12T09:21:10.666681Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-05-12T09:21:10.666983Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-05-12T09:21:10.666647Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-05-12T09:21:10.673969Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-05-12T09:21:10.675449Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-05-12T09:21:10.676236Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-05-12T09:21:10.676638Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-05-12T09:21:10.677056Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-05-12T09:21:10.677293Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-05-12T09:21:10.677398Z INFO screenpipe_core::pipes: loaded 6 pipes from \"/Users/lukas/.screenpipe/pipes\"\n\n\n\n _ \n __________________ ___ ____ ____ (_____ ___ \n / ___/ ___/ ___/ _ \\/ _ \\/ __ \\ / __ \\/ / __ \\/ _ \\\n (__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/\n/____/\\___/_/ \\___/\\___/_/ /_/ / .___/_/ .___/\\___/ \n /_/ /_/ \n\n\n\npower AI by everything you've seen, said or heard\nopen source | runs locally | developer friendly\n\n\n┌────────────────────────┬────────────────────────────────────┐\n│ setting │ value │\n├────────────────────────┼────────────────────────────────────┤\n│ audio chunk duration │ 30 seconds │\n│ port │ 3030 │\n│ audio disabled │ false │\n│ vision disabled │ false │\n│ pause on DRM content │ false │\n│ audio engine │ Parakeet │\n│ vad engine │ Silero │\n│ data directory │ /Users/lukas/.screenpipe │\n│ debug mode │ false │\n│ telemetry │ true │\n│ use pii removal │ true │\n│ use all monitors │ true │\n│ ignored windows │ [] │\n│ included windows │ [] │\n│ cloud sync │ disabled │\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n│ retention mode │ media-only (keep transcripts) │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ MacBook Pro Microphone (input) │\n│ │ System Audio (output) │\n└────────────────────────┴────────────────────────────────────┘\nyou are using local processing. all your data stays on your computer.\n\nwarning: telemetry is enabled. only error-level data will be sent.\nto disable, use the --disable-telemetry flag.\n\ncheck latest changes here: https://github.com/screenpipe/screenpipe/releases\n2026-05-12T09:21:10.684547Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\n2026-05-12T09:21:10.686111Z INFO screenpipe: starting UI event capture\n2026-05-12T09:21:10.696691Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n2026-05-12T09:21:10.705742Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-05-12T09:21:10.712331Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-05-12T09:21:10.753596Z INFO screenpipe_engine::ui_recorder: UI recording session started: eee53fe6-52d6-4c4e-a7e5-11ede410f444\n2026-05-12T09:21:10.753638Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-05-12T09:21:10.753679Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-11 06:21:10.753677 UTC to 2026-05-12 06:21:10.753677 UTC)\n2026-05-12T09:21:10.754945Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-05-12T09:21:10.764596Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-05-12T09:21:10.771437Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-05-12T09:21:15.451981Z WARN sqlx::query: summary=\"SELECT f.id, f.timestamp, f.offset_index, …\" db.statement=\"\\n\\nSELECT\\n f.id,\\n f.timestamp,\\n f.offset_index,\\n COALESCE(\\n SUBSTR(f.full_text, 1, 200),\\n SUBSTR(f.accessibility_text, 1, 200),\\n (\\n SELECT\\n SUBSTR(ot.text, 1, 200)\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as text,\\n COALESCE(\\n f.app_name,\\n (\\n SELECT\\n ot.app_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as app_name,\\n COALESCE(\\n f.window_name,\\n (\\n SELECT\\n ot.window_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as window_name,\\n COALESCE(vc.device_name, f.device_name) as screen_device,\\n COALESCE(vc.file_path, f.snapshot_path) as video_path,\\n COALESCE(vc.fps, 0.033) as chunk_fps,\\n f.browser_url,\\n f.machine_id\\nFROM\\n frames f\\n LEFT JOIN video_chunks vc ON f.video_chunk_id = vc.id\\nWHERE\\n f.timestamp >= ?1\\n AND f.timestamp <= ?2\\n AND COALESCE(vc.file_path, f.snapshot_path, '') NOT LIKE 'cloud://%'\\nORDER BY\\n f.timestamp DESC,\\n f.offset_index DESC\\nLIMIT\\n 10000\\n\" rows_affected=0 rows_returned=6633 elapsed=4.697616625s\n2026-05-12T09:21:15.476188Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 6633 frame entries, coverage from 2026-05-11 06:21:10.753677 UTC\n2026-05-12T09:21:16.549935Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-05-12T09:21:16.550139Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-05-12T09:21:16.550184Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-05-12T09:21:19.459497Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)\n2026-05-12T09:21:19.463986Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-05-12T09:21:19.465573Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)\n2026-05-12T09:21:19.467110Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)\n2026-05-12T09:21:19.468420Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-05-12T09:21:20.691544Z INFO screenpipe_audio::transcription::engine: whisper model available: \"/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin\"\n2026-05-12T09:21:20.692520Z INFO screenpipe_audio::transcription::whisper::model: whisper context: gpu acceleration enabled (Metal on macOS, Vulkan on Windows)\n2026-05-12T09:21:20.692565Z INFO screenpipe_audio::transcription::engine: loading whisper model with GPU acceleration...\nwhisper_init_from_file_with_params_no_state: loading model from '/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin'\nwhisper_init_with_params_no_state: use gpu = 1\nwhisper_init_with_params_no_state: flash attn = 0\nwhisper_init_with_params_no_state: gpu_device = 0\nwhisper_init_with_params_no_state: dtw = 0\nggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices\nggml_metal_library_init: using embedded metal library\nggml_metal_library_init: loaded in 0.036 sec\nggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)\nggml_metal_device_init: GPU name: Apple M1\nggml_metal_device_init: GPU family: MTLGPUFamilyApple7 (1007)\nggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)\nggml_metal_device_init: GPU family: MTLGPUFamilyMetal3 (5001)\nggml_metal_device_init: simdgroup reduction = true\nggml_metal_device_init: simdgroup matrix mul. = true\nggml_metal_device_init: has unified memory = true\nggml_metal_device_init: has bfloat = true\nggml_metal_device_init: has tensor = false\nggml_metal_device_init: use residency sets = true\nggml_metal_device_init: use shared buffers = true\nggml_metal_device_init: recommendedMaxWorkingSetSize = 11453.25 MB\nwhisper_init_with_params_no_state: devices = 3\nwhisper_init_with_params_no_state: backends = 3\nwhisper_model_load: loading model\nwhisper_model_load: n_vocab = 51865\nwhisper_model_load: n_audio_ctx = 1500\nwhisper_model_load: n_audio_state = 384\nwhisper_model_load: n_audio_head = 6\nwhisper_model_load: n_audio_layer = 4\nwhisper_model_load: n_text_ctx = 448\nwhisper_model_load: n_text_state = 384\nwhisper_model_load: n_text_head = 6\nwhisper_model_load: n_text_layer = 4\nwhisper_model_load: n_mels = 80\nwhisper_model_load: ftype = 1\nwhisper_model_load: qntvr = 0\nwhisper_model_load: type = 1 (tiny)\nwhisper_model_load: adding 1608 extra tokens\nwhisper_model_load: n_langs = 99\nwhisper_model_load: Metal total size = 77.11 MB\nwhisper_model_load: model size = 77.11 MB\n2026-05-12T09:21:20.866406Z INFO screenpipe_audio::transcription::engine: whisper model loaded successfully\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\n2026-05-12T09:21:20.896976Z INFO screenpipe_audio::audio_manager::manager: transcription session created (will be reused across segments)\n2026-05-12T09:21:20.928794Z INFO screenpipe_audio::audio_manager::manager: seeded 14 speakers (named + unnamed) from DB into embedding manager\n2026-05-12T09:21:20.929372Z INFO screenpipe_audio::audio_manager::manager: audio manager started\n2026-05-12T09:21:20.930136Z INFO screenpipe_audio::audio_manager::manager: calendar-assisted speaker diarization: listening for meeting events\n2026-05-12T09:21:21.212480Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-12T09:21:22.112224Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-12T09:21:22.697027Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 1: frame_id=21773, dur=116ms\n2026-05-12T09:21:23.853614Z INFO screenpipe_audio::device::device_manager: starting recording for device: System Audio (output)\n2026-05-12T09:21:23.854499Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for System Audio (output) (unknown / 30s segments)\n2026-05-12T09:21:23.854491Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-12T09:21:28.046940Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-12T09:21:28.381213Z WARN screenpipe_a11y::tree::macos_lines: lines: AXUIElementCopyParameterizedAttributeValue(AXLineForIndex) failed status=os::Status { raw: -25212, fcc: \"....\", help: \"https://www.osstatus.com?search=-25212\" } — first failure (further failures suppressed); search highlights will fall back to paragraph bbox on this app\n2026-05-12T09:21:28.684461Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 2: frame_id=21775, dur=90ms\n2026-05-12T09:22:12.427026Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=2 elapsed=1.759127041s\n2026-05-12T09:22:12.427274Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames\n2026-05-12T09:22:12.869213Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.2MB → 0.3MB (0.9x), 1 JPEGs deleted\n2026-05-12T09:22:13.304558Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.3MB → 0.4MB (0.9x), 1 JPEGs deleted\n2026-05-12T09:22:39.009649Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-1944753676112650055, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T09:23:23.041658Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.27027926,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.27227393,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (-zsh)","depth":2,"bounds":{"left":0.33759972,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.33959442,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.40492022,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.4069149,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.4722407,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.4742354,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.53956115,"top":1.0,"width":0.06715426,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.5415558,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.60671544,"top":1.0,"width":0.06715426,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.6087101,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.67386967,"top":1.0,"width":0.06715426,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.67586434,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.7273936,"top":1.0,"width":0.01861702,"height":-0.023144484},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"screenpipe\"","depth":1,"bounds":{"left":0.4956782,"top":1.0,"width":0.027925532,"height":-0.02394259},"on_screen":true,"role_description":"text"}]...
|
4600003808199063888
|
-852231712889047584
|
app_switch
|
accessibility
|
NULL
|
whisper_init_state: kv pad size = 2.36 MB
whi whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:33:55.437876Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:35:57.413206Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
2026-05-11T22:37:14.870936Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=0 elapsed=1.714129166s
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:37:59.603705Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:40:02.174925Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: install a starter bundle of pipes:
screenpipe install [URL_WITH_CREDENTIALS] record
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-05-12T09:21:07.201625Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store
checking permissions...
screen recording: ok
microphone: ok
accessibility: ok
2026-05-12T09:21:07.328817Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-05-12T09:21:10.020463Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-05-12T09:21:10.024711Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-05-12T09:21:10.025571Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-05-12T09:21:10.055207Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true
2026-05-12T09:21:10.055275Z INFO screenpipe: meeting detector enabled — independent of transcription mode
2026-05-12T09:21:10.666779Z INFO screenpipe: API server listening on [IP_ADDRESS]:3030 (localhost only)
2026-05-12T09:21:10.666832Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key
2026-05-12T09:21:10.666681Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)
2026-05-12T09:21:10.666983Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager
2026-05-12T09:21:10.666647Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)
2026-05-12T09:21:10.673969Z INFO screenpipe_core::pipes: loaded pipe: day-recap
2026-05-12T09:21:10.675449Z INFO screenpipe_core::pipes: loaded pipe: standup-update
2026-05-12T09:21:10.676236Z INFO screenpipe_core::pipes: loaded pipe: ai-habits
2026-05-12T09:21:10.676638Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown
2026-05-12T09:21:10.677056Z INFO screenpipe_core::pipes: loaded pipe: video-export
2026-05-12T09:21:10.677293Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary
2026-05-12T09:21:10.677398Z INFO screenpipe_core::pipes: loaded 6 pipes from "/Users/lukas/.screenpipe/pipes"
_
__________________ ___ ____ ____ (_____ ___
/ ___/ ___/ ___/ _ \/ _ \/ __ \ / __ \/ / __ \/ _ \
(__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/
/____/\___/_/ \___/\___/_/ /_/ / .___/_/ .___/\___/
/_/ /_/
power AI by everything you've seen, said or heard
open source | runs locally | developer friendly
┌────────────────────────┬────────────────────────────────────┐
│ setting │ value │
├────────────────────────┼────────────────────────────────────┤
│ audio chunk duration │ 30 seconds │
│ port │ 3030 │
│ audio disabled │ false │
│ vision disabled │ false │
│ pause on DRM content │ false │
│ audio engine │ Parakeet │
│ vad engine │ Silero │
│ data directory │ /Users/lukas/.screenpipe │
│ debug mode │ false │
│ telemetry │ true │
│ use pii removal │ true │
│ use all monitors │ true │
│ ignored windows │ [] │
│ included windows │ [] │
│ cloud sync │ disabled │
│ auto-destruct pid │ 0 │
│ deepgram key │ not set │
│ api auth │ enabled │
│ encrypt secrets │ disabled │
│ retention days │ 14 │
│ retention mode │ media-only (keep transcripts) │
├────────────────────────┼────────────────────────────────────┤
│ languages │ │
│ │ all languages │
├────────────────────────┼────────────────────────────────────┤
│ monitors │ │
│ │ id: 1 │
│ │ id: 2 │
├────────────────────────┼────────────────────────────────────┤
│ audio devices │ │
│ │ MacBook Pro Microphone (input) │
│ │ System Audio (output) │
└────────────────────────┴────────────────────────────────────┘
you are using local processing. all your data stays on your computer.
warning: telemetry is enabled. only error-level data will be sent.
to disable, use the --disable-telemetry flag.
check latest changes here: https://github.com/screenpipe/screenpipe/releases
2026-05-12T09:21:10.684547Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)
2026-05-12T09:21:10.686111Z INFO screenpipe: starting UI event capture
2026-05-12T09:21:10.696691Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh
2026-05-12T09:21:10.705742Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))
2026-05-12T09:21:10.712331Z INFO screenpipe_engine::ui_recorder: Starting UI event capture
2026-05-12T09:21:10.753596Z INFO screenpipe_engine::ui_recorder: UI recording session started: eee53fe6-52d6-4c4e-a7e5-11ede410f444
2026-05-12T09:21:10.753638Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)
2026-05-12T09:21:10.753679Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-11 06:21:10.753677 UTC to 2026-05-12 06:21:10.753677 UTC)
2026-05-12T09:21:10.754945Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)
2026-05-12T09:21:10.764596Z INFO screenpipe_engine::server: Server listening on [IP_ADDRESS]:3030
2026-05-12T09:21:10.771437Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030
2026-05-12T09:21:15.451981Z WARN sqlx::query: summary="SELECT f.id, f.timestamp, f.offset_index, …" db.statement="\n\nSELECT\n f.id,\n f.timestamp,\n f.offset_index,\n COALESCE(\n SUBSTR(f.full_text, 1, 200),\n SUBSTR(f.accessibility_text, 1, 200),\n (\n SELECT\n SUBSTR(ot.text, 1, 200)\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as text,\n COALESCE(\n f.app_name,\n (\n SELECT\n ot.app_name\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as app_name,\n COALESCE(\n f.window_name,\n (\n SELECT\n ot.window_name\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as window_name,\n COALESCE(vc.device_name, f.device_name) as screen_device,\n COALESCE(vc.file_path, f.snapshot_path) as video_path,\n COALESCE(vc.fps, 0.033) as chunk_fps,\n f.browser_url,\n f.machine_id\nFROM\n frames f\n LEFT JOIN video_chunks vc ON f.video_chunk_id = vc.id\nWHERE\n f.timestamp >= ?1\n AND f.timestamp <= ?2\n AND COALESCE(vc.file_path, f.snapshot_path, '') NOT LIKE 'cloud://%'\nORDER BY\n f.timestamp DESC,\n f.offset_index DESC\nLIMIT\n 10000\n" rows_affected=0 rows_returned=6633 elapsed=4.697616625s
2026-05-12T09:21:15.476188Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 6633 frame entries, coverage from 2026-05-11 06:21:10.753677 UTC
2026-05-12T09:21:16.549935Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)
2026-05-12T09:21:16.550139Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)
2026-05-12T09:21:16.550184Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)
2026-05-12T09:21:19.459497Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)
2026-05-12T09:21:19.463986Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)
2026-05-12T09:21:19.465573Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)
2026-05-12T09:21:19.467110Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)
2026-05-12T09:21:19.468420Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)
2026-05-12T09:21:20.691544Z INFO screenpipe_audio::transcription::engine: whisper model available: "/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin"
2026-05-12T09:21:20.692520Z INFO screenpipe_audio::transcription::whisper::model: whisper context: gpu acceleration enabled (Metal on macOS, Vulkan on Windows)
2026-05-12T09:21:20.692565Z INFO screenpipe_audio::transcription::engine: loading whisper model with GPU acceleration...
whisper_init_from_file_with_params_no_state: loading model from '/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin'
whisper_init_with_params_no_state: use gpu = 1
whisper_init_with_params_no_state: flash attn = 0
whisper_init_with_params_no_state: gpu_device = 0
whisper_init_with_params_no_state: dtw = 0
ggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices
ggml_metal_library_init: using embedded metal library
ggml_metal_library_init: loaded in 0.036 sec
ggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)
ggml_metal_device_init: GPU name: Apple M1
ggml_metal_device_init: GPU family: MTLGPUFamilyApple7 (1007)
ggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)
ggml_metal_device_init: GPU family: MTLGPUFamilyMetal3 (5001)
ggml_metal_device_init: simdgroup reduction = true
ggml_metal_device_init: simdgroup matrix mul. = true
ggml_metal_device_init: has unified memory = true
ggml_metal_device_init: has bfloat = true
ggml_metal_device_init: has tensor = false
ggml_metal_device_init: use residency sets = true
ggml_metal_device_init: use shared buffers = true
ggml_metal_device_init: recommendedMaxWorkingSetSize = 11453.25 MB
whisper_init_with_params_no_state: devices = 3
whisper_init_with_params_no_state: backends = 3
whisper_model_load: loading model
whisper_model_load: n_vocab = 51865
whisper_model_load: n_audio_ctx = 1500
whisper_model_load: n_audio_state = 384
whisper_model_load: n_audio_head = 6
whisper_model_load: n_audio_layer = 4
whisper_model_load: n_text_ctx = 448
whisper_model_load: n_text_state = 384
whisper_model_load: n_text_head = 6
whisper_model_load: n_text_layer = 4
whisper_model_load: n_mels = 80
whisper_model_load: ftype = 1
whisper_model_load: qntvr = 0
whisper_model_load: type = 1 (tiny)
whisper_model_load: adding 1608 extra tokens
whisper_model_load: n_langs = 99
whisper_model_load: Metal total size = 77.11 MB
whisper_model_load: model size = 77.11 MB
2026-05-12T09:21:20.866406Z INFO screenpipe_audio::transcription::engine: whisper model loaded successfully
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
2026-05-12T09:21:20.896976Z INFO screenpipe_audio::audio_manager::manager: transcription session created (will be reused across segments)
2026-05-12T09:21:20.928794Z INFO screenpipe_audio::audio_manager::manager: seeded 14 speakers (named + unnamed) from DB into embedding manager
2026-05-12T09:21:20.929372Z INFO screenpipe_audio::audio_manager::manager: audio manager started
2026-05-12T09:21:20.930136Z INFO screenpipe_audio::audio_manager::manager: calendar-assisted speaker diarization: listening for meeting events
2026-05-12T09:21:21.212480Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-12T09:21:22.112224Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)
2026-05-12T09:21:22.697027Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 1: frame_id=21773, dur=116ms
2026-05-12T09:21:23.853614Z INFO screenpipe_audio::device::device_manager: starting recording for device: System Audio (output)
2026-05-12T09:21:23.854499Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for System Audio (output) (unknown / 30s segments)
2026-05-12T09:21:23.854491Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-12T09:21:28.046940Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)
2026-05-12T09:21:28.381213Z WARN screenpipe_a11y::tree::macos_lines: lines: AXUIElementCopyParameterizedAttributeValue(AXLineForIndex) failed status=os::Status { raw: -25212, fcc: "....", help: "https://www.osstatus.com?search=-25212" } — first failure (further failures suppressed); search highlights will fall back to paragraph bbox on this app
2026-05-12T09:21:28.684461Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 2: frame_id=21775, dur=90ms
2026-05-12T09:22:12.427026Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=2 elapsed=1.759127041s
2026-05-12T09:22:12.427274Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames
2026-05-12T09:22:12.869213Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.2MB → 0.3MB (0.9x), 1 JPEGs deleted
2026-05-12T09:22:13.304558Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.3MB → 0.4MB (0.9x), 1 JPEGs deleted
2026-05-12T09:22:39.009649Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-1944753676112650055, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency...
|
NULL
|
NULL
|
NULL
|
NULL
|
|
21820
|
954
|
21
|
2026-05-12T06:26:38.615488+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-12/1778 /Users/lukas/.screenpipe/data/data/2026-05-12/1778567198615_m1.jpg...
|
iTerm2
|
screenpipe"
|
True
|
NULL
|
monitor_1
|
NULL
|
NULL
|
NULL
|
NULL
|
ggml_metal_init: use fusion = true
ggml_me ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:44:07.738461Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:46:10.863483Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: sign in for higher AI quotas + cloud sync:
screenpipe login
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:48:13.767660Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:50:16.132089Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: get the screenpipe desktop app for the full experience
[URL_WITH_CREDENTIALS] record
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-05-12T09:21:07.201625Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store
checking permissions...
screen recording: ok
microphone: ok
accessibility: ok
2026-05-12T09:21:07.328817Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-05-12T09:21:10.020463Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-05-12T09:21:10.024711Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-05-12T09:21:10.025571Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-05-12T09:21:10.055207Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true
2026-05-12T09:21:10.055275Z INFO screenpipe: meeting detector enabled — independent of transcription mode
2026-05-12T09:21:10.666779Z INFO screenpipe: API server listening on [IP_ADDRESS]:3030 (localhost only)
2026-05-12T09:21:10.666832Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key
2026-05-12T09:21:10.666681Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)
2026-05-12T09:21:10.666983Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager
2026-05-12T09:21:10.666647Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)
2026-05-12T09:21:10.673969Z INFO screenpipe_core::pipes: loaded pipe: day-recap
2026-05-12T09:21:10.675449Z INFO screenpipe_core::pipes: loaded pipe: standup-update
2026-05-12T09:21:10.676236Z INFO screenpipe_core::pipes: loaded pipe: ai-habits
2026-05-12T09:21:10.676638Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown
2026-05-12T09:21:10.677056Z INFO screenpipe_core::pipes: loaded pipe: video-export
2026-05-12T09:21:10.677293Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary
2026-05-12T09:21:10.677398Z INFO screenpipe_core::pipes: loaded 6 pipes from "/Users/lukas/.screenpipe/pipes"
_
__________________ ___ ____ ____ (_____ ___
/ ___/ ___/ ___/ _ \/ _ \/ __ \ / __ \/ / __ \/ _ \
(__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/
/____/\___/_/ \___/\___/_/ /_/ / .___/_/ .___/\___/
/_/ /_/
power AI by everything you've seen, said or heard
open source | runs locally | developer friendly
┌────────────────────────┬────────────────────────────────────┐
│ setting │ value │
├────────────────────────┼────────────────────────────────────┤
│ audio chunk duration │ 30 seconds │
│ port │ 3030 │
│ audio disabled │ false │
│ vision disabled │ false │
│ pause on DRM content │ false │
│ audio engine │ Parakeet │
│ vad engine │ Silero │
│ data directory │ /Users/lukas/.screenpipe │
│ debug mode │ false │
│ telemetry │ true │
│ use pii removal │ true │
│ use all monitors │ true │
│ ignored windows │ [] │
│ included windows │ [] │
│ cloud sync │ disabled │
│ auto-destruct pid │ 0 │
│ deepgram key │ not set │
│ api auth │ enabled │
│ encrypt secrets │ disabled │
│ retention days │ 14 │
│ retention mode │ media-only (keep transcripts) │
├────────────────────────┼────────────────────────────────────┤
│ languages │ │
│ │ all languages │
├────────────────────────┼────────────────────────────────────┤
│ monitors │ │
│ │ id: 1 │
│ │ id: 2 │
├────────────────────────┼────────────────────────────────────┤
│ audio devices │ │
│ │ MacBook Pro Microphone (input) │
│ │ System Audio (output) │
└────────────────────────┴────────────────────────────────────┘
you are using local processing. all your data stays on your computer.
warning: telemetry is enabled. only error-level data will be sent.
to disable, use the --disable-telemetry flag.
check latest changes here: https://github.com/screenpipe/screenpipe/releases
2026-05-12T09:21:10.684547Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)
2026-05-12T09:21:10.686111Z INFO screenpipe: starting UI event capture
2026-05-12T09:21:10.696691Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh
2026-05-12T09:21:10.705742Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))
2026-05-12T09:21:10.712331Z INFO screenpipe_engine::ui_recorder: Starting UI event capture
2026-05-12T09:21:10.753596Z INFO screenpipe_engine::ui_recorder: UI recording session started: eee53fe6-52d6-4c4e-a7e5-11ede410f444
2026-05-12T09:21:10.753638Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)
2026-05-12T09:21:10.753679Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-11 06:21:10.753677 UTC to 2026-05-12 06:21:10.753677 UTC)
2026-05-12T09:21:10.754945Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)
2026-05-12T09:21:10.764596Z INFO screenpipe_engine::server: Server listening on [IP_ADDRESS]:3030
2026-05-12T09:21:10.771437Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030
2026-05-12T09:21:15.451981Z WARN sqlx::query: summary="SELECT f.id, f.timestamp, f.offset_index, …" db.statement="\n\nSELECT\n f.id,\n f.timestamp,\n f.offset_index,\n COALESCE(\n SUBSTR(f.full_text, 1, 200),\n SUBSTR(f.accessibility_text, 1, 200),\n (\n SELECT\n SUBSTR(ot.text, 1, 200)\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as text,\n COALESCE(\n f.app_name,\n (\n SELECT\n ot.app_name\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as app_name,\n COALESCE(\n f.window_name,\n (\n SELECT\n ot.window_name\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as window_name,\n COALESCE(vc.device_name, f.device_name) as screen_device,\n COALESCE(vc.file_path, f.snapshot_path) as video_path,\n COALESCE(vc.fps, 0.033) as chunk_fps,\n f.browser_url,\n f.machine_id\nFROM\n frames f\n LEFT JOIN video_chunks vc ON f.video_chunk_id = vc.id\nWHERE\n f.timestamp >= ?1\n AND f.timestamp <= ?2\n AND COALESCE(vc.file_path, f.snapshot_path, '') NOT LIKE 'cloud://%'\nORDER BY\n f.timestamp DESC,\n f.offset_index DESC\nLIMIT\n 10000\n" rows_affected=0 rows_returned=6633 elapsed=4.697616625s
2026-05-12T09:21:15.476188Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 6633 frame entries, coverage from 2026-05-11 06:21:10.753677 UTC
2026-05-12T09:21:16.549935Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)
2026-05-12T09:21:16.550139Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)
2026-05-12T09:21:16.550184Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)
2026-05-12T09:21:19.459497Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)
2026-05-12T09:21:19.463986Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)
2026-05-12T09:21:19.465573Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)
2026-05-12T09:21:19.467110Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)
2026-05-12T09:21:19.468420Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)
2026-05-12T09:21:20.691544Z INFO screenpipe_audio::transcription::engine: whisper model available: "/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin"
2026-05-12T09:21:20.692520Z INFO screenpipe_audio::transcription::whisper::model: whisper context: gpu acceleration enabled (Metal on macOS, Vulkan on Windows)
2026-05-12T09:21:20.692565Z INFO screenpipe_audio::transcription::engine: loading whisper model with GPU acceleration...
whisper_init_from_file_with_params_no_state: loading model from '/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin'
whisper_init_with_params_no_state: use gpu = 1
whisper_init_with_params_no_state: flash attn = 0
whisper_init_with_params_no_state: gpu_device = 0
whisper_init_with_params_no_state: dtw = 0
ggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices
ggml_metal_library_init: using embedded metal library
ggml_metal_library_init: loaded in 0.036 sec
ggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)
ggml_metal_device_init: GPU name: Apple M1
ggml_metal_device_init: GPU family: MTLGPUFamilyApple7 (1007)
ggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)
ggml_metal_device_init: GPU family: MTLGPUFamilyMetal3 (5001)
ggml_metal_device_init: simdgroup reduction = true
ggml_metal_device_init: simdgroup matrix mul. = true
ggml_metal_device_init: has unified memory = true
ggml_metal_device_init: has bfloat = true
ggml_metal_device_init: has tensor = false
ggml_metal_device_init: use residency sets = true
ggml_metal_device_init: use shared buffers = true
ggml_metal_device_init: recommendedMaxWorkingSetSize = 11453.25 MB
whisper_init_with_params_no_state: devices = 3
whisper_init_with_params_no_state: backends = 3
whisper_model_load: loading model
whisper_model_load: n_vocab = 51865
whisper_model_load: n_audio_ctx = 1500
whisper_model_load: n_audio_state = 384
whisper_model_load: n_audio_head = 6
whisper_model_load: n_audio_layer = 4
whisper_model_load: n_text_ctx = 448
whisper_model_load: n_text_state = 384
whisper_model_load: n_text_head = 6
whisper_model_load: n_text_layer = 4
whisper_model_load: n_mels = 80
whisper_model_load: ftype = 1
whisper_model_load: qntvr = 0
whisper_model_load: type = 1 (tiny)
whisper_model_load: adding 1608 extra tokens
whisper_model_load: n_langs = 99
whisper_model_load: Metal total size = 77.11 MB
whisper_model_load: model size = 77.11 MB
2026-05-12T09:21:20.866406Z INFO screenpipe_audio::transcription::engine: whisper model loaded successfully
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
2026-05-12T09:21:20.896976Z INFO screenpipe_audio::audio_manager::manager: transcription session created (will be reused across segments)
2026-05-12T09:21:20.928794Z INFO screenpipe_audio::audio_manager::manager: seeded 14 speakers (named + unnamed) from DB into embedding manager
2026-05-12T09:21:20.929372Z INFO screenpipe_audio::audio_manager::manager: audio manager started
2026-05-12T09:21:20.930136Z INFO screenpipe_audio::audio_manager::manager: calendar-assisted speaker diarization: listening for meeting events
2026-05-12T09:21:21.212480Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-12T09:21:22.112224Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)
2026-05-12T09:21:22.697027Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 1: frame_id=21773, dur=116ms
2026-05-12T09:21:23.853614Z INFO screenpipe_audio::device::device_manager: starting recording for device: System Audio (output)
2026-05-12T09:21:23.854499Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for System Audio (output) (unknown / 30s segments)
2026-05-12T09:21:23.854491Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-12T09:21:28.046940Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)
2026-05-12T09:21:28.381213Z WARN screenpipe_a11y::tree::macos_lines: lines: AXUIElementCopyParameterizedAttributeValue(AXLineForIndex) failed status=os::Status { raw: -25212, fcc: "....", help: "https://www.osstatus.com?search=-25212" } — first failure (further failures suppressed); search highlights will fall back to paragraph bbox on this app
2026-05-12T09:21:28.684461Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 2: frame_id=21775, dur=90ms
2026-05-12T09:22:12.427026Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=2 elapsed=1.759127041s
2026-05-12T09:22:12.427274Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames
2026-05-12T09:22:12.869213Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.2MB → 0.3MB (0.9x), 1 JPEGs deleted
2026-05-12T09:22:13.304558Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.3MB → 0.4MB (0.9x), 1 JPEGs deleted
2026-05-12T09:22:39.009649Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-1944753676112650055, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T09:23:23.041658Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T09:25:08.112066Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-2757320308507279294, trigger=click)
2026-05-12T09:25:08.126094Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-2757320308507279294, trigger=click)
2026-05-12T09:25:08.743069Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-2757320308507279294, trigger=click)
2026-05-12T09:25:08.782136Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-2757320308507279294, trigger=click)
2026-05-12T09:25:18.022691Z WARN screenpipe_a11y::platform::macos: clipboard capture disabled — prior NSPasteboard crash detected. delete /Users/lukas/.screenpipe/clipboard-disabled-after-crash to re-enable
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buff...
|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"ggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:44:07.738461Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:46:10.863483Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:48:13.767660Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:50:16.132089Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:52:18.678586Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T22:52:18.727748Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=0 elapsed=1.378493375s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:54:20.840336Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T22:54:38.134704Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T22:54:38.619890Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for soundcore AeroClip (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-11T22:54:38.630348Z WARN screenpipe_audio::audio_manager::manager: recording for device soundcore AeroClip (input) exited with error: stream rebuild required after screen unlock for soundcore AeroClip (input) (recovery is automatic via device_monitor)\n2026-05-11T22:54:38.810449Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T22:54:40.719100Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for soundcore AeroClip (input), cleaning up for restart\n2026-05-11T22:54:40.719269Z INFO screenpipe_audio::device::device_manager: Stopping device: soundcore AeroClip (input)\n2026-05-11T22:54:41.038928Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-11T22:54:41.039052Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: soundcore AeroClip (input)\n2026-05-11T22:54:41.039131Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n2026-05-11T22:54:42.005620Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-11T22:54:44.076894Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-11T22:54:48.213325Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=0 rows_returned=234 elapsed=1.275494791s\n2026-05-11T22:54:48.379801Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\nzsh: terminated npx screenpipe@latest record\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-05-12T09:21:07.201625Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store\nchecking permissions...\n screen recording: ok\n microphone: ok\n accessibility: ok\n2026-05-12T09:21:07.328817Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-05-12T09:21:10.020463Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-05-12T09:21:10.024711Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-05-12T09:21:10.025571Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-05-12T09:21:10.055207Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true\n2026-05-12T09:21:10.055275Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-05-12T09:21:10.666779Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-05-12T09:21:10.666832Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-05-12T09:21:10.666681Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-05-12T09:21:10.666983Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-05-12T09:21:10.666647Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-05-12T09:21:10.673969Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-05-12T09:21:10.675449Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-05-12T09:21:10.676236Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-05-12T09:21:10.676638Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-05-12T09:21:10.677056Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-05-12T09:21:10.677293Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-05-12T09:21:10.677398Z INFO screenpipe_core::pipes: loaded 6 pipes from \"/Users/lukas/.screenpipe/pipes\"\n\n\n\n _ \n __________________ ___ ____ ____ (_____ ___ \n / ___/ ___/ ___/ _ \\/ _ \\/ __ \\ / __ \\/ / __ \\/ _ \\\n (__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/\n/____/\\___/_/ \\___/\\___/_/ /_/ / .___/_/ .___/\\___/ \n /_/ /_/ \n\n\n\npower AI by everything you've seen, said or heard\nopen source | runs locally | developer friendly\n\n\n┌────────────────────────┬────────────────────────────────────┐\n│ setting │ value │\n├────────────────────────┼────────────────────────────────────┤\n│ audio chunk duration │ 30 seconds │\n│ port │ 3030 │\n│ audio disabled │ false │\n│ vision disabled │ false │\n│ pause on DRM content │ false │\n│ audio engine │ Parakeet │\n│ vad engine │ Silero │\n│ data directory │ /Users/lukas/.screenpipe │\n│ debug mode │ false │\n│ telemetry │ true │\n│ use pii removal │ true │\n│ use all monitors │ true │\n│ ignored windows │ [] │\n│ included windows │ [] │\n│ cloud sync │ disabled │\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n│ retention mode │ media-only (keep transcripts) │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ MacBook Pro Microphone (input) │\n│ │ System Audio (output) │\n└────────────────────────┴────────────────────────────────────┘\nyou are using local processing. all your data stays on your computer.\n\nwarning: telemetry is enabled. only error-level data will be sent.\nto disable, use the --disable-telemetry flag.\n\ncheck latest changes here: https://github.com/screenpipe/screenpipe/releases\n2026-05-12T09:21:10.684547Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\n2026-05-12T09:21:10.686111Z INFO screenpipe: starting UI event capture\n2026-05-12T09:21:10.696691Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n2026-05-12T09:21:10.705742Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-05-12T09:21:10.712331Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-05-12T09:21:10.753596Z INFO screenpipe_engine::ui_recorder: UI recording session started: eee53fe6-52d6-4c4e-a7e5-11ede410f444\n2026-05-12T09:21:10.753638Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-05-12T09:21:10.753679Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-11 06:21:10.753677 UTC to 2026-05-12 06:21:10.753677 UTC)\n2026-05-12T09:21:10.754945Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-05-12T09:21:10.764596Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-05-12T09:21:10.771437Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-05-12T09:21:15.451981Z WARN sqlx::query: summary=\"SELECT f.id, f.timestamp, f.offset_index, …\" db.statement=\"\\n\\nSELECT\\n f.id,\\n f.timestamp,\\n f.offset_index,\\n COALESCE(\\n SUBSTR(f.full_text, 1, 200),\\n SUBSTR(f.accessibility_text, 1, 200),\\n (\\n SELECT\\n SUBSTR(ot.text, 1, 200)\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as text,\\n COALESCE(\\n f.app_name,\\n (\\n SELECT\\n ot.app_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as app_name,\\n COALESCE(\\n f.window_name,\\n (\\n SELECT\\n ot.window_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as window_name,\\n COALESCE(vc.device_name, f.device_name) as screen_device,\\n COALESCE(vc.file_path, f.snapshot_path) as video_path,\\n COALESCE(vc.fps, 0.033) as chunk_fps,\\n f.browser_url,\\n f.machine_id\\nFROM\\n frames f\\n LEFT JOIN video_chunks vc ON f.video_chunk_id = vc.id\\nWHERE\\n f.timestamp >= ?1\\n AND f.timestamp <= ?2\\n AND COALESCE(vc.file_path, f.snapshot_path, '') NOT LIKE 'cloud://%'\\nORDER BY\\n f.timestamp DESC,\\n f.offset_index DESC\\nLIMIT\\n 10000\\n\" rows_affected=0 rows_returned=6633 elapsed=4.697616625s\n2026-05-12T09:21:15.476188Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 6633 frame entries, coverage from 2026-05-11 06:21:10.753677 UTC\n2026-05-12T09:21:16.549935Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-05-12T09:21:16.550139Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-05-12T09:21:16.550184Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-05-12T09:21:19.459497Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)\n2026-05-12T09:21:19.463986Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-05-12T09:21:19.465573Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)\n2026-05-12T09:21:19.467110Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)\n2026-05-12T09:21:19.468420Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-05-12T09:21:20.691544Z INFO screenpipe_audio::transcription::engine: whisper model available: \"/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin\"\n2026-05-12T09:21:20.692520Z INFO screenpipe_audio::transcription::whisper::model: whisper context: gpu acceleration enabled (Metal on macOS, Vulkan on Windows)\n2026-05-12T09:21:20.692565Z INFO screenpipe_audio::transcription::engine: loading whisper model with GPU acceleration...\nwhisper_init_from_file_with_params_no_state: loading model from '/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin'\nwhisper_init_with_params_no_state: use gpu = 1\nwhisper_init_with_params_no_state: flash attn = 0\nwhisper_init_with_params_no_state: gpu_device = 0\nwhisper_init_with_params_no_state: dtw = 0\nggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices\nggml_metal_library_init: using embedded metal library\nggml_metal_library_init: loaded in 0.036 sec\nggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)\nggml_metal_device_init: GPU name: Apple M1\nggml_metal_device_init: GPU family: MTLGPUFamilyApple7 (1007)\nggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)\nggml_metal_device_init: GPU family: MTLGPUFamilyMetal3 (5001)\nggml_metal_device_init: simdgroup reduction = true\nggml_metal_device_init: simdgroup matrix mul. = true\nggml_metal_device_init: has unified memory = true\nggml_metal_device_init: has bfloat = true\nggml_metal_device_init: has tensor = false\nggml_metal_device_init: use residency sets = true\nggml_metal_device_init: use shared buffers = true\nggml_metal_device_init: recommendedMaxWorkingSetSize = 11453.25 MB\nwhisper_init_with_params_no_state: devices = 3\nwhisper_init_with_params_no_state: backends = 3\nwhisper_model_load: loading model\nwhisper_model_load: n_vocab = 51865\nwhisper_model_load: n_audio_ctx = 1500\nwhisper_model_load: n_audio_state = 384\nwhisper_model_load: n_audio_head = 6\nwhisper_model_load: n_audio_layer = 4\nwhisper_model_load: n_text_ctx = 448\nwhisper_model_load: n_text_state = 384\nwhisper_model_load: n_text_head = 6\nwhisper_model_load: n_text_layer = 4\nwhisper_model_load: n_mels = 80\nwhisper_model_load: ftype = 1\nwhisper_model_load: qntvr = 0\nwhisper_model_load: type = 1 (tiny)\nwhisper_model_load: adding 1608 extra tokens\nwhisper_model_load: n_langs = 99\nwhisper_model_load: Metal total size = 77.11 MB\nwhisper_model_load: model size = 77.11 MB\n2026-05-12T09:21:20.866406Z INFO screenpipe_audio::transcription::engine: whisper model loaded successfully\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\n2026-05-12T09:21:20.896976Z INFO screenpipe_audio::audio_manager::manager: transcription session created (will be reused across segments)\n2026-05-12T09:21:20.928794Z INFO screenpipe_audio::audio_manager::manager: seeded 14 speakers (named + unnamed) from DB into embedding manager\n2026-05-12T09:21:20.929372Z INFO screenpipe_audio::audio_manager::manager: audio manager started\n2026-05-12T09:21:20.930136Z INFO screenpipe_audio::audio_manager::manager: calendar-assisted speaker diarization: listening for meeting events\n2026-05-12T09:21:21.212480Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-12T09:21:22.112224Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-12T09:21:22.697027Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 1: frame_id=21773, dur=116ms\n2026-05-12T09:21:23.853614Z INFO screenpipe_audio::device::device_manager: starting recording for device: System Audio (output)\n2026-05-12T09:21:23.854499Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for System Audio (output) (unknown / 30s segments)\n2026-05-12T09:21:23.854491Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-12T09:21:28.046940Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-12T09:21:28.381213Z WARN screenpipe_a11y::tree::macos_lines: lines: AXUIElementCopyParameterizedAttributeValue(AXLineForIndex) failed status=os::Status { raw: -25212, fcc: \"....\", help: \"https://www.osstatus.com?search=-25212\" } — first failure (further failures suppressed); search highlights will fall back to paragraph bbox on this app\n2026-05-12T09:21:28.684461Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 2: frame_id=21775, dur=90ms\n2026-05-12T09:22:12.427026Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=2 elapsed=1.759127041s\n2026-05-12T09:22:12.427274Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames\n2026-05-12T09:22:12.869213Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.2MB → 0.3MB (0.9x), 1 JPEGs deleted\n2026-05-12T09:22:13.304558Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.3MB → 0.4MB (0.9x), 1 JPEGs deleted\n2026-05-12T09:22:39.009649Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-1944753676112650055, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T09:23:23.041658Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T09:25:08.112066Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-2757320308507279294, trigger=click)\n2026-05-12T09:25:08.126094Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-2757320308507279294, trigger=click)\n2026-05-12T09:25:08.743069Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-2757320308507279294, trigger=click)\n2026-05-12T09:25:08.782136Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-2757320308507279294, trigger=click)\n2026-05-12T09:25:18.022691Z WARN screenpipe_a11y::platform::macos: clipboard capture disabled — prior NSPasteboard crash detected. delete /Users/lukas/.screenpipe/clipboard-disabled-after-crash to re-enable\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T09:25:26.200795Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T09:25:59.192521Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=1681167153903710140, trigger=click)\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\n2026-05-12T09:26:37.982517Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 105.4ms elapsed (expected 5.3ms) → inserting 100.1ms silence (9608 samples)","depth":4,"on_screen":true,"value":"ggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:44:07.738461Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:46:10.863483Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:48:13.767660Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:50:16.132089Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:52:18.678586Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T22:52:18.727748Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=0 elapsed=1.378493375s\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-11T22:54:20.840336Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-11T22:54:38.134704Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T22:54:38.619890Z INFO screenpipe_audio::core::run_record_and_transcribe: screen unlocked — rebuilding stream for soundcore AeroClip (input) (avoids zombie-callback state observed after sleep/wake on macOS, Windows, and Linux)\n2026-05-11T22:54:38.630348Z WARN screenpipe_audio::audio_manager::manager: recording for device soundcore AeroClip (input) exited with error: stream rebuild required after screen unlock for soundcore AeroClip (input) (recovery is automatic via device_monitor)\n2026-05-11T22:54:38.810449Z INFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSession safety-net poll)\n2026-05-11T22:54:40.719100Z WARN screenpipe_audio::audio_manager::device_monitor: [DEVICE_RECOVERY] detected stale recording handle for soundcore AeroClip (input), cleaning up for restart\n2026-05-11T22:54:40.719269Z INFO screenpipe_audio::device::device_manager: Stopping device: soundcore AeroClip (input)\n2026-05-11T22:54:41.038928Z INFO screenpipe_audio::device::device_manager: starting recording for device: soundcore AeroClip (input)\n2026-05-11T22:54:41.039052Z INFO screenpipe_audio::audio_manager::device_monitor: restarted with system default device: soundcore AeroClip (input)\n2026-05-11T22:54:41.039131Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for soundcore AeroClip (input) (bluetooth / 30s segments)\n2026-05-11T22:54:42.005620Z INFO screenpipe_engine::event_driven_capture: invalidating persistent streams after unlock/wake for monitor 1\n2026-05-11T22:54:44.076894Z INFO sck_rs::stream_manager: stopped 2 persistent stream(s)\n2026-05-11T22:54:48.213325Z WARN sqlx::query: summary=\"SELECT DISTINCT app_name, window_name, …\" db.statement=\"\\n\\nSELECT\\n DISTINCT app_name,\\n window_name,\\n browser_url\\nFROM\\n frames\\nWHERE\\n timestamp > datetime('now', '-30 seconds')\\n AND app_name IS NOT NULL\\n AND window_name IS NOT NULL\\n\" rows_affected=0 rows_returned=234 elapsed=1.275494791s\n2026-05-11T22:54:48.379801Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\nzsh: terminated npx screenpipe@latest record\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record\ndetected hardware tier: Mid\nwarning: parakeet is not supported on this platform, using whisper-tiny instead\n2026-05-12T09:21:07.201625Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store\nchecking permissions...\n screen recording: ok\n microphone: ok\n accessibility: ok\n2026-05-12T09:21:07.328817Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6\n2026-05-12T09:21:10.020463Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor\n2026-05-12T09:21:10.024711Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)\n2026-05-12T09:21:10.025571Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)\n2026-05-12T09:21:10.055207Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true\n2026-05-12T09:21:10.055275Z INFO screenpipe: meeting detector enabled — independent of transcription mode\n2026-05-12T09:21:10.666779Z INFO screenpipe: API server listening on 127.0.0.1:3030 (localhost only)\n2026-05-12T09:21:10.666832Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key\n2026-05-12T09:21:10.666681Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)\n2026-05-12T09:21:10.666983Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager\n2026-05-12T09:21:10.666647Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)\n2026-05-12T09:21:10.673969Z INFO screenpipe_core::pipes: loaded pipe: day-recap\n2026-05-12T09:21:10.675449Z INFO screenpipe_core::pipes: loaded pipe: standup-update\n2026-05-12T09:21:10.676236Z INFO screenpipe_core::pipes: loaded pipe: ai-habits\n2026-05-12T09:21:10.676638Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown\n2026-05-12T09:21:10.677056Z INFO screenpipe_core::pipes: loaded pipe: video-export\n2026-05-12T09:21:10.677293Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary\n2026-05-12T09:21:10.677398Z INFO screenpipe_core::pipes: loaded 6 pipes from \"/Users/lukas/.screenpipe/pipes\"\n\n\n\n _ \n __________________ ___ ____ ____ (_____ ___ \n / ___/ ___/ ___/ _ \\/ _ \\/ __ \\ / __ \\/ / __ \\/ _ \\\n (__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/\n/____/\\___/_/ \\___/\\___/_/ /_/ / .___/_/ .___/\\___/ \n /_/ /_/ \n\n\n\npower AI by everything you've seen, said or heard\nopen source | runs locally | developer friendly\n\n\n┌────────────────────────┬────────────────────────────────────┐\n│ setting │ value │\n├────────────────────────┼────────────────────────────────────┤\n│ audio chunk duration │ 30 seconds │\n│ port │ 3030 │\n│ audio disabled │ false │\n│ vision disabled │ false │\n│ pause on DRM content │ false │\n│ audio engine │ Parakeet │\n│ vad engine │ Silero │\n│ data directory │ /Users/lukas/.screenpipe │\n│ debug mode │ false │\n│ telemetry │ true │\n│ use pii removal │ true │\n│ use all monitors │ true │\n│ ignored windows │ [] │\n│ included windows │ [] │\n│ cloud sync │ disabled │\n│ auto-destruct pid │ 0 │\n│ deepgram key │ not set │\n│ api auth │ enabled │\n│ encrypt secrets │ disabled │\n│ retention days │ 14 │\n│ retention mode │ media-only (keep transcripts) │\n├────────────────────────┼────────────────────────────────────┤\n│ languages │ │\n│ │ all languages │\n├────────────────────────┼────────────────────────────────────┤\n│ monitors │ │\n│ │ id: 1 │\n│ │ id: 2 │\n├────────────────────────┼────────────────────────────────────┤\n│ audio devices │ │\n│ │ MacBook Pro Microphone (input) │\n│ │ System Audio (output) │\n└────────────────────────┴────────────────────────────────────┘\nyou are using local processing. all your data stays on your computer.\n\nwarning: telemetry is enabled. only error-level data will be sent.\nto disable, use the --disable-telemetry flag.\n\ncheck latest changes here: https://github.com/screenpipe/screenpipe/releases\n2026-05-12T09:21:10.684547Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)\n2026-05-12T09:21:10.686111Z INFO screenpipe: starting UI event capture\n2026-05-12T09:21:10.696691Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh\n2026-05-12T09:21:10.705742Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))\n2026-05-12T09:21:10.712331Z INFO screenpipe_engine::ui_recorder: Starting UI event capture\n2026-05-12T09:21:10.753596Z INFO screenpipe_engine::ui_recorder: UI recording session started: eee53fe6-52d6-4c4e-a7e5-11ede410f444\n2026-05-12T09:21:10.753638Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)\n2026-05-12T09:21:10.753679Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-11 06:21:10.753677 UTC to 2026-05-12 06:21:10.753677 UTC)\n2026-05-12T09:21:10.754945Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)\n2026-05-12T09:21:10.764596Z INFO screenpipe_engine::server: Server listening on 127.0.0.1:3030\n2026-05-12T09:21:10.771437Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030\n2026-05-12T09:21:15.451981Z WARN sqlx::query: summary=\"SELECT f.id, f.timestamp, f.offset_index, …\" db.statement=\"\\n\\nSELECT\\n f.id,\\n f.timestamp,\\n f.offset_index,\\n COALESCE(\\n SUBSTR(f.full_text, 1, 200),\\n SUBSTR(f.accessibility_text, 1, 200),\\n (\\n SELECT\\n SUBSTR(ot.text, 1, 200)\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as text,\\n COALESCE(\\n f.app_name,\\n (\\n SELECT\\n ot.app_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as app_name,\\n COALESCE(\\n f.window_name,\\n (\\n SELECT\\n ot.window_name\\n FROM\\n ocr_text ot\\n WHERE\\n ot.frame_id = f.id\\n LIMIT\\n 1\\n )\\n ) as window_name,\\n COALESCE(vc.device_name, f.device_name) as screen_device,\\n COALESCE(vc.file_path, f.snapshot_path) as video_path,\\n COALESCE(vc.fps, 0.033) as chunk_fps,\\n f.browser_url,\\n f.machine_id\\nFROM\\n frames f\\n LEFT JOIN video_chunks vc ON f.video_chunk_id = vc.id\\nWHERE\\n f.timestamp >= ?1\\n AND f.timestamp <= ?2\\n AND COALESCE(vc.file_path, f.snapshot_path, '') NOT LIKE 'cloud://%'\\nORDER BY\\n f.timestamp DESC,\\n f.offset_index DESC\\nLIMIT\\n 10000\\n\" rows_affected=0 rows_returned=6633 elapsed=4.697616625s\n2026-05-12T09:21:15.476188Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 6633 frame entries, coverage from 2026-05-11 06:21:10.753677 UTC\n2026-05-12T09:21:16.549935Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)\n2026-05-12T09:21:16.550139Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)\n2026-05-12T09:21:16.550184Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)\n2026-05-12T09:21:19.459497Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)\n2026-05-12T09:21:19.463986Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)\n2026-05-12T09:21:19.465573Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)\n2026-05-12T09:21:19.467110Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)\n2026-05-12T09:21:19.468420Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)\n2026-05-12T09:21:20.691544Z INFO screenpipe_audio::transcription::engine: whisper model available: \"/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin\"\n2026-05-12T09:21:20.692520Z INFO screenpipe_audio::transcription::whisper::model: whisper context: gpu acceleration enabled (Metal on macOS, Vulkan on Windows)\n2026-05-12T09:21:20.692565Z INFO screenpipe_audio::transcription::engine: loading whisper model with GPU acceleration...\nwhisper_init_from_file_with_params_no_state: loading model from '/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin'\nwhisper_init_with_params_no_state: use gpu = 1\nwhisper_init_with_params_no_state: flash attn = 0\nwhisper_init_with_params_no_state: gpu_device = 0\nwhisper_init_with_params_no_state: dtw = 0\nggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices\nggml_metal_library_init: using embedded metal library\nggml_metal_library_init: loaded in 0.036 sec\nggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)\nggml_metal_device_init: GPU name: Apple M1\nggml_metal_device_init: GPU family: MTLGPUFamilyApple7 (1007)\nggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)\nggml_metal_device_init: GPU family: MTLGPUFamilyMetal3 (5001)\nggml_metal_device_init: simdgroup reduction = true\nggml_metal_device_init: simdgroup matrix mul. = true\nggml_metal_device_init: has unified memory = true\nggml_metal_device_init: has bfloat = true\nggml_metal_device_init: has tensor = false\nggml_metal_device_init: use residency sets = true\nggml_metal_device_init: use shared buffers = true\nggml_metal_device_init: recommendedMaxWorkingSetSize = 11453.25 MB\nwhisper_init_with_params_no_state: devices = 3\nwhisper_init_with_params_no_state: backends = 3\nwhisper_model_load: loading model\nwhisper_model_load: n_vocab = 51865\nwhisper_model_load: n_audio_ctx = 1500\nwhisper_model_load: n_audio_state = 384\nwhisper_model_load: n_audio_head = 6\nwhisper_model_load: n_audio_layer = 4\nwhisper_model_load: n_text_ctx = 448\nwhisper_model_load: n_text_state = 384\nwhisper_model_load: n_text_head = 6\nwhisper_model_load: n_text_layer = 4\nwhisper_model_load: n_mels = 80\nwhisper_model_load: ftype = 1\nwhisper_model_load: qntvr = 0\nwhisper_model_load: type = 1 (tiny)\nwhisper_model_load: adding 1608 extra tokens\nwhisper_model_load: n_langs = 99\nwhisper_model_load: Metal total size = 77.11 MB\nwhisper_model_load: model size = 77.11 MB\n2026-05-12T09:21:20.866406Z INFO screenpipe_audio::transcription::engine: whisper model loaded successfully\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\n2026-05-12T09:21:20.896976Z INFO screenpipe_audio::audio_manager::manager: transcription session created (will be reused across segments)\n2026-05-12T09:21:20.928794Z INFO screenpipe_audio::audio_manager::manager: seeded 14 speakers (named + unnamed) from DB into embedding manager\n2026-05-12T09:21:20.929372Z INFO screenpipe_audio::audio_manager::manager: audio manager started\n2026-05-12T09:21:20.930136Z INFO screenpipe_audio::audio_manager::manager: calendar-assisted speaker diarization: listening for meeting events\n2026-05-12T09:21:21.212480Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)\n2026-05-12T09:21:22.112224Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)\n2026-05-12T09:21:22.697027Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 1: frame_id=21773, dur=116ms\n2026-05-12T09:21:23.853614Z INFO screenpipe_audio::device::device_manager: starting recording for device: System Audio (output)\n2026-05-12T09:21:23.854499Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for System Audio (output) (unknown / 30s segments)\n2026-05-12T09:21:23.854491Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)\n2026-05-12T09:21:28.046940Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)\n2026-05-12T09:21:28.381213Z WARN screenpipe_a11y::tree::macos_lines: lines: AXUIElementCopyParameterizedAttributeValue(AXLineForIndex) failed status=os::Status { raw: -25212, fcc: \"....\", help: \"https://www.osstatus.com?search=-25212\" } — first failure (further failures suppressed); search highlights will fall back to paragraph bbox on this app\n2026-05-12T09:21:28.684461Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 2: frame_id=21775, dur=90ms\n2026-05-12T09:22:12.427026Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=2 elapsed=1.759127041s\n2026-05-12T09:22:12.427274Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames\n2026-05-12T09:22:12.869213Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.2MB → 0.3MB (0.9x), 1 JPEGs deleted\n2026-05-12T09:22:13.304558Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.3MB → 0.4MB (0.9x), 1 JPEGs deleted\n2026-05-12T09:22:39.009649Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-1944753676112650055, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T09:23:23.041658Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T09:25:08.112066Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-2757320308507279294, trigger=click)\n2026-05-12T09:25:08.126094Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-2757320308507279294, trigger=click)\n2026-05-12T09:25:08.743069Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-2757320308507279294, trigger=click)\n2026-05-12T09:25:08.782136Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-2757320308507279294, trigger=click)\n2026-05-12T09:25:18.022691Z WARN screenpipe_a11y::platform::macos: clipboard capture disabled — prior NSPasteboard crash detected. delete /Users/lukas/.screenpipe/clipboard-disabled-after-crash to re-enable\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T09:25:26.200795Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T09:25:59.192521Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=1681167153903710140, trigger=click)\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\n2026-05-12T09:26:37.982517Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 105.4ms elapsed (expected 5.3ms) → inserting 100.1ms silence (9608 samples)","is_focused":true}]...
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6008233772263176860
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-852231712889047584
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app_switch
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accessibility
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NULL
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ggml_metal_init: use fusion = true
ggml_me ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:44:07.738461Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:46:10.863483Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: sign in for higher AI quotas + cloud sync:
screenpipe login
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:48:13.767660Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-11T22:50:16.132089Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: get the screenpipe desktop app for the full experience
[URL_WITH_CREDENTIALS] record
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/.screenpipe $ npx screenpipe@latest record
detected hardware tier: Mid
warning: parakeet is not supported on this platform, using whisper-tiny instead
2026-05-12T09:21:07.201625Z INFO screenpipe_engine::auth_key: api auth: key resolved via secret store
checking permissions...
screen recording: ok
microphone: ok
accessibility: ok
2026-05-12T09:21:07.328817Z INFO screenpipe_screen::monitor::macos_version: Detected macOS version: 14.6
2026-05-12T09:21:10.020463Z INFO screenpipe_engine::sleep_monitor: Starting macOS sleep/wake monitor
2026-05-12T09:21:10.024711Z INFO screenpipe_engine::sleep_monitor: Screen lock/unlock observers registered (CFNotificationCenter)
2026-05-12T09:21:10.025571Z INFO screenpipe_engine::sleep_monitor: Display reconfiguration watcher registered (CGDisplayRegisterReconfigurationCallback)
2026-05-12T09:21:10.055207Z INFO screenpipe_engine::permission_monitor: permission monitor started screen=true mic=true accessibility=true keychain=true
2026-05-12T09:21:10.055275Z INFO screenpipe: meeting detector enabled — independent of transcription mode
2026-05-12T09:21:10.666779Z INFO screenpipe: API server listening on [IP_ADDRESS]:3030 (localhost only)
2026-05-12T09:21:10.666832Z INFO screenpipe: API auth enabled — run `screenpipe auth token` to view your key
2026-05-12T09:21:10.666681Z INFO screenpipe_engine::power::manager: power manager started (poll interval: 10s)
2026-05-12T09:21:10.666983Z INFO screenpipe_engine::vision_manager::manager: Starting VisionManager
2026-05-12T09:21:10.666647Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction worker started (min_age=600s, poll=300s)
2026-05-12T09:21:10.673969Z INFO screenpipe_core::pipes: loaded pipe: day-recap
2026-05-12T09:21:10.675449Z INFO screenpipe_core::pipes: loaded pipe: standup-update
2026-05-12T09:21:10.676236Z INFO screenpipe_core::pipes: loaded pipe: ai-habits
2026-05-12T09:21:10.676638Z INFO screenpipe_core::pipes: loaded pipe: time-breakdown
2026-05-12T09:21:10.677056Z INFO screenpipe_core::pipes: loaded pipe: video-export
2026-05-12T09:21:10.677293Z INFO screenpipe_core::pipes: loaded pipe: meeting-summary
2026-05-12T09:21:10.677398Z INFO screenpipe_core::pipes: loaded 6 pipes from "/Users/lukas/.screenpipe/pipes"
_
__________________ ___ ____ ____ (_____ ___
/ ___/ ___/ ___/ _ \/ _ \/ __ \ / __ \/ / __ \/ _ \
(__ / /__/ / / __/ __/ / / / / /_/ / / /_/ / __/
/____/\___/_/ \___/\___/_/ /_/ / .___/_/ .___/\___/
/_/ /_/
power AI by everything you've seen, said or heard
open source | runs locally | developer friendly
┌────────────────────────┬────────────────────────────────────┐
│ setting │ value │
├────────────────────────┼────────────────────────────────────┤
│ audio chunk duration │ 30 seconds │
│ port │ 3030 │
│ audio disabled │ false │
│ vision disabled │ false │
│ pause on DRM content │ false │
│ audio engine │ Parakeet │
│ vad engine │ Silero │
│ data directory │ /Users/lukas/.screenpipe │
│ debug mode │ false │
│ telemetry │ true │
│ use pii removal │ true │
│ use all monitors │ true │
│ ignored windows │ [] │
│ included windows │ [] │
│ cloud sync │ disabled │
│ auto-destruct pid │ 0 │
│ deepgram key │ not set │
│ api auth │ enabled │
│ encrypt secrets │ disabled │
│ retention days │ 14 │
│ retention mode │ media-only (keep transcripts) │
├────────────────────────┼────────────────────────────────────┤
│ languages │ │
│ │ all languages │
├────────────────────────┼────────────────────────────────────┤
│ monitors │ │
│ │ id: 1 │
│ │ id: 2 │
├────────────────────────┼────────────────────────────────────┤
│ audio devices │ │
│ │ MacBook Pro Microphone (input) │
│ │ System Audio (output) │
└────────────────────────┴────────────────────────────────────┘
you are using local processing. all your data stays on your computer.
warning: telemetry is enabled. only error-level data will be sent.
to disable, use the --disable-telemetry flag.
check latest changes here: https://github.com/screenpipe/screenpipe/releases
2026-05-12T09:21:10.684547Z INFO screenpipe_core::pipes: pipe scheduler started (generation 2)
2026-05-12T09:21:10.686111Z INFO screenpipe: starting UI event capture
2026-05-12T09:21:10.696691Z WARN screenpipe: pi agent install failed: bun not found — install from https://bun.sh
2026-05-12T09:21:10.705742Z INFO screenpipe_engine::power::manager: initial power profile: Performance (on_ac=true, battery=Some(100))
2026-05-12T09:21:10.712331Z INFO screenpipe_engine::ui_recorder: Starting UI event capture
2026-05-12T09:21:10.753596Z INFO screenpipe_engine::ui_recorder: UI recording session started: eee53fe6-52d6-4c4e-a7e5-11ede410f444
2026-05-12T09:21:10.753638Z INFO screenpipe_engine::calendar_speaker_id: speaker identification: started (user_name=<not set>)
2026-05-12T09:21:10.753679Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warming from DB (2026-05-11 06:21:10.753677 UTC to 2026-05-12 06:21:10.753677 UTC)
2026-05-12T09:21:10.754945Z INFO screenpipe_engine::meeting_detector: meeting v2: detection loop started (base_interval=5s, profiles=12)
2026-05-12T09:21:10.764596Z INFO screenpipe_engine::server: Server listening on [IP_ADDRESS]:3030
2026-05-12T09:21:10.771437Z INFO screenpipe_connect::mdns: mdns: advertising screenpipe on port 3030
2026-05-12T09:21:15.451981Z WARN sqlx::query: summary="SELECT f.id, f.timestamp, f.offset_index, …" db.statement="\n\nSELECT\n f.id,\n f.timestamp,\n f.offset_index,\n COALESCE(\n SUBSTR(f.full_text, 1, 200),\n SUBSTR(f.accessibility_text, 1, 200),\n (\n SELECT\n SUBSTR(ot.text, 1, 200)\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as text,\n COALESCE(\n f.app_name,\n (\n SELECT\n ot.app_name\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as app_name,\n COALESCE(\n f.window_name,\n (\n SELECT\n ot.window_name\n FROM\n ocr_text ot\n WHERE\n ot.frame_id = f.id\n LIMIT\n 1\n )\n ) as window_name,\n COALESCE(vc.device_name, f.device_name) as screen_device,\n COALESCE(vc.file_path, f.snapshot_path) as video_path,\n COALESCE(vc.fps, 0.033) as chunk_fps,\n f.browser_url,\n f.machine_id\nFROM\n frames f\n LEFT JOIN video_chunks vc ON f.video_chunk_id = vc.id\nWHERE\n f.timestamp >= ?1\n AND f.timestamp <= ?2\n AND COALESCE(vc.file_path, f.snapshot_path, '') NOT LIKE 'cloud://%'\nORDER BY\n f.timestamp DESC,\n f.offset_index DESC\nLIMIT\n 10000\n" rows_affected=0 rows_returned=6633 elapsed=4.697616625s
2026-05-12T09:21:15.476188Z INFO screenpipe_engine::hot_frame_cache: hot_frame_cache: warmed with 6633 frame entries, coverage from 2026-05-11 06:21:10.753677 UTC
2026-05-12T09:21:16.549935Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 1 (1440x900)
2026-05-12T09:21:16.550139Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 1 (device: monitor_1)
2026-05-12T09:21:16.550184Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 1 (device: monitor_1)
2026-05-12T09:21:19.459497Z INFO screenpipe_engine::vision_manager::manager: Starting vision recording for monitor 2 (3008x1253)
2026-05-12T09:21:19.463986Z INFO screenpipe_engine::vision_manager::manager: Starting event-driven capture for monitor 2 (device: monitor_2)
2026-05-12T09:21:19.465573Z INFO screenpipe_engine::vision_manager::manager: VisionManager started with 2/2 monitor(s)
2026-05-12T09:21:19.467110Z INFO screenpipe_engine::vision_manager::monitor_watcher: Starting monitor watcher (event-driven via CGDisplayRegisterReconfigurationCallback, 60s backstop poll)
2026-05-12T09:21:19.468420Z INFO screenpipe_engine::event_driven_capture: event-driven capture started for monitor 2 (device: monitor_2)
2026-05-12T09:21:20.691544Z INFO screenpipe_audio::transcription::engine: whisper model available: "/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin"
2026-05-12T09:21:20.692520Z INFO screenpipe_audio::transcription::whisper::model: whisper context: gpu acceleration enabled (Metal on macOS, Vulkan on Windows)
2026-05-12T09:21:20.692565Z INFO screenpipe_audio::transcription::engine: loading whisper model with GPU acceleration...
whisper_init_from_file_with_params_no_state: loading model from '/Users/lukas/.cache/huggingface/hub/models--ggerganov--whisper.cpp/snapshots/5359861c739e955e79d9a303bcbc70fb988958b1/ggml-tiny.bin'
whisper_init_with_params_no_state: use gpu = 1
whisper_init_with_params_no_state: flash attn = 0
whisper_init_with_params_no_state: gpu_device = 0
whisper_init_with_params_no_state: dtw = 0
ggml_metal_device_init: tensor API disabled for pre-M5 and pre-A19 devices
ggml_metal_library_init: using embedded metal library
ggml_metal_library_init: loaded in 0.036 sec
ggml_metal_rsets_init: creating a residency set collection (keep_alive = 180 s)
ggml_metal_device_init: GPU name: Apple M1
ggml_metal_device_init: GPU family: MTLGPUFamilyApple7 (1007)
ggml_metal_device_init: GPU family: MTLGPUFamilyCommon3 (3003)
ggml_metal_device_init: GPU family: MTLGPUFamilyMetal3 (5001)
ggml_metal_device_init: simdgroup reduction = true
ggml_metal_device_init: simdgroup matrix mul. = true
ggml_metal_device_init: has unified memory = true
ggml_metal_device_init: has bfloat = true
ggml_metal_device_init: has tensor = false
ggml_metal_device_init: use residency sets = true
ggml_metal_device_init: use shared buffers = true
ggml_metal_device_init: recommendedMaxWorkingSetSize = 11453.25 MB
whisper_init_with_params_no_state: devices = 3
whisper_init_with_params_no_state: backends = 3
whisper_model_load: loading model
whisper_model_load: n_vocab = 51865
whisper_model_load: n_audio_ctx = 1500
whisper_model_load: n_audio_state = 384
whisper_model_load: n_audio_head = 6
whisper_model_load: n_audio_layer = 4
whisper_model_load: n_text_ctx = 448
whisper_model_load: n_text_state = 384
whisper_model_load: n_text_head = 6
whisper_model_load: n_text_layer = 4
whisper_model_load: n_mels = 80
whisper_model_load: ftype = 1
whisper_model_load: qntvr = 0
whisper_model_load: type = 1 (tiny)
whisper_model_load: adding 1608 extra tokens
whisper_model_load: n_langs = 99
whisper_model_load: Metal total size = 77.11 MB
whisper_model_load: model size = 77.11 MB
2026-05-12T09:21:20.866406Z INFO screenpipe_audio::transcription::engine: whisper model loaded successfully
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
2026-05-12T09:21:20.896976Z INFO screenpipe_audio::audio_manager::manager: transcription session created (will be reused across segments)
2026-05-12T09:21:20.928794Z INFO screenpipe_audio::audio_manager::manager: seeded 14 speakers (named + unnamed) from DB into embedding manager
2026-05-12T09:21:20.929372Z INFO screenpipe_audio::audio_manager::manager: audio manager started
2026-05-12T09:21:20.930136Z INFO screenpipe_audio::audio_manager::manager: calendar-assisted speaker diarization: listening for meeting events
2026-05-12T09:21:21.212480Z INFO screenpipe_audio::device::device_manager: starting recording for device: MacBook Pro Microphone (input)
2026-05-12T09:21:22.112224Z INFO sck_rs::stream_manager: persistent SCK stream started for display 1 (1440x900, 2fps, 0 excluded)
2026-05-12T09:21:22.697027Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 1: frame_id=21773, dur=116ms
2026-05-12T09:21:23.853614Z INFO screenpipe_audio::device::device_manager: starting recording for device: System Audio (output)
2026-05-12T09:21:23.854499Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for System Audio (output) (unknown / 30s segments)
2026-05-12T09:21:23.854491Z INFO screenpipe_audio::core::run_record_and_transcribe: starting continuous recording for MacBook Pro Microphone (input) (wired / 30s segments)
2026-05-12T09:21:28.046940Z INFO sck_rs::stream_manager: persistent SCK stream started for display 2 (3008x1253, 2fps, 0 excluded)
2026-05-12T09:21:28.381213Z WARN screenpipe_a11y::tree::macos_lines: lines: AXUIElementCopyParameterizedAttributeValue(AXLineForIndex) failed status=os::Status { raw: -25212, fcc: "....", help: "https://www.osstatus.com?search=-25212" } — first failure (further failures suppressed); search highlights will fall back to paragraph bbox on this app
2026-05-12T09:21:28.684461Z INFO screenpipe_engine::event_driven_capture: startup capture for monitor 2: frame_id=21775, dur=90ms
2026-05-12T09:22:12.427026Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=2 elapsed=1.759127041s
2026-05-12T09:22:12.427274Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 2 eligible frames
2026-05-12T09:22:12.869213Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.2MB → 0.3MB (0.9x), 1 JPEGs deleted
2026-05-12T09:22:13.304558Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 1 frames, 0.3MB → 0.4MB (0.9x), 1 JPEGs deleted
2026-05-12T09:22:39.009649Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-1944753676112650055, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T09:23:23.041658Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T09:25:08.112066Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-2757320308507279294, trigger=click)
2026-05-12T09:25:08.126094Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-2757320308507279294, trigger=click)
2026-05-12T09:25:08.743069Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-2757320308507279294, trigger=click)
2026-05-12T09:25:08.782136Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-2757320308507279294, trigger=click)
2026-05-12T09:25:18.022691Z WARN screenpipe_a11y::platform::macos: clipboard capture disabled — prior NSPasteboard crash detected. delete /Users/lukas/.screenpipe/clipboard-disabled-after-crash to re-enable
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buff...
|
NULL
|
NULL
|
NULL
|
NULL
|
|
26306
|
1090
|
31
|
2026-05-12T12:19:37.543633+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-12/1778 /Users/lukas/.screenpipe/data/data/2026-05-12/1778588377543_m1.jpg...
|
iTerm2
|
screenpipe"
|
True
|
NULL
|
monitor_1
|
NULL
|
NULL
|
NULL
|
NULL
|
ggml_metal_init: found device: Apple M1
ggml_metal ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:47:23.838686Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T14:49:10.556142Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=1 rows_returned=35 elapsed=1.320759208s
2026-05-12T14:49:10.556536Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 35 eligible frames
2026-05-12T14:49:12.093113Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 14 frames, 2.7MB → 0.3MB (8.9x), 14 JPEGs deleted
2026-05-12T14:49:13.889798Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 19 frames, 3.6MB → 0.7MB (4.9x), 19 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:49:26.762419Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:51:29.801432Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T14:51:55.611515Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 105.3ms elapsed (expected 5.3ms) → inserting 100.0ms silence (9598 samples)
2026-05-12T14:51:55.781428Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 169.9ms elapsed (expected 5.3ms) → inserting 164.6ms silence (15800 samples)
2026-05-12T14:51:56.081737Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 139.9ms elapsed (expected 5.3ms) → inserting 134.5ms silence (12914 samples)
2026-05-12T14:53:02.556928Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 85.7ms elapsed (expected 5.3ms) → inserting 80.4ms silence (7717 samples)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:53:33.473658Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T14:54:14.604527Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 57 eligible frames
2026-05-12T14:54:16.150850Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 23 frames, 4.4MB → 0.3MB (14.3x), 23 JPEGs deleted
2026-05-12T14:54:18.438626Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 32 frames, 5.7MB → 1.4MB (4.2x), 32 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:55:36.875217Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: install a starter bundle of pipes:
screenpipe install https://screenpi.pe/start.json
2026-05-12T14:56:43.513652Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6205158385764507775, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:57:43.527916Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T14:57:51.020481Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)
2026-05-12T14:57:54.005004Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)
2026-05-12T14:58:00.087355Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)
2026-05-12T14:58:03.103321Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)
2026-05-12T14:58:08.055814Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-9035457757750653601, trigger=click)
2026-05-12T14:58:08.062982Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=click)
2026-05-12T14:58:12.199518Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)
2026-05-12T14:59:20.391870Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=101 elapsed=1.967512791s
2026-05-12T14:59:20.392758Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 101 eligible frames
2026-05-12T14:59:22.488440Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 33 frames, 9.8MB → 1.0MB (9.7x), 33 JPEGs deleted
2026-05-12T14:59:29.272518Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 66 frames, 10.5MB → 4.5MB (2.3x), 66 JPEGs deleted
2026-05-12T14:59:34.683966Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9180842073176773313, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:59:47.398325Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T14:59:47.459122Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=3999125719128242167, trigger=click)
2026-05-12T14:59:50.807323Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 101.4ms elapsed (expected 5.3ms) → inserting 96.0ms silence (9219 samples)
2026-05-12T15:00:25.458921Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=visual_change)
2026-05-12T15:00:28.452080Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=visual_change)
2026-05-12T15:00:29.167946Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8147332135429607620, trigger=visual_change)
2026-05-12T15:00:38.277066Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=click)
2026-05-12T15:00:39.475884Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=click)
2026-05-12T15:00:58.089090Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=7442982011400540096, trigger=click)
2026-05-12T15:00:58.095618Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=7442982011400540096, trigger=click)
2026-05-12T15:01:02.550033Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-545273533072853505, trigger=visual_change)
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whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:01:50.346393Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:03:52.628434Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T15:04:31.563819Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=140 elapsed=2.253134667s
2026-05-12T15:04:31.564540Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 140 eligible frames
2026-05-12T15:04:34.375276Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 47 frames, 15.0MB → 0.8MB (19.1x), 47 JPEGs deleted
2026-05-12T15:04:41.481988Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 91 frames, 13.6MB → 5.6MB (2.4x), 91 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:05:55.231679Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: get the screenpipe desktop app for the full experience
https://screenpi.pe
2026-05-12T15:07:10.598829Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 82.8ms elapsed (expected 5.3ms) → inserting 77.5ms silence (7439 samples)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:07:57.738534Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T15:09:41.576620Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 110 eligible frames
2026-05-12T15:09:44.361015Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 46 frames, 13.4MB → 1.3MB (10.1x), 46 JPEGs deleted
2026-05-12T15:09:49.818095Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 62 frames, 10.4MB → 4.2MB (2.5x), 62 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:10:00.032837Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:12:02.830584Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:14:05.195695Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T15:14:53.091375Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=94 elapsed=3.184523292s
2026-05-12T15:14:53.091512Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 94 eligible frames
2026-05-12T15:14:55.411976Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 36 frames, 6.9MB → 1.0MB (6.6x), 36 JPEGs deleted
2026-05-12T15:15:00.362839Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 56 frames, 8.4MB → 3.7MB (2.3x), 56 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_i...
|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"ggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:47:23.838686Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T14:49:10.556142Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=35 elapsed=1.320759208s\n2026-05-12T14:49:10.556536Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 35 eligible frames\n2026-05-12T14:49:12.093113Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 14 frames, 2.7MB → 0.3MB (8.9x), 14 JPEGs deleted\n2026-05-12T14:49:13.889798Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 19 frames, 3.6MB → 0.7MB (4.9x), 19 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:49:26.762419Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:51:29.801432Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T14:51:55.611515Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 105.3ms elapsed (expected 5.3ms) → inserting 100.0ms silence (9598 samples)\n2026-05-12T14:51:55.781428Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 169.9ms elapsed (expected 5.3ms) → inserting 164.6ms silence (15800 samples)\n2026-05-12T14:51:56.081737Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 139.9ms elapsed (expected 5.3ms) → inserting 134.5ms silence (12914 samples)\n2026-05-12T14:53:02.556928Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 85.7ms elapsed (expected 5.3ms) → inserting 80.4ms silence (7717 samples)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:53:33.473658Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T14:54:14.604527Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 57 eligible frames\n2026-05-12T14:54:16.150850Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 23 frames, 4.4MB → 0.3MB (14.3x), 23 JPEGs deleted\n2026-05-12T14:54:18.438626Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 32 frames, 5.7MB → 1.4MB (4.2x), 32 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:55:36.875217Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-12T14:56:43.513652Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6205158385764507775, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:57:43.527916Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T14:57:51.020481Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)\n2026-05-12T14:57:54.005004Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)\n2026-05-12T14:58:00.087355Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)\n2026-05-12T14:58:03.103321Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)\n2026-05-12T14:58:08.055814Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-9035457757750653601, trigger=click)\n2026-05-12T14:58:08.062982Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=click)\n2026-05-12T14:58:12.199518Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)\n2026-05-12T14:59:20.391870Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=101 elapsed=1.967512791s\n2026-05-12T14:59:20.392758Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 101 eligible frames\n2026-05-12T14:59:22.488440Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 33 frames, 9.8MB → 1.0MB (9.7x), 33 JPEGs deleted\n2026-05-12T14:59:29.272518Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 66 frames, 10.5MB → 4.5MB (2.3x), 66 JPEGs deleted\n2026-05-12T14:59:34.683966Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9180842073176773313, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:59:47.398325Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T14:59:47.459122Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=3999125719128242167, trigger=click)\n2026-05-12T14:59:50.807323Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 101.4ms elapsed (expected 5.3ms) → inserting 96.0ms silence (9219 samples)\n2026-05-12T15:00:25.458921Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=visual_change)\n2026-05-12T15:00:28.452080Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=visual_change)\n2026-05-12T15:00:29.167946Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8147332135429607620, trigger=visual_change)\n2026-05-12T15:00:38.277066Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=click)\n2026-05-12T15:00:39.475884Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=click)\n2026-05-12T15:00:58.089090Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=7442982011400540096, trigger=click)\n2026-05-12T15:00:58.095618Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=7442982011400540096, trigger=click)\n2026-05-12T15:01:02.550033Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-545273533072853505, trigger=visual_change)\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:01:50.346393Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:03:52.628434Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T15:04:31.563819Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=140 elapsed=2.253134667s\n2026-05-12T15:04:31.564540Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 140 eligible frames\n2026-05-12T15:04:34.375276Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 47 frames, 15.0MB → 0.8MB (19.1x), 47 JPEGs deleted\n2026-05-12T15:04:41.481988Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 91 frames, 13.6MB → 5.6MB (2.4x), 91 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:05:55.231679Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\n2026-05-12T15:07:10.598829Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 82.8ms elapsed (expected 5.3ms) → inserting 77.5ms silence (7439 samples)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:07:57.738534Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T15:09:41.576620Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 110 eligible frames\n2026-05-12T15:09:44.361015Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 46 frames, 13.4MB → 1.3MB (10.1x), 46 JPEGs deleted\n2026-05-12T15:09:49.818095Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 62 frames, 10.4MB → 4.2MB (2.5x), 62 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:10:00.032837Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:12:02.830584Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:14:05.195695Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T15:14:53.091375Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=94 elapsed=3.184523292s\n2026-05-12T15:14:53.091512Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 94 eligible frames\n2026-05-12T15:14:55.411976Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 36 frames, 6.9MB → 1.0MB (6.6x), 36 JPEGs deleted\n2026-05-12T15:15:00.362839Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 56 frames, 8.4MB → 3.7MB (2.3x), 56 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:16:07.714574Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-12T15:16:48.671305Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=8414032348020665010, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:18:11.484810Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks","depth":4,"bounds":{"left":0.0,"top":0.08777778,"width":1.0,"height":0.9122222},"on_screen":true,"value":"ggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:47:23.838686Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T14:49:10.556142Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=35 elapsed=1.320759208s\n2026-05-12T14:49:10.556536Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 35 eligible frames\n2026-05-12T14:49:12.093113Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 14 frames, 2.7MB → 0.3MB (8.9x), 14 JPEGs deleted\n2026-05-12T14:49:13.889798Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 19 frames, 3.6MB → 0.7MB (4.9x), 19 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:49:26.762419Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:51:29.801432Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T14:51:55.611515Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 105.3ms elapsed (expected 5.3ms) → inserting 100.0ms silence (9598 samples)\n2026-05-12T14:51:55.781428Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 169.9ms elapsed (expected 5.3ms) → inserting 164.6ms silence (15800 samples)\n2026-05-12T14:51:56.081737Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 139.9ms elapsed (expected 5.3ms) → inserting 134.5ms silence (12914 samples)\n2026-05-12T14:53:02.556928Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 85.7ms elapsed (expected 5.3ms) → inserting 80.4ms silence (7717 samples)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:53:33.473658Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T14:54:14.604527Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 57 eligible frames\n2026-05-12T14:54:16.150850Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 23 frames, 4.4MB → 0.3MB (14.3x), 23 JPEGs deleted\n2026-05-12T14:54:18.438626Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 32 frames, 5.7MB → 1.4MB (4.2x), 32 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:55:36.875217Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-12T14:56:43.513652Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6205158385764507775, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:57:43.527916Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T14:57:51.020481Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)\n2026-05-12T14:57:54.005004Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)\n2026-05-12T14:58:00.087355Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)\n2026-05-12T14:58:03.103321Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)\n2026-05-12T14:58:08.055814Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-9035457757750653601, trigger=click)\n2026-05-12T14:58:08.062982Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=click)\n2026-05-12T14:58:12.199518Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)\n2026-05-12T14:59:20.391870Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=101 elapsed=1.967512791s\n2026-05-12T14:59:20.392758Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 101 eligible frames\n2026-05-12T14:59:22.488440Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 33 frames, 9.8MB → 1.0MB (9.7x), 33 JPEGs deleted\n2026-05-12T14:59:29.272518Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 66 frames, 10.5MB → 4.5MB (2.3x), 66 JPEGs deleted\n2026-05-12T14:59:34.683966Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9180842073176773313, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:59:47.398325Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T14:59:47.459122Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=3999125719128242167, trigger=click)\n2026-05-12T14:59:50.807323Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 101.4ms elapsed (expected 5.3ms) → inserting 96.0ms silence (9219 samples)\n2026-05-12T15:00:25.458921Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=visual_change)\n2026-05-12T15:00:28.452080Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=visual_change)\n2026-05-12T15:00:29.167946Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8147332135429607620, trigger=visual_change)\n2026-05-12T15:00:38.277066Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=click)\n2026-05-12T15:00:39.475884Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=click)\n2026-05-12T15:00:58.089090Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=7442982011400540096, trigger=click)\n2026-05-12T15:00:58.095618Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=7442982011400540096, trigger=click)\n2026-05-12T15:01:02.550033Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-545273533072853505, trigger=visual_change)\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:01:50.346393Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:03:52.628434Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T15:04:31.563819Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=140 elapsed=2.253134667s\n2026-05-12T15:04:31.564540Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 140 eligible frames\n2026-05-12T15:04:34.375276Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 47 frames, 15.0MB → 0.8MB (19.1x), 47 JPEGs deleted\n2026-05-12T15:04:41.481988Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 91 frames, 13.6MB → 5.6MB (2.4x), 91 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:05:55.231679Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\n2026-05-12T15:07:10.598829Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 82.8ms elapsed (expected 5.3ms) → inserting 77.5ms silence (7439 samples)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:07:57.738534Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T15:09:41.576620Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 110 eligible frames\n2026-05-12T15:09:44.361015Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 46 frames, 13.4MB → 1.3MB (10.1x), 46 JPEGs deleted\n2026-05-12T15:09:49.818095Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 62 frames, 10.4MB → 4.2MB (2.5x), 62 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:10:00.032837Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:12:02.830584Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:14:05.195695Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T15:14:53.091375Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=94 elapsed=3.184523292s\n2026-05-12T15:14:53.091512Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 94 eligible frames\n2026-05-12T15:14:55.411976Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 36 frames, 6.9MB → 1.0MB (6.6x), 36 JPEGs deleted\n2026-05-12T15:15:00.362839Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 56 frames, 8.4MB → 3.7MB (2.3x), 56 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:16:07.714574Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-12T15:16:48.671305Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=8414032348020665010, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:18:11.484810Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.0,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.004166667,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (-zsh)","depth":2,"bounds":{"left":0.140625,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.14479166,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.28125,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.28541666,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"ec2-user@ip-10-30-129-190:~ (-zsh)","depth":2,"bounds":{"left":0.421875,"top":0.05888889,"width":0.140625,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.42604166,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.5625,"top":0.05888889,"width":0.14027777,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.56666666,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.7027778,"top":0.05888889,"width":0.14027777,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.70694447,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.84305555,"top":0.05888889,"width":0.14027777,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.8472222,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.9548611,"top":0.032222223,"width":0.03888889,"height":0.018888889},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"screenpipe\"","depth":1,"bounds":{"left":0.47083333,"top":0.033333335,"width":0.058333334,"height":0.017777778},"on_screen":true,"role_description":"text"}]...
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click
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accessibility
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ggml_metal_init: found device: Apple M1
ggml_metal ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:47:23.838686Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T14:49:10.556142Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=1 rows_returned=35 elapsed=1.320759208s
2026-05-12T14:49:10.556536Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 35 eligible frames
2026-05-12T14:49:12.093113Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 14 frames, 2.7MB → 0.3MB (8.9x), 14 JPEGs deleted
2026-05-12T14:49:13.889798Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 19 frames, 3.6MB → 0.7MB (4.9x), 19 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:49:26.762419Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:51:29.801432Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T14:51:55.611515Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 105.3ms elapsed (expected 5.3ms) → inserting 100.0ms silence (9598 samples)
2026-05-12T14:51:55.781428Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 169.9ms elapsed (expected 5.3ms) → inserting 164.6ms silence (15800 samples)
2026-05-12T14:51:56.081737Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 139.9ms elapsed (expected 5.3ms) → inserting 134.5ms silence (12914 samples)
2026-05-12T14:53:02.556928Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 85.7ms elapsed (expected 5.3ms) → inserting 80.4ms silence (7717 samples)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:53:33.473658Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T14:54:14.604527Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 57 eligible frames
2026-05-12T14:54:16.150850Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 23 frames, 4.4MB → 0.3MB (14.3x), 23 JPEGs deleted
2026-05-12T14:54:18.438626Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 32 frames, 5.7MB → 1.4MB (4.2x), 32 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:55:36.875217Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: install a starter bundle of pipes:
screenpipe install https://screenpi.pe/start.json
2026-05-12T14:56:43.513652Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6205158385764507775, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:57:43.527916Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T14:57:51.020481Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)
2026-05-12T14:57:54.005004Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)
2026-05-12T14:58:00.087355Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)
2026-05-12T14:58:03.103321Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)
2026-05-12T14:58:08.055814Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-9035457757750653601, trigger=click)
2026-05-12T14:58:08.062982Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=click)
2026-05-12T14:58:12.199518Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)
2026-05-12T14:59:20.391870Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=101 elapsed=1.967512791s
2026-05-12T14:59:20.392758Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 101 eligible frames
2026-05-12T14:59:22.488440Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 33 frames, 9.8MB → 1.0MB (9.7x), 33 JPEGs deleted
2026-05-12T14:59:29.272518Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 66 frames, 10.5MB → 4.5MB (2.3x), 66 JPEGs deleted
2026-05-12T14:59:34.683966Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9180842073176773313, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:59:47.398325Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T14:59:47.459122Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=3999125719128242167, trigger=click)
2026-05-12T14:59:50.807323Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 101.4ms elapsed (expected 5.3ms) → inserting 96.0ms silence (9219 samples)
2026-05-12T15:00:25.458921Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=visual_change)
2026-05-12T15:00:28.452080Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=visual_change)
2026-05-12T15:00:29.167946Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8147332135429607620, trigger=visual_change)
2026-05-12T15:00:38.277066Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=click)
2026-05-12T15:00:39.475884Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=click)
2026-05-12T15:00:58.089090Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=7442982011400540096, trigger=click)
2026-05-12T15:00:58.095618Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=7442982011400540096, trigger=click)
2026-05-12T15:01:02.550033Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-545273533072853505, trigger=visual_change)
tip: sign in for higher AI quotas + cloud sync:
screenpipe login
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:01:50.346393Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:03:52.628434Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T15:04:31.563819Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=140 elapsed=2.253134667s
2026-05-12T15:04:31.564540Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 140 eligible frames
2026-05-12T15:04:34.375276Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 47 frames, 15.0MB → 0.8MB (19.1x), 47 JPEGs deleted
2026-05-12T15:04:41.481988Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 91 frames, 13.6MB → 5.6MB (2.4x), 91 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:05:55.231679Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: get the screenpipe desktop app for the full experience
https://screenpi.pe
2026-05-12T15:07:10.598829Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 82.8ms elapsed (expected 5.3ms) → inserting 77.5ms silence (7439 samples)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:07:57.738534Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T15:09:41.576620Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 110 eligible frames
2026-05-12T15:09:44.361015Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 46 frames, 13.4MB → 1.3MB (10.1x), 46 JPEGs deleted
2026-05-12T15:09:49.818095Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 62 frames, 10.4MB → 4.2MB (2.5x), 62 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:10:00.032837Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:12:02.830584Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:14:05.195695Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T15:14:53.091375Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=94 elapsed=3.184523292s
2026-05-12T15:14:53.091512Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 94 eligible frames
2026-05-12T15:14:55.411976Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 36 frames, 6.9MB → 1.0MB (6.6x), 36 JPEGs deleted
2026-05-12T15:15:00.362839Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 56 frames, 8.4MB → 3.7MB (2.3x), 56 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_i...
|
NULL
|
NULL
|
NULL
|
NULL
|
|
26307
|
1091
|
37
|
2026-05-12T12:19:37.508028+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-12/1778 /Users/lukas/.screenpipe/data/data/2026-05-12/1778588377508_m2.jpg...
|
iTerm2
|
screenpipe"
|
True
|
NULL
|
monitor_2
|
NULL
|
NULL
|
NULL
|
NULL
|
ggml_metal_init: found device: Apple M1
ggml_metal ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:47:23.838686Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T14:49:10.556142Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=1 rows_returned=35 elapsed=1.320759208s
2026-05-12T14:49:10.556536Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 35 eligible frames
2026-05-12T14:49:12.093113Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 14 frames, 2.7MB → 0.3MB (8.9x), 14 JPEGs deleted
2026-05-12T14:49:13.889798Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 19 frames, 3.6MB → 0.7MB (4.9x), 19 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:49:26.762419Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:51:29.801432Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T14:51:55.611515Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 105.3ms elapsed (expected 5.3ms) → inserting 100.0ms silence (9598 samples)
2026-05-12T14:51:55.781428Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 169.9ms elapsed (expected 5.3ms) → inserting 164.6ms silence (15800 samples)
2026-05-12T14:51:56.081737Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 139.9ms elapsed (expected 5.3ms) → inserting 134.5ms silence (12914 samples)
2026-05-12T14:53:02.556928Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 85.7ms elapsed (expected 5.3ms) → inserting 80.4ms silence (7717 samples)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:53:33.473658Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T14:54:14.604527Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 57 eligible frames
2026-05-12T14:54:16.150850Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 23 frames, 4.4MB → 0.3MB (14.3x), 23 JPEGs deleted
2026-05-12T14:54:18.438626Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 32 frames, 5.7MB → 1.4MB (4.2x), 32 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:55:36.875217Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: install a starter bundle of pipes:
screenpipe install https://screenpi.pe/start.json
2026-05-12T14:56:43.513652Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6205158385764507775, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:57:43.527916Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T14:57:51.020481Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)
2026-05-12T14:57:54.005004Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)
2026-05-12T14:58:00.087355Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)
2026-05-12T14:58:03.103321Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)
2026-05-12T14:58:08.055814Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-9035457757750653601, trigger=click)
2026-05-12T14:58:08.062982Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=click)
2026-05-12T14:58:12.199518Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)
2026-05-12T14:59:20.391870Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=101 elapsed=1.967512791s
2026-05-12T14:59:20.392758Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 101 eligible frames
2026-05-12T14:59:22.488440Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 33 frames, 9.8MB → 1.0MB (9.7x), 33 JPEGs deleted
2026-05-12T14:59:29.272518Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 66 frames, 10.5MB → 4.5MB (2.3x), 66 JPEGs deleted
2026-05-12T14:59:34.683966Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9180842073176773313, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:59:47.398325Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T14:59:47.459122Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=3999125719128242167, trigger=click)
2026-05-12T14:59:50.807323Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 101.4ms elapsed (expected 5.3ms) → inserting 96.0ms silence (9219 samples)
2026-05-12T15:00:25.458921Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=visual_change)
2026-05-12T15:00:28.452080Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=visual_change)
2026-05-12T15:00:29.167946Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8147332135429607620, trigger=visual_change)
2026-05-12T15:00:38.277066Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=click)
2026-05-12T15:00:39.475884Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=click)
2026-05-12T15:00:58.089090Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=7442982011400540096, trigger=click)
2026-05-12T15:00:58.095618Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=7442982011400540096, trigger=click)
2026-05-12T15:01:02.550033Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-545273533072853505, trigger=visual_change)
tip: sign in for higher AI quotas + cloud sync:
screenpipe login
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:01:50.346393Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:03:52.628434Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T15:04:31.563819Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=140 elapsed=2.253134667s
2026-05-12T15:04:31.564540Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 140 eligible frames
2026-05-12T15:04:34.375276Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 47 frames, 15.0MB → 0.8MB (19.1x), 47 JPEGs deleted
2026-05-12T15:04:41.481988Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 91 frames, 13.6MB → 5.6MB (2.4x), 91 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:05:55.231679Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: get the screenpipe desktop app for the full experience
https://screenpi.pe
2026-05-12T15:07:10.598829Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 82.8ms elapsed (expected 5.3ms) → inserting 77.5ms silence (7439 samples)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:07:57.738534Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T15:09:41.576620Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 110 eligible frames
2026-05-12T15:09:44.361015Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 46 frames, 13.4MB → 1.3MB (10.1x), 46 JPEGs deleted
2026-05-12T15:09:49.818095Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 62 frames, 10.4MB → 4.2MB (2.5x), 62 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:10:00.032837Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:12:02.830584Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:14:05.195695Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T15:14:53.091375Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=94 elapsed=3.184523292s
2026-05-12T15:14:53.091512Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 94 eligible frames
2026-05-12T15:14:55.411976Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 36 frames, 6.9MB → 1.0MB (6.6x), 36 JPEGs deleted
2026-05-12T15:15:00.362839Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 56 frames, 8.4MB → 3.7MB (2.3x), 56 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_i...
|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"ggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:47:23.838686Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T14:49:10.556142Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=35 elapsed=1.320759208s\n2026-05-12T14:49:10.556536Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 35 eligible frames\n2026-05-12T14:49:12.093113Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 14 frames, 2.7MB → 0.3MB (8.9x), 14 JPEGs deleted\n2026-05-12T14:49:13.889798Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 19 frames, 3.6MB → 0.7MB (4.9x), 19 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:49:26.762419Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:51:29.801432Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T14:51:55.611515Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 105.3ms elapsed (expected 5.3ms) → inserting 100.0ms silence (9598 samples)\n2026-05-12T14:51:55.781428Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 169.9ms elapsed (expected 5.3ms) → inserting 164.6ms silence (15800 samples)\n2026-05-12T14:51:56.081737Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 139.9ms elapsed (expected 5.3ms) → inserting 134.5ms silence (12914 samples)\n2026-05-12T14:53:02.556928Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 85.7ms elapsed (expected 5.3ms) → inserting 80.4ms silence (7717 samples)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:53:33.473658Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T14:54:14.604527Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 57 eligible frames\n2026-05-12T14:54:16.150850Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 23 frames, 4.4MB → 0.3MB (14.3x), 23 JPEGs deleted\n2026-05-12T14:54:18.438626Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 32 frames, 5.7MB → 1.4MB (4.2x), 32 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:55:36.875217Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-12T14:56:43.513652Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6205158385764507775, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:57:43.527916Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T14:57:51.020481Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)\n2026-05-12T14:57:54.005004Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)\n2026-05-12T14:58:00.087355Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)\n2026-05-12T14:58:03.103321Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)\n2026-05-12T14:58:08.055814Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-9035457757750653601, trigger=click)\n2026-05-12T14:58:08.062982Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=click)\n2026-05-12T14:58:12.199518Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)\n2026-05-12T14:59:20.391870Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=101 elapsed=1.967512791s\n2026-05-12T14:59:20.392758Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 101 eligible frames\n2026-05-12T14:59:22.488440Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 33 frames, 9.8MB → 1.0MB (9.7x), 33 JPEGs deleted\n2026-05-12T14:59:29.272518Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 66 frames, 10.5MB → 4.5MB (2.3x), 66 JPEGs deleted\n2026-05-12T14:59:34.683966Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9180842073176773313, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:59:47.398325Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T14:59:47.459122Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=3999125719128242167, trigger=click)\n2026-05-12T14:59:50.807323Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 101.4ms elapsed (expected 5.3ms) → inserting 96.0ms silence (9219 samples)\n2026-05-12T15:00:25.458921Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=visual_change)\n2026-05-12T15:00:28.452080Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=visual_change)\n2026-05-12T15:00:29.167946Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8147332135429607620, trigger=visual_change)\n2026-05-12T15:00:38.277066Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=click)\n2026-05-12T15:00:39.475884Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=click)\n2026-05-12T15:00:58.089090Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=7442982011400540096, trigger=click)\n2026-05-12T15:00:58.095618Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=7442982011400540096, trigger=click)\n2026-05-12T15:01:02.550033Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-545273533072853505, trigger=visual_change)\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:01:50.346393Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:03:52.628434Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T15:04:31.563819Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=140 elapsed=2.253134667s\n2026-05-12T15:04:31.564540Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 140 eligible frames\n2026-05-12T15:04:34.375276Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 47 frames, 15.0MB → 0.8MB (19.1x), 47 JPEGs deleted\n2026-05-12T15:04:41.481988Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 91 frames, 13.6MB → 5.6MB (2.4x), 91 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:05:55.231679Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\n2026-05-12T15:07:10.598829Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 82.8ms elapsed (expected 5.3ms) → inserting 77.5ms silence (7439 samples)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:07:57.738534Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T15:09:41.576620Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 110 eligible frames\n2026-05-12T15:09:44.361015Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 46 frames, 13.4MB → 1.3MB (10.1x), 46 JPEGs deleted\n2026-05-12T15:09:49.818095Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 62 frames, 10.4MB → 4.2MB (2.5x), 62 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:10:00.032837Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:12:02.830584Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:14:05.195695Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T15:14:53.091375Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=94 elapsed=3.184523292s\n2026-05-12T15:14:53.091512Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 94 eligible frames\n2026-05-12T15:14:55.411976Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 36 frames, 6.9MB → 1.0MB (6.6x), 36 JPEGs deleted\n2026-05-12T15:15:00.362839Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 56 frames, 8.4MB → 3.7MB (2.3x), 56 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:16:07.714574Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-12T15:16:48.671305Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=8414032348020665010, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:18:11.484810Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks","depth":4,"bounds":{"left":0.27027926,"top":1.0,"width":0.4787234,"height":-0.06304872},"on_screen":true,"value":"ggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:47:23.838686Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T14:49:10.556142Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=1 rows_returned=35 elapsed=1.320759208s\n2026-05-12T14:49:10.556536Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 35 eligible frames\n2026-05-12T14:49:12.093113Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 14 frames, 2.7MB → 0.3MB (8.9x), 14 JPEGs deleted\n2026-05-12T14:49:13.889798Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 19 frames, 3.6MB → 0.7MB (4.9x), 19 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:49:26.762419Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:51:29.801432Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T14:51:55.611515Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 105.3ms elapsed (expected 5.3ms) → inserting 100.0ms silence (9598 samples)\n2026-05-12T14:51:55.781428Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 169.9ms elapsed (expected 5.3ms) → inserting 164.6ms silence (15800 samples)\n2026-05-12T14:51:56.081737Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 139.9ms elapsed (expected 5.3ms) → inserting 134.5ms silence (12914 samples)\n2026-05-12T14:53:02.556928Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 85.7ms elapsed (expected 5.3ms) → inserting 80.4ms silence (7717 samples)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:53:33.473658Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T14:54:14.604527Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 57 eligible frames\n2026-05-12T14:54:16.150850Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 23 frames, 4.4MB → 0.3MB (14.3x), 23 JPEGs deleted\n2026-05-12T14:54:18.438626Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 32 frames, 5.7MB → 1.4MB (4.2x), 32 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:55:36.875217Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-12T14:56:43.513652Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6205158385764507775, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:57:43.527916Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T14:57:51.020481Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)\n2026-05-12T14:57:54.005004Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)\n2026-05-12T14:58:00.087355Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)\n2026-05-12T14:58:03.103321Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)\n2026-05-12T14:58:08.055814Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-9035457757750653601, trigger=click)\n2026-05-12T14:58:08.062982Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=click)\n2026-05-12T14:58:12.199518Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)\n2026-05-12T14:59:20.391870Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=101 elapsed=1.967512791s\n2026-05-12T14:59:20.392758Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 101 eligible frames\n2026-05-12T14:59:22.488440Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 33 frames, 9.8MB → 1.0MB (9.7x), 33 JPEGs deleted\n2026-05-12T14:59:29.272518Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 66 frames, 10.5MB → 4.5MB (2.3x), 66 JPEGs deleted\n2026-05-12T14:59:34.683966Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9180842073176773313, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T14:59:47.398325Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T14:59:47.459122Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=3999125719128242167, trigger=click)\n2026-05-12T14:59:50.807323Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 101.4ms elapsed (expected 5.3ms) → inserting 96.0ms silence (9219 samples)\n2026-05-12T15:00:25.458921Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=visual_change)\n2026-05-12T15:00:28.452080Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=visual_change)\n2026-05-12T15:00:29.167946Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8147332135429607620, trigger=visual_change)\n2026-05-12T15:00:38.277066Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=click)\n2026-05-12T15:00:39.475884Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=click)\n2026-05-12T15:00:58.089090Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=7442982011400540096, trigger=click)\n2026-05-12T15:00:58.095618Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=7442982011400540096, trigger=click)\n2026-05-12T15:01:02.550033Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-545273533072853505, trigger=visual_change)\n\n tip: sign in for higher AI quotas + cloud sync:\n screenpipe login\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:01:50.346393Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:03:52.628434Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T15:04:31.563819Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=140 elapsed=2.253134667s\n2026-05-12T15:04:31.564540Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 140 eligible frames\n2026-05-12T15:04:34.375276Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 47 frames, 15.0MB → 0.8MB (19.1x), 47 JPEGs deleted\n2026-05-12T15:04:41.481988Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 91 frames, 13.6MB → 5.6MB (2.4x), 91 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:05:55.231679Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: get the screenpipe desktop app for the full experience\n https://screenpi.pe\n\n2026-05-12T15:07:10.598829Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 82.8ms elapsed (expected 5.3ms) → inserting 77.5ms silence (7439 samples)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:07:57.738534Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T15:09:41.576620Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 110 eligible frames\n2026-05-12T15:09:44.361015Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 46 frames, 13.4MB → 1.3MB (10.1x), 46 JPEGs deleted\n2026-05-12T15:09:49.818095Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 62 frames, 10.4MB → 4.2MB (2.5x), 62 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:10:00.032837Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: wire screenpipe into claude with one command:\n claude mcp add screenpipe -- npx -y screenpipe-mcp\n then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity\n\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:12:02.830584Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:14:05.195695Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-12T15:14:53.091375Z WARN sqlx::query: summary=\"SELECT id, snapshot_path, device_name, …\" db.statement=\"\\n\\nSELECT\\n id,\\n snapshot_path,\\n device_name,\\n timestamp\\nFROM\\n frames\\nWHERE\\n snapshot_path IS NOT NULL\\n AND timestamp < ?1\\nORDER BY\\n device_name,\\n timestamp ASC\\nLIMIT\\n 5000\\n\" rows_affected=0 rows_returned=94 elapsed=3.184523292s\n2026-05-12T15:14:53.091512Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 94 eligible frames\n2026-05-12T15:14:55.411976Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 36 frames, 6.9MB → 1.0MB (6.6x), 36 JPEGs deleted\n2026-05-12T15:15:00.362839Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 56 frames, 8.4MB → 3.7MB (2.3x), 56 JPEGs deleted\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:16:07.714574Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n\n tip: install a starter bundle of pipes:\n screenpipe install https://screenpi.pe/start.json\n\n2026-05-12T15:16:48.671305Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=8414032348020665010, trigger=click)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-12T15:18:11.484810Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.27027926,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.27227393,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (-zsh)","depth":2,"bounds":{"left":0.33759972,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.33959442,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"APP (-zsh)","depth":2,"bounds":{"left":0.40492022,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.4069149,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"ec2-user@ip-10-30-129-190:~ (-zsh)","depth":2,"bounds":{"left":0.4722407,"top":1.0,"width":0.06732048,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.4742354,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.53956115,"top":1.0,"width":0.06715426,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.5415558,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"screenpipe\"","depth":2,"bounds":{"left":0.60671544,"top":1.0,"width":0.06715426,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.6087101,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"-zsh","depth":2,"bounds":{"left":0.67386967,"top":1.0,"width":0.06715426,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.67586434,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"⌥⌘1","depth":1,"bounds":{"left":0.7273936,"top":1.0,"width":0.01861702,"height":-0.023144484},"on_screen":true,"automation_id":"_NS:8","role_description":"text"},{"role":"AXStaticText","text":"screenpipe\"","depth":1,"bounds":{"left":0.4956782,"top":1.0,"width":0.027925532,"height":-0.02394259},"on_screen":true,"role_description":"text"}]...
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-7364628208594104327
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-816202909427632671
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click
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accessibility
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ggml_metal_init: found device: Apple M1
ggml_metal ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:47:23.838686Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T14:49:10.556142Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=1 rows_returned=35 elapsed=1.320759208s
2026-05-12T14:49:10.556536Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 35 eligible frames
2026-05-12T14:49:12.093113Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 14 frames, 2.7MB → 0.3MB (8.9x), 14 JPEGs deleted
2026-05-12T14:49:13.889798Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 19 frames, 3.6MB → 0.7MB (4.9x), 19 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:49:26.762419Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:51:29.801432Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T14:51:55.611515Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 105.3ms elapsed (expected 5.3ms) → inserting 100.0ms silence (9598 samples)
2026-05-12T14:51:55.781428Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 169.9ms elapsed (expected 5.3ms) → inserting 164.6ms silence (15800 samples)
2026-05-12T14:51:56.081737Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 139.9ms elapsed (expected 5.3ms) → inserting 134.5ms silence (12914 samples)
2026-05-12T14:53:02.556928Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 85.7ms elapsed (expected 5.3ms) → inserting 80.4ms silence (7717 samples)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:53:33.473658Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T14:54:14.604527Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 57 eligible frames
2026-05-12T14:54:16.150850Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 23 frames, 4.4MB → 0.3MB (14.3x), 23 JPEGs deleted
2026-05-12T14:54:18.438626Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 32 frames, 5.7MB → 1.4MB (4.2x), 32 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:55:36.875217Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: install a starter bundle of pipes:
screenpipe install https://screenpi.pe/start.json
2026-05-12T14:56:43.513652Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=6205158385764507775, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:57:43.527916Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T14:57:51.020481Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)
2026-05-12T14:57:54.005004Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)
2026-05-12T14:58:00.087355Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)
2026-05-12T14:58:03.103321Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)
2026-05-12T14:58:08.055814Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-9035457757750653601, trigger=click)
2026-05-12T14:58:08.062982Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=click)
2026-05-12T14:58:12.199518Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9035457757750653601, trigger=visual_change)
2026-05-12T14:59:20.391870Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=101 elapsed=1.967512791s
2026-05-12T14:59:20.392758Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 101 eligible frames
2026-05-12T14:59:22.488440Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 33 frames, 9.8MB → 1.0MB (9.7x), 33 JPEGs deleted
2026-05-12T14:59:29.272518Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 66 frames, 10.5MB → 4.5MB (2.3x), 66 JPEGs deleted
2026-05-12T14:59:34.683966Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-9180842073176773313, trigger=click)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T14:59:47.398325Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T14:59:47.459122Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=3999125719128242167, trigger=click)
2026-05-12T14:59:50.807323Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 101.4ms elapsed (expected 5.3ms) → inserting 96.0ms silence (9219 samples)
2026-05-12T15:00:25.458921Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=visual_change)
2026-05-12T15:00:28.452080Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=visual_change)
2026-05-12T15:00:29.167946Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=-8147332135429607620, trigger=visual_change)
2026-05-12T15:00:38.277066Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=click)
2026-05-12T15:00:39.475884Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-8147332135429607620, trigger=click)
2026-05-12T15:00:58.089090Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=7442982011400540096, trigger=click)
2026-05-12T15:00:58.095618Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 2 (hash=7442982011400540096, trigger=click)
2026-05-12T15:01:02.550033Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=-545273533072853505, trigger=visual_change)
tip: sign in for higher AI quotas + cloud sync:
screenpipe login
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:01:50.346393Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:03:52.628434Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T15:04:31.563819Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=140 elapsed=2.253134667s
2026-05-12T15:04:31.564540Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 140 eligible frames
2026-05-12T15:04:34.375276Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 47 frames, 15.0MB → 0.8MB (19.1x), 47 JPEGs deleted
2026-05-12T15:04:41.481988Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 91 frames, 13.6MB → 5.6MB (2.4x), 91 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:05:55.231679Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: get the screenpipe desktop app for the full experience
https://screenpi.pe
2026-05-12T15:07:10.598829Z WARN screenpipe_audio::core::source_buffer: [MacBook Pro Microphone (input)] large gap on wired device: 82.8ms elapsed (expected 5.3ms) → inserting 77.5ms silence (7439 samples)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:07:57.738534Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T15:09:41.576620Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 110 eligible frames
2026-05-12T15:09:44.361015Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 46 frames, 13.4MB → 1.3MB (10.1x), 46 JPEGs deleted
2026-05-12T15:09:49.818095Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 62 frames, 10.4MB → 4.2MB (2.5x), 62 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:10:00.032837Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
tip: wire screenpipe into claude with one command:
claude mcp add screenpipe -- npx -y screenpipe-mcp
then ask claude to build a pipe that tracks who you are, your todos, and how you spend your time from your screen activity
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:12:02.830584Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-12T15:14:05.195695Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-12T15:14:53.091375Z WARN sqlx::query: summary="SELECT id, snapshot_path, device_name, …" db.statement="\n\nSELECT\n id,\n snapshot_path,\n device_name,\n timestamp\nFROM\n frames\nWHERE\n snapshot_path IS NOT NULL\n AND timestamp < ?1\nORDER BY\n device_name,\n timestamp ASC\nLIMIT\n 5000\n" rows_affected=0 rows_returned=94 elapsed=3.184523292s
2026-05-12T15:14:53.091512Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: found 94 eligible frames
2026-05-12T15:14:55.411976Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 36 frames, 6.9MB → 1.0MB (6.6x), 36 JPEGs deleted
2026-05-12T15:15:00.362839Z INFO screenpipe_engine::snapshot_compaction: snapshot compaction: 56 frames, 8.4MB → 3.7MB (2.3x), 56 JPEGs deleted
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_i...
|
NULL
|
NULL
|
NULL
|
NULL
|
|
7072
|
317
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6
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2026-05-08T08:13:42.767415+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-08/1778 /Users/lukas/.screenpipe/data/data/2026-05-08/1778228022767_m1.jpg...
|
Finder
|
screenpipe
|
True
|
NULL
|
monitor_1
|
NULL
|
NULL
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NULL
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NULL
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Favourites
jiminny
AirDrop
Recents
Applications
Do Favourites
jiminny
AirDrop
Recents
Applications
Documents
Downloads
lukas
iCloud
iCloud Drive
Sync folder
Locations
DXP4800PLUS-B5F
Eject
Network
Tags
CRM
Orange
Red
Yellow
Green
Blue
Purple
All Tags…
Name
Date Modified
Size
Kind
Name
Date Modified
Size
Kind
0 items
screenpipe...
|
[{"role":"AXStaticText","text& [{"role":"AXStaticText","text":"Favourites","depth":6,"on_screen":true,"automation_id":"xSidebarHeader","role_description":"text"},{"role":"AXStaticText","text":"jiminny","depth":6,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"AirDrop","depth":6,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"Recents","depth":6,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"Applications","depth":6,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"Documents","depth":6,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"Downloads","depth":6,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"lukas","depth":6,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"iCloud","depth":6,"on_screen":true,"automation_id":"xSidebarHeader","role_description":"text"},{"role":"AXStaticText","text":"iCloud Drive","depth":6,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"Sync folder","depth":6,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"Locations","depth":6,"on_screen":true,"automation_id":"xSidebarHeader","role_description":"text"},{"role":"AXStaticText","text":"DXP4800PLUS-B5F","depth":6,"on_screen":true,"role_description":"text"},{"role":"AXButton","text":"Eject","depth":6,"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false},{"role":"AXStaticText","text":"Network","depth":6,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"Tags","depth":6,"on_screen":false,"automation_id":"xSidebarHeader","role_description":"text"},{"role":"AXStaticText","text":"CRM","depth":6,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Orange","depth":6,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Red","depth":6,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Yellow","depth":6,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Green","depth":6,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Blue","depth":6,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Purple","depth":6,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"All Tags…","depth":6,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Name","depth":7,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"Date Modified","depth":7,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"Size","depth":7,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"Kind","depth":7,"on_screen":true,"role_description":"text"},{"role":"AXButton","text":"Name","depth":6,"on_screen":true,"role_description":"sort button","subrole":"AXSortButton","is_enabled":true,"is_focused":false},{"role":"AXButton","text":"Date Modified","depth":6,"on_screen":true,"role_description":"sort button","subrole":"AXSortButton","is_enabled":true,"is_focused":false},{"role":"AXButton","text":"Size","depth":6,"on_screen":true,"role_description":"sort button","subrole":"AXSortButton","is_enabled":true,"is_focused":false},{"role":"AXButton","text":"Kind","depth":6,"on_screen":true,"role_description":"sort button","subrole":"AXSortButton","is_enabled":true,"is_focused":false},{"role":"AXStaticText","text":"0 items","depth":2,"on_screen":true,"automation_id":"_NS:34","role_description":"text"},{"role":"AXStaticText","text":"screenpipe","depth":1,"on_screen":true,"role_description":"text"}]...
|
-4696675471702771510
|
-1841934550831116516
|
click
|
accessibility
|
NULL
|
Favourites
jiminny
AirDrop
Recents
Applications
Do Favourites
jiminny
AirDrop
Recents
Applications
Documents
Downloads
lukas
iCloud
iCloud Drive
Sync folder
Locations
DXP4800PLUS-B5F
Eject
Network
Tags
CRM
Orange
Red
Yellow
Green
Blue
Purple
All Tags…
Name
Date Modified
Size
Kind
Name
Date Modified
Size
Kind
0 items
screenpipe...
|
7071
|
NULL
|
NULL
|
NULL
|
|
7073
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318
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4
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2026-05-08T08:13:42.862300+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-08/1778 /Users/lukas/.screenpipe/data/data/2026-05-08/1778228022862_m2.jpg...
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Finder
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screenpipe
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True
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NULL
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monitor_2
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NULL
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NULL
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NULL
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NULL
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Favourites
jiminny
AirDrop
Recents
Applications
Do Favourites
jiminny
AirDrop
Recents
Applications
Documents
Downloads
lukas
iCloud
iCloud Drive
Sync folder
Locations
DXP4800PLUS-B5F
Eject
Network
Tags
CRM
Orange
Red
Yellow
Green
Blue
Purple
All Tags…
Name
Date Modified
Size
Kind
db.sqlite-shm...
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4233611889010268352
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click
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accessibility
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NULL
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Favourites
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db.sqlite-shm...
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NULL
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NULL
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NULL
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NULL
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7074
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318
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5
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2026-05-08T08:13:45.273225+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-08/1778 /Users/lukas/.screenpipe/data/data/2026-05-08/1778228025273_m2.jpg...
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Finder
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screenpipe
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True
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NULL
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monitor_2
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NULL
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NULL
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NULL
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NULL
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Favourites
jiminny
AirDrop
Recents
Applications
Do Favourites
jiminny
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Applications
Documents
Downloads
lukas
iCloud
iCloud Drive
Sync folder
Locations
DXP4800PLUS-B5F
Eject
Network
Tags
CRM
Orange
Red
Yellow
Green
Blue
Purple
All Tags…
Name
Date Modified
Size
Kind
db.sqlite-shm
Today at 11:04
33 KB
Document
data
Yesterday at 9:23
6,9 GB
Folder
archive.db
Yesterday at 9:21
11,13 GB
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#recycle
Yesterday at 9:21
54,04 GB
Folder
app
26 Apr 2026 at 20:10
193 KB
Folder
db.sqlite-wal
26 Apr 2026 at 17:17
Zero bytes
Document
db.sqlite
26 Apr 2026 at 16:44
8,63 GB
Document
screenpipe_sync.sh
18 Apr 2026 at 18:35
15 KB
Terminal scripts
app_settings.json
18 Apr 2026 at 17:42
31 bytes
JSON
screenpipe.db
13 Apr 2026 at 17:21
Zero bytes
Document
pipes
11 Apr 2026 at 16:51
13 KB
Folder
Name
Date Modified
Size
Kind
11 items, 1,97 TB available
screenpipe...
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visual_change
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accessibility
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Favourites
jiminny
AirDrop
Recents
Applications
Do Favourites
jiminny
AirDrop
Recents
Applications
Documents
Downloads
lukas
iCloud
iCloud Drive
Sync folder
Locations
DXP4800PLUS-B5F
Eject
Network
Tags
CRM
Orange
Red
Yellow
Green
Blue
Purple
All Tags…
Name
Date Modified
Size
Kind
db.sqlite-shm
Today at 14:41
33 KB
Document
#recycle
Today at 14:36
62,68 GB
Folder
db.sqlite
Today at 14:10
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logs
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sync.log
Today at 13:47
7 KB
Log File
screenpipe.2026-05-07.0.log
7 May 2026 at 21:50
566 KB
Log File
data
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7,2 GB
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2026-05-07
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305,6 MB
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18,8 MB
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2026-04-28
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2026-04-21
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2026-04-17
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699,6 MB
Folder
2026-04-16
17 Apr 2026 at 8:57
837,2 MB
Folder
2026-04-15
16 Apr 2026 at 9:13
2,15 GB
Folder
2026-04-14...
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NULL
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NULL
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NULL
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NULL
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14622
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649
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10
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2026-05-10T11:44:18.664382+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-10/1778 /Users/lukas/.screenpipe/data/data/2026-05-10/1778413458664_m1.jpg...
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Finder
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screenpipe
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Applications
Documents
Downloads
lukas
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iCloud Drive
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Locations
DXP4800PLUS-B5F
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Orange
Red
Yellow
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Purple
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Today at 14:41
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screenpipe...
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2026-04-22
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265,5 MB
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2026-04-23
24 Apr 2026 at 12:07
171,8 MB
Folder
2026-04-20
22 Apr 2026 at 18:44
525,4 MB
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2026-04-21
22 Apr 2026 at 9:16
450,8 MB
Folder
2026-04-17
18 Apr 2026 at 13:35
699,6 MB
Folder
2026-04-16
17 Apr 2026 at 8:57
837,2 MB
Folder
2026-04-15
16 Apr 2026 at 9:13
2,15 GB
Folder
2026-04-14
15 Apr 2026 at 9:59
1,09 GB
Folder
archive.db
Today at 13:44
12,19 GB
Document
screenpipe_sync_updated.sh
Today at 13:06
20 KB
Terminal scripts
archive.db-bak
Today at 12:31
11,13 GB
Document
app
26 Apr 2026 at 20:10
193 KB
Folder
db.sqlite-wal
26 Apr 2026 at 17:17
Zero bytes
Document
screenpipe_sync.sh
18 Apr 2026 at 18:35
15 KB
Terminal scripts
app_settings.json
18 Apr 2026 at 17:42
31 bytes
JSON
screenpipe.db
13 Apr 2026 at 17:21
Zero bytes
Document
pipes
11 Apr 2026 at 16:51
13 KB
Folder
Name
Date Modified
Size
Kind
30 items, 1,95 TB available
screenpipe...
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screenpipe
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CRM
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Red
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536278912574507229
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accessibility
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DXP4800PLUS-B5F
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app
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31 bytes
JSON
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30 items, 1,95 TB available
screenpipe...
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14630
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NULL
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NULL
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NULL
|
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16776
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748
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17
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2026-05-11T09:23:17.010121+00:00
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Finder
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screenpipe
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True
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NULL
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monitor_1
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NULL
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NULL
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NULL
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NULL
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Favourites
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AirDrop
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Applications
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Recents
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DXP4800PLUS-B5F
Eject
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CRM
Orange
Red
Yellow
Green
Blue
Purple
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data
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166,7 MB
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450,8 MB
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17 Apr 2026 at 8:57
837,2 MB
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2026-04-15
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2,15 GB
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1,09 GB
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31 bytes
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13 Apr 2026 at 17:21
Zero bytes
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11 Apr 2026 at 16:51
13 KB
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Name
Date Modified
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30 items, 1,94 TB available
screenpipe...
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iCloud Drive
Sync folder
Locations
DXP4800PLUS-B5F
Eject
Network
Tags
CRM
Orange
Red
Yellow
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Blue
Purple
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Yesterday at 20:48
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1,09 GB
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31 bytes
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screenpipe
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True
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monitor_2
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Favourites
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CRM
Orange
Red
Yellow
Green
Blue
Purple
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screenpipe...
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archive.db
Yesterday at 20:48
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Locations
DXP4800PLUS-B5F
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Date Modified
Size
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archive.db
Yesterday at 20:48
12,92 GB
Document
#recycle
Yesterday at 20:47
62,68 GB
Folder
db.sqlite-shm
Yesterday at 14:49
33 KB
Document
db.sqlite
Yesterday at 14:45
2,37 GB
Document
logs
Yesterday at 13:47
573 KB
Folder
sync.log
Yesterday at 13:47
7 KB
Log File
screenpipe.2026-05-07.0.log
7 May 2026 at 21:50
566 KB
Log File
data
Yesterday at 13:46
7,2 GB
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2026-05-07
8 May 2026 at 9:26
305,6 MB
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2026-05-06
6 May 2026 at 21:02
18,8 MB
Folder
2026-04-28
28 Apr 2026 at 22:23
166,7 MB
Folder
2026-04-27
28 Apr 2026 at 9:19
339,8 MB
Folder
2026-04-25
26 Apr 2026 at 16:35
39,7 MB
Folder
2026-04-24
24 Apr 2026 at 22:30
149,1 MB
Folder
2026-04-22
24 Apr 2026 at 12:08
265,5 MB
Folder
2026-04-23
24 Apr 2026 at 12:07
171,8 MB
Folder
2026-04-20
22 Apr 2026 at 18:44
525,4 MB
Folder
2026-04-21
22 Apr 2026 at 9:16
450,8 MB
Folder
2026-04-17
18 Apr 2026 at 13:35
699,6 MB
Folder
2026-04-16
17 Apr 2026 at 8:57
837,2 MB
Folder
2026-04-15
16 Apr 2026 at 9:13
2,15 GB
Folder
2026-04-14
15 Apr 2026 at 9:59
1,09 GB
Folder
screenpipe_sync_updated.sh
Yesterday at 13:06
20 KB
Terminal scripts
archive.db-bak
Yesterday at 12:31
11,13 GB
Document
app
26 Apr 2026 at 20:10
193 KB
Folder
db.sqlite-wal
26 Apr 2026 at 17:17
Zero bytes
Document
screenpipe_sync.sh
18 Apr 2026 at 18:35
15 KB
Terminal scripts
app_settings.json
18 Apr 2026 at 17:42
31 bytes
JSON
screenpipe.db
13 Apr 2026 at 17:21
Zero bytes
Document
pipes
11 Apr 2026 at 16:51
13 KB
Folder
Name
Date Modified
Size
Kind
30 items, 1,94 TB available...
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|
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visual_change
|
accessibility
|
NULL
|
Favourites
jiminny
AirDrop
Recents
Applications
Do Favourites
jiminny
AirDrop
Recents
Applications
Documents
Downloads
lukas
iCloud
iCloud Drive
Sync folder
Locations
DXP4800PLUS-B5F
Eject
Network
Tags
CRM
Orange
Red
Yellow
Green
Blue
Purple
All Tags…
Name
Date Modified
Size
Kind
archive.db
Yesterday at 20:48
12,92 GB
Document
#recycle
Yesterday at 20:47
62,68 GB
Folder
db.sqlite-shm
Yesterday at 14:49
33 KB
Document
db.sqlite
Yesterday at 14:45
2,37 GB
Document
logs
Yesterday at 13:47
573 KB
Folder
sync.log
Yesterday at 13:47
7 KB
Log File
screenpipe.2026-05-07.0.log
7 May 2026 at 21:50
566 KB
Log File
data
Yesterday at 13:46
7,2 GB
Folder
2026-05-07
8 May 2026 at 9:26
305,6 MB
Folder
2026-05-06
6 May 2026 at 21:02
18,8 MB
Folder
2026-04-28
28 Apr 2026 at 22:23
166,7 MB
Folder
2026-04-27
28 Apr 2026 at 9:19
339,8 MB
Folder
2026-04-25
26 Apr 2026 at 16:35
39,7 MB
Folder
2026-04-24
24 Apr 2026 at 22:30
149,1 MB
Folder
2026-04-22
24 Apr 2026 at 12:08
265,5 MB
Folder
2026-04-23
24 Apr 2026 at 12:07
171,8 MB
Folder
2026-04-20
22 Apr 2026 at 18:44
525,4 MB
Folder
2026-04-21
22 Apr 2026 at 9:16
450,8 MB
Folder
2026-04-17
18 Apr 2026 at 13:35
699,6 MB
Folder
2026-04-16
17 Apr 2026 at 8:57
837,2 MB
Folder
2026-04-15
16 Apr 2026 at 9:13
2,15 GB
Folder
2026-04-14
15 Apr 2026 at 9:59
1,09 GB
Folder
screenpipe_sync_updated.sh
Yesterday at 13:06
20 KB
Terminal scripts
archive.db-bak
Yesterday at 12:31
11,13 GB
Document
app
26 Apr 2026 at 20:10
193 KB
Folder
db.sqlite-wal
26 Apr 2026 at 17:17
Zero bytes
Document
screenpipe_sync.sh
18 Apr 2026 at 18:35
15 KB
Terminal scripts
app_settings.json
18 Apr 2026 at 17:42
31 bytes
JSON
screenpipe.db
13 Apr 2026 at 17:21
Zero bytes
Document
pipes
11 Apr 2026 at 16:51
13 KB
Folder
Name
Date Modified
Size
Kind
30 items, 1,94 TB available...
|
17270
|
NULL
|
NULL
|
NULL
|
|
21007
|
919
|
6
|
2026-05-11T17:03:17.158901+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778518997158_m2.jpg...
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Finder
|
screenpipe
|
True
|
NULL
|
monitor_2
|
NULL
|
NULL
|
NULL
|
NULL
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Favourites
jiminny
AirDrop
Recents
Applications
Do Favourites
jiminny
AirDrop
Recents
Applications
Documents
Downloads
lukas
iCloud
iCloud Drive
Sync folder
Locations
DXP4800PLUS-B5F
Eject
Network
Tags
CRM
Orange
Red
Yellow
Green
Blue
Purple
All Tags…
Name
Date Modified
Size
Kind
db.sqlite-shm
Today at 19:16
33 KB
Document
archive.db
Yesterday at 20:48
12,92 GB
Document
#recycle
Yesterday at 20:47
62,68 GB
Folder
db.sqlite
Yesterday at 14:45
2,37 GB
Document
logs
Yesterday at 13:47
573 KB
Folder
sync.log
Yesterday at 13:47
7 KB
Log File
screenpipe.2026-05-07.0.log
7 May 2026 at 21:50
566 KB
Log File
data
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7,2 GB
Folder
2026-05-07
8 May 2026 at 9:26
305,6 MB
Folder
2026-05-06
6 May 2026 at 21:02
18,8 MB
Folder
2026-04-28
28 Apr 2026 at 22:23
166,7 MB
Folder
2026-04-27
28 Apr 2026 at 9:19
339,8 MB
Folder
2026-04-25
26 Apr 2026 at 16:35
39,7 MB
Folder
2026-04-24
24 Apr 2026 at 22:30
149,1 MB
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2026-04-22
24 Apr 2026 at 12:08
265,5 MB
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2026-04-23
24 Apr 2026 at 12:07
171,8 MB
Folder
2026-04-20
22 Apr 2026 at 18:44
525,4 MB
Folder
2026-04-21
22 Apr 2026 at 9:16
450,8 MB
Folder
2026-04-17
18 Apr 2026 at 13:35
699,6 MB
Folder
2026-04-16
17 Apr 2026 at 8:57
837,2 MB
Folder
2026-04-15
16 Apr 2026 at 9:13
2,15 GB
Folder
2026-04-14
15 Apr 2026 at 9:59
1,09 GB
Folder
screenpipe_sync_updated.sh
Yesterday at 13:06
20 KB
Terminal scripts
archive.db-bak
Yesterday at 12:31
11,13 GB
Document
app
26 Apr 2026 at 20:10
193 KB
Folder
db.sqlite-wal
26 Apr 2026 at 17:17
Zero bytes
Document
screenpipe_sync.sh
18 Apr 2026 at 18:35
15 KB
Terminal scripts
app_settings.json
18 Apr 2026 at 17:42
31 bytes
JSON
screenpipe.db
13 Apr 2026 at 17:21
Zero bytes
Document
pipes
11 Apr 2026 at 16:51
13 KB
Folder
Name
Date Modified
Size
Kind
30 items, 1,94 TB available
screenpipe...
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Log File
screenpipe.2026-05-07.0.log
7 May 2026 at 21:50
566 KB
Log File
data...
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jiminny
AirDrop
Recents
Applications
Do Favourites
jiminny
AirDrop
Recents
Applications
Documents
Downloads
lukas
iCloud
iCloud Drive
Sync folder
Locations
DXP4800PLUS-B5F
Eject
Network
Tags
CRM
Orange
Red
Yellow
Green
Blue
Purple
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db.sqlite-shm
Today at 19:16
33 KB
Document
archive.db
Yesterday at 20:48
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Document
#recycle
Yesterday at 20:47
62,68 GB
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db.sqlite
Yesterday at 14:45
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logs
Yesterday at 13:47
573 KB
Folder
sync.log
Yesterday at 13:47
7 KB
Log File
screenpipe.2026-05-07.0.log
7 May 2026 at 21:50
566 KB
Log File
data...
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2026-05-11T17:15:17.073812+00:00
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screenpipe
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True
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NULL
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monitor_2
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NULL
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NULL
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NULL
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NULL
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Favourites
jiminny
AirDrop
Recents
Applications
Do Favourites
jiminny
AirDrop
Recents
Applications
Documents
Downloads
lukas
iCloud
iCloud Drive
Sync folder
Locations
DXP4800PLUS-B5F
Eject
Network
Tags
CRM
Orange
Red
Yellow
Green
Blue
Purple
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Name
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db.sqlite-shm
Today at 19:16
33 KB
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Yesterday at 20:48
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#recycle
Yesterday at 20:47
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db.sqlite
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logs
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screenpipe.2026-05-07.0.log
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2,15 GB
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2026-04-14
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1,09 GB
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screenpipe_sync_updated.sh
Yesterday at 13:06
20 KB
Terminal scripts
archive.db-bak
Yesterday at 12:31
11,13 GB
Document
app
26 Apr 2026 at 20:10
193 KB
Folder
db.sqlite-wal
26 Apr 2026 at 17:17
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18 Apr 2026 at 18:35
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app_settings.json
18 Apr 2026 at 17:42
31 bytes
JSON
screenpipe.db
13 Apr 2026 at 17:21
Zero bytes
Document
pipes
11 Apr 2026 at 16:51
13 KB
Folder
Name
Date Modified
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Kind
30 items, 1,94 TB available
screenpipe...
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-2215740180618935707
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6577094367223971794
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visual_change
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accessibility
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NULL
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screenpipe_sync.sh
Today at 20:48
32 KB
Terminal scripts
db.sqlite-shm
Today at 20:46
33 KB
Document
#recycle
Today at 20:15
62,68 GB
Folder
db.sqlite
Today at 20:15
3,71 GB
Document
archive.db
Yesterday at 20:48
12,92 GB
Document
logs
Yesterday at 13:47
573 KB
Folder
sync.log
Yesterday at 13:47
7 KB
Log File
screenpipe.2026-05-07.0.log
7 May 2026 at 21:50
566 KB
Log File
data
Yesterday at 13:46
7,2 GB
Folder
2026-05-07
8 May 2026 at 9:26
305,6 MB
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2026-05-06
6 May 2026 at 21:02
18,8 MB
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28 Apr 2026 at 22:23
166,7 MB
Folder
2026-04-27
28 Apr 2026 at 9:19
339,8 MB
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2026-04-25
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39,7 MB
Folder
2026-04-24
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149,1 MB
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2026-04-22
24 Apr 2026 at 12:08
265,5 MB
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2026-04-23
24 Apr 2026 at 12:07
171,8 MB
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2026-04-20
22 Apr 2026 at 18:44
525,4 MB
Folder
2026-04-21
22 Apr 2026 at 9:16
450,8 MB
Folder
2026-04-17
18 Apr 2026 at 13:35
699,6 MB
Folder
2026-04-16
17 Apr 2026 at 8:57
837,2 MB
Folder
2026-04-15
16 Apr 2026 at 9:13
2,15 GB
Folder
2026-04-14
15 Apr 2026 at 9:59
1,09 GB
Folder
screenpipe_sync_updated.sh
Yesterday at 13:06...
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21430
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NULL
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NULL
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db.sqlite-shm
Today at 21:19
33 KB
Document
#recycle
Today at 20:55
62,68 GB
Folder
archive.db...
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visual_change
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accessibility
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Favourites
jiminny
AirDrop
Recents
Applications
Do Favourites
jiminny
AirDrop
Recents
Applications
Documents
Downloads
lukas
iCloud
iCloud Drive
Sync folder
Locations
DXP4800PLUS-B5F
Eject
Network
Tags
CRM
Orange
Red
Yellow
Green
Blue
Purple
All Tags…
Name
Date Modified
Size
Kind
db.sqlite-shm
Today at 21:19
33 KB
Document
#recycle
Today at 20:55
62,68 GB
Folder
archive.db...
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21733
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NULL
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NULL
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NULL
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12157
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540
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13
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2026-05-09T08:30:44.464415+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-09/1778 /Users/lukas/.screenpipe/data/data/2026-05-09/1778315444464_m2.jpg...
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Code
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report(2).csv — finance [SSH: nas]
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True
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NULL
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monitor_2
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NULL
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NULL
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NULL
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G)
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
report(1).csv, Editor Group 1
report(2).csv, Editor Group 1
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
Design new payment-logge…, Editor Group 2
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Info: Setting up SSH Host nas: Setting up SSH tunnel
Design new payment-logger and dsk-uploader hybrid app
Session history
New session
Message actions
payments.js
payments.js
ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.
Thinking
Thinking
I'll explore all three reference projects in parallel to understand their structure before planning.
Agent:
Explore payment-logger app structure and functionality
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How data flows (ingest, storage, retrieval)
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.
Agent:
Explore dsk-uploader app structure and functionality
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How file uploads work - what files, what format, how parsed
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.
Agent:
Explore auth folder and authentik integration
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. What auth system is being used (Authentik)
2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?
3. Middleware - how is auth enforced on routes?
4. Any frontend auth flow - login redirect, token handling, protected routes
5. Environment variables related to auth
6. Docker/deployment setup for the auth service itself
7. Any example of how other apps integrate with this auth
Report with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.
Message actions
payments.js
payments.js
continue
Thinking
Thinking
Launching parallel exploration of all three reference projects.
Agent:
Explore payment-logger app structure
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How data is ingested (look at /ingest route especially)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore dsk-uploader app structure
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How file uploads work (what format, what processing happens)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore auth project structure
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. What authentication system is used (authentik integration details)
3. How OAuth/OIDC flow works
4. Any middleware or helper functions for protecting routes
5. Session management approach
6. How frontend handles auth state
7. Any example of how other apps integrate with this auth system
8. Docker setup and environment variables
Please read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.
Thinking
Thinking
Now I have a complete picture of all three. Let me design the plan.
Agent:
Design combined app architecture
IN
Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:
---
## App 1: payments-logger (Node.js)
- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI
- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS
- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage
- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)
- **Schema** (PostgreSQL via Prisma):
- `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at
- `tags` table: id, name, color — M2M with payments via `_PaymentToTag`
- `users` table: id, username, hashed_password (this will be REMOVED)
- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system
- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance
## App 2: dsk-uploader (Python/Flask)
- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database
- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5
- **Auth**: None (open)
- **CSV format** (DSK Bank Bulgarian format, columns):
- `Дата` (date, DD.MM.YYYY)
- `Вид на трансакцията` (transaction type, Bulgarian)
- `Основание` (reason/description — contains card number regex: `^\d{6}x{6}\d{4}$`)
- `Дебит BGN` (debit amount, may be empty)
- `Кредит BGN` (credit amount, may be empty)
- `Наредител/Получател` (orderer/recipient name)
- `Номер сметка на наредителя / получателя` (account number)
- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers
- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)
## App 3: auth (Authentik)
- **Mode**: Proxy mode via NPM (forward auth)
- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:
- `X-authentik-username`
- `X-authentik-email`
- `X-authentik-groups`
- **No code integration needed** in the app itself — just trust these headers from NPM
- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`
---
## What the New Combined App Must Do
1. **Single PostgreSQL database** for all transactions
2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST
3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema
4. **Unified UI** — show all payments in one table regardless of source
5. **Source indicator** in UI — badge showing "INGEST", "UPLOAD", or "BOTH" (if duplicate detection added)
6. **Source filter** in FilterBar — filter by All/Ingest/Upload
7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM
8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination
9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL
---
## Technical Constraints
- Keep Node.js backend (not Python) — extend payments-logger's stack
- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)
- File upload: use `multer` npm middleware
- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)
- Add `source` enum field (INGEST/UPLOAD) to payments schema
- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is
- Remove `users` table from schema
---
## Please Design
1. Complete folder structure for the new app (suggest name: "finance-hub" or similar — note this is a placeholder, user will confirm)
2. Prisma schema with new fields (`source`, `currency`)
3. All backend API routes
4. CSV parser design in Node.js (port of the Python logic)
5. Authentik auth middleware
6. Frontend component structure (React) — what's reused from payments-logger, what's new
7. Docker Compose setup
8. Environment variables needed
9. Step-by-step implementation order
10. Verification checklist
Be specific about file paths and code structure. This will be used to write actual implementation code.
Thinking
Thinking
Good plan. Let me ask the one thing I need before writing the final plan.
AskUserQuestion
OUT
User has answered your questions: "What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding."="finance-hub". You can now continue with the user's answers in mind.
Thinking
Thinking
Writing the final plan now.
Thinking
Thinking
Write
ets-create-a-new-generic-sun.md
ets-create-a-new-generic-sun.md
326 lines
# finance-hub — Implementation Plan
## Context
Two separate finance apps exist as references and will be retired:
- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.
- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.
The new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).
---
## Tech Stack
| Layer | Choice | Rationale |
|-------|--------|-----------|
| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |
| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |
| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |
| Database | PostgreSQL 16 | Same as payments-logger |
| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |
| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |
| Container | Docker Compose | Same pattern as both reference apps |
**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage.
**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references.
**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.
---
## Folder Structure
```
/volume2/docker/finance/finance-hub/
├── docker-compose.yml
├── .env
├── .env.example
├── .gitignore
├── backend/
│ ├── Dockerfile
│ ├── package.json
│ ├── prisma/
│ │ ├── schema.prisma
│ │ └── migrations/
│ │ ├── migration_lock.toml
│ │ └── 20260508_init/
│ │ └── migration.sql
│ └── src/
│ ├── index.js ← entry point (Authentik middleware wired here)
│ ├── auth.js ← Authentik header middleware (replaces JWT auth)
│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)
│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)
│ └── routes/
│ ├── payments.js ← existing routes + source/currency additions
│ └── upload.js ← NEW: POST /api/upload/csv
└── frontend/
├── Dockerfile
├── package.json
├── vite.config.js
├── tailwind.config.js
├── postcss.config.js
├── index.html
└── src/
├── main.jsx ← remove AuthProvider wrapper
├── index.css
├── App.jsx ← remove auth state, add Upload tab toggle
└── components/
├── FilterBar.jsx ← add source filter select
├── PaymentTable.jsx ← add Source badge column + currency display
├── PaymentCard.jsx ← minor source badge addition
├── PaymentList.jsx ← unchanged
└── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI
```
---
## Database Schema (Prisma)
File: `backend/prisma/schema.prisma`
```prisma
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
}
model Payment {
id Int @id @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
auth.js
auth.js
27 lines
const PUBLIC_PATHS = new Set([
'/api/health',
'/api/payments/ingest',
]);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) {
return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });
}
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '')
.split(',')
.map(g => g.trim())
.filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
Write
parser.js
parser.js
104 lines
/**
* Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)
*
* Supported formats:
*
* POS / INTERNET / ECOM / P2P payment:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM withdrawal:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM utility payment (amount may include fee as AMOUNT/FEE):
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.
*/
const LOCAL_TZ = process.env.TZ || 'Europe/Sofia';
/**
* Convert a local-timezone date/time to a UTC Date object.
* Uses Intl to resolve the actual UTC offset (DST-aware).
*/
function localToUtc(year, month, day, hour, minute) {
const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));
const formatter = new Intl.DateTimeFormat('en-US', {
timeZone: LOCAL_TZ,
year: 'numeric', month: '2-digit', day: '2-digit',
hour: '2-digit', minute: '2-digit', second: '2-digit',
hour12: false,
});
const parts = {};
formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });
const localAtNaive = new Date(Date.UTC(
parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),
parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),
));
const offsetMs = localAtNaive.getTime() - naive.getTime();
return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);
}
function parsePaymentSms(message) {
const result = {
rawMessage: message,
date: null,
type: null,
card: null,
recipient: null,
amount: null,
balance: null,
};
// Date and time: "Na DD/MM/YYYY v HH:MM"
const dateMatch = message.match(/Na (\d{2})\/(\d{2})\/(\d{4}) v (\d{2}):(\d{2})/i);
if (dateMatch) {
const [, day, month, year, hour, minute] = dateMatch;
result.date = localToUtc(
parseInt(year), parseInt(month), parseInt(day),
parseInt(hour), parseInt(minute),
);
}
// Card mask: "s karta 400915***4447" or "s karta 483890***7162"
const cardMatch = message.match(/s karta\s+([\d*]+)/i);
if (cardMatch) {
result.card = cardMatch[1];
}
// Transaction type: supports both prepositions
// "na POS" / "na ATM" / "na INTERNET" etc. (payment)
// "ot ATM" (withdrawal)
const typeMatch = message.match(/(?:na|ot)\s+(POS|ATM|INTERNET|ECOM|P2P)\b/i);
if (typeMatch) {
result.type = typeMatch[1].toUpperCase();
}
// Recipient address: "s adres: MERCHANT" or "s adres:MERCHANT" (no space variant)
const recipientMatch = message.match(/s adres:\s*([^.]+)\./i);
if (recipientMatch) {
result.recipient = recipientMatch[1].trim();
}
// Amount: handles both verbs and the AMOUNT/FEE suffix format
// "sa plateni 7.78 EUR"
// "sa iztegleni 400.00 EUR"
// "sa plateni 0.50 EUR/0.50 EUR" → captures 0.50 (the charged amount, ignoring fee)
const amountMatch = message.match(/sa (?:plateni|iztegleni)\s+([\d.,]+)\s+[A-Z]{3}/i);
if (amountMatch) {
result.amount = parseFloat(amountMatch[1].replace(',', '.'));
}
// Balance: "Nalichni: 2583.07 EUR."
const balanceMatch = message.match(/Nalichni:\s*([\d.,]+)\s+[A-Z]{3}/i);
if (balanceMatch) {
result.balance = parseFloat(balanceMatch[1].replace(',', '.'));
}
return result;
}
module.exports = { parsePaymentSms };
Write
csvParser.js
csvParser.js
175 lines
/**
* DSK Bank CSV parser — Node.js port of dskuploader.py
*
* DSK Bank exports use Windows-1251 (cp1251) encoding.
* Each row maps to a Payment record with source=UPLOAD, currency=BGN.
*/
const { parse } = require('csv-parse');
const iconv = require('iconv-lite');
const SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';
const CARD_REGEX = /^\d{6}x{6}\d{4}$/;
const POS_REGEX = /^\s*ПЛАЩАНЕ\s+НА\s+ПОС\s+\d{2}\.\d{2}\.\d{4}\s+\d{2}:\d{2}/;
const COL = {
DATE: 'Дата',
TYPE: 'Вид на трансакцията',
REASON: 'Основание',
DEBIT: 'Дебит BGN',
CREDIT: 'Кредит BGN',
PAYEE: 'Наредител/Получател',
ACCT: 'Номер сметка на наредителя / получателя',
};
const TAG_RULES = [
['reason', 'ЗАПЛАТА', 'Salary'],
['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],
['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],
['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],
['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],
['payee', 'VIVACOM', 'Subscriptions'],
['payee', 'Google', 'Subscriptions'],
['payee', 'SkyShowtime', 'Subscriptions'],
['payee', 'NETFLIX', 'Subscriptions'],
['payee', 'LUKOIL', 'Bills'],
['payee', 'CityGate', 'Bills'],
['payee', 'CBA', 'Groceries'],
['payee', 'FANTASTICO', 'Groceries'],
['payee', 'LIDL', 'Groceries'],
];
function parseNum(val) {
if (val == null || val === '') return null;
if (typeof val === 'number') return isNaN(val) ? null : val;
const s = String(val).trim().replace(/\xa0/g, '').replace(/ /g, '').replace(',', '.');
const n = parseFloat(s);
return isNaN(n) ? null : n;
}
function parseDate(val) {
if (!val) return null;
const s = String(val).trim();
const m = s.match(/^(\d{2})\.(\d{2})\.(\d{4})$/);
if (m) {
return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));
}
return null;
}
function processReasonAndCard(reason) {
if (!reason || typeof reason !== 'string') return { reason: '', card: null };
const parts = reason.trim().split(' ');
let card = null;
let cleanReason = reason.trim();
if (parts[0] && CARD_REGEX.test(parts[0])) {
card = parts[0];
cleanReason = parts.slice(1).join(' ').trim();
}
if (POS_REGEX.test(cleanReason)) {
const posParts = cleanReason.split('<br/>');
try {
const dateTime = posParts[0].split('ПОС ')[1];
cleanReason = `POS PAYMENT ${dateTime}`;
} catch (_) { /* keep original */ }
}
return { reason: cleanReason.replace(/\s+/g, ' ').trim(), card };
}
function generateTags(fields) {
const tags = new Set();
for (const [field, keyword, tagName] of TAG_RULES) {
if ((fields[field] || '').includes(keyword)) {
tags.add(tagName);
}
}
return Array.from(tags);
}
function processRow(row) {
const transactionType = (row[COL.TYPE] || '').trim();
if (transactionType === SKIP_TYPE) return null;
const { reason, card } = processReasonAndCard(row[COL.REASON]);
const payee = (row[COL.PAYEE] || '...
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actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"payments.js","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"I'll explore all three reference projects in parallel to understand their structure before planning.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How data flows (ingest, storage, retrieval)\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How file uploads work - what files, what format, how parsed\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth folder and authentik integration","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. What auth system is being used (Authentik)\n2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?\n3. Middleware - how is auth enforced on routes?\n4. Any frontend auth flow - login redirect, token handling, protected routes\n5. Environment variables related to auth\n6. Docker/deployment setup for the auth service itself\n7. Any example of how other apps integrate with this auth\n\nReport with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"payments.js","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"continue","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Launching parallel exploration of all three reference projects.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How data is ingested (look at /ingest route especially)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How file uploads work (what format, what processing happens)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth project structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. What authentication system is used (authentik integration details)\n3. How OAuth/OIDC flow works\n4. Any middleware or helper functions for protecting routes\n5. Session management approach\n6. How frontend handles auth state\n7. Any example of how other apps integrate with this auth system\n8. Docker setup and environment variables\n\nPlease read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now I have a complete picture of all three. Let me design the plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design combined app architecture","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:\n\n---\n\n## App 1: payments-logger (Node.js)\n- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI\n- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS\n- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage\n- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)\n- **Schema** (PostgreSQL via Prisma):\n - `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at\n - `tags` table: id, name, color — M2M with payments via `_PaymentToTag`\n - `users` table: id, username, hashed_password (this will be REMOVED)\n- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system\n- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance\n\n## App 2: dsk-uploader (Python/Flask)\n- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database\n- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5\n- **Auth**: None (open)\n- **CSV format** (DSK Bank Bulgarian format, columns):\n - `Дата` (date, DD.MM.YYYY)\n - `Вид на трансакцията` (transaction type, Bulgarian)\n - `Основание` (reason/description — contains card number regex: `^\\d{6}x{6}\\d{4}$`)\n - `Дебит BGN` (debit amount, may be empty)\n - `Кредит BGN` (credit amount, may be empty)\n - `Наредител/Получател` (orderer/recipient name)\n - `Номер сметка на наредителя / получателя` (account number)\n- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers\n- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)\n\n## App 3: auth (Authentik)\n- **Mode**: Proxy mode via NPM (forward auth)\n- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:\n - `X-authentik-username` \n - `X-authentik-email`\n - `X-authentik-groups`\n- **No code integration needed** in the app itself — just trust these headers from NPM\n- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`\n\n---\n\n## What the New Combined App Must Do\n\n1. **Single PostgreSQL database** for all transactions\n2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST\n3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema\n4. **Unified UI** — show all payments in one table regardless of source\n5. **Source indicator** in UI — badge showing \"INGEST\", \"UPLOAD\", or \"BOTH\" (if duplicate detection added)\n6. **Source filter** in FilterBar — filter by All/Ingest/Upload\n7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM\n8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination\n9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL\n\n---\n\n## Technical Constraints\n\n- Keep Node.js backend (not Python) — extend payments-logger's stack\n- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)\n- File upload: use `multer` npm middleware\n- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)\n- Add `source` enum field (INGEST/UPLOAD) to payments schema\n- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is\n- Remove `users` table from schema\n\n---\n\n## Please Design\n\n1. Complete folder structure for the new app (suggest name: \"finance-hub\" or similar — note this is a placeholder, user will confirm)\n2. Prisma schema with new fields (`source`, `currency`)\n3. All backend API routes\n4. CSV parser design in Node.js (port of the Python logic)\n5. Authentik auth middleware\n6. Frontend component structure (React) — what's reused from payments-logger, what's new\n7. Docker Compose setup\n8. Environment variables needed\n9. Step-by-step implementation order\n10. Verification checklist\n\nBe specific about file paths and code structure. This will be used to write actual implementation code.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good plan. Let me ask the one thing I need before writing the final plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"AskUserQuestion","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"OUT","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"User has answered your questions: \"What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding.\"=\"finance-hub\". You can now continue with the user's answers in mind.","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Writing the final plan now.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"326 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# finance-hub — Implementation Plan\n\n## Context\n\nTwo separate finance apps exist as references and will be retired:\n- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.\n- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.\n\nThe new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).\n\n---\n\n## Tech Stack\n\n| Layer | Choice | Rationale |\n|-------|--------|-----------|\n| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |\n| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |\n| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |\n| Database | PostgreSQL 16 | Same as payments-logger |\n| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |\n| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |\n| Container | Docker Compose | Same pattern as both reference apps |\n\n**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage. \n**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references. \n**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.\n\n---\n\n## Folder Structure\n\n```\n/volume2/docker/finance/finance-hub/\n├── docker-compose.yml\n├── .env\n├── .env.example\n├── .gitignore\n├── backend/\n│ ├── Dockerfile\n│ ├── package.json\n│ ├── prisma/\n│ │ ├── schema.prisma\n│ │ └── migrations/\n│ │ ├── migration_lock.toml\n│ │ └── 20260508_init/\n│ │ └── migration.sql\n│ └── src/\n│ ├── index.js ← entry point (Authentik middleware wired here)\n│ ├── auth.js ← Authentik header middleware (replaces JWT auth)\n│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)\n│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)\n│ └── routes/\n│ ├── payments.js ← existing routes + source/currency additions\n│ └── upload.js ← NEW: POST /api/upload/csv\n└── frontend/\n ├── Dockerfile\n ├── package.json\n ├── vite.config.js\n ├── tailwind.config.js\n ├── postcss.config.js\n ├── index.html\n └── src/\n ├── main.jsx ← remove AuthProvider wrapper\n ├── index.css\n ├── App.jsx ← remove auth state, add Upload tab toggle\n └── components/\n ├── FilterBar.jsx ← add source filter select\n ├── PaymentTable.jsx ← add Source badge column + currency display\n ├── PaymentCard.jsx ← minor source badge addition\n ├── PaymentList.jsx ← unchanged\n └── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI\n```\n\n---\n\n## Database Schema (Prisma)\n\nFile: `backend/prisma/schema.prisma`\n\n```prisma\ngenerator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status { UNPROCESSED SENT SKIPPED }\nenum Source { INGEST UPLOAD }\n```\n\n**Key decisions:**\n- No `User` model — Authentik owns identity.\n- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.\n- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.\n- `balance` is always null for CSV rows (DSK export does not include running balance).\n- Fresh consolidated migration — no data migration from reference apps required.\n\n---\n\n## API Routes\n\n| Method | Path | Auth | Description |\n|--------|------|------|-------------|\n| GET | /api/health | public | Health check |\n| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |\n| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |\n| GET | /api/payments/meta/tags | required | All tags |\n| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |\n| GET | /api/payments/:id | required | Single payment |\n| PATCH | /api/payments/:id | required | Update status |\n| DELETE | /api/payments/:id | required | Delete |\n| POST | /api/payments/:id/send | required | Send notification |\n| POST | /api/payments/:id/skip | required | Skip |\n| POST | /api/payments/:id/tags | required | Add/upsert tag |\n| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |\n| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |\n\n---\n\n## Key Implementation Details\n\n### auth.js (replaces entire old auth module)\n```js\nconst PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n const username = req.headers['x-authentik-username'];\n if (!username) return res.status(401).json({ error: 'Unauthorized' });\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),\n };\n next();\n}\nmodule.exports = { authentikMiddleware };\n```\n\n### csvParser.js (port of dskuploader.py)\n- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8\n- `csv-parse` parses the decoded text with `columns: true`\n- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`\n- Card extraction: regex `/^\\d{6}x{6}\\d{4}$/` on first token of `Основание`\n- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`\n- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`\n- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`\n\n### payments.js changes from payments-logger\n1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call\n2. Add `source` to the `GET /` where clause filter\n3. Add `sources` to `meta/filters` response\n4. Currency-aware amount formatting in notification message\n5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)\n\n### upload.js (new)\n- `multer` memory storage, max 10 files × 10 MB\n- Calls `parseDskCsv(buffer)` per file\n- Upserts tags via `prisma.tag.upsert` then connects\n- Returns `{ imported, skipped, errors, payments[] }`\n\n### Frontend changes\n- **Delete**: `auth.js`, `AuthProvider.jsx`\n- **main.jsx**: Remove `<AuthProvider>` wrapper\n- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add \"Payments\" / \"Upload CSV\" tab toggle\n- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols\n- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell\n- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`\n\n---\n\n## Docker Compose\n\n```yaml\nservices:\n db:\n image: postgres:16-alpine\n environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: ${DB_PASSWORD}, POSTGRES_DB: finance_hub }\n volumes: [pgdata:/var/lib/postgresql/data]\n healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }\n\n backend:\n build: ./backend\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports: [\"${BACKEND_PORT:-3001}:3001\"]\n depends_on: { db: { condition: service_healthy } }\n\n frontend:\n build: ./frontend\n ports: [\"${FRONTEND_PORT:-5175}:5173\"]\n depends_on: [backend]\n\nvolumes: { pgdata: }\n```\n\n**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.\n\n---\n\n## Environment Variables (.env)\n\n```bash\nDB_PASSWORD=change_me\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\nTZ=Europe/Sofia\nBACKEND_PORT=3001\nFRONTEND_PORT=5175\n```\n\nRemoved vs payments-logger: `JWT_SECRET`, `JWT_EXPIRE_MINUTES`.\n\n---\n\n## Implementation Order\n\n1. Create folder structure and write `docker-compose.yml`, `.env.example`, `.gitignore`\n2. Write `backend/prisma/schema.prisma` and migration SQL\n3. Write `backend/package.json` (add `csv-parse`, `iconv-lite`, `multer`; remove `bcryptjs`, `jose`)\n4. Write `backend/Dockerfile`\n5. Write `backend/src/auth.js` (Authentik middleware)\n6. Copy `backend/src/parser.js` verbatim from payments-logger\n7. Write `backend/src/csvParser.js` (Python port)\n8. Write `backend/src/routes/upload.js`\n9. Write `backend/src/routes/payments.js` (from payments-logger + 5 changes listed above)\n10. Write `backend/src/index.js`\n11. Copy frontend base from payments-logger; delete `auth.js` + `AuthProvider.jsx`\n12. Update `main.jsx`, `App.jsx`, `FilterBar.jsx`, `PaymentTable.jsx`\n13. Write `frontend/src/components/UploadPanel.jsx`\n14. Update `frontend/vite.config.js`\n15. `docker compose build && docker compose up -d`\n16. Run verification checklist\n\n---\n\n## Verification\n\n**Schema**\n- `payments` table has `source`, `currency`, `debit_bgn`, `credit_bgn`, `transaction_type`, `payer_account`\n- No `users` table; `Source` enum exists\n\n**Auth**\n- `GET /api/payments` → 401 without `x-authentik-username` header\n- `POST /api/payments/ingest` → 201 without any header\n- `curl -H \"x-authentik-username: test\" localhost:3001/api/payments` → 200\n\n**SMS Ingest**\n- DSK POS SMS → `source=INGEST`, `currency=EUR`, correct amount/card/recipient\n- Apple Wallet structured body → `type=WALLET`, `source=INGEST`\n- Rate limiter → 429 after 200 req/min\n\n**CSV Upload**\n- Single DSK CSV → rows with `source=UPLOAD`, `currency=BGN`\n- Multiple CSVs in one request → all merged\n- `ТРАНСФЕР СОБСТВЕНИ СМЕТКИ` rows counted in `skipped`, not imported\n- Card regex match from `Основание` column\n- Auto-tags applied (ЗАПЛАТА→Salary, LIDL→Groceries)\n- cp1251 file imports correctly\n\n**UI**\n- Source badge visible in payment table (SMS indigo, CSV emerald)\n- Source dropdown in FilterBar filters correctly\n- Amount shows correct currency per row\n- Upload Panel: drag-and-drop works, result summary shows counts\n- Logout redirects to Authentik sign_out\n- No login form shown (Authentik handles it at NPM level)\n- Tags, send, skip, delete all still work\n\n## Reference Files\n\n- `/volume2/docker/finance/payments-logger/backend/src/routes/payments.js`\n- `/volume2/docker/finance/payments-logger/backend/src/parser.js`\n- `/volume2/docker/finance/payments-logger/backend/src/index.js`\n- `/volume2/docker/finance/payments-logger/backend/src/auth.js`\n- `/volume2/docker/finance/payments-logger/backend/prisma/schema.prisma`\n- `/volume2/docker/finance/payments-logger/frontend/src/App.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/PaymentTable.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/FilterBar.jsx`\n- `/volume2/docker/finance/dsk-uploader/dskuploader.py`\n- `/volume2/docker/finance/auth/docker-compose.yml`","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Claude’s Plan","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Stayed in plan mode","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good question. Here's the full breakdown:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Backend Tech Stack — Options","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Backend Tech Stack — Options","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Why:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"payments-logger is already Node.js/Express/Prisma. The new app is 80% payments-logger with CSV upload added on top. Keeping the same stack means:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"verbatim, zero rewrite","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy the entire","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"routes/payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with minimal edits","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Same Prisma schema workflow, same migrations, same Docker image","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The CSV parsing logic (the only Python-specific thing) ports cleanly to","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"csv-parse","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— it's just regex + string manipulation, nothing pandas-specific","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Trade-off:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Have to port the Python CSV parsing to JS. It's ~150 lines and mostly string manipulation — straightforward.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option B: Python + FastAPI + SQLAlchemy","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option B: Python + FastAPI + SQLAlchemy","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rewrite everything in Python. dsk-uploader is Python, so CSV parsing is already done.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep the dsk-uploader CSV logic as-is (no porting). Python has better data science libraries if you later add analytics.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Lose the entire payments-logger backend (routes, parser, Prisma schema) — full rewrite. FastAPI + SQLAlchemy is a different mental model than Express + Prisma. Frontend stays React anyway, so the stack split doesn't simplify anything.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"More work overall, gains almost nothing.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep Node.js as the main API, add a separate Python FastAPI service just for CSV parsing. They share the DB.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Zero porting — Python CSV code used as-is.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two backend services to maintain, deploy, and keep in sync. Inter-service HTTP calls. Two Dockerfiles. For ~150 lines of CSV logic, this is massively over-engineered.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Not worth it.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Extend dsk-uploader into a full payments app.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pandas for CSV, no porting.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Jinja2 templates instead of React (or add React separately). Would need to reimplement the entire payments-logger (SMS parser, notification system, tag management, pagination/filtering). Flask's Jinja templating is far less capable than the existing React UI. The React frontend is the stronger UI foundation.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Worst of all options — rebuild the harder parts (UI, SMS parser, notification) for no gain.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Summary","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Summary","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"CSV porting effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"App rewrite effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Result 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Everything else in the plan reuses payments-logger code directly. That's why Node.js is the clear winner here.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Want to adjust the stack, or shall I proceed with Option A?","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ok sounds good. Implement all you suggested","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Starting implementation. Let me first read all the reference files I'll need to copy from.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"payments.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"App.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"App.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"FilterBar.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"FilterBar.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentTable.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentTable.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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payments-logger.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.css","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.css","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"vite.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"vite.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"tailwind.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"tailwind.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"postcss.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"postcss.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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components.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentCard.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentCard.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentList.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentList.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"schema.prisma","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"schema.prisma","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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Let me set up the todo list and start building.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create finance-hub directory structure","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"mkdir -p /volume2/docker/finance/finance-hub/backend/src/routes \\\n /volume2/docker/finance/finance-hub/backend/prisma/migrations/20260508_init \\\n /volume2/docker/finance/finance-hub/frontend/src/components && echo \"done\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":24,"on_screen":false,"help_text":"Copy code","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"OUT","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"done","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"docker-compose.yml","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"docker-compose.yml","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"45 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"version: '3.8'\n\nservices:\n db:\n image: postgres:16-alpine\n restart: unless-stopped\n environment:\n POSTGRES_USER: finance\n POSTGRES_PASSWORD: ${DB_PASSWORD}\n POSTGRES_DB: finance_hub\n volumes:\n - pgdata:/var/lib/postgresql/data\n healthcheck:\n test: [\"CMD-SHELL\", \"pg_isready -U finance -d finance_hub\"]\n interval: 5s\n timeout: 5s\n retries: 5\n\n backend:\n build: ./backend\n restart: unless-stopped\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports:\n - \"${BACKEND_PORT:-3001}:3001\"\n depends_on:\n db:\n condition: service_healthy\n\n frontend:\n build: ./frontend\n restart: unless-stopped\n ports:\n - \"${FRONTEND_PORT:-5175}:5173\"\n depends_on:\n - backend\n\nvolumes:\n pgdata:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".env.example","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".env.example","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"15 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Database\nDB_PASSWORD=change_me_strong_password\n\n# Notifier service (for SMS payment notifications)\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\n\n# Timezone (used by SMS parser for Bulgarian bank timestamps)\nTZ=Europe/Sofia\n\n# Ports (optional — defaults shown)\nBACKEND_PORT=3001\nFRONTEND_PORT=5175","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".gitignore","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".gitignore","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"5 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env\nnode_modules/\ndist/\n*.log","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"schema.prisma","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"schema.prisma","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"54 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"generator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status {\n UNPROCESSED\n SENT\n SKIPPED\n}\n\nenum Source {\n INGEST\n UPLOAD\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration.sql","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration.sql","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"55 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- CreateEnum\nCREATE TYPE \"Status\" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');\nCREATE TYPE \"Source\" AS ENUM ('INGEST', 'UPLOAD');\n\n-- CreateTable\nCREATE TABLE \"payments\" (\n \"id\" SERIAL PRIMARY KEY,\n \"raw_message\" TEXT NOT NULL,\n \"date\" TIMESTAMP(3),\n \"type\" TEXT,\n \"card\" TEXT,\n \"recipient\" TEXT,\n \"amount\" DOUBLE PRECISION,\n \"currency\" TEXT DEFAULT 'EUR',\n \"balance\" DOUBLE PRECISION,\n \"source\" \"Source\" NOT NULL DEFAULT 'INGEST',\n \"status\" \"Status\" NOT NULL DEFAULT 'UNPROCESSED',\n \"notified_at\" TIMESTAMP(3),\n \"notify_phone\" TEXT,\n \"debit_bgn\" DOUBLE PRECISION,\n \"credit_bgn\" DOUBLE PRECISION,\n \"transaction_type\" TEXT,\n \"payer_account\" TEXT,\n \"created_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,\n \"updated_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP\n);\n\n-- CreateTable\nCREATE TABLE \"tags\" (\n \"id\" SERIAL PRIMARY KEY,\n \"name\" TEXT NOT NULL,\n \"color\" TEXT NOT NULL DEFAULT '#6b7280'\n);\n\n-- CreateUniqueIndex\nCREATE UNIQUE INDEX \"tags_name_key\" ON \"tags\"(\"name\");\n\n-- CreateTable (M2M join)\nCREATE TABLE \"_PaymentToTag\" (\n \"A\" INTEGER NOT NULL,\n \"B\" INTEGER NOT NULL,\n CONSTRAINT \"_PaymentToTag_AB_pkey\" PRIMARY KEY (\"A\", \"B\")\n);\n\nCREATE INDEX \"_PaymentToTag_B_index\" ON \"_PaymentToTag\"(\"B\");\n\n-- AddForeignKey\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_A_fkey\"\n FOREIGN KEY (\"A\") REFERENCES \"payments\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;\n\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_B_fkey\"\n FOREIGN KEY (\"B\") REFERENCES \"tags\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration_lock.toml","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration_lock.toml","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"4 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Please do not edit this file manually\n# It should be added in your version-control system (e.g., Git)\nprovider = \"postgresql\"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"26 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"{\n \"name\": \"finance-hub-backend\",\n \"version\": \"1.0.0\",\n \"main\": \"src/index.js\",\n \"scripts\": {\n \"start\": \"node src/index.js\",\n \"dev\": \"nodemon src/index.js\",\n \"prisma:generate\": \"prisma generate\",\n \"prisma:migrate\": \"prisma migrate deploy\"\n },\n \"dependencies\": {\n \"@prisma/client\": \"^5.22.0\",\n \"cors\": \"^2.8.5\",\n \"csv-parse\": \"^5.5.6\",\n \"express\": \"^4.21.1\",\n \"express-rate-limit\": \"^7.4.0\",\n \"iconv-lite\": \"^0.6.3\",\n \"morgan\": \"^1.10.0\",\n \"multer\": \"^1.4.5-lts.1\"\n },\n \"devDependencies\": {\n \"nodemon\": \"^3.1.7\",\n \"prisma\": \"^5.22.0\"\n }\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"18 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"FROM node:20-alpine\n\nRUN apk add --no-cache openssl\n\nWORKDIR /app\n\nCOPY package.json package-lock.json* ./\nRUN npm install\n\nCOPY prisma ./prisma\nRUN npx prisma generate\n\nCOPY src ./src\n\nEXPOSE 3001\n\nCMD [\"sh\", \"-c\", \"npx prisma migrate deploy && node src/index.js\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"auth.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"auth.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"27 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const PUBLIC_PATHS = new Set([\n '/api/health',\n '/api/payments/ingest',\n]);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n\n const username = req.headers['x-authentik-username'];\n if (!username) {\n return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });\n }\n\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '')\n .split(',')\n .map(g => g.trim())\n .filter(Boolean),\n };\n\n next();\n}\n\nmodule.exports = { authentikMiddleware };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"104 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/**\n * Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)\n *\n * Supported formats:\n *\n * POS / INTERNET / ECOM / P2P payment:\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.\n *\n * ATM withdrawal:\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.\n *\n * ATM utility payment (amount may include fee as AMOUNT/FEE):\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.\n */\n\nconst LOCAL_TZ = process.env.TZ || 'Europe/Sofia';\n\n/**\n * Convert a local-timezone date/time to a UTC Date object.\n * Uses Intl to resolve the actual UTC offset (DST-aware).\n */\nfunction localToUtc(year, month, day, hour, minute) {\n const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));\n\n const formatter = new Intl.DateTimeFormat('en-US', {\n timeZone: LOCAL_TZ,\n year: 'numeric', month: '2-digit', day: '2-digit',\n hour: '2-digit', minute: '2-digit', second: '2-digit',\n hour12: false,\n });\n\n const parts = {};\n formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });\n\n const localAtNaive = new Date(Date.UTC(\n parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),\n parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),\n ));\n\n const offsetMs = localAtNaive.getTime() - naive.getTime();\n return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);\n}\n\nfunction parsePaymentSms(message) {\n const result = {\n rawMessage: message,\n date: null,\n type: null,\n card: null,\n recipient: null,\n amount: null,\n balance: null,\n };\n\n // Date and time: \"Na DD/MM/YYYY v HH:MM\"\n const dateMatch = message.match(/Na (\\d{2})\\/(\\d{2})\\/(\\d{4}) v (\\d{2}):(\\d{2})/i);\n if (dateMatch) {\n const [, day, month, year, hour, minute] = dateMatch;\n result.date = localToUtc(\n parseInt(year), parseInt(month), parseInt(day),\n parseInt(hour), parseInt(minute),\n );\n }\n\n // Card mask: \"s karta 400915***4447\" or \"s karta 483890***7162\"\n const cardMatch = message.match(/s karta\\s+([\\d*]+)/i);\n if (cardMatch) {\n result.card = cardMatch[1];\n }\n\n // Transaction type: supports both prepositions\n // \"na POS\" / \"na ATM\" / \"na INTERNET\" etc. (payment)\n // \"ot ATM\" (withdrawal)\n const typeMatch = message.match(/(?:na|ot)\\s+(POS|ATM|INTERNET|ECOM|P2P)\\b/i);\n if (typeMatch) {\n result.type = typeMatch[1].toUpperCase();\n }\n\n // Recipient address: \"s adres: MERCHANT\" or \"s adres:MERCHANT\" (no space variant)\n const recipientMatch = message.match(/s adres:\\s*([^.]+)\\./i);\n if (recipientMatch) {\n result.recipient = recipientMatch[1].trim();\n }\n\n // Amount: handles both verbs and the AMOUNT/FEE suffix format\n // \"sa plateni 7.78 EUR\"\n // \"sa iztegleni 400.00 EUR\"\n // \"sa plateni 0.50 EUR/0.50 EUR\" → captures 0.50 (the charged amount, ignoring fee)\n const amountMatch = message.match(/sa (?:plateni|iztegleni)\\s+([\\d.,]+)\\s+[A-Z]{3}/i);\n if (amountMatch) {\n result.amount = parseFloat(amountMatch[1].replace(',', '.'));\n }\n\n // Balance: \"Nalichni: 2583.07 EUR.\"\n const balanceMatch = message.match(/Nalichni:\\s*([\\d.,]+)\\s+[A-Z]{3}/i);\n if (balanceMatch) {\n result.balance = parseFloat(balanceMatch[1].replace(',', '.'));\n }\n\n return result;\n}\n\nmodule.exports = { parsePaymentSms };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"csvParser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"csvParser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"175 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/**\n * DSK Bank CSV parser — Node.js port of dskuploader.py\n *\n * DSK Bank exports use Windows-1251 (cp1251) encoding.\n * Each row maps to a Payment record with source=UPLOAD, currency=BGN.\n */\n\nconst { parse } = require('csv-parse');\nconst iconv = require('iconv-lite');\n\nconst SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';\nconst CARD_REGEX = /^\\d{6}x{6}\\d{4}$/;\nconst POS_REGEX = /^\\s*ПЛАЩАНЕ\\s+НА\\s+ПОС\\s+\\d{2}\\.\\d{2}\\.\\d{4}\\s+\\d{2}:\\d{2}/;\n\nconst COL = {\n DATE: 'Дата',\n TYPE: 'Вид на трансакцията',\n REASON: 'Основание',\n DEBIT: 'Дебит BGN',\n CREDIT: 'Кредит BGN',\n PAYEE: 'Наредител/Получател',\n ACCT: 'Номер сметка на наредителя / получателя',\n};\n\nconst TAG_RULES = [\n ['reason', 'ЗАПЛАТА', 'Salary'],\n ['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],\n ['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],\n ['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],\n ['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],\n ['payee', 'VIVACOM', 'Subscriptions'],\n ['payee', 'Google', 'Subscriptions'],\n ['payee', 'SkyShowtime', 'Subscriptions'],\n ['payee', 'NETFLIX', 'Subscriptions'],\n ['payee', 'LUKOIL', 'Bills'],\n ['payee', 'CityGate', 'Bills'],\n ['payee', 'CBA', 'Groceries'],\n ['payee', 'FANTASTICO', 'Groceries'],\n ['payee', 'LIDL', 'Groceries'],\n];\n\nfunction parseNum(val) {\n if (val == null || val === '') return null;\n if (typeof val === 'number') return isNaN(val) ? null : val;\n const s = String(val).trim().replace(/\\xa0/g, '').replace(/ /g, '').replace(',', '.');\n const n = parseFloat(s);\n return isNaN(n) ? null : n;\n}\n\nfunction parseDate(val) {\n if (!val) return null;\n const s = String(val).trim();\n const m = s.match(/^(\\d{2})\\.(\\d{2})\\.(\\d{4})$/);\n if (m) {\n return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));\n }\n return null;\n}\n\nfunction processReasonAndCard(reason) {\n if (!reason || typeof reason !== 'string') return { reason: '', card: null };\n\n const parts = reason.trim().split(' ');\n let card = null;\n let cleanReason = reason.trim();\n\n if (parts[0] && CARD_REGEX.test(parts[0])) {\n card = parts[0];\n cleanReason = parts.slice(1).join(' ').trim();\n }\n\n if (POS_REGEX.test(cleanReason)) {\n const posParts = cleanReason.split('<br/>');\n try {\n const dateTime = posParts[0].split('ПОС ')[1];\n cleanReason = `POS PAYMENT ${dateTime}`;\n } catch (_) { /* keep original */ }\n }\n\n return { reason: cleanReason.replace(/\\s+/g, ' ').trim(), card };\n}\n\nfunction generateTags(fields) {\n const tags = new Set();\n for (const [field, keyword, tagName] of TAG_RULES) {\n if ((fields[field] || '').includes(keyword)) {\n tags.add(tagName);\n }\n }\n return Array.from(tags);\n}\n\nfunction processRow(row) {\n const transactionType = (row[COL.TYPE] || '').trim();\n if (transactionType === SKIP_TYPE) return null;\n\n const { reason, card } = processReasonAndCard(row[COL.REASON]);\n const payee = (row[COL.PAYEE] || '').trim();\n const payerAccount = (row[COL.ACCT] || '').trim();\n const debitBgn = parseNum(row[COL.DEBIT]);\n const creditBgn = parseNum(row[COL.CREDIT]);\n const date = parseDate(row[COL.DATE]);\n\n const autoTags = generateTags({ reason, transactionType, payee, debitBgn, creditBgn });\n\n const amount = debitBgn ?? creditBgn ?? null;\n\n const rawMessage = [\n row[COL.DATE] && `Date: ${row[COL.DATE]}`,\n transactionType && `Type: ${transactionType}`,\n payee && `Payee: ${payee}`,\n debitBgn != null && `Debit: ${debitBgn} BGN`,\n creditBgn != null && `Credit: ${creditBgn} BGN`,\n ].filter(Boolean).join(' | ');\n\n return {\n rawMessage,\n date,\n type: null,\n card,\n recipient: payee || null,\n amount,\n currency: 'BGN',\n balance: null,\n source: 'UPLOAD',\n debitBgn,\n creditBgn,\n transactionType: transactionType || null,\n payerAccount: payerAccount || null,\n autoTags,\n };\n}\n\n/**\n * Parse a Buffer containing a DSK Bank CSV (cp1251 or UTF-8).\n * Returns { rows, skipped, errors }.\n */\nasync function parseDskCsv(buffer) {\n // Try cp1251 first (DSK Bank export encoding), fall back to UTF-8\n let text = iconv.decode(buffer, 'cp1251');\n if (!text.includes(COL.DATE)) {\n text = buffer.toString('utf-8');\n }\n\n return new Promise((resolve, reject) => {\n const rows = [];\n const errors = [];\n let skipped = 0;\n\n const parser = parse(text, {\n columns: true,\n skip_empty_lines: true,\n trim: true,\n relax_column_count: true,\n });\n\n parser.on('readable', () => {\n let record;\n while ((record = parser.read()) !== null) {\n try {\n const row = processRow(record);\n if (row === null) { skipped++; } else { rows.push(row); }\n } catch (err) {\n errors.push(err.message);\n }\n }\n });\n\n parser.on('error', reject);\n parser.on('end', () => resolve({ rows, skipped, errors }));\n });\n}\n\nmodule.exports = { parseDskCsv };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"39 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst cors = require('cors');\nconst morgan = require('morgan');\nconst rateLimit = require('express-rate-limit');\nconst { authentikMiddleware } = require('./auth');\nconst paymentsRouter = require('./routes/payments');\nconst uploadRouter = require('./routes/upload');\n\nconst app = express();\nconst PORT = process.env.PORT || 3001;\n\napp.use(cors());\napp.use(express.json({ limit: '16kb' }));\napp.use(morgan('combined'));\n\n// Rate-limit the public ingest endpoint before auth middleware\nconst ingestLimiter = rateLimit({\n windowMs: 60 * 1000,\n max: 200,\n standardHeaders: true,\n legacyHeaders: false,\n message: { error: 'Too many requests, slow down' },\n});\napp.use('/api/payments/ingest', ingestLimiter);\n\n// Authentik header auth (skips /api/health and /api/payments/ingest)\napp.use(authentikMiddleware);\n\napp.get('/api/health', (_req, res) => {\n res.json({ status: 'ok', timestamp: new Date().toISOString() });\n});\n\napp.use('/api/payments', paymentsRouter);\napp.use('/api/upload', uploadRouter);\n\napp.listen(PORT, '0.0.0.0', () => {\n console.log(`Finance Hub API running on port ${PORT}`);\n});","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"payments.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"399 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst { PrismaClient } = require('@prisma/client');\nconst { parsePaymentSms } = require('../parser');\n\nconst router = express.Router();\nconst prisma = new PrismaClient();\n\nconst NOTIFIER_URL = process.env.NOTIFIER_URL;\nconst NOTIFIER_CHANNEL = process.env.NOTIFIER_CHANNEL || 'viber';\nconst DEFAULT_PHONE = process.env.NOTIFY_DEFAULT_PHONE;\n\n// ── Helpers ───────────────────────────────────────────────────────────────────\n\nfunction parseId(raw) {\n const id = parseInt(raw, 10);\n return Number.isFinite(id) ? id : null;\n}\n\nfunction formatNotifyMessage(payment) {\n const currency = payment.currency || 'EUR';\n const parts = [];\n if (payment.amount != null) parts.push(`Amount: ${payment.amount.toFixed(2)} ${currency}`);\n if (payment.recipient) parts.push(`At: ${payment.recipient}`);\n if (payment.balance != null) parts.push(`Balance: ${payment.balance.toFixed(2)} ${currency}`);\n if (payment.date) parts.push(`Date: ${new Date(payment.date).toLocaleString('en-GB')}`);\n return parts.join('\\n');\n}\n\nasync function sendNotification(payment) {\n if (!NOTIFIER_URL) {\n console.warn('[NOTIFY] NOTIFIER_URL not set — skipping notification');\n return;\n }\n\n const phone = payment.notifyPhone || DEFAULT_PHONE;\n if (!phone) {\n console.warn('[NOTIFY] No phone number for payment #' + payment.id + ' and NOTIFY_DEFAULT_PHONE not set');\n return;\n }\n\n const body = {\n phone,\n notification: NOTIFIER_CHANNEL,\n message: formatNotifyMessage(payment),\n };\n\n const res = await fetch(NOTIFIER_URL, {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify(body),\n });\n\n if (!res.ok) {\n const text = await res.text().catch(() => '');\n throw new Error(`Notifier responded ${res.status}: ${text}`);\n }\n}\n\n// ── Ingest a payment (public — no auth) ──────────────────────────────────────\n//\n// Two modes:\n//\n// SMS mode (default):\n// { \"message\": \"<raw SMS text>\", \"notifyPhone\": \"...\" }\n//\n// Structured mode (Apple Wallet / manual):\n// { \"ingestMode\": \"apple_wallet\", \"amount\": 7.78, \"recipient\": \"Apple Store\",\n// \"type\": \"WALLET\", \"card\": \"••••4447\", \"date\": \"2026-02-22T10:30:00Z\" }\n//\nrouter.post('/ingest', async (req, res) => {\n try {\n const { message, notifyPhone, ingestMode } = req.body;\n\n let data;\n\n if (ingestMode === 'apple_wallet' || (!message && req.body.amount != null)) {\n // ── Structured / Apple Wallet mode ──────────────────────────────────────\n const { amount, recipient, type, card, date, balance } = req.body;\n if (amount == null || !recipient) {\n return res.status(400).json({ error: 'amount and recipient are required for structured ingest' });\n }\n\n const rawMessage = [\n `Source: ${ingestMode || 'structured'}`,\n `Amount: ${amount}`,\n recipient && `Recipient: ${recipient}`,\n type && `Type: ${type}`,\n card && `Card: ${card}`,\n ].filter(Boolean).join(' | ');\n\n data = {\n rawMessage,\n date: date ? new Date(date) : new Date(),\n type: type || 'WALLET',\n card: card || null,\n recipient,\n amount: parseFloat(amount),\n currency: 'EUR',\n balance: balance != null ? parseFloat(balance) : null,\n source: 'INGEST',\n notifyPhone: notifyPhone || null,\n };\n\n } else {\n // ── SMS mode ─────────────────────────────────────────────────────────────\n if (!message) {\n return res.status(400).json({ error: 'message is required' });\n }\n if (typeof message !== 'string' || message.length > 2000) {\n return res.status(400).json({ error: 'message must be a string under 2000 characters' });\n }\n\n const parsed = parsePaymentSms(message);\n data = {\n rawMessage: parsed.rawMessage,\n date: parsed.date,\n type: parsed.type,\n card: parsed.card,\n recipient: parsed.recipient,\n amount: parsed.amount,\n currency: 'EUR',\n balance: parsed.balance,\n source: 'INGEST',\n notifyPhone: notifyPhone || null,\n };\n }\n\n const payment = await prisma.payment.create({\n data,\n include: { tags: true },\n });\n\n res.status(201).json(payment);\n } catch (err) {\n console.error('Ingest error:', err);\n res.status(500).json({ error: 'Failed to ingest payment' });\n }\n});\n\n// ── List payments with filtering ──────────────────────────────────────────────\nrouter.get('/', async (req, res) => {\n try {\n const {\n status,\n type,\n tag,\n source,\n recipient,\n dateFrom,\n dateTo,\n search,\n sortBy = 'createdAt',\n sortDir = 'desc',\n page = 1,\n } = req.query;\n\n const limit = Math.min(parseInt(req.query.limit, 10) || 50, 200);\n\n const where = {};\n\n if (status) where.status = status;\n if (type) where.type = type;\n if (source) where.source = source;\n if (recipient) where.recipient = { contains: recipient, mode: 'insensitive' };\n if (tag) where.tags = { some: { name: tag } };\n if (search) {\n where.OR = [\n { rawMessage: { contains: search, mode: 'insensitive' } },\n { recipient: { contains: search, mode: 'insensitive' } },\n ];\n }\n if (dateFrom || dateTo) {\n where.date = {};\n if (dateFrom) where.date.gte = new Date(dateFrom);\n if (dateTo) where.date.lte = new Date(dateTo);\n }\n\n const allowedSortFields = ['date', 'amount', 'balance', 'recipient', 'type', 'source', 'createdAt', 'status'];\n const orderField = allowedSortFields.includes(sortBy) ? sortBy : 'createdAt';\n const orderDir = sortDir === 'asc' ? 'asc' : 'desc';\n\n const skip = (parseInt(page, 10) - 1) * limit;\n\n const [payments, total] = await Promise.all([\n prisma.payment.findMany({\n where,\n include: { tags: true },\n orderBy: { [orderField]: orderDir },\n skip,\n take: limit,\n }),\n prisma.payment.count({ where }),\n ]);\n\n res.json({ payments, total, page: parseInt(page, 10), limit });\n } catch (err) {\n console.error('List error:', err);\n res.status(500).json({ error: 'Failed to list payments' });\n }\n});\n\n// ── Get filter options ────────────────────────────────────────────────────────\nrouter.get('/meta/filters', async (_req, res) => {\n try {\n const [types, recipients, tags, sources] = await Promise.all([\n prisma.payment.findMany({ distinct: ['type'], select: { type: true }, where: { type: { not: null } } }),\n prisma.payment.findMany({ distinct: ['recipient'], select: { recipient: true }, where: { recipient: { not: null } } }),\n prisma.tag.findMany({ orderBy: { name: 'asc' } }),\n prisma.payment.findMany({ distinct: ['source'], select: { source: true } }),\n ]);\n\n res.json({\n types: types.map(t => t.type),\n recipients: recipients.map(r => r.recipient),\n tags,\n sources: sources.map(s => s.source),\n });\n } catch (err) {\n res.status(500).json({ error: 'Failed to get filters' });\n }\n});\n\n// ── Get all tags ──────────────────────────────────────────────────────────────\nrouter.get('/meta/tags', async (_req, res) => {\n try {\n const tags = await prisma.tag.findMany({ orderBy: { name: 'asc' } });\n res.json(tags);\n } catch (err) {\n res.status(500).json({ error: 'Failed to list tags' });\n }\n});\n\n// ── Get single payment ────────────────────────────────────────────────────────\nrouter.get('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({\n where: { id },\n include: { tags: true },\n });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n res.json(payment);\n } catch (err) {\n console.error('Get error:', err);\n res.status(500).json({ error: 'Failed to get payment' });\n }\n});\n\n// ── Update payment metadata (status) ─────────────────────────────────────────\nrouter.patch('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const { status } = req.body;\n const data = {};\n\n if (status) {\n const validStatuses = ['UNPROCESSED', 'SENT', 'SKIPPED'];\n if (!validStatuses.includes(status)) {\n return res.status(400).json({ error: `Invalid status. Must be one of: ${validStatuses.join(', ')}` });\n }\n data.status = status;\n }\n\n if (Object.keys(data).length === 0) {\n return res.status(400).json({ error: 'No valid fields to update' });\n }\n\n const updated = await prisma.payment.update({\n where: { id },\n data,\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n if (err.code === 'P2025') return res.status(404).json({ error: 'Not found' });\n console.error('Update error:', err);\n res.status(500).json({ error: 'Failed to update payment' });\n }\n});\n\n// ── Delete payment ───────────────────────────────────────────────────────────\nrouter.delete('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n await prisma.payment.delete({ where: { id } });\n res.json({ success: true });\n } catch (err) {\n if (err.code === 'P2025') return res.status(404).json({ error: 'Not found' });\n console.error('Delete error:', err);\n res.status(500).json({ error: 'Failed to delete payment' });\n }\n});\n\n// ── Send notification (mark as SENT + call notifier service) ─────────────────\nrouter.post('/:id/send', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({ where: { id } });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n if (payment.status !== 'UNPROCESSED') {\n return res.status(409).json({ error: `Payment is already ${payment.status.toLowerCase()}` });\n }\n\n await sendNotification(payment);\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { status: 'SENT', notifiedAt: new Date() },\n include: { tags: true },\n });\n\n res.json(updated);\n } catch (err) {\n console.error('Send error:', err);\n res.status(500).json({ error: 'Failed to send notification' });\n }\n});\n\n// ── Skip notification (mark as SKIPPED) ──────────────────────────────────────\nrouter.post('/:id/skip', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({ where: { id } });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n if (payment.status !== 'UNPROCESSED') {\n return res.status(409).json({ error: `Payment is already ${payment.status.toLowerCase()}` });\n }\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { status: 'SKIPPED' },\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n console.error('Skip error:', err);\n res.status(500).json({ error: 'Failed to skip payment' });\n }\n});\n\n// ── Add tag to payment ────────────────────────────────────────────────────────\nrouter.post('/:id/tags', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const { name, color } = req.body;\n if (!name) return res.status(400).json({ error: 'tag name is required' });\n\n const tag = await prisma.tag.upsert({\n where: { name },\n update: {},\n create: { name, color: color || '#6b7280' },\n });\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { tags: { connect: { id: tag.id } } },\n include: { tags: true },\n });\n\n res.json(updated);\n } catch (err) {\n console.error('Tag error:', err);\n res.status(500).json({ error: 'Failed to add tag' });\n }\n});\n\n// ── Remove tag from payment ───────────────────────────────────────────────────\nrouter.delete('/:id/tags/:tagId', async (req, res) => {\n const id = parseId(req.params.id);\n const tagId = parseId(req.params.tagId);\n if (id === null || tagId === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const updated = await prisma.payment.update({\n where: { id },\n data: { tags: { disconnect: { id: tagId } } },\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n console.error('Remove tag error:', err);\n res.status(500).json({ error: 'Failed to remove tag' });\n }\n});\n\nmodule.exports = router;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"upload.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"upload.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"89 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst multer = require('multer');\nconst { PrismaClient } = require('@prisma/client');\nconst { parseDskCsv } = require('../csvParser');\n\nconst router = express.Router();\nconst prisma = new PrismaClient();\n\nconst upload = multer({\n storage: multer.memoryStorage(),\n limits: { fileSize: 10 * 1024 * 1024, files: 10 },\n fileFilter: (_req, file, cb) => {\n if (file.mimetype === 'text/csv' || file.originalname.toLowerCase().endsWith('.csv')) {\n cb(null, true);\n } else {\n cb(new Error('Only CSV files are accepted'));\n }\n },\n});\n\n// POST /api/upload/csv\n// Accepts 1-10 CSV files, parses them, stores to DB with source=UPLOAD.\n// Returns { imported, skipped, errors, payments[] }\nrouter.post('/csv', upload.array('files', 10), async (req, res) => {\n if (!req.files || req.files.length === 0) {\n return res.status(400).json({ error: 'No files uploaded' });\n }\n\n const allRows = [];\n const allErrors = [];\n let totalSkipped = 0;\n\n for (const file of req.files) {\n try {\n const { rows, skipped, errors } = await parseDskCsv(file.buffer);\n allRows.push(...rows);\n totalSkipped += skipped;\n allErrors.push(...errors.map(e => `${file.originalname}: ${e}`));\n } catch (err) {\n allErrors.push(`${file.originalname}: ${err.message}`);\n }\n }\n\n if (allRows.length === 0) {\n return res.status(422).json({\n error: 'No importable rows found',\n skipped: totalSkipped,\n errors: allErrors,\n });\n }\n\n const created = [];\n\n for (const row of allRows) {\n const { autoTags, ...paymentData } = row;\n try {\n const tagConnects = [];\n for (const tagName of autoTags) {\n const tag = await prisma.tag.upsert({\n where: { name: tagName },\n update: {},\n create: { name: tagName, color: '#6b7280' },\n });\n tagConnects.push({ id: tag.id });\n }\n\n const payment = await prisma.payment.create({\n data: {\n ...paymentData,\n ...(tagConnects.length ? { tags: { connect: tagConnects } } : {}),\n },\n include: { tags: true },\n });\n created.push(payment);\n } catch (err) {\n allErrors.push(`Row insert failed: ${err.message}`);\n }\n }\n\n res.status(201).json({\n imported: created.length,\n skipped: totalSkipped,\n errors: allErrors,\n payments: created,\n });\n});\n\nmodule.exports = router;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now writing all frontend config files:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"24 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"{\n \"name\": \"finance-hub-frontend\",\n \"version\": \"1.0.0\",\n \"type\": \"module\",\n \"scripts\": {\n \"dev\": \"vite\",\n \"build\": \"vite build\",\n \"preview\": \"vite preview\"\n },\n \"dependencies\": {\n \"lucide-react\": \"^0.460.0\",\n \"react\": \"^18.3.1\",\n \"react-dom\": \"^18.3.1\"\n },\n \"devDependencies\": {\n \"@types/react\": \"^18.3.12\",\n \"@vitejs/plugin-react\": \"^4.3.4\",\n \"autoprefixer\": \"^10.4.20\",\n \"postcss\": \"^8.4.49\",\n \"tailwindcss\": \"^3.4.15\",\n \"vite\": \"^6.0.1\"\n }\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"FROM node:20-alpine\n\nWORKDIR /app\n\nCOPY package.json package-lock.json* ./\nRUN npm install\n\nCOPY . .\n\nEXPOSE 5173\n\nCMD [\"npm\", \"run\", \"dev\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"vite.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"vite.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"18 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import { defineConfig } from 'vite';\nimport react from '@vitejs/plugin-react';\n\nexport default defineConfig({\n plugins: [react()],\n server: {\n host: '0.0.0.0',\n port: 5173,\n allowedHosts: ['finance-hub.lakylak.xyz'],\n proxy: {\n '/api': {\n target: 'http://backend:3001',\n changeOrigin: true,\n },\n },\n },\n});","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"tailwind.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"tailwind.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"12 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/** @type {import('tailwindcss').Config} */\nexport default {\n content: [\n \"./index.html\",\n \"./src/**/*.{js,ts,jsx,tsx}\",\n ],\n theme: {\n extend: {},\n },\n plugins: [],\n};","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"postcss.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"postcss.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"7 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"export default {\n plugins: {\n tailwindcss: {},\n autoprefixer: {},\n },\n};","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.html","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.html","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"14 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"<!DOCTYPE html>\n<html lang=\"en\">\n <head>\n <meta charset=\"UTF-8\" />\n <meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\" />\n <title>Finance Hub</title>\n <link rel=\"icon\" type=\"image/svg+xml\" href=\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 100 100'><text y='.9em' font-size='90'>💰</text></svg>\" />\n </head>\n <body class=\"bg-gray-50 min-h-screen\">\n <div id=\"root\"></div>\n <script type=\"module\" src=\"/src/main.jsx\"></script>\n </body>\n</html>","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.css","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.css","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"4 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"@tailwind base;\n@tailwind components;\n@tailwind utilities;","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now writing all React components:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"11 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React from 'react';\nimport ReactDOM from 'react-dom/client';\nimport App from './App';\nimport './index.css';\n\nReactDOM.createRoot(document.getElementById('root')).render(\n <React.StrictMode>\n <App />\n </React.StrictMode>\n);","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"App.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"App.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"257 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState, useEffect, useCallback } from 'react';\nimport { LayoutDashboard, Upload, RefreshCw, LogOut } from 'lucide-react';\nimport FilterBar from './components/FilterBar';\nimport PaymentTable from './components/PaymentTable';\nimport UploadPanel from './components/UploadPanel';\n\nconst API_BASE = '/api/payments';\n\nexport default function App() {\n const [activeTab, setActiveTab] = useState('payments');\n const [payments, setPayments] = useState([]);\n const [total, setTotal] = useState(0);\n const [page, setPage] = useState(1);\n const [filters, setFilters] = useState({});\n const [sortBy, setSortBy] = useState('createdAt');\n const [sortDir, setSortDir] = useState('desc');\n const [filterOptions, setFilterOptions] = useState({ types: [], recipients: [], tags: [], sources: [] });\n const [loading, setLoading] = useState(false);\n\n const fetchPayments = useCallback(async () => {\n setLoading(true);\n try {\n const params = new URLSearchParams();\n params.set('page', page);\n params.set('limit', 50);\n params.set('sortBy', sortBy);\n params.set('sortDir', sortDir);\n Object.entries(filters).forEach(([key, val]) => {\n if (val) params.set(key, val);\n });\n const res = await fetch(`${API_BASE}?${params}`);\n const data = await res.json();\n setPayments(data.payments || []);\n setTotal(data.total || 0);\n } catch (err) {\n console.error('Failed to fetch payments:', err);\n } finally {\n setLoading(false);\n }\n }, [page, filters, sortBy, sortDir]);\n\n const fetchFilterOptions = useCallback(async () => {\n try {\n const res = await fetch(`${API_BASE}/meta/filters`);\n const data = await res.json();\n setFilterOptions(data);\n } catch (err) {\n console.error('Failed to fetch filter options:', err);\n }\n }, []);\n\n useEffect(() => {\n fetchPayments();\n }, [fetchPayments]);\n\n useEffect(() => {\n fetchFilterOptions();\n }, [fetchFilterOptions]);\n\n // Refresh payments list after a successful CSV upload\n const handleUploadSuccess = () => {\n fetchPayments();\n fetchFilterOptions();\n setActiveTab('payments');\n };\n\n const handleAction = async (id, action) => {\n try {\n await fetch(`${API_BASE}/${id}/${action}`, { method: 'POST' });\n fetchPayments();\n fetchFilterOptions();\n } catch (err) {\n console.error(`Failed to ${action} payment:`, err);\n }\n };\n\n const handleAddTag = async (id, tagName, tagColor) => {\n try {\n await fetch(`${API_BASE}/${id}/tags`, {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify({ name: tagName, color: tagColor }),\n });\n fetchPayments();\n fetchFilterOptions();\n } catch (err) {\n console.error('Failed to add tag:', err);\n }\n };\n\n const handleRemoveTag = async (paymentId, tagId) => {\n try {\n await fetch(`${API_BASE}/${paymentId}/tags/${tagId}`, { method: 'DELETE' });\n fetchPayments();\n } catch (err) {\n console.error('Failed to remove tag:', err);\n }\n };\n\n const handleDelete = async (id) => {\n try {\n await fetch(`${API_BASE}/${id}`, { method: 'DELETE' });\n fetchPayments();\n fetchFilterOptions();\n } catch (err) {\n console.error('Failed to delete payment:', err);\n }\n };\n\n const handleUpdateStatus = async (id, status) => {\n try {\n await fetch(`${API_BASE}/${id}`, {\n method: 'PATCH',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify({ status }),\n });\n fetchPayments();\n } catch (err) {\n console.error('Failed to update status:', err);\n }\n };\n\n const handleFilterChange = (newFilters) => {\n setFilters(newFilters);\n setPage(1);\n };\n\n const handleSort = (field) => {\n if (sortBy === field) {\n setSortDir(d => d === 'asc' ? 'desc' : 'asc');\n } else {\n setSortBy(field);\n setSortDir('desc');\n }\n setPage(1);\n };\n\n const totalPages = Math.ceil(total / 50);\n\n return (\n <div className=\"min-h-screen bg-gray-50\">\n <header className=\"bg-white border-b border-gray-200 shadow-sm\">\n <div className=\"max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-4\">\n <div className=\"flex items-center justify-between\">\n <div className=\"flex items-center gap-3\">\n <div className=\"bg-indigo-600 p-2 rounded-lg\">\n <LayoutDashboard className=\"w-6 h-6 text-white\" />\n </div>\n <div>\n <h1 className=\"text-xl font-bold text-gray-900\">Finance Hub</h1>\n <p className=\"text-sm text-gray-500\">{total} transaction{total !== 1 ? 's' : ''} total</p>\n </div>\n </div>\n\n <div className=\"flex items-center gap-2\">\n {/* Tab switcher */}\n <div className=\"flex items-center rounded-lg border border-gray-200 bg-gray-50 p-1 gap-1\">\n <button\n onClick={() => setActiveTab('payments')}\n className={`flex items-center gap-1.5 px-3 py-1.5 text-sm font-medium rounded-md transition-colors ${\n activeTab === 'payments'\n ? 'bg-white text-indigo-700 shadow-sm'\n : 'text-gray-600 hover:text-gray-900'\n }`}\n >\n <LayoutDashboard className=\"w-4 h-4\" />\n Payments\n </button>\n <button\n onClick={() => setActiveTab('upload')}\n className={`flex items-center gap-1.5 px-3 py-1.5 text-sm font-medium rounded-md transition-colors ${\n activeTab === 'upload'\n ? 'bg-white text-emerald-700 shadow-sm'\n : 'text-gray-600 hover:text-gray-900'\n }`}\n >\n <Upload className=\"w-4 h-4\" />\n Upload CSV\n </button>\n </div>\n\n {activeTab === 'payments' && (\n <button\n onClick={() => { fetchPayments(); fetchFilterOptions(); }}\n className=\"flex items-center gap-2 px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 transition-colors\"\n >\n <RefreshCw className={`w-4 h-4 ${loading ? 'animate-spin' : ''}`} />\n Refresh\n </button>\n )}\n\n <button\n onClick={() => { window.location.href = '/outpost.goauthentik.io/sign_out'; }}\n className=\"flex items-center gap-2 px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 transition-colors\"\n title=\"Sign out\"\n >\n <LogOut className=\"w-4 h-4\" />\n </button>\n </div>\n </div>\n </div>\n </header>\n\n <main className=\"max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-6\">\n {activeTab === 'payments' ? (\n <>\n <FilterBar\n filters={filters}\n filterOptions={filterOptions}\n onFilterChange={handleFilterChange}\n />\n\n <PaymentTable\n payments={payments}\n loading={loading}\n sortBy={sortBy}\n sortDir={sortDir}\n onSort={handleSort}\n onSend={(id) => handleAction(id, 'send')}\n onSkip={(id) => handleAction(id, 'skip')}\n onAddTag={handleAddTag}\n onRemoveTag={handleRemoveTag}\n onDelete={handleDelete}\n onUpdateStatus={handleUpdateStatus}\n existingTags={filterOptions.tags}\n />\n\n {totalPages > 1 && (\n <div className=\"flex items-center justify-center gap-2 mt-6\">\n <button\n onClick={() => setPage(p => Math.max(1, p - 1))}\n disabled={page === 1}\n className=\"px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 disabled:opacity-50 disabled:cursor-not-allowed\"\n >\n Previous\n </button>\n <span className=\"text-sm text-gray-600\">\n Page {page} of {totalPages}\n </span>\n <button\n onClick={() => setPage(p => Math.min(totalPages, p + 1))}\n disabled={page === totalPages}\n className=\"px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 disabled:opacity-50 disabled:cursor-not-allowed\"\n >\n Next\n </button>\n </div>\n )}\n </>\n ) : (\n <UploadPanel onUploadSuccess={handleUploadSuccess} />\n )}\n </main>\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"FilterBar.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"FilterBar.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"167 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState, useEffect } from 'react';\nimport { Search, Filter, X, Calendar, ChevronDown, ChevronUp } from 'lucide-react';\n\nconst STATUS_OPTIONS = [\n { value: '', label: 'All Statuses' },\n { value: 'UNPROCESSED', label: 'Unprocessed' },\n { value: 'SENT', label: 'Sent' },\n { value: 'SKIPPED', label: 'Skipped' },\n];\n\nconst SOURCE_OPTIONS = [\n { value: '', label: 'All Sources' },\n { value: 'INGEST', label: 'SMS Ingest' },\n { value: 'UPLOAD', label: 'CSV Upload' },\n];\n\nexport default function FilterBar({ filters, filterOptions, onFilterChange }) {\n const [search, setSearch] = useState(filters.search || '');\n const [isOpen, setIsOpen] = useState(() => window.innerWidth >= 768);\n\n useEffect(() => {\n const mq = window.matchMedia('(min-width: 768px)');\n const handler = (e) => setIsOpen(e.matches);\n mq.addEventListener('change', handler);\n return () => mq.removeEventListener('change', handler);\n }, []);\n\n const handleSearchSubmit = (e) => {\n e.preventDefault();\n onFilterChange({ ...filters, search: search || undefined });\n };\n\n const handleSelectChange = (key, value) => {\n const newFilters = { ...filters };\n if (value) {\n newFilters[key] = value;\n } else {\n delete newFilters[key];\n }\n onFilterChange(newFilters);\n };\n\n const clearFilters = () => {\n setSearch('');\n onFilterChange({});\n };\n\n const activeFilterCount = Object.keys(filters).length;\n const hasActiveFilters = activeFilterCount > 0;\n\n return (\n <div className=\"bg-white rounded-xl border border-gray-200 shadow-sm p-4 mb-6\">\n <button\n onClick={() => setIsOpen(!isOpen)}\n className=\"w-full flex items-center gap-2\"\n >\n <Filter className=\"w-4 h-4 text-gray-500\" />\n <span className=\"text-sm font-medium text-gray-700\">Filters</span>\n {hasActiveFilters && (\n <span className=\"inline-flex items-center justify-center w-5 h-5 text-xs font-bold text-white bg-indigo-600 rounded-full\">\n {activeFilterCount}\n </span>\n )}\n {hasActiveFilters && (\n <span\n onClick={(e) => { e.stopPropagation(); clearFilters(); }}\n className=\"ml-1 flex items-center gap-1 text-xs text-red-600 hover:text-red-700\"\n >\n <X className=\"w-3 h-3\" />\n Clear\n </span>\n )}\n <span className=\"ml-auto\">\n {isOpen\n ? <ChevronUp className=\"w-4 h-4 text-gray-400\" />\n : <ChevronDown className=\"w-4 h-4 text-gray-400\" />\n }\n </span>\n </button>\n\n {isOpen && (\n <div className=\"space-y-3 mt-3 pt-3 border-t border-gray-100\">\n <div className=\"grid grid-cols-1 sm:grid-cols-2 lg:grid-cols-5 gap-3\">\n <form onSubmit={handleSearchSubmit} className=\"relative\">\n <Search className=\"absolute left-3 top-1/2 -translate-y-1/2 w-4 h-4 text-gray-400\" />\n <input\n type=\"text\"\n placeholder=\"Search...\"\n value={search}\n onChange={(e) => setSearch(e.target.value)}\n onBlur={() => onFilterChange({ ...filters, search: search || undefined })}\n className=\"w-full pl-9 pr-3 py-2 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none\"\n />\n </form>\n\n <select\n value={filters.source || ''}\n onChange={(e) => handleSelectChange('source', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n {SOURCE_OPTIONS.map(opt => (\n <option key={opt.value} value={opt.value}>{opt.label}</option>\n ))}\n </select>\n\n <select\n value={filters.status || ''}\n onChange={(e) => handleSelectChange('status', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n {STATUS_OPTIONS.map(opt => (\n <option key={opt.value} value={opt.value}>{opt.label}</option>\n ))}\n </select>\n\n <select\n value={filters.type || ''}\n onChange={(e) => handleSelectChange('type', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n <option value=\"\">All Types</option>\n {(filterOptions.types || []).map(t => (\n <option key={t} value={t}>{t}</option>\n ))}\n </select>\n\n <select\n value={filters.tag || ''}\n onChange={(e) => handleSelectChange('tag', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n <option value=\"\">All Tags</option>\n {(filterOptions.tags || []).map(t => (\n <option key={t.id} value={t.name}>{t.name}</option>\n ))}\n </select>\n </div>\n\n <div className=\"grid grid-cols-1 sm:grid-cols-2 gap-3\">\n <div className=\"relative\">\n <Calendar className=\"absolute left-3 top-1/2 -translate-y-1/2 w-4 h-4 text-gray-400\" />\n <input\n type=\"date\"\n placeholder=\"From date\"\n value={filters.dateFrom || ''}\n onChange={(e) => handleSelectChange('dateFrom', e.target.value)}\n className=\"w-full pl-9 pr-3 py-2 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none\"\n />\n </div>\n\n <div className=\"relative\">\n <Calendar className=\"absolute left-3 top-1/2 -translate-y-1/2 w-4 h-4 text-gray-400\" />\n <input\n type=\"date\"\n placeholder=\"To date\"\n value={filters.dateTo || ''}\n onChange={(e) => handleSelectChange('dateTo', e.target.value)}\n className=\"w-full pl-9 pr-3 py-2 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none\"\n />\n </div>\n </div>\n </div>\n )}\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentTable.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentTable.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"339 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState } from 'react';\nimport {\n ArrowUpDown, ArrowUp, ArrowDown,\n Send, XCircle, CheckCircle, MinusCircle, Clock,\n Inbox, Plus, X, ChevronDown, ChevronUp, Trash2,\n} from 'lucide-react';\n\nconst STATUS_CONFIG = {\n UNPROCESSED: { label: 'Unprocessed', icon: Clock, color: 'bg-amber-100 text-amber-700' },\n SENT: { label: 'Sent', icon: CheckCircle, color: 'bg-green-100 text-green-700' },\n SKIPPED: { label: 'Skipped', icon: MinusCircle, color: 'bg-gray-100 text-gray-500' },\n};\n\nconst TAG_COLORS = [\n '#ef4444', '#f97316', '#eab308', '#22c55e', '#06b6d4',\n '#3b82f6', '#8b5cf6', '#ec4899', '#6b7280',\n];\n\nconst COLUMNS = [\n { key: 'date', label: 'Date & Time', sortable: true },\n { key: 'source', label: 'Source', sortable: true },\n { key: 'type', label: 'Type', sortable: true },\n { key: 'recipient', label: 'Recipient', sortable: true },\n { key: 'amount', label: 'Amount', sortable: true },\n { key: 'balance', label: 'Balance', sortable: true },\n { key: 'status', label: 'Status', sortable: true },\n { key: 'tags', label: 'Tags', sortable: false },\n { key: 'actions', label: 'Actions', sortable: false },\n];\n\nfunction SortIcon({ column, sortBy, sortDir }) {\n if (sortBy !== column) return <ArrowUpDown className=\"w-3 h-3 text-gray-400\" />;\n return sortDir === 'asc'\n ? <ArrowUp className=\"w-3 h-3 text-indigo-600\" />\n : <ArrowDown className=\"w-3 h-3 text-indigo-600\" />;\n}\n\nfunction SourceBadge({ source }) {\n if (source === 'UPLOAD') {\n return (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-emerald-50 text-emerald-700\">\n CSV\n </span>\n );\n }\n return (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-indigo-50 text-indigo-700\">\n SMS\n </span>\n );\n}\n\nfunction TagCell({ payment, onAddTag, onRemoveTag, existingTags }) {\n const [open, setOpen] = useState(false);\n const [newTagName, setNewTagName] = useState('');\n const [newTagColor, setNewTagColor] = useState('#3b82f6');\n\n const paymentTags = payment.tags || [];\n const availableTags = existingTags.filter(t => !paymentTags.some(pt => pt.id === t.id));\n\n const handleAdd = (e) => {\n e.preventDefault();\n if (newTagName.trim()) {\n onAddTag(payment.id, newTagName.trim(), newTagColor);\n setNewTagName('');\n setOpen(false);\n }\n };\n\n return (\n <div className=\"flex flex-wrap items-center gap-1\">\n {paymentTags.map(tag => (\n <span\n key={tag.id}\n className=\"inline-flex items-center gap-0.5 px-1.5 py-0.5 text-xs font-medium rounded-full text-white\"\n style={{ backgroundColor: tag.color }}\n >\n {tag.name}\n <button onClick={() => onRemoveTag(payment.id, tag.id)} className=\"hover:opacity-75\">\n <X className=\"w-2.5 h-2.5\" />\n </button>\n </span>\n ))}\n <div className=\"relative\">\n <button\n onClick={() => setOpen(!open)}\n className=\"inline-flex items-center gap-0.5 px-1.5 py-0.5 text-xs text-gray-500 border border-dashed border-gray-300 rounded-full hover:border-gray-400\"\n >\n <Plus className=\"w-2.5 h-2.5\" />\n </button>\n {open && (\n <div className=\"absolute z-20 top-full left-0 mt-1 bg-white border border-gray-200 rounded-lg shadow-lg p-2 w-56\">\n <form onSubmit={handleAdd} className=\"flex items-center gap-1 mb-2\">\n <input\n type=\"text\"\n value={newTagName}\n onChange={(e) => setNewTagName(e.target.value)}\n placeholder=\"New tag\"\n autoFocus\n className=\"flex-1 px-2 py-1 text-xs border border-gray-300 rounded focus:ring-1 focus:ring-indigo-500 outline-none\"\n />\n <button type=\"submit\" className=\"text-xs text-indigo-600 font-medium hover:text-indigo-700 whitespace-nowrap\">Add</button>\n </form>\n <div className=\"flex gap-1 mb-2\">\n {TAG_COLORS.map(c => (\n <button\n key={c}\n type=\"button\"\n onClick={() => setNewTagColor(c)}\n className={`w-4 h-4 rounded-full border-2 ${newTagColor === c ? 'border-gray-800' : 'border-transparent'}`}\n style={{ backgroundColor: c }}\n />\n ))}\n </div>\n {availableTags.length > 0 && (\n <div className=\"border-t border-gray-100 pt-1 flex flex-wrap gap-1\">\n {availableTags.map(tag => (\n <button\n key={tag.id}\n onClick={() => { onAddTag(payment.id, tag.name, tag.color); setOpen(false); }}\n className=\"px-1.5 py-0.5 text-xs rounded-full border border-gray-200 text-gray-600 hover:bg-gray-100\"\n >\n {tag.name}\n </button>\n ))}\n </div>\n )}\n </div>\n )}\n </div>\n </div>\n );\n}\n\nfunction ExpandedRow({ payment }) {\n return (\n <tr className=\"bg-gray-50\">\n <td colSpan={COLUMNS.length} className=\"px-4 py-3\">\n <div className=\"text-xs text-gray-500 uppercase tracking-wide mb-1\">Original Message / Raw Data</div>\n <p className=\"text-sm text-gray-700 whitespace-pre-wrap break-words\">{payment.rawMessage}</p>\n {payment.debitBgn != null && (\n <p className=\"text-xs text-gray-500 mt-1\">Debit: {payment.debitBgn.toFixed(2)} BGN</p>\n )}\n {payment.creditBgn != null && (\n <p className=\"text-xs text-gray-500 mt-0.5\">Credit: {payment.creditBgn.toFixed(2)} BGN</p>\n )}\n {payment.transactionType && (\n <p className=\"text-xs text-gray-500 mt-0.5\">Transaction type: {payment.transactionType}</p>\n )}\n {payment.payerAccount && (\n <p className=\"text-xs text-gray-500 mt-0.5\">Account: {payment.payerAccount}</p>\n )}\n {payment.notifiedAt && (\n <p className=\"text-xs text-green-600 mt-2\">\n Notified on {new Date(payment.notifiedAt).toLocaleString('en-GB')}\n {payment.notifyPhone && ` to ${payment.notifyPhone}`}\n </p>\n )}\n </td>\n </tr>\n );\n}\n\nfunction StatusCell({ payment, onUpdateStatus }) {\n const [open, setOpen] = useState(false);\n const statusCfg = STATUS_CONFIG[payment.status] || STATUS_CONFIG.UNPROCESSED;\n const StatusIcon = statusCfg.icon;\n\n return (\n <div className=\"relative\">\n <button\n onClick={() => setOpen(!open)}\n className={`inline-flex items-center gap-1 px-2 py-0.5 text-xs font-medium rounded-full cursor-pointer ${statusCfg.color}`}\n >\n <StatusIcon className=\"w-3 h-3\" />\n {statusCfg.label}\n </button>\n {open && (\n <div className=\"absolute z-20 top-full left-0 mt-1 bg-white border border-gray-200 rounded-lg shadow-lg py-1 w-36\">\n {Object.entries(STATUS_CONFIG).map(([key, cfg]) => {\n const Icon = cfg.icon;\n return (\n <button\n key={key}\n onClick={() => { onUpdateStatus(payment.id, key); setOpen(false); }}\n className={`w-full flex items-center gap-2 px-3 py-1.5 text-xs hover:bg-gray-50 ${payment.status === key ? 'font-bold' : ''}`}\n >\n <Icon className=\"w-3 h-3\" />\n {cfg.label}\n </button>\n );\n })}\n </div>\n )}\n </div>\n );\n}\n\nexport default function PaymentTable({\n payments, loading, sortBy, sortDir, onSort,\n onSend, onSkip, onAddTag, onRemoveTag, onDelete, onUpdateStatus, existingTags,\n}) {\n const [expandedId, setExpandedId] = useState(null);\n\n if (loading) {\n return (\n <div className=\"flex items-center justify-center py-20\">\n <div className=\"animate-spin rounded-full h-8 w-8 border-b-2 border-indigo-600\"></div>\n </div>\n );\n }\n\n if (!payments || payments.length === 0) {\n return (\n <div className=\"flex flex-col items-center justify-center py-20 text-gray-400\">\n <Inbox className=\"w-12 h-12 mb-3\" />\n <p className=\"text-lg font-medium\">No transactions found</p>\n <p className=\"text-sm\">Try adjusting your filters, ingest a payment SMS, or upload a CSV.</p>\n </div>\n );\n }\n\n const formatDate = (d) => {\n if (!d) return '—';\n return new Date(d).toLocaleDateString('en-GB', {\n day: '2-digit', month: 'short', year: 'numeric', hour: '2-digit', minute: '2-digit',\n });\n };\n\n const formatAmount = (v, currency) =>\n v != null ? `${v.toFixed(2)} ${currency || 'EUR'}` : '—';\n\n return (\n <div className=\"bg-white rounded-xl border border-gray-200 shadow-sm overflow-hidden\">\n <div className=\"overflow-x-auto\">\n <table className=\"w-full text-sm\">\n <thead>\n <tr className=\"bg-gray-50 border-b border-gray-200\">\n {COLUMNS.map(col => (\n <th\n key={col.key}\n className={`px-4 py-3 text-left text-xs font-semibold text-gray-600 uppercase tracking-wider ${col.sortable ? 'cursor-pointer select-none hover:bg-gray-100' : ''}`}\n onClick={() => col.sortable && onSort(col.key)}\n >\n <span className=\"inline-flex items-center gap-1\">\n {col.label}\n {col.sortable && <SortIcon column={col.key} sortBy={sortBy} sortDir={sortDir} />}\n </span>\n </th>\n ))}\n </tr>\n </thead>\n <tbody className=\"divide-y divide-gray-100\">\n {payments.map(p => {\n const isExpanded = expandedId === p.id;\n return (\n <React.Fragment key={p.id}>\n <tr className=\"hover:bg-gray-50 transition-colors\">\n <td className=\"px-4 py-3 whitespace-nowrap text-gray-700\">{formatDate(p.date)}</td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n <SourceBadge source={p.source} />\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n {p.type ? (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-blue-50 text-blue-700\">{p.type}</span>\n ) : (p.transactionType ? (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-gray-100 text-gray-600 max-w-24 truncate block\" title={p.transactionType}>{p.transactionType}</span>\n ) : '—')}\n </td>\n <td className=\"px-4 py-3 text-gray-700 max-w-xs truncate\" title={p.recipient || ''}>\n <div className=\"flex items-center gap-1\">\n <span className=\"truncate\">{p.recipient || '—'}</span>\n <button\n onClick={() => setExpandedId(isExpanded ? null : p.id)}\n className=\"flex-shrink-0 text-gray-400 hover:text-gray-600\"\n title=\"Show raw data\"\n >\n {isExpanded ? <ChevronUp className=\"w-3.5 h-3.5\" /> : <ChevronDown className=\"w-3.5 h-3.5\" />}\n </button>\n </div>\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap font-medium text-gray-900\">\n {formatAmount(p.amount, p.currency)}\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap text-gray-600\">\n {formatAmount(p.balance, p.currency)}\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n <StatusCell payment={p} onUpdateStatus={onUpdateStatus} />\n </td>\n <td className=\"px-4 py-3\">\n <TagCell\n payment={p}\n onAddTag={onAddTag}\n onRemoveTag={onRemoveTag}\n existingTags={existingTags}\n />\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n <div className=\"flex items-center gap-1.5\">\n {p.status === 'UNPROCESSED' && (\n <>\n <button\n onClick={() => onSend(p.id)}\n className=\"inline-flex items-center gap-1 px-2.5 py-1 text-xs font-medium text-white bg-indigo-600 rounded-md hover:bg-indigo-700 transition-colors\"\n >\n <Send className=\"w-3 h-3\" />\n Send\n </button>\n <button\n onClick={() => onSkip(p.id)}\n className=\"inline-flex items-center gap-1 px-2.5 py-1 text-xs font-medium text-gray-600 bg-white border border-gray-300 rounded-md hover:bg-gray-50 transition-colors\"\n >\n <XCircle className=\"w-3 h-3\" />\n Skip\n </button>\n </>\n )}\n <button\n onClick={() => { if (window.confirm('Delete this transaction?')) onDelete(p.id); }}\n className=\"inline-flex items-center gap-1 px-2 py-1 text-xs font-medium text-red-600 bg-white border border-red-200 rounded-md hover:bg-red-50 transition-colors\"\n title=\"Delete transaction\"\n >\n <Trash2 className=\"w-3 h-3\" />\n </button>\n </div>\n </td>\n </tr>\n {isExpanded && <ExpandedRow payment={p} />}\n </React.Fragment>\n );\n })}\n </tbody>\n </table>\n </div>\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"UploadPanel.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"UploadPanel.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"192 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState, useRef } from 'react';\nimport { Upload, FileText, CheckCircle, AlertCircle, X, ArrowLeft } from 'lucide-react';\n\nexport default function UploadPanel({ onUploadSuccess }) {\n const [files, setFiles] = useState([]);\n const [loading, setLoading] = useState(false);\n const [result, setResult] = useState(null);\n const [error, setError] = useState(null);\n const [dragging, setDragging] = useState(false);\n const fileInputRef = useRef();\n\n const addFiles = (incoming) => {\n const csvFiles = Array.from(incoming).filter(f =>\n f.name.toLowerCase().endsWith('.csv')\n );\n setFiles(prev => {\n const existingNames = new Set(prev.map(f => f.name));\n return [...prev, ...csvFiles.filter(f => !existingNames.has(f.name))];\n });\n };\n\n const handleDrop = (e) => {\n e.preventDefault();\n setDragging(false);\n addFiles(e.dataTransfer.files);\n };\n\n const handleFileSelect = (e) => {\n addFiles(e.target.files);\n e.target.value = '';\n };\n\n const removeFile = (idx) => setFiles(prev => prev.filter((_, i) => i !== idx));\n\n const handleUpload = async () => {\n if (!files.length) return;\n setLoading(true);\n setError(null);\n setResult(null);\n\n const formData = new FormData();\n files.forEach(f => formData.append('files', f));\n\n try {\n const res = await fetch('/api/upload/csv', { method: 'POST', body: formData });\n const data = await res.json();\n if (!res.ok) throw new Error(data.error || 'Upload failed');\n setResult(data);\n setFiles([]);\n } catch (err) {\n setError(err.message);\n } finally {\n setLoading(false);\n }\n };\n\n return (\n <div className=\"max-w-2xl mx-auto\">\n <div className=\"mb-6\">\n <h2 className=\"text-lg font-semibold text-gray-900\">Upload DSK Bank CSV</h2>\n <p className=\"text-sm text-gray-500 mt-1\">\n Import transactions from DSK Bank CSV exports. Multiple files are merged automatically.\n Internal transfers are skipped. Tags are auto-assigned based on payee and description.\n </p>\n </div>\n\n {/* Drop zone */}\n <div\n onDrop={handleDrop}\n onDragOver={(e) => { e.preventDefault(); setDragging(true); }}\n onDragLeave={() => setDragging(false)}\n onClick={() => fileInputRef.current.click()}\n className={`border-2 border-dashed rounded-xl p-12 text-center cursor-pointer transition-colors ${\n dragging\n ? 'border-emerald-400 bg-emerald-50'\n : 'border-gray-300 hover:border-emerald-400 hover:bg-emerald-50'\n }`}\n >\n <Upload className={`w-10 h-10 mx-auto mb-3 ${dragging ? 'text-emerald-500' : 'text-gray-400'}`} />\n <p className=\"text-sm font-medium text-gray-700\">Drop DSK Bank CSV files here</p>\n <p className=\"text-xs text-gray-500 mt-1\">or click to select files — multiple files supported</p>\n <input\n ref={fileInputRef}\n type=\"file\"\n multiple\n accept=\".csv\"\n className=\"hidden\"\n onChange={handleFileSelect}\n />\n </div>\n\n {/* File list */}\n {files.length > 0 && (\n <div className=\"mt-4 space-y-2\">\n {files.map((f, i) => (\n <div key={i} className=\"flex items-center gap-2 bg-white rounded-lg border border-gray-200 px-3 py-2\">\n <FileText className=\"w-4 h-4 text-gray-400 flex-shrink-0\" />\n <span className=\"text-sm text-gray-700 flex-1 truncate\">{f.name}</span>\n <span className=\"text-xs text-gray-400 flex-shrink-0\">{(f.size / 1024).toFixed(1)} KB</span>\n <button\n onClick={(e) => { e.stopPropagation(); removeFile(i); }}\n className=\"text-gray-400 hover:text-gray-600 flex-shrink-0\"\n >\n <X className=\"w-4 h-4\" />\n </button>\n </div>\n ))}\n\n <button\n onClick={handleUpload}\n disabled={loading}\n className=\"w-full py-2.5 text-sm font-medium text-white bg-emerald-600 rounded-lg hover:bg-emerald-700 disabled:opacity-50 disabled:cursor-not-allowed transition-colors mt-2\"\n >\n {loading\n ? 'Importing…'\n : `Import ${files.length} file${files.length !== 1 ? 's' : ''}`\n }\n </button>\n </div>\n )}\n\n {/* Success result */}\n {result && (\n <div className=\"mt-6 bg-green-50 border border-green-200 rounded-xl p-5\">\n <div className=\"flex items-center gap-2 mb-3\">\n <CheckCircle className=\"w-5 h-5 text-green-600 flex-shrink-0\" />\n <span className=\"font-medium text-green-800\">Import complete</span>\n </div>\n <div className=\"grid grid-cols-3 gap-3 text-center mb-3\">\n <div className=\"bg-white rounded-lg border border-green-100 py-2 px-3\">\n <p className=\"text-2xl font-bold text-green-700\">{result.imported}</p>\n <p className=\"text-xs text-gray-500\">Imported</p>\n </div>\n <div className=\"bg-white rounded-lg border border-green-100 py-2 px-3\">\n <p className=\"text-2xl font-bold text-gray-500\">{result.skipped}</p>\n <p className=\"text-xs text-gray-500\">Skipped</p>\n </div>\n <div className=\"bg-white rounded-lg border border-green-100 py-2 px-3\">\n <p className=\"text-2xl font-bold text-amber-600\">{result.errors?.length ?? 0}</p>\n <p className=\"text-xs text-gray-500\">Warnings</p>\n </div>\n </div>\n <p className=\"text-xs text-gray-500 mb-3\">\n Skipped rows are internal bank transfers (ТРАНСФЕР СОБСТВЕНИ СМЕТКИ).\n </p>\n {result.errors?.length > 0 && (\n <details className=\"mb-3\">\n <summary className=\"text-xs text-amber-700 cursor-pointer hover:text-amber-800\">\n Show {result.errors.length} warning{result.errors.length !== 1 ? 's' : ''}\n </summary>\n <ul className=\"mt-2 text-xs text-amber-600 space-y-0.5 max-h-32 overflow-y-auto\">\n {result.errors.map((e, i) => <li key={i} className=\"font-mono\">{e}</li>)}\n </ul>\n </details>\n )}\n <button\n onClick={onUploadSuccess}\n className=\"flex items-center gap-1.5 text-sm font-medium text-green-700 hover:text-green-800\"\n >\n <ArrowLeft className=\"w-4 h-4\" />\n View imported transactions\n </button>\n </div>\n )}\n\n {/* Error */}\n {error && (\n <div className=\"mt-4 bg-red-50 border border-red-200 rounded-xl p-4 flex items-start gap-3\">\n <AlertCircle className=\"w-5 h-5 text-red-500 flex-shrink-0 mt-0.5\" />\n <div>\n <p className=\"text-sm font-medium text-red-800\">Upload failed</p>\n <p className=\"text-sm text-red-700 mt-0.5\">{error}</p>\n </div>\n </div>\n )}\n\n {/* Info box */}\n {!result && !error && (\n <div className=\"mt-6 bg-blue-50 border border-blue-100 rounded-xl p-4\">\n <p className=\"text-xs font-medium text-blue-800 mb-1\">Expected CSV format (DSK Bank export)</p>\n <p className=\"text-xs text-blue-700 font-mono\">\n Дата, Вид на трансакцията, Основание, Дебит BGN, Кредит BGN, Наредител/Получател, Номер сметка...\n </p>\n <p className=\"text-xs text-blue-600 mt-2\">\n Both UTF-8 and Windows-1251 encodings are supported. Tags are auto-applied based on payee and description keywords.\n </p>\n </div>\n )}\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentCard.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentCard.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"186 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState } from 'react';\nimport {\n Send, XCircle, CheckCircle, MinusCircle, Clock,\n CreditCard, Tag, Plus, X,\n} from 'lucide-react';\n\nconst STATUS_CONFIG = {\n UNPROCESSED: { label: 'Unprocessed', icon: Clock, color: 'bg-amber-100 text-amber-700 border-amber-200' },\n SENT: { label: 'Sent', icon: CheckCircle, color: 'bg-green-100 text-green-700 border-green-200' },\n SKIPPED: { label: 'Skipped', icon: MinusCircle, color: 'bg-gray-100 text-gray-500 border-gray-200' },\n};\n\nconst TAG_COLORS = [\n '#ef4444', '#f97316', '#eab308', '#22c55e', '#06b6d4',\n '#3b82f6', '#8b5cf6', '#ec4899', '#6b7280',\n];\n\nexport default function PaymentCard({ payment, onSend, onSkip, onAddTag, onRemoveTag, existingTags }) {\n const [showTagInput, setShowTagInput] = useState(false);\n const [newTagName, setNewTagName] = useState('');\n const [newTagColor, setNewTagColor] = useState('#3b82f6');\n\n const statusCfg = STATUS_CONFIG[payment.status] || STATUS_CONFIG.UNPROCESSED;\n const StatusIcon = statusCfg.icon;\n\n const handleAddTag = (e) => {\n e.preventDefault();\n if (newTagName.trim()) {\n onAddTag(payment.id, newTagName.trim(), newTagColor);\n setNewTagName('');\n setShowTagInput(false);\n }\n };\n\n const paymentTags = payment.tags || [];\n const availableTags = existingTags.filter(t => !paymentTags.some(pt => pt.id === t.id));\n\n const formattedDate = payment.date\n ? new Date(payment.date).toLocaleDateString('en-GB', {\n day: '2-digit', month: 'short', year: 'numeric', hour: '2-digit', minute: '2-digit',\n })\n : 'N/A';\n\n const currency = payment.currency || 'EUR';\n\n return (\n <div className=\"bg-white rounded-xl border border-gray-200 shadow-sm hover:shadow-md transition-shadow p-4\">\n <div className=\"flex items-start justify-between gap-3 mb-3\">\n <div className=\"flex-1 min-w-0\">\n <div className=\"flex items-center gap-2 mb-1\">\n <span className={`inline-flex items-center gap-1 px-2 py-0.5 text-xs font-medium rounded-full border ${statusCfg.color}`}>\n <StatusIcon className=\"w-3 h-3\" />\n {statusCfg.label}\n </span>\n {payment.source === 'UPLOAD' ? (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-emerald-50 text-emerald-700\">CSV</span>\n ) : (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-indigo-50 text-indigo-700\">SMS</span>\n )}\n </div>\n <p className=\"text-sm text-gray-600 break-words leading-relaxed\">{payment.rawMessage}</p>\n </div>\n </div>\n\n <div className=\"grid grid-cols-2 sm:grid-cols-4 gap-3 mb-3 text-sm\">\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Amount</span>\n <p className=\"font-semibold text-gray-900\">\n {payment.amount != null ? `${payment.amount.toFixed(2)} ${currency}` : 'N/A'}\n </p>\n </div>\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Date</span>\n <p className=\"text-gray-700\">{formattedDate}</p>\n </div>\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Card</span>\n <p className=\"text-gray-700 flex items-center gap-1\">\n <CreditCard className=\"w-3 h-3 text-gray-400\" />\n {payment.card || 'N/A'}\n </p>\n </div>\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Balance</span>\n <p className=\"text-gray-700\">\n {payment.balance != null ? `${payment.balance.toFixed(2)} ${currency}` : 'N/A'}\n </p>\n </div>\n </div>\n\n {/* Tags */}\n <div className=\"flex flex-wrap items-center gap-1.5 mb-3\">\n <Tag className=\"w-3 h-3 text-gray-400\" />\n {paymentTags.map(tag => (\n <span\n key={tag.id}\n className=\"inline-flex items-center gap-1 px-2 py-0.5 text-xs font-medium rounded-full text-white\"\n style={{ backgroundColor: tag.color }}\n >\n {tag.name}\n <button onClick={() => onRemoveTag(payment.id, tag.id)} className=\"hover:opacity-75\">\n <X className=\"w-3 h-3\" />\n </button>\n </span>\n ))}\n {!showTagInput ? (\n <button\n onClick={() => setShowTagInput(true)}\n className=\"inline-flex items-center gap-0.5 px-2 py-0.5 text-xs text-gray-500 border border-dashed border-gray-300 rounded-full hover:border-gray-400 hover:text-gray-600\"\n >\n <Plus className=\"w-3 h-3\" />\n Tag\n </button>\n ) : (\n <form onSubmit={handleAddTag} className=\"inline-flex items-center gap-1\">\n <input\n type=\"text\"\n value={newTagName}\n onChange={(e) => setNewTagName(e.target.value)}\n placeholder=\"Tag name\"\n autoFocus\n className=\"w-24 px-2 py-0.5 text-xs border border-gray-300 rounded-md focus:ring-1 focus:ring-indigo-500 outline-none\"\n />\n <div className=\"flex gap-0.5\">\n {TAG_COLORS.map(c => (\n <button\n key={c}\n type=\"button\"\n onClick={() => setNewTagColor(c)}\n className={`w-4 h-4 rounded-full border-2 ${newTagColor === c ? 'border-gray-800' : 'border-transparent'}`}\n style={{ backgroundColor: c }}\n />\n ))}\n </div>\n <button type=\"submit\" className=\"text-xs text-indigo-600 font-medium hover:text-indigo-700\">Add</button>\n <button type=\"button\" onClick={() => setShowTagInput(false)} className=\"text-xs text-gray-400 hover:text-gray-600\">\n <X className=\"w-3 h-3\" />\n </button>\n </form>\n )}\n {showTagInput && availableTags.length > 0 && (\n <div className=\"flex flex-wrap gap-1 ml-1\">\n {availableTags.slice(0, 5).map(tag => (\n <button\n key={tag.id}\n onClick={() => { onAddTag(payment.id, tag.name, tag.color); setShowTagInput(false); }}\n className=\"px-2 py-0.5 text-xs rounded-full border border-gray-200 text-gray-600 hover:bg-gray-100\"\n >\n {tag.name}\n </button>\n ))}\n </div>\n )}\n </div>\n\n {payment.status === 'UNPROCESSED' && (\n <div className=\"flex items-center gap-2 pt-3 border-t border-gray-100\">\n <button\n onClick={() => onSend(payment.id)}\n className=\"flex items-center gap-1.5 px-4 py-2 text-sm font-medium text-white bg-indigo-600 rounded-lg hover:bg-indigo-700 transition-colors\"\n >\n <Send className=\"w-4 h-4\" />\n Send\n </button>\n <button\n onClick={() => onSkip(payment.id)}\n className=\"flex items-center gap-1.5 px-4 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 transition-colors\"\n >\n <XCircle className=\"w-4 h-4\" />\n Do Not Send\n </button>\n </div>\n )}\n\n {payment.status === 'SENT' && payment.notifiedAt && (\n <div className=\"pt-3 border-t border-gray-100\">\n <p className=\"text-xs text-green-600\">\n Notified on {new Date(payment.notifiedAt).toLocaleString('en-GB')}\n {payment.notifyPhone && ` to ${payment.notifyPhone}`}\n </p>\n </div>\n )}\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentList.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentList.jsx","depth":25,"on_screen":false,"role_description":"text"}]...
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Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
report(1).csv, Editor Group 1
report(2).csv, Editor Group 1
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
Design new payment-logge…, Editor Group 2
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Info: Setting up SSH Host nas: Setting up SSH tunnel
Design new payment-logger and dsk-uploader hybrid app
Session history
New session
Message actions
payments.js
payments.js
ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.
Thinking
Thinking
I'll explore all three reference projects in parallel to understand their structure before planning.
Agent:
Explore payment-logger app structure and functionality
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How data flows (ingest, storage, retrieval)
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.
Agent:
Explore dsk-uploader app structure and functionality
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How file uploads work - what files, what format, how parsed
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.
Agent:
Explore auth folder and authentik integration
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. What auth system is being used (Authentik)
2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?
3. Middleware - how is auth enforced on routes?
4. Any frontend auth flow - login redirect, token handling, protected routes
5. Environment variables related to auth
6. Docker/deployment setup for the auth service itself
7. Any example of how other apps integrate with this auth
Report with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.
Message actions
payments.js
payments.js
continue
Thinking
Thinking
Launching parallel exploration of all three reference projects.
Agent:
Explore payment-logger app structure
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How data is ingested (look at /ingest route especially)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore dsk-uploader app structure
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How file uploads work (what format, what processing happens)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore auth project structure
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. What authentication system is used (authentik integration details)
3. How OAuth/OIDC flow works
4. Any middleware or helper functions for protecting routes
5. Session management approach
6. How frontend handles auth state
7. Any example of how other apps integrate with this auth system
8. Docker setup and environment variables
Please read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.
Thinking
Thinking
Now I have a complete picture of all three. Let me design the plan.
Agent:
Design combined app architecture
IN
Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:
---
## App 1: payments-logger (Node.js)
- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI
- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS
- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage
- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)
- **Schema** (PostgreSQL via Prisma):
- `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at
- `tags` table: id, name, color — M2M with payments via `_PaymentToTag`
- `users` table: id, username, hashed_password (this will be REMOVED)
- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system
- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance
## App 2: dsk-uploader (Python/Flask)
- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database
- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5
- **Auth**: None (open)
- **CSV format** (DSK Bank Bulgarian format, columns):
- `Дата` (date, DD.MM.YYYY)
- `Вид на трансакцията` (transaction type, Bulgarian)
- `Основание` (reason/description — contains card number regex: `^\d{6}x{6}\d{4}$`)
- `Дебит BGN` (debit amount, may be empty)
- `Кредит BGN` (credit amount, may be empty)
- `Наредител/Получател` (orderer/recipient name)
- `Номер сметка на наредителя / получателя` (account number)
- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers
- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)
## App 3: auth (Authentik)
- **Mode**: Proxy mode via NPM (forward auth)
- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:
- `X-authentik-username`
- `X-authentik-email`
- `X-authentik-groups`
- **No code integration needed** in the app itself — just trust these headers from NPM
- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`
---
## What the New Combined App Must Do
1. **Single PostgreSQL database** for all transactions
2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST
3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema
4. **Unified UI** — show all payments in one table regardless of source
5. **Source indicator** in UI — badge showing "INGEST", "UPLOAD", or "BOTH" (if duplicate detection added)
6. **Source filter** in FilterBar — filter by All/Ingest/Upload
7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM
8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination
9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL
---
## Technical Constraints
- Keep Node.js backend (not Python) — extend payments-logger's stack
- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)
- File upload: use `multer` npm middleware
- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)
- Add `source` enum field (INGEST/UPLOAD) to payments schema
- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is
- Remove `users` table from schema
---
## Please Design
1. Complete folder structure for the new app (suggest name: "finance-hub" or similar — note this is a placeholder, user will confirm)
2. Prisma schema with new fields (`source`, `currency`)
3. All backend API routes
4. CSV parser design in Node.js (port of the Python logic)
5. Authentik auth middleware
6. Frontend component structure (React) — what's reused from payments-logger, what's new
7. Docker Compose setup
8. Environment variables needed
9. Step-by-step implementation order
10. Verification checklist
Be specific about file paths and code structure. This will be used to write actual implementation code.
Thinking
Thinking
Good plan. Let me ask the one thing I need before writing the final plan.
AskUserQuestion
OUT
User has answered your questions: "What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding."="finance-hub". You can now continue with the user's answers in mind.
Thinking
Thinking
Writing the final plan now.
Thinking
Thinking
Write
ets-create-a-new-generic-sun.md
ets-create-a-new-generic-sun.md
326 lines
# finance-hub — Implementation Plan
## Context
Two separate finance apps exist as references and will be retired:
- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.
- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.
The new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).
---
## Tech Stack
| Layer | Choice | Rationale |
|-------|--------|-----------|
| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |
| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |
| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |
| Database | PostgreSQL 16 | Same as payments-logger |
| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |
| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |
| Container | Docker Compose | Same pattern as both reference apps |
**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage.
**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references.
**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.
---
## Folder Structure
```
/volume2/docker/finance/finance-hub/
├── docker-compose.yml
├── .env
├── .env.example
├── .gitignore
├── backend/
│ ├── Dockerfile
│ ├── package.json
│ ├── prisma/
│ │ ├── schema.prisma
│ │ └── migrations/
│ │ ├── migration_lock.toml
│ │ └── 20260508_init/
│ │ └── migration.sql
│ └── src/
│ ├── index.js ← entry point (Authentik middleware wired here)
│ ├── auth.js ← Authentik header middleware (replaces JWT auth)
│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)
│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)
│ └── routes/
│ ├── payments.js ← existing routes + source/currency additions
│ └── upload.js ← NEW: POST /api/upload/csv
└── frontend/
├── Dockerfile
├── package.json
├── vite.config.js
├── tailwind.config.js
├── postcss.config.js
├── index.html
└── src/
├── main.jsx ← remove AuthProvider wrapper
├── index.css
├── App.jsx ← remove auth state, add Upload tab toggle
└── components/
├── FilterBar.jsx ← add source filter select
├── PaymentTable.jsx ← add Source badge column + currency display
├── PaymentCard.jsx ← minor source badge addition
├── PaymentList.jsx ← unchanged
└── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI
```
---
## Database Schema (Prisma)
File: `backend/prisma/schema.prisma`
```prisma
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
}
model Payment {
id Int @id @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
auth.js
auth.js
27 lines
const PUBLIC_PATHS = new Set([
'/api/health',
'/api/payments/ingest',
]);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) {
return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });
}
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '')
.split(',')
.map(g => g.trim())
.filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
Write
parser.js
parser.js
104 lines
/**
* Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)
*
* Supported formats:
*
* POS / INTERNET / ECOM / P2P payment:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM withdrawal:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM utility payment (amount may include fee as AMOUNT/FEE):
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.
*/
const LOCAL_TZ = process.env.TZ || 'Europe/Sofia';
/**
* Convert a local-timezone date/time to a UTC Date object.
* Uses Intl to resolve the actual UTC offset (DST-aware).
*/
function localToUtc(year, month, day, hour, minute) {
const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));
const formatter = new Intl.DateTimeFormat('en-US', {
timeZone: LOCAL_TZ,
year: 'numeric', month: '2-digit', day: '2-digit',
hour: '2-digit', minute: '2-digit', second: '2-digit',
hour12: false,
});
const parts = {};
formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });
const localAtNaive = new Date(Date.UTC(
parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),
parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),
));
const offsetMs = localAtNaive.getTime() - naive.getTime();
return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);
}
function parsePaymentSms(message) {
const result = {
rawMessage: message,
date: null,
type: null,
card: null,
recipient: null,
amount: null,
balance: null,
};
// Date and time: "Na DD/MM/YYYY v HH:MM"
const dateMatch = message.match(/Na (\d{2})\/(\d{2})\/(\d{4}) v (\d{2}):(\d{2})/i);
if (dateMatch) {
const [, day, month, year, hour, minute] = dateMatch;
result.date = localToUtc(
parseInt(year), parseInt(month), parseInt(day),
parseInt(hour), parseInt(minute),
);
}
// Card mask: "s karta 400915***4447" or "s karta 483890***7162"
const cardMatch = message.match(/s karta\s+([\d*]+)/i);
if (cardMatch) {
result.card = cardMatch[1];
}
// Transaction type: supports both prepositions
// "na POS" / "na ATM" / "na INTERNET" etc. (payment)
// "ot ATM" (withdrawal)
const typeMatch = message.match(/(?:na|ot)\s+(POS|ATM|INTERNET|ECOM|P2P)\b/i);
if (typeMatch) {
result.type = typeMatch[1].toUpperCase();
}
// Recipient address: "s adres: MERCHANT" or "s adres:MERCHANT" (no space variant)
const recipientMatch = message.match(/s adres:\s*([^.]+)\./i);
if (recipientMatch) {
result.recipient = recipientMatch[1].trim();
}
// Amount: handles both verbs and the AMOUNT/FEE suffix format
// "sa plateni 7.78 EUR"
// "sa iztegleni 400.00 EUR"
// "sa plateni 0.50 EUR/0.50 EUR" → captures 0.50 (the charged amount, ignoring fee)
const amountMatch = message.match(/sa (?:plateni|iztegleni)\s+([\d.,]+)\s+[A-Z]{3}/i);
if (amountMatch) {
result.amount = parseFloat(amountMatch[1].replace(',', '.'));
}
// Balance: "Nalichni: 2583.07 EUR."
const balanceMatch = message.match(/Nalichni:\s*([\d.,]+)\s+[A-Z]{3}/i);
if (balanceMatch) {
result.balance = parseFloat(balanceMatch[1].replace(',', '.'));
}
return result;
}
module.exports = { parsePaymentSms };
Write
csvParser.js
csvParser.js
175 lines
/**
* DSK Bank CSV parser — Node.js port of dskuploader.py
*
* DSK Bank exports use Windows-1251 (cp1251) encoding.
* Each row maps to a Payment record with source=UPLOAD, currency=BGN.
*/
const { parse } = require('csv-parse');
const iconv = require('iconv-lite');
const SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';
const CARD_REGEX = /^\d{6}x{6}\d{4}$/;
const POS_REGEX = /^\s*ПЛАЩАНЕ\s+НА\s+ПОС\s+\d{2}\.\d{2}\.\d{4}\s+\d{2}:\d{2}/;
const COL = {
DATE: 'Дата',
TYPE: 'Вид на трансакцията',
REASON: 'Основание',
DEBIT: 'Дебит BGN',
CREDIT: 'Кредит BGN',
PAYEE: 'Наредител/Получател',
ACCT: 'Номер сметка на наредителя / получателя',
};
const TAG_RULES = [
['reason', 'ЗАПЛАТА', 'Salary'],
['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],
['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],
['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],
['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],
['payee', 'VIVACOM', 'Subscriptions'],
['payee', 'Google', 'Subscriptions'],
['payee', 'SkyShowtime', 'Subscriptions'],
['payee', 'NETFLIX', 'Subscriptions'],
['payee', 'LUKOIL', 'Bills'],
['payee', 'CityGate', 'Bills'],
['payee', 'CBA', 'Groceries'],
['payee', 'FANTASTICO', 'Groceries'],
['payee', 'LIDL', 'Groceries'],
];
function parseNum(val) {
if (val == null || val === '') return null;
if (typeof val === 'number') return isNaN(val) ? null : val;
const s = String(val).trim().replace(/\xa0/g, '').replace(/ /g, '').replace(',', '.');
const n = parseFloat(s);
return isNaN(n) ? null : n;
}
function parseDate(val) {
if (!val) return null;
const s = String(val).trim();
const m = s.match(/^(\d{2})\.(\d{2})\.(\d{4})$/);
if (m) {
return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));
}
return null;
}
function processReasonAndCard(reason) {
if (!reason || typeof reason !== 'string') return { reason: '', card: null };
const parts = reason.trim().split(' ');
let card = null;
let cleanReason = reason.trim();
if (parts[0] && CARD_REGEX.test(parts[0])) {
card = parts[0];
cleanReason = parts.slice(1).join(' ').trim();
}
if (POS_REGEX.test(cleanReason)) {
const posParts = cleanReason.split('<br/>');
try {
const dateTime = posParts[0].split('ПОС ')[1];
cleanReason = `POS PAYMENT ${dateTime}`;
} catch (_) { /* keep original */ }
}
return { reason: cleanReason.replace(/\s+/g, ' ').trim(), card };
}
function generateTags(fields) {
const tags = new Set();
for (const [field, keyword, tagName] of TAG_RULES) {
if ((fields[field] || '').includes(keyword)) {
tags.add(tagName);
}
}
return Array.from(tags);
}
function processRow(row) {
const transactionType = (row[COL.TYPE] || '').trim();
if (transactionType === SKIP_TYPE) return null;
const { reason, card } = processReasonAndCard(row[COL.REASON]);
const payee = (row[COL.PAYEE] || '...
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Explorer (⇧⌘E)
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EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
report(1).csv, Editor Group 1
report(2).csv, Editor Group 1
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
Design new payment-logge…, Editor Group 2
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Design new payment-logger and dsk-uploader hybrid app
Session history
New session
Message actions
payments.js
payments.js
ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.
Thinking
Thinking
I'll explore all three reference projects in parallel to understand their structure before planning.
Agent:
Explore payment-logger app structure and functionality
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How data flows (ingest, storage, retrieval)
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.
Agent:
Explore dsk-uploader app structure and functionality
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How file uploads work - what files, what format, how parsed
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.
Agent:
Explore auth folder and authentik integration
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. What auth system is being used (Authentik)
2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?
3. Middleware - how is auth enforced on routes?
4. Any frontend auth flow - login redirect, token handling, protected routes
5. Environment variables related to auth
6. Docker/deployment setup for the auth service itself
7. Any example of how other apps integrate with this auth
Report with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.
Message actions
payments.js
payments.js
continue
Thinking
Thinking
Launching parallel exploration of all three reference projects.
Agent:
Explore payment-logger app structure
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How data is ingested (look at /ingest route especially)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore dsk-uploader app structure
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How file uploads work (what format, what processing happens)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore auth project structure
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. What authentication system is used (authentik integration details)
3. How OAuth/OIDC flow works
4. Any middleware or helper functions for protecting routes
5. Session management approach
6. How frontend handles auth state
7. Any example of how other apps integrate with this auth system
8. Docker setup and environment variables
Please read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.
Thinking
Thinking
Now I have a complete picture of all three. Let me design the plan.
Agent:
Design combined app architecture
IN
Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:
---
## App 1: payments-logger (Node.js)
- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI
- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS
- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage
- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)
- **Schema** (PostgreSQL via Prisma):
- `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at
- `tags` table: id, name, color — M2M with payments via `_PaymentToTag`
- `users` table: id, username, hashed_password (this will be REMOVED)
- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system
- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance
## App 2: dsk-uploader (Python/Flask)
- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database
- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5
- **Auth**: None (open)
- **CSV format** (DSK Bank Bulgarian format, columns):
- `Дата` (date, DD.MM.YYYY)
- `Вид на трансакцията` (transaction type, Bulgarian)
- `Основание` (reason/description — contains card number regex: `^\d{6}x{6}\d{4}$`)
- `Дебит BGN` (debit amount, may be empty)
- `Кредит BGN` (credit amount, may be empty)
- `Наредител/Получател` (orderer/recipient name)
- `Номер сметка на наредителя / получателя` (account number)
- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers
- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)
## App 3: auth (Authentik)
- **Mode**: Proxy mode via NPM (forward auth)
- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:
- `X-authentik-username`
- `X-authentik-email`
- `X-authentik-groups`
- **No code integration needed** in the app itself — just trust these headers from NPM
- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`
---
## What the New Combined App Must Do
1. **Single PostgreSQL database** for all transactions
2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST
3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema
4. **Unified UI** — show all payments in one table regardless of source
5. **Source indicator** in UI — badge showing "INGEST", "UPLOAD", or "BOTH" (if duplicate detection added)
6. **Source filter** in FilterBar — filter by All/Ingest/Upload
7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM
8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination
9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL
---
## Technical Constraints
- Keep Node.js backend (not Python) — extend payments-logger's stack
- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)
- File upload: use `multer` npm middleware
- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)
- Add `source` enum field (INGEST/UPLOAD) to payments schema
- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is
- Remove `users` table from schema
---
## Please Design
1. Complete folder structure for the new app (suggest name: "finance-hub" or similar — note this is a placeholder, user will confirm)
2. Prisma schema with new fields (`source`, `currency`)
3. All backend API routes
4. CSV parser design in Node.js (port of the Python logic)
5. Authentik auth middleware
6. Frontend component structure (React) — what's reused from payments-logger, what's new
7. Docker Compose setup
8. Environment variables needed
9. Step-by-step implementation order
10. Verification checklist
Be specific about file paths and code structure. This will be used to write actual implementation code.
Thinking
Thinking
Good plan. Let me ask the one thing I need before writing the final plan.
AskUserQuestion
OUT
User has answered your questions: "What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding."="finance-hub". You can now continue with the user's answers in mind.
Thinking
Thinking
Writing the final plan now.
Thinking
Thinking
Write
ets-create-a-new-generic-sun.md
ets-create-a-new-generic-sun.md
326 lines
# finance-hub — Implementation Plan
## Context
Two separate finance apps exist as references and will be retired:
- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.
- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.
The new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).
---
## Tech Stack
| Layer | Choice | Rationale |
|-------|--------|-----------|
| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |
| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |
| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |
| Database | PostgreSQL 16 | Same as payments-logger |
| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |
| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |
| Container | Docker Compose | Same pattern as both reference apps |
**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage.
**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references.
**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.
---
## Folder Structure
```
/volume2/docker/finance/finance-hub/
├── docker-compose.yml
├── .env
├── .env.example
├── .gitignore
├── backend/
│ ├── Dockerfile
│ ├── package.json
│ ├── prisma/
│ │ ├── schema.prisma
│ │ └── migrations/
│ │ ├── migration_lock.toml
│ │ └── 20260508_init/
│ │ └── migration.sql
│ └── src/
│ ├── index.js ← entry point (Authentik middleware wired here)
│ ├── auth.js ← Authentik header middleware (replaces JWT auth)
│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)
│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)
│ └── routes/
│ ├── payments.js ← existing routes + source/currency additions
│ └── upload.js ← NEW: POST /api/upload/csv
└── frontend/
├── Dockerfile
├── package.json
├── vite.config.js
├── tailwind.config.js
├── postcss.config.js
├── index.html
└── src/
├── main.jsx ← remove AuthProvider wrapper
├── index.css
├── App.jsx ← remove auth state, add Upload tab toggle
└── components/
├── FilterBar.jsx ← add source filter select
├── PaymentTable.jsx ← add Source badge column + currency display
├── PaymentCard.jsx ← minor source badge addition
├── PaymentList.jsx ← unchanged
└── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI
```
---
## Database Schema (Prisma)
File: `backend/prisma/schema.prisma`
```prisma
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
}
model Payment {
id Int @id @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
auth.js
auth.js
27 lines
const PUBLIC_PATHS = new Set([
'/api/health',
'/api/payments/ingest',
]);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) {
return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });
}
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '')
.split(',')
.map(g => g.trim())
.filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
Write
parser.js
parser.js
104 lines
/**
* Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)
*
* Supported formats:
*
* POS / INTERNET / ECOM / P2P payment:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM withdrawal:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM utility payment (amount may include fee as AMOUNT/FEE):
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.
*/
const LOCAL_TZ = process.env.TZ || 'Europe/Sofia';
/**
* Convert a local-timezone date/time to a UTC Date object.
* Uses Intl to resolve the actual UTC offset (DST-aware).
*/
function localToUtc(year, month, day, hour, minute) {
const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));
const formatter = new Intl.DateTimeFormat('en-US', {
timeZone: LOCAL_TZ,
year: 'numeric', month: '2-digit', day: '2-digit',
hour: '2-digit', minute: '2-digit', second: '2-digit',
hour12: false,
});
const parts = {};
formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });
const localAtNaive = new Date(Date.UTC(
parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),
parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),
));
const offsetMs = localAtNaive.getTime() - naive.getTime();
return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);
}
function parsePaymentSms(message) {
const result = {
rawMessage: message,
date: null,
type: null,
card: null,
recipient: null,
amount: null,
balance: null,
};
// Date and time: "Na DD/MM/YYYY v HH:MM"
const dateMatch = message.match(/Na (\d{2})\/(\d{2})\/(\d{4}) v (\d{2}):(\d{2})/i);
if (dateMatch) {
const [, day, month, year, hour, minute] = dateMatch;
result.date = localToUtc(
parseInt(year), parseInt(month), parseInt(day),
parseInt(hour), parseInt(minute),
);
}
// Card mask: "s karta 400915***4447" or "s karta 483890***7162"
const cardMatch = message.match(/s karta\s+([\d*]+)/i);
if (cardMatch) {
result.card = cardMatch[1];
}
// Transaction type: supports both prepositions
// "na POS" / "na ATM" / "na INTERNET" etc. (payment)
// "ot ATM" (withdrawal)
const typeMatch = message.match(/(?:na|ot)\s+(POS|ATM|INTERNET|ECOM|P2P)\b/i);
if (typeMatch) {
result.type = typeMatch[1].toUpperCase();
}
// Recipient address: "s adres: MERCHANT" or "s adres:MERCHANT" (no space variant)
const recipientMatch = message.match(/s adres:\s*([^.]+)\./i);
if (recipientMatch) {
result.recipient = recipientMatch[1].trim();
}
// Amount: handles both verbs and the AMOUNT/FEE suffix format
// "sa plateni 7.78 EUR"
// "sa iztegleni 400.00 EUR"
// "sa plateni 0.50 EUR/0.50 EUR" → captures 0.50 (the charged amount, ignoring fee)
const amountMatch = message.match(/sa (?:plateni|iztegleni)\s+([\d.,]+)\s+[A-Z]{3}/i);
if (amountMatch) {
result.amount = parseFloat(amountMatch[1].replace(',', '.'));
}
// Balance: "Nalichni: 2583.07 EUR."
const balanceMatch = message.match(/Nalichni:\s*([\d.,]+)\s+[A-Z]{3}/i);
if (balanceMatch) {
result.balance = parseFloat(balanceMatch[1].replace(',', '.'));
}
return result;
}
module.exports = { parsePaymentSms };
Write
csvParser.js
csvParser.js
175 lines
/**
* DSK Bank CSV parser — Node.js port of dskuploader.py
*
* DSK Bank exports use Windows-1251 (cp1251) encoding.
* Each row maps to a Payment record with source=UPLOAD, currency=BGN.
*/
const { parse } = require('csv-parse');
const iconv = require('iconv-lite');
const SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';
const CARD_REGEX = /^\d{6}x{6}\d{4}$/;
const POS_REGEX = /^\s*ПЛАЩАНЕ\s+НА\s+ПОС\s+\d{2}\.\d{2}\.\d{4}\s+\d{2}:\d{2}/;
const COL = {
DATE: 'Дата',
TYPE: 'Вид на трансакцията',
REASON: 'Основание',
DEBIT: 'Дебит BGN',
CREDIT: 'Кредит BGN',
PAYEE: 'Наредител/Получател',
ACCT: 'Номер сметка на наредителя / получателя',
};
const TAG_RULES = [
['reason', 'ЗАПЛАТА', 'Salary'],
['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],
['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],
['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],
['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],
['payee', 'VIVACOM', 'Subscriptions'],
['payee', 'Google', 'Subscriptions'],
['payee', 'SkyShowtime', 'Subscriptions'],
['payee', 'NETFLIX', 'Subscriptions'],
['payee', 'LUKOIL', 'Bills'],
['payee', 'CityGate', 'Bills'],
['payee', 'CBA', 'Groceries'],
['payee', 'FANTASTICO', 'Groceries'],
['payee', 'LIDL', 'Groceries'],
];
function parseNum(val) {
if (val == null || val === '') return null;
if (typeof val === 'number') return isNaN(val) ? null : val;
const s = String(val).trim().replace(/\xa0/g, '').replace(/ /g, '').replace(',', '.');
const n = parseFloat(s);
return isNaN(n) ? null : n;
}
function parseDate(val) {
if (!val) return null;
const s = String(val).trim();
const m = s.match(/^(\d{2})\.(\d{2})\.(\d{4})$/);
if (m) {
return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));
}
return null;
}
function processReasonAndCard(reason) {
if (!reason || typeof reason !== 'string') return { reason: '', card: null };
const parts = reason.trim().split(' ');
let card = null;
let cleanReason = reason.trim();
if (parts[0] && CARD_REGEX.test(parts[0])) {
card = parts[0];
cleanReason = parts.slice(1).join(' ').trim();
}
if (POS_REGEX.test(cleanReason)) {
const posParts = cleanReason.split('<br/>');
try {
const dateTime = posParts[0].split('ПОС ')[1];
cleanReason = `POS PAYMENT ${dateTime}`;
} catch (_) { /* keep original */ }
}
return { reason: cleanReason.replace(/\s+/g, ' ').trim(), card };
}
function generateTags(fields) {
const tags = new Set();
for (const [field, keyword, tagName] of TAG_RULES) {
if ((fields[field] || '').includes(keyword)) {
tags.add(tagName);
}
}
return Array.from(tags);
}
function processRow(row) {
const transactionType = (row[COL.TYPE] || '').trim();
if (transactionType === SKIP_TYPE) return null;
const { reason, card } = processReasonAndCard(row[COL.REASON]);
const payee = (row[COL.PAYEE] || '...
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It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"I'll explore all three reference projects in parallel to understand their structure before planning.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How data flows (ingest, storage, retrieval)\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How file uploads work - what files, what format, how parsed\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth folder and authentik integration","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. What auth system is being used (Authentik)\n2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?\n3. Middleware - how is auth enforced on routes?\n4. Any frontend auth flow - login redirect, token handling, protected routes\n5. Environment variables related to auth\n6. Docker/deployment setup for the auth service itself\n7. Any example of how other apps integrate with this auth\n\nReport with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"payments.js","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"continue","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Launching parallel exploration of all three reference projects.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How data is ingested (look at /ingest route especially)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How file uploads work (what format, what processing happens)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth project structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. What authentication system is used (authentik integration details)\n3. How OAuth/OIDC flow works\n4. Any middleware or helper functions for protecting routes\n5. Session management approach\n6. How frontend handles auth state\n7. Any example of how other apps integrate with this auth system\n8. Docker setup and environment variables\n\nPlease read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now I have a complete picture of all three. Let me design the plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design combined app architecture","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:\n\n---\n\n## App 1: payments-logger (Node.js)\n- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI\n- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS\n- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage\n- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)\n- **Schema** (PostgreSQL via Prisma):\n - `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at\n - `tags` table: id, name, color — M2M with payments via `_PaymentToTag`\n - `users` table: id, username, hashed_password (this will be REMOVED)\n- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system\n- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance\n\n## App 2: dsk-uploader (Python/Flask)\n- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database\n- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5\n- **Auth**: None (open)\n- **CSV format** (DSK Bank Bulgarian format, columns):\n - `Дата` (date, DD.MM.YYYY)\n - `Вид на трансакцията` (transaction type, Bulgarian)\n - `Основание` (reason/description — contains card number regex: `^\\d{6}x{6}\\d{4}$`)\n - `Дебит BGN` (debit amount, may be empty)\n - `Кредит BGN` (credit amount, may be empty)\n - `Наредител/Получател` (orderer/recipient name)\n - `Номер сметка на наредителя / получателя` (account number)\n- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers\n- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)\n\n## App 3: auth (Authentik)\n- **Mode**: Proxy mode via NPM (forward auth)\n- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:\n - `X-authentik-username` \n - `X-authentik-email`\n - `X-authentik-groups`\n- **No code integration needed** in the app itself — just trust these headers from NPM\n- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`\n\n---\n\n## What the New Combined App Must Do\n\n1. **Single PostgreSQL database** for all transactions\n2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST\n3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema\n4. **Unified UI** — show all payments in one table regardless of source\n5. **Source indicator** in UI — badge showing \"INGEST\", \"UPLOAD\", or \"BOTH\" (if duplicate detection added)\n6. **Source filter** in FilterBar — filter by All/Ingest/Upload\n7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM\n8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination\n9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL\n\n---\n\n## Technical Constraints\n\n- Keep Node.js backend (not Python) — extend payments-logger's stack\n- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)\n- File upload: use `multer` npm middleware\n- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)\n- Add `source` enum field (INGEST/UPLOAD) to payments schema\n- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is\n- Remove `users` table from schema\n\n---\n\n## Please Design\n\n1. Complete folder structure for the new app (suggest name: \"finance-hub\" or similar — note this is a placeholder, user will confirm)\n2. Prisma schema with new fields (`source`, `currency`)\n3. All backend API routes\n4. CSV parser design in Node.js (port of the Python logic)\n5. Authentik auth middleware\n6. Frontend component structure (React) — what's reused from payments-logger, what's new\n7. Docker Compose setup\n8. Environment variables needed\n9. Step-by-step implementation order\n10. Verification checklist\n\nBe specific about file paths and code structure. This will be used to write actual implementation code.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good plan. Let me ask the one thing I need before writing the final plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"AskUserQuestion","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"OUT","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"User has answered your questions: \"What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding.\"=\"finance-hub\". You can now continue with the user's answers in mind.","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Writing the final plan now.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"326 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# finance-hub — Implementation Plan\n\n## Context\n\nTwo separate finance apps exist as references and will be retired:\n- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.\n- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.\n\nThe new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).\n\n---\n\n## Tech Stack\n\n| Layer | Choice | Rationale |\n|-------|--------|-----------|\n| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |\n| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |\n| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |\n| Database | PostgreSQL 16 | Same as payments-logger |\n| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |\n| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |\n| Container | Docker Compose | Same pattern as both reference apps |\n\n**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage. \n**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references. \n**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.\n\n---\n\n## Folder Structure\n\n```\n/volume2/docker/finance/finance-hub/\n├── docker-compose.yml\n├── .env\n├── .env.example\n├── .gitignore\n├── backend/\n│ ├── Dockerfile\n│ ├── package.json\n│ ├── prisma/\n│ │ ├── schema.prisma\n│ │ └── migrations/\n│ │ ├── migration_lock.toml\n│ │ └── 20260508_init/\n│ │ └── migration.sql\n│ └── src/\n│ ├── index.js ← entry point (Authentik middleware wired here)\n│ ├── auth.js ← Authentik header middleware (replaces JWT auth)\n│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)\n│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)\n│ └── routes/\n│ ├── payments.js ← existing routes + source/currency additions\n│ └── upload.js ← NEW: POST /api/upload/csv\n└── frontend/\n ├── Dockerfile\n ├── package.json\n ├── vite.config.js\n ├── tailwind.config.js\n ├── postcss.config.js\n ├── index.html\n └── src/\n ├── main.jsx ← remove AuthProvider wrapper\n ├── index.css\n ├── App.jsx ← remove auth state, add Upload tab toggle\n └── components/\n ├── FilterBar.jsx ← add source filter select\n ├── PaymentTable.jsx ← add Source badge column + currency display\n ├── PaymentCard.jsx ← minor source badge addition\n ├── PaymentList.jsx ← unchanged\n └── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI\n```\n\n---\n\n## Database Schema (Prisma)\n\nFile: `backend/prisma/schema.prisma`\n\n```prisma\ngenerator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status { UNPROCESSED SENT SKIPPED }\nenum Source { INGEST UPLOAD }\n```\n\n**Key decisions:**\n- No `User` model — Authentik owns identity.\n- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.\n- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.\n- `balance` is always null for CSV rows (DSK export does not include running balance).\n- Fresh consolidated migration — no data migration from reference apps required.\n\n---\n\n## API Routes\n\n| Method | Path | Auth | Description |\n|--------|------|------|-------------|\n| GET | /api/health | public | Health check |\n| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |\n| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |\n| GET | /api/payments/meta/tags | required | All tags |\n| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |\n| GET | /api/payments/:id | required | Single payment |\n| PATCH | /api/payments/:id | required | Update status |\n| DELETE | /api/payments/:id | required | Delete |\n| POST | /api/payments/:id/send | required | Send notification |\n| POST | /api/payments/:id/skip | required | Skip |\n| POST | /api/payments/:id/tags | required | Add/upsert tag |\n| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |\n| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |\n\n---\n\n## Key Implementation Details\n\n### auth.js (replaces entire old auth module)\n```js\nconst PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n const username = req.headers['x-authentik-username'];\n if (!username) return res.status(401).json({ error: 'Unauthorized' });\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),\n };\n next();\n}\nmodule.exports = { authentikMiddleware };\n```\n\n### csvParser.js (port of dskuploader.py)\n- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8\n- `csv-parse` parses the decoded text with `columns: true`\n- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`\n- Card extraction: regex `/^\\d{6}x{6}\\d{4}$/` on first token of `Основание`\n- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`\n- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`\n- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`\n\n### payments.js changes from payments-logger\n1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call\n2. Add `source` to the `GET /` where clause filter\n3. Add `sources` to `meta/filters` response\n4. Currency-aware amount formatting in notification message\n5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)\n\n### upload.js (new)\n- `multer` memory storage, max 10 files × 10 MB\n- Calls `parseDskCsv(buffer)` per file\n- Upserts tags via `prisma.tag.upsert` then connects\n- Returns `{ imported, skipped, errors, payments[] }`\n\n### Frontend changes\n- **Delete**: `auth.js`, `AuthProvider.jsx`\n- **main.jsx**: Remove `<AuthProvider>` wrapper\n- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add \"Payments\" / \"Upload CSV\" tab toggle\n- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols\n- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell\n- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`\n\n---\n\n## Docker Compose\n\n```yaml\nservices:\n db:\n image: postgres:16-alpine\n environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: ${DB_PASSWORD}, POSTGRES_DB: finance_hub }\n volumes: [pgdata:/var/lib/postgresql/data]\n healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }\n\n backend:\n build: ./backend\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports: [\"${BACKEND_PORT:-3001}:3001\"]\n depends_on: { db: { condition: service_healthy } }\n\n frontend:\n build: ./frontend\n ports: [\"${FRONTEND_PORT:-5175}:5173\"]\n depends_on: [backend]\n\nvolumes: { pgdata: }\n```\n\n**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.\n\n---\n\n## Environment Variables (.env)\n\n```bash\nDB_PASSWORD=change_me\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\nTZ=Europe/Sofia\nBACKEND_PORT=3001\nFRONTEND_PORT=5175\n```\n\nRemoved vs payments-logger: `JWT_SECRET`, `JWT_EXPIRE_MINUTES`.\n\n---\n\n## Implementation Order\n\n1. Create folder structure and write `docker-compose.yml`, `.env.example`, `.gitignore`\n2. Write `backend/prisma/schema.prisma` and migration SQL\n3. Write `backend/package.json` (add `csv-parse`, `iconv-lite`, `multer`; remove `bcryptjs`, `jose`)\n4. Write `backend/Dockerfile`\n5. Write `backend/src/auth.js` (Authentik middleware)\n6. Copy `backend/src/parser.js` verbatim from payments-logger\n7. Write `backend/src/csvParser.js` (Python port)\n8. Write `backend/src/routes/upload.js`\n9. Write `backend/src/routes/payments.js` (from payments-logger + 5 changes listed above)\n10. Write `backend/src/index.js`\n11. Copy frontend base from payments-logger; delete `auth.js` + `AuthProvider.jsx`\n12. Update `main.jsx`, `App.jsx`, `FilterBar.jsx`, `PaymentTable.jsx`\n13. Write `frontend/src/components/UploadPanel.jsx`\n14. Update `frontend/vite.config.js`\n15. `docker compose build && docker compose up -d`\n16. Run verification checklist\n\n---\n\n## Verification\n\n**Schema**\n- `payments` table has `source`, `currency`, `debit_bgn`, `credit_bgn`, `transaction_type`, `payer_account`\n- No `users` table; `Source` enum exists\n\n**Auth**\n- `GET /api/payments` → 401 without `x-authentik-username` header\n- `POST /api/payments/ingest` → 201 without any header\n- `curl -H \"x-authentik-username: test\" localhost:3001/api/payments` → 200\n\n**SMS Ingest**\n- DSK POS SMS → `source=INGEST`, `currency=EUR`, correct amount/card/recipient\n- Apple Wallet structured body → `type=WALLET`, `source=INGEST`\n- Rate limiter → 429 after 200 req/min\n\n**CSV Upload**\n- Single DSK CSV → rows with `source=UPLOAD`, `currency=BGN`\n- Multiple CSVs in one request → all merged\n- `ТРАНСФЕР СОБСТВЕНИ СМЕТКИ` rows counted in `skipped`, not imported\n- Card regex match from `Основание` column\n- Auto-tags applied (ЗАПЛАТА→Salary, LIDL→Groceries)\n- cp1251 file imports correctly\n\n**UI**\n- Source badge visible in payment table (SMS indigo, CSV emerald)\n- Source dropdown in FilterBar filters correctly\n- Amount shows correct currency per row\n- Upload Panel: drag-and-drop works, result summary shows counts\n- Logout redirects to Authentik sign_out\n- No login form shown (Authentik handles it at NPM level)\n- Tags, send, skip, delete all still work\n\n## Reference Files\n\n- `/volume2/docker/finance/payments-logger/backend/src/routes/payments.js`\n- `/volume2/docker/finance/payments-logger/backend/src/parser.js`\n- `/volume2/docker/finance/payments-logger/backend/src/index.js`\n- `/volume2/docker/finance/payments-logger/backend/src/auth.js`\n- `/volume2/docker/finance/payments-logger/backend/prisma/schema.prisma`\n- `/volume2/docker/finance/payments-logger/frontend/src/App.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/PaymentTable.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/FilterBar.jsx`\n- `/volume2/docker/finance/dsk-uploader/dskuploader.py`\n- `/volume2/docker/finance/auth/docker-compose.yml`","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Claude’s Plan","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Stayed in plan mode","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good question. Here's the full breakdown:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Backend Tech Stack — Options","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Backend Tech Stack — Options","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Why:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"payments-logger is already Node.js/Express/Prisma. The new app is 80% payments-logger with CSV upload added on top. Keeping the same stack means:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"verbatim, zero rewrite","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy the entire","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"routes/payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with minimal edits","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Same Prisma schema workflow, same migrations, same Docker image","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The CSV parsing logic (the only Python-specific thing) ports cleanly to","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"csv-parse","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— it's just regex + string manipulation, nothing pandas-specific","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Trade-off:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Have to port the Python CSV parsing to JS. It's ~150 lines and mostly string manipulation — straightforward.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option B: Python + FastAPI + SQLAlchemy","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option B: Python + FastAPI + SQLAlchemy","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rewrite everything in Python. dsk-uploader is Python, so CSV parsing is already done.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep the dsk-uploader CSV logic as-is (no porting). Python has better data science libraries if you later add analytics.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Lose the entire payments-logger backend (routes, parser, Prisma schema) — full rewrite. FastAPI + SQLAlchemy is a different mental model than Express + Prisma. Frontend stays React anyway, so the stack split doesn't simplify anything.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"More work overall, gains almost nothing.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep Node.js as the main API, add a separate Python FastAPI service just for CSV parsing. They share the DB.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Zero porting — Python CSV code used as-is.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two backend services to maintain, deploy, and keep in sync. Inter-service HTTP calls. Two Dockerfiles. For ~150 lines of CSV logic, this is massively over-engineered.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Not worth it.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Extend dsk-uploader into a full payments app.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pandas for CSV, no porting.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Jinja2 templates instead of React (or add React separately). Would need to reimplement the entire payments-logger (SMS parser, notification system, tag management, pagination/filtering). Flask's Jinja templating is far less capable than the existing React UI. The React frontend is the stronger UI foundation.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Worst of all options — rebuild the harder parts (UI, SMS parser, notification) for no gain.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Summary","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Summary","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"CSV porting effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"App rewrite effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Result 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Everything else in the plan reuses payments-logger code directly. That's why Node.js is the clear winner here.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Want to adjust the stack, or shall I proceed with Option A?","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ok sounds good. Implement all you suggested","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Starting implementation. Let me first read all the reference files I'll need to copy from.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"payments.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"App.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"App.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"FilterBar.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"FilterBar.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentTable.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentTable.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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payments-logger.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.css","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.css","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"vite.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"vite.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"tailwind.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"tailwind.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"postcss.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"postcss.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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components.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentCard.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentCard.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentList.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentList.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"schema.prisma","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"schema.prisma","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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Let me set up the todo list and start building.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create finance-hub directory structure","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"mkdir -p /volume2/docker/finance/finance-hub/backend/src/routes \\\n /volume2/docker/finance/finance-hub/backend/prisma/migrations/20260508_init \\\n /volume2/docker/finance/finance-hub/frontend/src/components && echo \"done\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":24,"on_screen":false,"help_text":"Copy code","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"OUT","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"done","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"docker-compose.yml","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"docker-compose.yml","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"45 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"version: '3.8'\n\nservices:\n db:\n image: postgres:16-alpine\n restart: unless-stopped\n environment:\n POSTGRES_USER: finance\n POSTGRES_PASSWORD: ${DB_PASSWORD}\n POSTGRES_DB: finance_hub\n volumes:\n - pgdata:/var/lib/postgresql/data\n healthcheck:\n test: [\"CMD-SHELL\", \"pg_isready -U finance -d finance_hub\"]\n interval: 5s\n timeout: 5s\n retries: 5\n\n backend:\n build: ./backend\n restart: unless-stopped\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports:\n - \"${BACKEND_PORT:-3001}:3001\"\n depends_on:\n db:\n condition: service_healthy\n\n frontend:\n build: ./frontend\n restart: unless-stopped\n ports:\n - \"${FRONTEND_PORT:-5175}:5173\"\n depends_on:\n - backend\n\nvolumes:\n pgdata:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".env.example","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".env.example","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"15 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Database\nDB_PASSWORD=change_me_strong_password\n\n# Notifier service (for SMS payment notifications)\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\n\n# Timezone (used by SMS parser for Bulgarian bank timestamps)\nTZ=Europe/Sofia\n\n# Ports (optional — defaults shown)\nBACKEND_PORT=3001\nFRONTEND_PORT=5175","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".gitignore","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".gitignore","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"5 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env\nnode_modules/\ndist/\n*.log","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"schema.prisma","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"schema.prisma","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"54 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"generator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status {\n UNPROCESSED\n SENT\n SKIPPED\n}\n\nenum Source {\n INGEST\n UPLOAD\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration.sql","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration.sql","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"55 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- CreateEnum\nCREATE TYPE \"Status\" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');\nCREATE TYPE \"Source\" AS ENUM ('INGEST', 'UPLOAD');\n\n-- CreateTable\nCREATE TABLE \"payments\" (\n \"id\" SERIAL PRIMARY KEY,\n \"raw_message\" TEXT NOT NULL,\n \"date\" TIMESTAMP(3),\n \"type\" TEXT,\n \"card\" TEXT,\n \"recipient\" TEXT,\n \"amount\" DOUBLE PRECISION,\n \"currency\" TEXT DEFAULT 'EUR',\n \"balance\" DOUBLE PRECISION,\n \"source\" \"Source\" NOT NULL DEFAULT 'INGEST',\n \"status\" \"Status\" NOT NULL DEFAULT 'UNPROCESSED',\n \"notified_at\" TIMESTAMP(3),\n \"notify_phone\" TEXT,\n \"debit_bgn\" DOUBLE PRECISION,\n \"credit_bgn\" DOUBLE PRECISION,\n \"transaction_type\" TEXT,\n \"payer_account\" TEXT,\n \"created_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,\n \"updated_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP\n);\n\n-- CreateTable\nCREATE TABLE \"tags\" (\n \"id\" SERIAL PRIMARY KEY,\n \"name\" TEXT NOT NULL,\n \"color\" TEXT NOT NULL DEFAULT '#6b7280'\n);\n\n-- CreateUniqueIndex\nCREATE UNIQUE INDEX \"tags_name_key\" ON \"tags\"(\"name\");\n\n-- CreateTable (M2M join)\nCREATE TABLE \"_PaymentToTag\" (\n \"A\" INTEGER NOT NULL,\n \"B\" INTEGER NOT NULL,\n CONSTRAINT \"_PaymentToTag_AB_pkey\" PRIMARY KEY (\"A\", \"B\")\n);\n\nCREATE INDEX \"_PaymentToTag_B_index\" ON \"_PaymentToTag\"(\"B\");\n\n-- AddForeignKey\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_A_fkey\"\n FOREIGN KEY (\"A\") REFERENCES \"payments\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;\n\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_B_fkey\"\n FOREIGN KEY (\"B\") REFERENCES \"tags\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration_lock.toml","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration_lock.toml","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"4 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Please do not edit this file manually\n# It should be added in your version-control system (e.g., Git)\nprovider = \"postgresql\"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"26 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"{\n \"name\": \"finance-hub-backend\",\n \"version\": \"1.0.0\",\n \"main\": \"src/index.js\",\n \"scripts\": {\n \"start\": \"node src/index.js\",\n \"dev\": \"nodemon src/index.js\",\n \"prisma:generate\": \"prisma generate\",\n \"prisma:migrate\": \"prisma migrate deploy\"\n },\n \"dependencies\": {\n \"@prisma/client\": \"^5.22.0\",\n \"cors\": \"^2.8.5\",\n \"csv-parse\": \"^5.5.6\",\n \"express\": \"^4.21.1\",\n \"express-rate-limit\": \"^7.4.0\",\n \"iconv-lite\": \"^0.6.3\",\n \"morgan\": \"^1.10.0\",\n \"multer\": \"^1.4.5-lts.1\"\n },\n \"devDependencies\": {\n \"nodemon\": \"^3.1.7\",\n \"prisma\": \"^5.22.0\"\n }\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"18 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"FROM node:20-alpine\n\nRUN apk add --no-cache openssl\n\nWORKDIR /app\n\nCOPY package.json package-lock.json* ./\nRUN npm install\n\nCOPY prisma ./prisma\nRUN npx prisma generate\n\nCOPY src ./src\n\nEXPOSE 3001\n\nCMD [\"sh\", \"-c\", \"npx prisma migrate deploy && node src/index.js\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"auth.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"auth.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"27 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const PUBLIC_PATHS = new Set([\n '/api/health',\n '/api/payments/ingest',\n]);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n\n const username = req.headers['x-authentik-username'];\n if (!username) {\n return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });\n }\n\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '')\n .split(',')\n .map(g => g.trim())\n .filter(Boolean),\n };\n\n next();\n}\n\nmodule.exports = { authentikMiddleware };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"104 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/**\n * Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)\n *\n * Supported formats:\n *\n * POS / INTERNET / ECOM / P2P payment:\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.\n *\n * ATM withdrawal:\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.\n *\n * ATM utility payment (amount may include fee as AMOUNT/FEE):\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.\n */\n\nconst LOCAL_TZ = process.env.TZ || 'Europe/Sofia';\n\n/**\n * Convert a local-timezone date/time to a UTC Date object.\n * Uses Intl to resolve the actual UTC offset (DST-aware).\n */\nfunction localToUtc(year, month, day, hour, minute) {\n const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));\n\n const formatter = new Intl.DateTimeFormat('en-US', {\n timeZone: LOCAL_TZ,\n year: 'numeric', month: '2-digit', day: '2-digit',\n hour: '2-digit', minute: '2-digit', second: '2-digit',\n hour12: false,\n });\n\n const parts = {};\n formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });\n\n const localAtNaive = new Date(Date.UTC(\n parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),\n parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),\n ));\n\n const offsetMs = localAtNaive.getTime() - naive.getTime();\n return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);\n}\n\nfunction parsePaymentSms(message) {\n const result = {\n rawMessage: message,\n date: null,\n type: null,\n card: null,\n recipient: null,\n amount: null,\n balance: null,\n };\n\n // Date and time: \"Na DD/MM/YYYY v HH:MM\"\n const dateMatch = message.match(/Na (\\d{2})\\/(\\d{2})\\/(\\d{4}) v (\\d{2}):(\\d{2})/i);\n if (dateMatch) {\n const [, day, month, year, hour, minute] = dateMatch;\n result.date = localToUtc(\n parseInt(year), parseInt(month), parseInt(day),\n parseInt(hour), parseInt(minute),\n );\n }\n\n // Card mask: \"s karta 400915***4447\" or \"s karta 483890***7162\"\n const cardMatch = message.match(/s karta\\s+([\\d*]+)/i);\n if (cardMatch) {\n result.card = cardMatch[1];\n }\n\n // Transaction type: supports both prepositions\n // \"na POS\" / \"na ATM\" / \"na INTERNET\" etc. (payment)\n // \"ot ATM\" (withdrawal)\n const typeMatch = message.match(/(?:na|ot)\\s+(POS|ATM|INTERNET|ECOM|P2P)\\b/i);\n if (typeMatch) {\n result.type = typeMatch[1].toUpperCase();\n }\n\n // Recipient address: \"s adres: MERCHANT\" or \"s adres:MERCHANT\" (no space variant)\n const recipientMatch = message.match(/s adres:\\s*([^.]+)\\./i);\n if (recipientMatch) {\n result.recipient = recipientMatch[1].trim();\n }\n\n // Amount: handles both verbs and the AMOUNT/FEE suffix format\n // \"sa plateni 7.78 EUR\"\n // \"sa iztegleni 400.00 EUR\"\n // \"sa plateni 0.50 EUR/0.50 EUR\" → captures 0.50 (the charged amount, ignoring fee)\n const amountMatch = message.match(/sa (?:plateni|iztegleni)\\s+([\\d.,]+)\\s+[A-Z]{3}/i);\n if (amountMatch) {\n result.amount = parseFloat(amountMatch[1].replace(',', '.'));\n }\n\n // Balance: \"Nalichni: 2583.07 EUR.\"\n const balanceMatch = message.match(/Nalichni:\\s*([\\d.,]+)\\s+[A-Z]{3}/i);\n if (balanceMatch) {\n result.balance = parseFloat(balanceMatch[1].replace(',', '.'));\n }\n\n return result;\n}\n\nmodule.exports = { parsePaymentSms };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"csvParser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"csvParser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"175 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/**\n * DSK Bank CSV parser — Node.js port of dskuploader.py\n *\n * DSK Bank exports use Windows-1251 (cp1251) encoding.\n * Each row maps to a Payment record with source=UPLOAD, currency=BGN.\n */\n\nconst { parse } = require('csv-parse');\nconst iconv = require('iconv-lite');\n\nconst SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';\nconst CARD_REGEX = /^\\d{6}x{6}\\d{4}$/;\nconst POS_REGEX = /^\\s*ПЛАЩАНЕ\\s+НА\\s+ПОС\\s+\\d{2}\\.\\d{2}\\.\\d{4}\\s+\\d{2}:\\d{2}/;\n\nconst COL = {\n DATE: 'Дата',\n TYPE: 'Вид на трансакцията',\n REASON: 'Основание',\n DEBIT: 'Дебит BGN',\n CREDIT: 'Кредит BGN',\n PAYEE: 'Наредител/Получател',\n ACCT: 'Номер сметка на наредителя / получателя',\n};\n\nconst TAG_RULES = [\n ['reason', 'ЗАПЛАТА', 'Salary'],\n ['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],\n ['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],\n ['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],\n ['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],\n ['payee', 'VIVACOM', 'Subscriptions'],\n ['payee', 'Google', 'Subscriptions'],\n ['payee', 'SkyShowtime', 'Subscriptions'],\n ['payee', 'NETFLIX', 'Subscriptions'],\n ['payee', 'LUKOIL', 'Bills'],\n ['payee', 'CityGate', 'Bills'],\n ['payee', 'CBA', 'Groceries'],\n ['payee', 'FANTASTICO', 'Groceries'],\n ['payee', 'LIDL', 'Groceries'],\n];\n\nfunction parseNum(val) {\n if (val == null || val === '') return null;\n if (typeof val === 'number') return isNaN(val) ? null : val;\n const s = String(val).trim().replace(/\\xa0/g, '').replace(/ /g, '').replace(',', '.');\n const n = parseFloat(s);\n return isNaN(n) ? null : n;\n}\n\nfunction parseDate(val) {\n if (!val) return null;\n const s = String(val).trim();\n const m = s.match(/^(\\d{2})\\.(\\d{2})\\.(\\d{4})$/);\n if (m) {\n return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));\n }\n return null;\n}\n\nfunction processReasonAndCard(reason) {\n if (!reason || typeof reason !== 'string') return { reason: '', card: null };\n\n const parts = reason.trim().split(' ');\n let card = null;\n let cleanReason = reason.trim();\n\n if (parts[0] && CARD_REGEX.test(parts[0])) {\n card = parts[0];\n cleanReason = parts.slice(1).join(' ').trim();\n }\n\n if (POS_REGEX.test(cleanReason)) {\n const posParts = cleanReason.split('<br/>');\n try {\n const dateTime = posParts[0].split('ПОС ')[1];\n cleanReason = `POS PAYMENT ${dateTime}`;\n } catch (_) { /* keep original */ }\n }\n\n return { reason: cleanReason.replace(/\\s+/g, ' ').trim(), card };\n}\n\nfunction generateTags(fields) {\n const tags = new Set();\n for (const [field, keyword, tagName] of TAG_RULES) {\n if ((fields[field] || '').includes(keyword)) {\n tags.add(tagName);\n }\n }\n return Array.from(tags);\n}\n\nfunction processRow(row) {\n const transactionType = (row[COL.TYPE] || '').trim();\n if (transactionType === SKIP_TYPE) return null;\n\n const { reason, card } = processReasonAndCard(row[COL.REASON]);\n const payee = (row[COL.PAYEE] || '').trim();\n const payerAccount = (row[COL.ACCT] || '').trim();\n const debitBgn = parseNum(row[COL.DEBIT]);\n const creditBgn = parseNum(row[COL.CREDIT]);\n const date = parseDate(row[COL.DATE]);\n\n const autoTags = generateTags({ reason, transactionType, payee, debitBgn, creditBgn });\n\n const amount = debitBgn ?? creditBgn ?? null;\n\n const rawMessage = [\n row[COL.DATE] && `Date: ${row[COL.DATE]}`,\n transactionType && `Type: ${transactionType}`,\n payee && `Payee: ${payee}`,\n debitBgn != null && `Debit: ${debitBgn} BGN`,\n creditBgn != null && `Credit: ${creditBgn} BGN`,\n ].filter(Boolean).join(' | ');\n\n return {\n rawMessage,\n date,\n type: null,\n card,\n recipient: payee || null,\n amount,\n currency: 'BGN',\n balance: null,\n source: 'UPLOAD',\n debitBgn,\n creditBgn,\n transactionType: transactionType || null,\n payerAccount: payerAccount || null,\n autoTags,\n };\n}\n\n/**\n * Parse a Buffer containing a DSK Bank CSV (cp1251 or UTF-8).\n * Returns { rows, skipped, errors }.\n */\nasync function parseDskCsv(buffer) {\n // Try cp1251 first (DSK Bank export encoding), fall back to UTF-8\n let text = iconv.decode(buffer, 'cp1251');\n if (!text.includes(COL.DATE)) {\n text = buffer.toString('utf-8');\n }\n\n return new Promise((resolve, reject) => {\n const rows = [];\n const errors = [];\n let skipped = 0;\n\n const parser = parse(text, {\n columns: true,\n skip_empty_lines: true,\n trim: true,\n relax_column_count: true,\n });\n\n parser.on('readable', () => {\n let record;\n while ((record = parser.read()) !== null) {\n try {\n const row = processRow(record);\n if (row === null) { skipped++; } else { rows.push(row); }\n } catch (err) {\n errors.push(err.message);\n }\n }\n });\n\n parser.on('error', reject);\n parser.on('end', () => resolve({ rows, skipped, errors }));\n });\n}\n\nmodule.exports = { parseDskCsv };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"39 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst cors = require('cors');\nconst morgan = require('morgan');\nconst rateLimit = require('express-rate-limit');\nconst { authentikMiddleware } = require('./auth');\nconst paymentsRouter = require('./routes/payments');\nconst uploadRouter = require('./routes/upload');\n\nconst app = express();\nconst PORT = process.env.PORT || 3001;\n\napp.use(cors());\napp.use(express.json({ limit: '16kb' }));\napp.use(morgan('combined'));\n\n// Rate-limit the public ingest endpoint before auth middleware\nconst ingestLimiter = rateLimit({\n windowMs: 60 * 1000,\n max: 200,\n standardHeaders: true,\n legacyHeaders: false,\n message: { error: 'Too many requests, slow down' },\n});\napp.use('/api/payments/ingest', ingestLimiter);\n\n// Authentik header auth (skips /api/health and /api/payments/ingest)\napp.use(authentikMiddleware);\n\napp.get('/api/health', (_req, res) => {\n res.json({ status: 'ok', timestamp: new Date().toISOString() });\n});\n\napp.use('/api/payments', paymentsRouter);\napp.use('/api/upload', uploadRouter);\n\napp.listen(PORT, '0.0.0.0', () => {\n console.log(`Finance Hub API running on port ${PORT}`);\n});","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"payments.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"399 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst { PrismaClient } = require('@prisma/client');\nconst { parsePaymentSms } = require('../parser');\n\nconst router = express.Router();\nconst prisma = new PrismaClient();\n\nconst NOTIFIER_URL = process.env.NOTIFIER_URL;\nconst NOTIFIER_CHANNEL = process.env.NOTIFIER_CHANNEL || 'viber';\nconst DEFAULT_PHONE = process.env.NOTIFY_DEFAULT_PHONE;\n\n// ── Helpers ───────────────────────────────────────────────────────────────────\n\nfunction parseId(raw) {\n const id = parseInt(raw, 10);\n return Number.isFinite(id) ? id : null;\n}\n\nfunction formatNotifyMessage(payment) {\n const currency = payment.currency || 'EUR';\n const parts = [];\n if (payment.amount != null) parts.push(`Amount: ${payment.amount.toFixed(2)} ${currency}`);\n if (payment.recipient) parts.push(`At: ${payment.recipient}`);\n if (payment.balance != null) parts.push(`Balance: ${payment.balance.toFixed(2)} ${currency}`);\n if (payment.date) parts.push(`Date: ${new Date(payment.date).toLocaleString('en-GB')}`);\n return parts.join('\\n');\n}\n\nasync function sendNotification(payment) {\n if (!NOTIFIER_URL) {\n console.warn('[NOTIFY] NOTIFIER_URL not set — skipping notification');\n return;\n }\n\n const phone = payment.notifyPhone || DEFAULT_PHONE;\n if (!phone) {\n console.warn('[NOTIFY] No phone number for payment #' + payment.id + ' and NOTIFY_DEFAULT_PHONE not set');\n return;\n }\n\n const body = {\n phone,\n notification: NOTIFIER_CHANNEL,\n message: formatNotifyMessage(payment),\n };\n\n const res = await fetch(NOTIFIER_URL, {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify(body),\n });\n\n if (!res.ok) {\n const text = await res.text().catch(() => '');\n throw new Error(`Notifier responded ${res.status}: ${text}`);\n }\n}\n\n// ── Ingest a payment (public — no auth) ──────────────────────────────────────\n//\n// Two modes:\n//\n// SMS mode (default):\n// { \"message\": \"<raw SMS text>\", \"notifyPhone\": \"...\" }\n//\n// Structured mode (Apple Wallet / manual):\n// { \"ingestMode\": \"apple_wallet\", \"amount\": 7.78, \"recipient\": \"Apple Store\",\n// \"type\": \"WALLET\", \"card\": \"••••4447\", \"date\": \"2026-02-22T10:30:00Z\" }\n//\nrouter.post('/ingest', async (req, res) => {\n try {\n const { message, notifyPhone, ingestMode } = req.body;\n\n let data;\n\n if (ingestMode === 'apple_wallet' || (!message && req.body.amount != null)) {\n // ── Structured / Apple Wallet mode ──────────────────────────────────────\n const { amount, recipient, type, card, date, balance } = req.body;\n if (amount == null || !recipient) {\n return res.status(400).json({ error: 'amount and recipient are required for structured ingest' });\n }\n\n const rawMessage = [\n `Source: ${ingestMode || 'structured'}`,\n `Amount: ${amount}`,\n recipient && `Recipient: ${recipient}`,\n type && `Type: ${type}`,\n card && `Card: ${card}`,\n ].filter(Boolean).join(' | ');\n\n data = {\n rawMessage,\n date: date ? new Date(date) : new Date(),\n type: type || 'WALLET',\n card: card || null,\n recipient,\n amount: parseFloat(amount),\n currency: 'EUR',\n balance: balance != null ? parseFloat(balance) : null,\n source: 'INGEST',\n notifyPhone: notifyPhone || null,\n };\n\n } else {\n // ── SMS mode ─────────────────────────────────────────────────────────────\n if (!message) {\n return res.status(400).json({ error: 'message is required' });\n }\n if (typeof message !== 'string' || message.length > 2000) {\n return res.status(400).json({ error: 'message must be a string under 2000 characters' });\n }\n\n const parsed = parsePaymentSms(message);\n data = {\n rawMessage: parsed.rawMessage,\n date: parsed.date,\n type: parsed.type,\n card: parsed.card,\n recipient: parsed.recipient,\n amount: parsed.amount,\n currency: 'EUR',\n balance: parsed.balance,\n source: 'INGEST',\n notifyPhone: notifyPhone || null,\n };\n }\n\n const payment = await prisma.payment.create({\n data,\n include: { tags: true },\n });\n\n res.status(201).json(payment);\n } catch (err) {\n console.error('Ingest error:', err);\n res.status(500).json({ error: 'Failed to ingest payment' });\n }\n});\n\n// ── List payments with filtering ──────────────────────────────────────────────\nrouter.get('/', async (req, res) => {\n try {\n const {\n status,\n type,\n tag,\n source,\n recipient,\n dateFrom,\n dateTo,\n search,\n sortBy = 'createdAt',\n sortDir = 'desc',\n page = 1,\n } = req.query;\n\n const limit = Math.min(parseInt(req.query.limit, 10) || 50, 200);\n\n const where = {};\n\n if (status) where.status = status;\n if (type) where.type = type;\n if (source) where.source = source;\n if (recipient) where.recipient = { contains: recipient, mode: 'insensitive' };\n if (tag) where.tags = { some: { name: tag } };\n if (search) {\n where.OR = [\n { rawMessage: { contains: search, mode: 'insensitive' } },\n { recipient: { contains: search, mode: 'insensitive' } },\n ];\n }\n if (dateFrom || dateTo) {\n where.date = {};\n if (dateFrom) where.date.gte = new Date(dateFrom);\n if (dateTo) where.date.lte = new Date(dateTo);\n }\n\n const allowedSortFields = ['date', 'amount', 'balance', 'recipient', 'type', 'source', 'createdAt', 'status'];\n const orderField = allowedSortFields.includes(sortBy) ? sortBy : 'createdAt';\n const orderDir = sortDir === 'asc' ? 'asc' : 'desc';\n\n const skip = (parseInt(page, 10) - 1) * limit;\n\n const [payments, total] = await Promise.all([\n prisma.payment.findMany({\n where,\n include: { tags: true },\n orderBy: { [orderField]: orderDir },\n skip,\n take: limit,\n }),\n prisma.payment.count({ where }),\n ]);\n\n res.json({ payments, total, page: parseInt(page, 10), limit });\n } catch (err) {\n console.error('List error:', err);\n res.status(500).json({ error: 'Failed to list payments' });\n }\n});\n\n// ── Get filter options ────────────────────────────────────────────────────────\nrouter.get('/meta/filters', async (_req, res) => {\n try {\n const [types, recipients, tags, sources] = await Promise.all([\n prisma.payment.findMany({ distinct: ['type'], select: { type: true }, where: { type: { not: null } } }),\n prisma.payment.findMany({ distinct: ['recipient'], select: { recipient: true }, where: { recipient: { not: null } } }),\n prisma.tag.findMany({ orderBy: { name: 'asc' } }),\n prisma.payment.findMany({ distinct: ['source'], select: { source: true } }),\n ]);\n\n res.json({\n types: types.map(t => t.type),\n recipients: recipients.map(r => r.recipient),\n tags,\n sources: sources.map(s => s.source),\n });\n } catch (err) {\n res.status(500).json({ error: 'Failed to get filters' });\n }\n});\n\n// ── Get all tags ──────────────────────────────────────────────────────────────\nrouter.get('/meta/tags', async (_req, res) => {\n try {\n const tags = await prisma.tag.findMany({ orderBy: { name: 'asc' } });\n res.json(tags);\n } catch (err) {\n res.status(500).json({ error: 'Failed to list tags' });\n }\n});\n\n// ── Get single payment ────────────────────────────────────────────────────────\nrouter.get('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({\n where: { id },\n include: { tags: true },\n });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n res.json(payment);\n } catch (err) {\n console.error('Get error:', err);\n res.status(500).json({ error: 'Failed to get payment' });\n }\n});\n\n// ── Update payment metadata (status) ─────────────────────────────────────────\nrouter.patch('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const { status } = req.body;\n const data = {};\n\n if (status) {\n const validStatuses = ['UNPROCESSED', 'SENT', 'SKIPPED'];\n if (!validStatuses.includes(status)) {\n return res.status(400).json({ error: `Invalid status. Must be one of: ${validStatuses.join(', ')}` });\n }\n data.status = status;\n }\n\n if (Object.keys(data).length === 0) {\n return res.status(400).json({ error: 'No valid fields to update' });\n }\n\n const updated = await prisma.payment.update({\n where: { id },\n data,\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n if (err.code === 'P2025') return res.status(404).json({ error: 'Not found' });\n console.error('Update error:', err);\n res.status(500).json({ error: 'Failed to update payment' });\n }\n});\n\n// ── Delete payment ───────────────────────────────────────────────────────────\nrouter.delete('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n await prisma.payment.delete({ where: { id } });\n res.json({ success: true });\n } catch (err) {\n if (err.code === 'P2025') return res.status(404).json({ error: 'Not found' });\n console.error('Delete error:', err);\n res.status(500).json({ error: 'Failed to delete payment' });\n }\n});\n\n// ── Send notification (mark as SENT + call notifier service) ─────────────────\nrouter.post('/:id/send', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({ where: { id } });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n if (payment.status !== 'UNPROCESSED') {\n return res.status(409).json({ error: `Payment is already ${payment.status.toLowerCase()}` });\n }\n\n await sendNotification(payment);\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { status: 'SENT', notifiedAt: new Date() },\n include: { tags: true },\n });\n\n res.json(updated);\n } catch (err) {\n console.error('Send error:', err);\n res.status(500).json({ error: 'Failed to send notification' });\n }\n});\n\n// ── Skip notification (mark as SKIPPED) ──────────────────────────────────────\nrouter.post('/:id/skip', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({ where: { id } });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n if (payment.status !== 'UNPROCESSED') {\n return res.status(409).json({ error: `Payment is already ${payment.status.toLowerCase()}` });\n }\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { status: 'SKIPPED' },\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n console.error('Skip error:', err);\n res.status(500).json({ error: 'Failed to skip payment' });\n }\n});\n\n// ── Add tag to payment ────────────────────────────────────────────────────────\nrouter.post('/:id/tags', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const { name, color } = req.body;\n if (!name) return res.status(400).json({ error: 'tag name is required' });\n\n const tag = await prisma.tag.upsert({\n where: { name },\n update: {},\n create: { name, color: color || '#6b7280' },\n });\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { tags: { connect: { id: tag.id } } },\n include: { tags: true },\n });\n\n res.json(updated);\n } catch (err) {\n console.error('Tag error:', err);\n res.status(500).json({ error: 'Failed to add tag' });\n }\n});\n\n// ── Remove tag from payment ───────────────────────────────────────────────────\nrouter.delete('/:id/tags/:tagId', async (req, res) => {\n const id = parseId(req.params.id);\n const tagId = parseId(req.params.tagId);\n if (id === null || tagId === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const updated = await prisma.payment.update({\n where: { id },\n data: { tags: { disconnect: { id: tagId } } },\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n console.error('Remove tag error:', err);\n res.status(500).json({ error: 'Failed to remove tag' });\n }\n});\n\nmodule.exports = router;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"upload.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"upload.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"89 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst multer = require('multer');\nconst { PrismaClient } = require('@prisma/client');\nconst { parseDskCsv } = require('../csvParser');\n\nconst router = express.Router();\nconst prisma = new PrismaClient();\n\nconst upload = multer({\n storage: multer.memoryStorage(),\n limits: { fileSize: 10 * 1024 * 1024, files: 10 },\n fileFilter: (_req, file, cb) => {\n if (file.mimetype === 'text/csv' || file.originalname.toLowerCase().endsWith('.csv')) {\n cb(null, true);\n } else {\n cb(new Error('Only CSV files are accepted'));\n }\n },\n});\n\n// POST /api/upload/csv\n// Accepts 1-10 CSV files, parses them, stores to DB with source=UPLOAD.\n// Returns { imported, skipped, errors, payments[] }\nrouter.post('/csv', upload.array('files', 10), async (req, res) => {\n if (!req.files || req.files.length === 0) {\n return res.status(400).json({ error: 'No files uploaded' });\n }\n\n const allRows = [];\n const allErrors = [];\n let totalSkipped = 0;\n\n for (const file of req.files) {\n try {\n const { rows, skipped, errors } = await parseDskCsv(file.buffer);\n allRows.push(...rows);\n totalSkipped += skipped;\n allErrors.push(...errors.map(e => `${file.originalname}: ${e}`));\n } catch (err) {\n allErrors.push(`${file.originalname}: ${err.message}`);\n }\n }\n\n if (allRows.length === 0) {\n return res.status(422).json({\n error: 'No importable rows found',\n skipped: totalSkipped,\n errors: allErrors,\n });\n }\n\n const created = [];\n\n for (const row of allRows) {\n const { autoTags, ...paymentData } = row;\n try {\n const tagConnects = [];\n for (const tagName of autoTags) {\n const tag = await prisma.tag.upsert({\n where: { name: tagName },\n update: {},\n create: { name: tagName, color: '#6b7280' },\n });\n tagConnects.push({ id: tag.id });\n }\n\n const payment = await prisma.payment.create({\n data: {\n ...paymentData,\n ...(tagConnects.length ? { tags: { connect: tagConnects } } : {}),\n },\n include: { tags: true },\n });\n created.push(payment);\n } catch (err) {\n allErrors.push(`Row insert failed: ${err.message}`);\n }\n }\n\n res.status(201).json({\n imported: created.length,\n skipped: totalSkipped,\n errors: allErrors,\n payments: created,\n });\n});\n\nmodule.exports = router;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now writing all frontend config files:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"24 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"{\n \"name\": \"finance-hub-frontend\",\n \"version\": \"1.0.0\",\n \"type\": \"module\",\n \"scripts\": {\n \"dev\": \"vite\",\n \"build\": \"vite build\",\n \"preview\": \"vite preview\"\n },\n \"dependencies\": {\n \"lucide-react\": \"^0.460.0\",\n \"react\": \"^18.3.1\",\n \"react-dom\": \"^18.3.1\"\n },\n \"devDependencies\": {\n \"@types/react\": \"^18.3.12\",\n \"@vitejs/plugin-react\": \"^4.3.4\",\n \"autoprefixer\": \"^10.4.20\",\n \"postcss\": \"^8.4.49\",\n \"tailwindcss\": \"^3.4.15\",\n \"vite\": \"^6.0.1\"\n }\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"FROM node:20-alpine\n\nWORKDIR /app\n\nCOPY package.json package-lock.json* ./\nRUN npm install\n\nCOPY . .\n\nEXPOSE 5173\n\nCMD [\"npm\", \"run\", \"dev\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"vite.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"vite.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"18 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import { defineConfig } from 'vite';\nimport react from '@vitejs/plugin-react';\n\nexport default defineConfig({\n plugins: [react()],\n server: {\n host: '0.0.0.0',\n port: 5173,\n allowedHosts: ['finance-hub.lakylak.xyz'],\n proxy: {\n '/api': {\n target: 'http://backend:3001',\n changeOrigin: true,\n },\n },\n },\n});","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"tailwind.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"tailwind.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"12 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/** @type {import('tailwindcss').Config} */\nexport default {\n content: [\n \"./index.html\",\n \"./src/**/*.{js,ts,jsx,tsx}\",\n ],\n theme: {\n extend: {},\n },\n plugins: [],\n};","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"postcss.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"postcss.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"7 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"export default {\n plugins: {\n tailwindcss: {},\n autoprefixer: {},\n },\n};","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.html","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.html","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"14 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"<!DOCTYPE html>\n<html lang=\"en\">\n <head>\n <meta charset=\"UTF-8\" />\n <meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\" />\n <title>Finance Hub</title>\n <link rel=\"icon\" type=\"image/svg+xml\" href=\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 100 100'><text y='.9em' font-size='90'>💰</text></svg>\" />\n </head>\n <body class=\"bg-gray-50 min-h-screen\">\n <div id=\"root\"></div>\n <script type=\"module\" src=\"/src/main.jsx\"></script>\n </body>\n</html>","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.css","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.css","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"4 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"@tailwind base;\n@tailwind components;\n@tailwind utilities;","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now writing all React components:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"11 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React from 'react';\nimport ReactDOM from 'react-dom/client';\nimport App from './App';\nimport './index.css';\n\nReactDOM.createRoot(document.getElementById('root')).render(\n <React.StrictMode>\n <App />\n </React.StrictMode>\n);","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"App.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"App.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"257 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState, useEffect, useCallback } from 'react';\nimport { LayoutDashboard, Upload, RefreshCw, LogOut } from 'lucide-react';\nimport FilterBar from './components/FilterBar';\nimport PaymentTable from './components/PaymentTable';\nimport UploadPanel from './components/UploadPanel';\n\nconst API_BASE = '/api/payments';\n\nexport default function App() {\n const [activeTab, setActiveTab] = useState('payments');\n const [payments, setPayments] = useState([]);\n const [total, setTotal] = useState(0);\n const [page, setPage] = useState(1);\n const [filters, setFilters] = useState({});\n const [sortBy, setSortBy] = useState('createdAt');\n const [sortDir, setSortDir] = useState('desc');\n const [filterOptions, setFilterOptions] = useState({ types: [], recipients: [], tags: [], sources: [] });\n const [loading, setLoading] = useState(false);\n\n const fetchPayments = useCallback(async () => {\n setLoading(true);\n try {\n const params = new URLSearchParams();\n params.set('page', page);\n params.set('limit', 50);\n params.set('sortBy', sortBy);\n params.set('sortDir', sortDir);\n Object.entries(filters).forEach(([key, val]) => {\n if (val) params.set(key, val);\n });\n const res = await fetch(`${API_BASE}?${params}`);\n const data = await res.json();\n setPayments(data.payments || []);\n setTotal(data.total || 0);\n } catch (err) {\n console.error('Failed to fetch payments:', err);\n } finally {\n setLoading(false);\n }\n }, [page, filters, sortBy, sortDir]);\n\n const fetchFilterOptions = useCallback(async () => {\n try {\n const res = await fetch(`${API_BASE}/meta/filters`);\n const data = await res.json();\n setFilterOptions(data);\n } catch (err) {\n console.error('Failed to fetch filter options:', err);\n }\n }, []);\n\n useEffect(() => {\n fetchPayments();\n }, [fetchPayments]);\n\n useEffect(() => {\n fetchFilterOptions();\n }, [fetchFilterOptions]);\n\n // Refresh payments list after a successful CSV upload\n const handleUploadSuccess = () => {\n fetchPayments();\n fetchFilterOptions();\n setActiveTab('payments');\n };\n\n const handleAction = async (id, action) => {\n try {\n await fetch(`${API_BASE}/${id}/${action}`, { method: 'POST' });\n fetchPayments();\n fetchFilterOptions();\n } catch (err) {\n console.error(`Failed to ${action} payment:`, err);\n }\n };\n\n const handleAddTag = async (id, tagName, tagColor) => {\n try {\n await fetch(`${API_BASE}/${id}/tags`, {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify({ name: tagName, color: tagColor }),\n });\n fetchPayments();\n fetchFilterOptions();\n } catch (err) {\n console.error('Failed to add tag:', err);\n }\n };\n\n const handleRemoveTag = async (paymentId, tagId) => {\n try {\n await fetch(`${API_BASE}/${paymentId}/tags/${tagId}`, { method: 'DELETE' });\n fetchPayments();\n } catch (err) {\n console.error('Failed to remove tag:', err);\n }\n };\n\n const handleDelete = async (id) => {\n try {\n await fetch(`${API_BASE}/${id}`, { method: 'DELETE' });\n fetchPayments();\n fetchFilterOptions();\n } catch (err) {\n console.error('Failed to delete payment:', err);\n }\n };\n\n const handleUpdateStatus = async (id, status) => {\n try {\n await fetch(`${API_BASE}/${id}`, {\n method: 'PATCH',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify({ status }),\n });\n fetchPayments();\n } catch (err) {\n console.error('Failed to update status:', err);\n }\n };\n\n const handleFilterChange = (newFilters) => {\n setFilters(newFilters);\n setPage(1);\n };\n\n const handleSort = (field) => {\n if (sortBy === field) {\n setSortDir(d => d === 'asc' ? 'desc' : 'asc');\n } else {\n setSortBy(field);\n setSortDir('desc');\n }\n setPage(1);\n };\n\n const totalPages = Math.ceil(total / 50);\n\n return (\n <div className=\"min-h-screen bg-gray-50\">\n <header className=\"bg-white border-b border-gray-200 shadow-sm\">\n <div className=\"max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-4\">\n <div className=\"flex items-center justify-between\">\n <div className=\"flex items-center gap-3\">\n <div className=\"bg-indigo-600 p-2 rounded-lg\">\n <LayoutDashboard className=\"w-6 h-6 text-white\" />\n </div>\n <div>\n <h1 className=\"text-xl font-bold text-gray-900\">Finance Hub</h1>\n <p className=\"text-sm text-gray-500\">{total} transaction{total !== 1 ? 's' : ''} total</p>\n </div>\n </div>\n\n <div className=\"flex items-center gap-2\">\n {/* Tab switcher */}\n <div className=\"flex items-center rounded-lg border border-gray-200 bg-gray-50 p-1 gap-1\">\n <button\n onClick={() => setActiveTab('payments')}\n className={`flex items-center gap-1.5 px-3 py-1.5 text-sm font-medium rounded-md transition-colors ${\n activeTab === 'payments'\n ? 'bg-white text-indigo-700 shadow-sm'\n : 'text-gray-600 hover:text-gray-900'\n }`}\n >\n <LayoutDashboard className=\"w-4 h-4\" />\n Payments\n </button>\n <button\n onClick={() => setActiveTab('upload')}\n className={`flex items-center gap-1.5 px-3 py-1.5 text-sm font-medium rounded-md transition-colors ${\n activeTab === 'upload'\n ? 'bg-white text-emerald-700 shadow-sm'\n : 'text-gray-600 hover:text-gray-900'\n }`}\n >\n <Upload className=\"w-4 h-4\" />\n Upload CSV\n </button>\n </div>\n\n {activeTab === 'payments' && (\n <button\n onClick={() => { fetchPayments(); fetchFilterOptions(); }}\n className=\"flex items-center gap-2 px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 transition-colors\"\n >\n <RefreshCw className={`w-4 h-4 ${loading ? 'animate-spin' : ''}`} />\n Refresh\n </button>\n )}\n\n <button\n onClick={() => { window.location.href = '/outpost.goauthentik.io/sign_out'; }}\n className=\"flex items-center gap-2 px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 transition-colors\"\n title=\"Sign out\"\n >\n <LogOut className=\"w-4 h-4\" />\n </button>\n </div>\n </div>\n </div>\n </header>\n\n <main className=\"max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-6\">\n {activeTab === 'payments' ? (\n <>\n <FilterBar\n filters={filters}\n filterOptions={filterOptions}\n onFilterChange={handleFilterChange}\n />\n\n <PaymentTable\n payments={payments}\n loading={loading}\n sortBy={sortBy}\n sortDir={sortDir}\n onSort={handleSort}\n onSend={(id) => handleAction(id, 'send')}\n onSkip={(id) => handleAction(id, 'skip')}\n onAddTag={handleAddTag}\n onRemoveTag={handleRemoveTag}\n onDelete={handleDelete}\n onUpdateStatus={handleUpdateStatus}\n existingTags={filterOptions.tags}\n />\n\n {totalPages > 1 && (\n <div className=\"flex items-center justify-center gap-2 mt-6\">\n <button\n onClick={() => setPage(p => Math.max(1, p - 1))}\n disabled={page === 1}\n className=\"px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 disabled:opacity-50 disabled:cursor-not-allowed\"\n >\n Previous\n </button>\n <span className=\"text-sm text-gray-600\">\n Page {page} of {totalPages}\n </span>\n <button\n onClick={() => setPage(p => Math.min(totalPages, p + 1))}\n disabled={page === totalPages}\n className=\"px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 disabled:opacity-50 disabled:cursor-not-allowed\"\n >\n Next\n </button>\n </div>\n )}\n </>\n ) : (\n <UploadPanel onUploadSuccess={handleUploadSuccess} />\n )}\n </main>\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"FilterBar.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"FilterBar.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"167 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState, useEffect } from 'react';\nimport { Search, Filter, X, Calendar, ChevronDown, ChevronUp } from 'lucide-react';\n\nconst STATUS_OPTIONS = [\n { value: '', label: 'All Statuses' },\n { value: 'UNPROCESSED', label: 'Unprocessed' },\n { value: 'SENT', label: 'Sent' },\n { value: 'SKIPPED', label: 'Skipped' },\n];\n\nconst SOURCE_OPTIONS = [\n { value: '', label: 'All Sources' },\n { value: 'INGEST', label: 'SMS Ingest' },\n { value: 'UPLOAD', label: 'CSV Upload' },\n];\n\nexport default function FilterBar({ filters, filterOptions, onFilterChange }) {\n const [search, setSearch] = useState(filters.search || '');\n const [isOpen, setIsOpen] = useState(() => window.innerWidth >= 768);\n\n useEffect(() => {\n const mq = window.matchMedia('(min-width: 768px)');\n const handler = (e) => setIsOpen(e.matches);\n mq.addEventListener('change', handler);\n return () => mq.removeEventListener('change', handler);\n }, []);\n\n const handleSearchSubmit = (e) => {\n e.preventDefault();\n onFilterChange({ ...filters, search: search || undefined });\n };\n\n const handleSelectChange = (key, value) => {\n const newFilters = { ...filters };\n if (value) {\n newFilters[key] = value;\n } else {\n delete newFilters[key];\n }\n onFilterChange(newFilters);\n };\n\n const clearFilters = () => {\n setSearch('');\n onFilterChange({});\n };\n\n const activeFilterCount = Object.keys(filters).length;\n const hasActiveFilters = activeFilterCount > 0;\n\n return (\n <div className=\"bg-white rounded-xl border border-gray-200 shadow-sm p-4 mb-6\">\n <button\n onClick={() => setIsOpen(!isOpen)}\n className=\"w-full flex items-center gap-2\"\n >\n <Filter className=\"w-4 h-4 text-gray-500\" />\n <span className=\"text-sm font-medium text-gray-700\">Filters</span>\n {hasActiveFilters && (\n <span className=\"inline-flex items-center justify-center w-5 h-5 text-xs font-bold text-white bg-indigo-600 rounded-full\">\n {activeFilterCount}\n </span>\n )}\n {hasActiveFilters && (\n <span\n onClick={(e) => { e.stopPropagation(); clearFilters(); }}\n className=\"ml-1 flex items-center gap-1 text-xs text-red-600 hover:text-red-700\"\n >\n <X className=\"w-3 h-3\" />\n Clear\n </span>\n )}\n <span className=\"ml-auto\">\n {isOpen\n ? <ChevronUp className=\"w-4 h-4 text-gray-400\" />\n : <ChevronDown className=\"w-4 h-4 text-gray-400\" />\n }\n </span>\n </button>\n\n {isOpen && (\n <div className=\"space-y-3 mt-3 pt-3 border-t border-gray-100\">\n <div className=\"grid grid-cols-1 sm:grid-cols-2 lg:grid-cols-5 gap-3\">\n <form onSubmit={handleSearchSubmit} className=\"relative\">\n <Search className=\"absolute left-3 top-1/2 -translate-y-1/2 w-4 h-4 text-gray-400\" />\n <input\n type=\"text\"\n placeholder=\"Search...\"\n value={search}\n onChange={(e) => setSearch(e.target.value)}\n onBlur={() => onFilterChange({ ...filters, search: search || undefined })}\n className=\"w-full pl-9 pr-3 py-2 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none\"\n />\n </form>\n\n <select\n value={filters.source || ''}\n onChange={(e) => handleSelectChange('source', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n {SOURCE_OPTIONS.map(opt => (\n <option key={opt.value} value={opt.value}>{opt.label}</option>\n ))}\n </select>\n\n <select\n value={filters.status || ''}\n onChange={(e) => handleSelectChange('status', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n {STATUS_OPTIONS.map(opt => (\n <option key={opt.value} value={opt.value}>{opt.label}</option>\n ))}\n </select>\n\n <select\n value={filters.type || ''}\n onChange={(e) => handleSelectChange('type', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n <option value=\"\">All Types</option>\n {(filterOptions.types || []).map(t => (\n <option key={t} value={t}>{t}</option>\n ))}\n </select>\n\n <select\n value={filters.tag || ''}\n onChange={(e) => handleSelectChange('tag', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n <option value=\"\">All Tags</option>\n {(filterOptions.tags || []).map(t => (\n <option key={t.id} value={t.name}>{t.name}</option>\n ))}\n </select>\n </div>\n\n <div className=\"grid grid-cols-1 sm:grid-cols-2 gap-3\">\n <div className=\"relative\">\n <Calendar className=\"absolute left-3 top-1/2 -translate-y-1/2 w-4 h-4 text-gray-400\" />\n <input\n type=\"date\"\n placeholder=\"From date\"\n value={filters.dateFrom || ''}\n onChange={(e) => handleSelectChange('dateFrom', e.target.value)}\n className=\"w-full pl-9 pr-3 py-2 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none\"\n />\n </div>\n\n <div className=\"relative\">\n <Calendar className=\"absolute left-3 top-1/2 -translate-y-1/2 w-4 h-4 text-gray-400\" />\n <input\n type=\"date\"\n placeholder=\"To date\"\n value={filters.dateTo || ''}\n onChange={(e) => handleSelectChange('dateTo', e.target.value)}\n className=\"w-full pl-9 pr-3 py-2 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none\"\n />\n </div>\n </div>\n </div>\n )}\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentTable.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentTable.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"339 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState } from 'react';\nimport {\n ArrowUpDown, ArrowUp, ArrowDown,\n Send, XCircle, CheckCircle, MinusCircle, Clock,\n Inbox, Plus, X, ChevronDown, ChevronUp, Trash2,\n} from 'lucide-react';\n\nconst STATUS_CONFIG = {\n UNPROCESSED: { label: 'Unprocessed', icon: Clock, color: 'bg-amber-100 text-amber-700' },\n SENT: { label: 'Sent', icon: CheckCircle, color: 'bg-green-100 text-green-700' },\n SKIPPED: { label: 'Skipped', icon: MinusCircle, color: 'bg-gray-100 text-gray-500' },\n};\n\nconst TAG_COLORS = [\n '#ef4444', '#f97316', '#eab308', '#22c55e', '#06b6d4',\n '#3b82f6', '#8b5cf6', '#ec4899', '#6b7280',\n];\n\nconst COLUMNS = [\n { key: 'date', label: 'Date & Time', sortable: true },\n { key: 'source', label: 'Source', sortable: true },\n { key: 'type', label: 'Type', sortable: true },\n { key: 'recipient', label: 'Recipient', sortable: true },\n { key: 'amount', label: 'Amount', sortable: true },\n { key: 'balance', label: 'Balance', sortable: true },\n { key: 'status', label: 'Status', sortable: true },\n { key: 'tags', label: 'Tags', sortable: false },\n { key: 'actions', label: 'Actions', sortable: false },\n];\n\nfunction SortIcon({ column, sortBy, sortDir }) {\n if (sortBy !== column) return <ArrowUpDown className=\"w-3 h-3 text-gray-400\" />;\n return sortDir === 'asc'\n ? <ArrowUp className=\"w-3 h-3 text-indigo-600\" />\n : <ArrowDown className=\"w-3 h-3 text-indigo-600\" />;\n}\n\nfunction SourceBadge({ source }) {\n if (source === 'UPLOAD') {\n return (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-emerald-50 text-emerald-700\">\n CSV\n </span>\n );\n }\n return (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-indigo-50 text-indigo-700\">\n SMS\n </span>\n );\n}\n\nfunction TagCell({ payment, onAddTag, onRemoveTag, existingTags }) {\n const [open, setOpen] = useState(false);\n const [newTagName, setNewTagName] = useState('');\n const [newTagColor, setNewTagColor] = useState('#3b82f6');\n\n const paymentTags = payment.tags || [];\n const availableTags = existingTags.filter(t => !paymentTags.some(pt => pt.id === t.id));\n\n const handleAdd = (e) => {\n e.preventDefault();\n if (newTagName.trim()) {\n onAddTag(payment.id, newTagName.trim(), newTagColor);\n setNewTagName('');\n setOpen(false);\n }\n };\n\n return (\n <div className=\"flex flex-wrap items-center gap-1\">\n {paymentTags.map(tag => (\n <span\n key={tag.id}\n className=\"inline-flex items-center gap-0.5 px-1.5 py-0.5 text-xs font-medium rounded-full text-white\"\n style={{ backgroundColor: tag.color }}\n >\n {tag.name}\n <button onClick={() => onRemoveTag(payment.id, tag.id)} className=\"hover:opacity-75\">\n <X className=\"w-2.5 h-2.5\" />\n </button>\n </span>\n ))}\n <div className=\"relative\">\n <button\n onClick={() => setOpen(!open)}\n className=\"inline-flex items-center gap-0.5 px-1.5 py-0.5 text-xs text-gray-500 border border-dashed border-gray-300 rounded-full hover:border-gray-400\"\n >\n <Plus className=\"w-2.5 h-2.5\" />\n </button>\n {open && (\n <div className=\"absolute z-20 top-full left-0 mt-1 bg-white border border-gray-200 rounded-lg shadow-lg p-2 w-56\">\n <form onSubmit={handleAdd} className=\"flex items-center gap-1 mb-2\">\n <input\n type=\"text\"\n value={newTagName}\n onChange={(e) => setNewTagName(e.target.value)}\n placeholder=\"New tag\"\n autoFocus\n className=\"flex-1 px-2 py-1 text-xs border border-gray-300 rounded focus:ring-1 focus:ring-indigo-500 outline-none\"\n />\n <button type=\"submit\" className=\"text-xs text-indigo-600 font-medium hover:text-indigo-700 whitespace-nowrap\">Add</button>\n </form>\n <div className=\"flex gap-1 mb-2\">\n {TAG_COLORS.map(c => (\n <button\n key={c}\n type=\"button\"\n onClick={() => setNewTagColor(c)}\n className={`w-4 h-4 rounded-full border-2 ${newTagColor === c ? 'border-gray-800' : 'border-transparent'}`}\n style={{ backgroundColor: c }}\n />\n ))}\n </div>\n {availableTags.length > 0 && (\n <div className=\"border-t border-gray-100 pt-1 flex flex-wrap gap-1\">\n {availableTags.map(tag => (\n <button\n key={tag.id}\n onClick={() => { onAddTag(payment.id, tag.name, tag.color); setOpen(false); }}\n className=\"px-1.5 py-0.5 text-xs rounded-full border border-gray-200 text-gray-600 hover:bg-gray-100\"\n >\n {tag.name}\n </button>\n ))}\n </div>\n )}\n </div>\n )}\n </div>\n </div>\n );\n}\n\nfunction ExpandedRow({ payment }) {\n return (\n <tr className=\"bg-gray-50\">\n <td colSpan={COLUMNS.length} className=\"px-4 py-3\">\n <div className=\"text-xs text-gray-500 uppercase tracking-wide mb-1\">Original Message / Raw Data</div>\n <p className=\"text-sm text-gray-700 whitespace-pre-wrap break-words\">{payment.rawMessage}</p>\n {payment.debitBgn != null && (\n <p className=\"text-xs text-gray-500 mt-1\">Debit: {payment.debitBgn.toFixed(2)} BGN</p>\n )}\n {payment.creditBgn != null && (\n <p className=\"text-xs text-gray-500 mt-0.5\">Credit: {payment.creditBgn.toFixed(2)} BGN</p>\n )}\n {payment.transactionType && (\n <p className=\"text-xs text-gray-500 mt-0.5\">Transaction type: {payment.transactionType}</p>\n )}\n {payment.payerAccount && (\n <p className=\"text-xs text-gray-500 mt-0.5\">Account: {payment.payerAccount}</p>\n )}\n {payment.notifiedAt && (\n <p className=\"text-xs text-green-600 mt-2\">\n Notified on {new Date(payment.notifiedAt).toLocaleString('en-GB')}\n {payment.notifyPhone && ` to ${payment.notifyPhone}`}\n </p>\n )}\n </td>\n </tr>\n );\n}\n\nfunction StatusCell({ payment, onUpdateStatus }) {\n const [open, setOpen] = useState(false);\n const statusCfg = STATUS_CONFIG[payment.status] || STATUS_CONFIG.UNPROCESSED;\n const StatusIcon = statusCfg.icon;\n\n return (\n <div className=\"relative\">\n <button\n onClick={() => setOpen(!open)}\n className={`inline-flex items-center gap-1 px-2 py-0.5 text-xs font-medium rounded-full cursor-pointer ${statusCfg.color}`}\n >\n <StatusIcon className=\"w-3 h-3\" />\n {statusCfg.label}\n </button>\n {open && (\n <div className=\"absolute z-20 top-full left-0 mt-1 bg-white border border-gray-200 rounded-lg shadow-lg py-1 w-36\">\n {Object.entries(STATUS_CONFIG).map(([key, cfg]) => {\n const Icon = cfg.icon;\n return (\n <button\n key={key}\n onClick={() => { onUpdateStatus(payment.id, key); setOpen(false); }}\n className={`w-full flex items-center gap-2 px-3 py-1.5 text-xs hover:bg-gray-50 ${payment.status === key ? 'font-bold' : ''}`}\n >\n <Icon className=\"w-3 h-3\" />\n {cfg.label}\n </button>\n );\n })}\n </div>\n )}\n </div>\n );\n}\n\nexport default function PaymentTable({\n payments, loading, sortBy, sortDir, onSort,\n onSend, onSkip, onAddTag, onRemoveTag, onDelete, onUpdateStatus, existingTags,\n}) {\n const [expandedId, setExpandedId] = useState(null);\n\n if (loading) {\n return (\n <div className=\"flex items-center justify-center py-20\">\n <div className=\"animate-spin rounded-full h-8 w-8 border-b-2 border-indigo-600\"></div>\n </div>\n );\n }\n\n if (!payments || payments.length === 0) {\n return (\n <div className=\"flex flex-col items-center justify-center py-20 text-gray-400\">\n <Inbox className=\"w-12 h-12 mb-3\" />\n <p className=\"text-lg font-medium\">No transactions found</p>\n <p className=\"text-sm\">Try adjusting your filters, ingest a payment SMS, or upload a CSV.</p>\n </div>\n );\n }\n\n const formatDate = (d) => {\n if (!d) return '—';\n return new Date(d).toLocaleDateString('en-GB', {\n day: '2-digit', month: 'short', year: 'numeric', hour: '2-digit', minute: '2-digit',\n });\n };\n\n const formatAmount = (v, currency) =>\n v != null ? `${v.toFixed(2)} ${currency || 'EUR'}` : '—';\n\n return (\n <div className=\"bg-white rounded-xl border border-gray-200 shadow-sm overflow-hidden\">\n <div className=\"overflow-x-auto\">\n <table className=\"w-full text-sm\">\n <thead>\n <tr className=\"bg-gray-50 border-b border-gray-200\">\n {COLUMNS.map(col => (\n <th\n key={col.key}\n className={`px-4 py-3 text-left text-xs font-semibold text-gray-600 uppercase tracking-wider ${col.sortable ? 'cursor-pointer select-none hover:bg-gray-100' : ''}`}\n onClick={() => col.sortable && onSort(col.key)}\n >\n <span className=\"inline-flex items-center gap-1\">\n {col.label}\n {col.sortable && <SortIcon column={col.key} sortBy={sortBy} sortDir={sortDir} />}\n </span>\n </th>\n ))}\n </tr>\n </thead>\n <tbody className=\"divide-y divide-gray-100\">\n {payments.map(p => {\n const isExpanded = expandedId === p.id;\n return (\n <React.Fragment key={p.id}>\n <tr className=\"hover:bg-gray-50 transition-colors\">\n <td className=\"px-4 py-3 whitespace-nowrap text-gray-700\">{formatDate(p.date)}</td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n <SourceBadge source={p.source} />\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n {p.type ? (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-blue-50 text-blue-700\">{p.type}</span>\n ) : (p.transactionType ? (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-gray-100 text-gray-600 max-w-24 truncate block\" title={p.transactionType}>{p.transactionType}</span>\n ) : '—')}\n </td>\n <td className=\"px-4 py-3 text-gray-700 max-w-xs truncate\" title={p.recipient || ''}>\n <div className=\"flex items-center gap-1\">\n <span className=\"truncate\">{p.recipient || '—'}</span>\n <button\n onClick={() => setExpandedId(isExpanded ? null : p.id)}\n className=\"flex-shrink-0 text-gray-400 hover:text-gray-600\"\n title=\"Show raw data\"\n >\n {isExpanded ? <ChevronUp className=\"w-3.5 h-3.5\" /> : <ChevronDown className=\"w-3.5 h-3.5\" />}\n </button>\n </div>\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap font-medium text-gray-900\">\n {formatAmount(p.amount, p.currency)}\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap text-gray-600\">\n {formatAmount(p.balance, p.currency)}\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n <StatusCell payment={p} onUpdateStatus={onUpdateStatus} />\n </td>\n <td className=\"px-4 py-3\">\n <TagCell\n payment={p}\n onAddTag={onAddTag}\n onRemoveTag={onRemoveTag}\n existingTags={existingTags}\n />\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n <div className=\"flex items-center gap-1.5\">\n {p.status === 'UNPROCESSED' && (\n <>\n <button\n onClick={() => onSend(p.id)}\n className=\"inline-flex items-center gap-1 px-2.5 py-1 text-xs font-medium text-white bg-indigo-600 rounded-md hover:bg-indigo-700 transition-colors\"\n >\n <Send className=\"w-3 h-3\" />\n Send\n </button>\n <button\n onClick={() => onSkip(p.id)}\n className=\"inline-flex items-center gap-1 px-2.5 py-1 text-xs font-medium text-gray-600 bg-white border border-gray-300 rounded-md hover:bg-gray-50 transition-colors\"\n >\n <XCircle className=\"w-3 h-3\" />\n Skip\n </button>\n </>\n )}\n <button\n onClick={() => { if (window.confirm('Delete this transaction?')) onDelete(p.id); }}\n className=\"inline-flex items-center gap-1 px-2 py-1 text-xs font-medium text-red-600 bg-white border border-red-200 rounded-md hover:bg-red-50 transition-colors\"\n title=\"Delete transaction\"\n >\n <Trash2 className=\"w-3 h-3\" />\n </button>\n </div>\n </td>\n </tr>\n {isExpanded && <ExpandedRow payment={p} />}\n </React.Fragment>\n );\n })}\n </tbody>\n </table>\n </div>\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"UploadPanel.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"UploadPanel.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"192 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState, useRef } from 'react';\nimport { Upload, FileText, CheckCircle, AlertCircle, X, ArrowLeft } from 'lucide-react';\n\nexport default function UploadPanel({ onUploadSuccess }) {\n const [files, setFiles] = useState([]);\n const [loading, setLoading] = useState(false);\n const [result, setResult] = useState(null);\n const [error, setError] = useState(null);\n const [dragging, setDragging] = useState(false);\n const fileInputRef = useRef();\n\n const addFiles = (incoming) => {\n const csvFiles = Array.from(incoming).filter(f =>\n f.name.toLowerCase().endsWith('.csv')\n );\n setFiles(prev => {\n const existingNames = new Set(prev.map(f => f.name));\n return [...prev, ...csvFiles.filter(f => !existingNames.has(f.name))];\n });\n };\n\n const handleDrop = (e) => {\n e.preventDefault();\n setDragging(false);\n addFiles(e.dataTransfer.files);\n };\n\n const handleFileSelect = (e) => {\n addFiles(e.target.files);\n e.target.value = '';\n };\n\n const removeFile = (idx) => setFiles(prev => prev.filter((_, i) => i !== idx));\n\n const handleUpload = async () => {\n if (!files.length) return;\n setLoading(true);\n setError(null);\n setResult(null);\n\n const formData = new FormData();\n files.forEach(f => formData.append('files', f));\n\n try {\n const res = await fetch('/api/upload/csv', { method: 'POST', body: formData });\n const data = await res.json();\n if (!res.ok) throw new Error(data.error || 'Upload failed');\n setResult(data);\n setFiles([]);\n } catch (err) {\n setError(err.message);\n } finally {\n setLoading(false);\n }\n };\n\n return (\n <div className=\"max-w-2xl mx-auto\">\n <div className=\"mb-6\">\n <h2 className=\"text-lg font-semibold text-gray-900\">Upload DSK Bank CSV</h2>\n <p className=\"text-sm text-gray-500 mt-1\">\n Import transactions from DSK Bank CSV exports. Multiple files are merged automatically.\n Internal transfers are skipped. Tags are auto-assigned based on payee and description.\n </p>\n </div>\n\n {/* Drop zone */}\n <div\n onDrop={handleDrop}\n onDragOver={(e) => { e.preventDefault(); setDragging(true); }}\n onDragLeave={() => setDragging(false)}\n onClick={() => fileInputRef.current.click()}\n className={`border-2 border-dashed rounded-xl p-12 text-center cursor-pointer transition-colors ${\n dragging\n ? 'border-emerald-400 bg-emerald-50'\n : 'border-gray-300 hover:border-emerald-400 hover:bg-emerald-50'\n }`}\n >\n <Upload className={`w-10 h-10 mx-auto mb-3 ${dragging ? 'text-emerald-500' : 'text-gray-400'}`} />\n <p className=\"text-sm font-medium text-gray-700\">Drop DSK Bank CSV files here</p>\n <p className=\"text-xs text-gray-500 mt-1\">or click to select files — multiple files supported</p>\n <input\n ref={fileInputRef}\n type=\"file\"\n multiple\n accept=\".csv\"\n className=\"hidden\"\n onChange={handleFileSelect}\n />\n </div>\n\n {/* File list */}\n {files.length > 0 && (\n <div className=\"mt-4 space-y-2\">\n {files.map((f, i) => (\n <div key={i} className=\"flex items-center gap-2 bg-white rounded-lg border border-gray-200 px-3 py-2\">\n <FileText className=\"w-4 h-4 text-gray-400 flex-shrink-0\" />\n <span className=\"text-sm text-gray-700 flex-1 truncate\">{f.name}</span>\n <span className=\"text-xs text-gray-400 flex-shrink-0\">{(f.size / 1024).toFixed(1)} KB</span>\n <button\n onClick={(e) => { e.stopPropagation(); removeFile(i); }}\n className=\"text-gray-400 hover:text-gray-600 flex-shrink-0\"\n >\n <X className=\"w-4 h-4\" />\n </button>\n </div>\n ))}\n\n <button\n onClick={handleUpload}\n disabled={loading}\n className=\"w-full py-2.5 text-sm font-medium text-white bg-emerald-600 rounded-lg hover:bg-emerald-700 disabled:opacity-50 disabled:cursor-not-allowed transition-colors mt-2\"\n >\n {loading\n ? 'Importing…'\n : `Import ${files.length} file${files.length !== 1 ? 's' : ''}`\n }\n </button>\n </div>\n )}\n\n {/* Success result */}\n {result && (\n <div className=\"mt-6 bg-green-50 border border-green-200 rounded-xl p-5\">\n <div className=\"flex items-center gap-2 mb-3\">\n <CheckCircle className=\"w-5 h-5 text-green-600 flex-shrink-0\" />\n <span className=\"font-medium text-green-800\">Import complete</span>\n </div>\n <div className=\"grid grid-cols-3 gap-3 text-center mb-3\">\n <div className=\"bg-white rounded-lg border border-green-100 py-2 px-3\">\n <p className=\"text-2xl font-bold text-green-700\">{result.imported}</p>\n <p className=\"text-xs text-gray-500\">Imported</p>\n </div>\n <div className=\"bg-white rounded-lg border border-green-100 py-2 px-3\">\n <p className=\"text-2xl font-bold text-gray-500\">{result.skipped}</p>\n <p className=\"text-xs text-gray-500\">Skipped</p>\n </div>\n <div className=\"bg-white rounded-lg border border-green-100 py-2 px-3\">\n <p className=\"text-2xl font-bold text-amber-600\">{result.errors?.length ?? 0}</p>\n <p className=\"text-xs text-gray-500\">Warnings</p>\n </div>\n </div>\n <p className=\"text-xs text-gray-500 mb-3\">\n Skipped rows are internal bank transfers (ТРАНСФЕР СОБСТВЕНИ СМЕТКИ).\n </p>\n {result.errors?.length > 0 && (\n <details className=\"mb-3\">\n <summary className=\"text-xs text-amber-700 cursor-pointer hover:text-amber-800\">\n Show {result.errors.length} warning{result.errors.length !== 1 ? 's' : ''}\n </summary>\n <ul className=\"mt-2 text-xs text-amber-600 space-y-0.5 max-h-32 overflow-y-auto\">\n {result.errors.map((e, i) => <li key={i} className=\"font-mono\">{e}</li>)}\n </ul>\n </details>\n )}\n <button\n onClick={onUploadSuccess}\n className=\"flex items-center gap-1.5 text-sm font-medium text-green-700 hover:text-green-800\"\n >\n <ArrowLeft className=\"w-4 h-4\" />\n View imported transactions\n </button>\n </div>\n )}\n\n {/* Error */}\n {error && (\n <div className=\"mt-4 bg-red-50 border border-red-200 rounded-xl p-4 flex items-start gap-3\">\n <AlertCircle className=\"w-5 h-5 text-red-500 flex-shrink-0 mt-0.5\" />\n <div>\n <p className=\"text-sm font-medium text-red-800\">Upload failed</p>\n <p className=\"text-sm text-red-700 mt-0.5\">{error}</p>\n </div>\n </div>\n )}\n\n {/* Info box */}\n {!result && !error && (\n <div className=\"mt-6 bg-blue-50 border border-blue-100 rounded-xl p-4\">\n <p className=\"text-xs font-medium text-blue-800 mb-1\">Expected CSV format (DSK Bank export)</p>\n <p className=\"text-xs text-blue-700 font-mono\">\n Дата, Вид на трансакцията, Основание, Дебит BGN, Кредит BGN, Наредител/Получател, Номер сметка...\n </p>\n <p className=\"text-xs text-blue-600 mt-2\">\n Both UTF-8 and Windows-1251 encodings are supported. Tags are auto-applied based on payee and description keywords.\n </p>\n </div>\n )}\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentCard.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentCard.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"186 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState } from 'react';\nimport {\n Send, XCircle, CheckCircle, MinusCircle, Clock,\n CreditCard, Tag, Plus, X,\n} from 'lucide-react';\n\nconst STATUS_CONFIG = {\n UNPROCESSED: { label: 'Unprocessed', icon: Clock, color: 'bg-amber-100 text-amber-700 border-amber-200' },\n SENT: { label: 'Sent', icon: CheckCircle, color: 'bg-green-100 text-green-700 border-green-200' },\n SKIPPED: { label: 'Skipped', icon: MinusCircle, color: 'bg-gray-100 text-gray-500 border-gray-200' },\n};\n\nconst TAG_COLORS = [\n '#ef4444', '#f97316', '#eab308', '#22c55e', '#06b6d4',\n '#3b82f6', '#8b5cf6', '#ec4899', '#6b7280',\n];\n\nexport default function PaymentCard({ payment, onSend, onSkip, onAddTag, onRemoveTag, existingTags }) {\n const [showTagInput, setShowTagInput] = useState(false);\n const [newTagName, setNewTagName] = useState('');\n const [newTagColor, setNewTagColor] = useState('#3b82f6');\n\n const statusCfg = STATUS_CONFIG[payment.status] || STATUS_CONFIG.UNPROCESSED;\n const StatusIcon = statusCfg.icon;\n\n const handleAddTag = (e) => {\n e.preventDefault();\n if (newTagName.trim()) {\n onAddTag(payment.id, newTagName.trim(), newTagColor);\n setNewTagName('');\n setShowTagInput(false);\n }\n };\n\n const paymentTags = payment.tags || [];\n const availableTags = existingTags.filter(t => !paymentTags.some(pt => pt.id === t.id));\n\n const formattedDate = payment.date\n ? new Date(payment.date).toLocaleDateString('en-GB', {\n day: '2-digit', month: 'short', year: 'numeric', hour: '2-digit', minute: '2-digit',\n })\n : 'N/A';\n\n const currency = payment.currency || 'EUR';\n\n return (\n <div className=\"bg-white rounded-xl border border-gray-200 shadow-sm hover:shadow-md transition-shadow p-4\">\n <div className=\"flex items-start justify-between gap-3 mb-3\">\n <div className=\"flex-1 min-w-0\">\n <div className=\"flex items-center gap-2 mb-1\">\n <span className={`inline-flex items-center gap-1 px-2 py-0.5 text-xs font-medium rounded-full border ${statusCfg.color}`}>\n <StatusIcon className=\"w-3 h-3\" />\n {statusCfg.label}\n </span>\n {payment.source === 'UPLOAD' ? (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-emerald-50 text-emerald-700\">CSV</span>\n ) : (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-indigo-50 text-indigo-700\">SMS</span>\n )}\n </div>\n <p className=\"text-sm text-gray-600 break-words leading-relaxed\">{payment.rawMessage}</p>\n </div>\n </div>\n\n <div className=\"grid grid-cols-2 sm:grid-cols-4 gap-3 mb-3 text-sm\">\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Amount</span>\n <p className=\"font-semibold text-gray-900\">\n {payment.amount != null ? `${payment.amount.toFixed(2)} ${currency}` : 'N/A'}\n </p>\n </div>\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Date</span>\n <p className=\"text-gray-700\">{formattedDate}</p>\n </div>\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Card</span>\n <p className=\"text-gray-700 flex items-center gap-1\">\n <CreditCard className=\"w-3 h-3 text-gray-400\" />\n {payment.card || 'N/A'}\n </p>\n </div>\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Balance</span>\n <p className=\"text-gray-700\">\n {payment.balance != null ? `${payment.balance.toFixed(2)} ${currency}` : 'N/A'}\n </p>\n </div>\n </div>\n\n {/* Tags */}\n <div className=\"flex flex-wrap items-center gap-1.5 mb-3\">\n <Tag className=\"w-3 h-3 text-gray-400\" />\n {paymentTags.map(tag => (\n <span\n key={tag.id}\n className=\"inline-flex items-center gap-1 px-2 py-0.5 text-xs font-medium rounded-full text-white\"\n style={{ backgroundColor: tag.color }}\n >\n {tag.name}\n <button onClick={() => onRemoveTag(payment.id, tag.id)} className=\"hover:opacity-75\">\n <X className=\"w-3 h-3\" />\n </button>\n </span>\n ))}\n {!showTagInput ? (\n <button\n onClick={() => setShowTagInput(true)}\n className=\"inline-flex items-center gap-0.5 px-2 py-0.5 text-xs text-gray-500 border border-dashed border-gray-300 rounded-full hover:border-gray-400 hover:text-gray-600\"\n >\n <Plus className=\"w-3 h-3\" />\n Tag\n </button>\n ) : (\n <form onSubmit={handleAddTag} className=\"inline-flex items-center gap-1\">\n <input\n type=\"text\"\n value={newTagName}\n onChange={(e) => setNewTagName(e.target.value)}\n placeholder=\"Tag name\"\n autoFocus\n className=\"w-24 px-2 py-0.5 text-xs border border-gray-300 rounded-md focus:ring-1 focus:ring-indigo-500 outline-none\"\n />\n <div className=\"flex gap-0.5\">\n {TAG_COLORS.map(c => (\n <button\n key={c}\n type=\"button\"\n onClick={() => setNewTagColor(c)}\n className={`w-4 h-4 rounded-full border-2 ${newTagColor === c ? 'border-gray-800' : 'border-transparent'}`}\n style={{ backgroundColor: c }}\n />\n ))}\n </div>\n <button type=\"submit\" className=\"text-xs text-indigo-600 font-medium hover:text-indigo-700\">Add</button>\n <button type=\"button\" onClick={() => setShowTagInput(false)} className=\"text-xs text-gray-400 hover:text-gray-600\">\n <X className=\"w-3 h-3\" />\n </button>\n </form>\n )}\n {showTagInput && availableTags.length > 0 && (\n <div className=\"flex flex-wrap gap-1 ml-1\">\n {availableTags.slice(0, 5).map(tag => (\n <button\n key={tag.id}\n onClick={() => { onAddTag(payment.id, tag.name, tag.color); setShowTagInput(false); }}\n className=\"px-2 py-0.5 text-xs rounded-full border border-gray-200 text-gray-600 hover:bg-gray-100\"\n >\n {tag.name}\n </button>\n ))}\n </div>\n )}\n </div>\n\n {payment.status === 'UNPROCESSED' && (\n <div className=\"flex items-center gap-2 pt-3 border-t border-gray-100\">\n <button\n onClick={() => onSend(payment.id)}\n className=\"flex items-center gap-1.5 px-4 py-2 text-sm font-medium text-white bg-indigo-600 rounded-lg hover:bg-indigo-700 transition-colors\"\n >\n <Send className=\"w-4 h-4\" />\n Send\n </button>\n <button\n onClick={() => onSkip(payment.id)}\n className=\"flex items-center gap-1.5 px-4 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 transition-colors\"\n >\n <XCircle className=\"w-4 h-4\" />\n Do Not Send\n </button>\n </div>\n )}\n\n {payment.status === 'SENT' && payment.notifiedAt && (\n <div className=\"pt-3 border-t border-gray-100\">\n <p className=\"text-xs text-green-600\">\n Notified on {new Date(payment.notifiedAt).toLocaleString('en-GB')}\n {payment.notifyPhone && ` to ${payment.notifyPhone}`}\n </p>\n </div>\n )}\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentList.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentList.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"40 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React from 'react';\nimport { Inbox } from 'lucide-react';\nimport PaymentCard from './PaymentCard';\n\nexport default function PaymentList({ payments, loading, onSend, onSkip, onAddTag, onRemoveTag, existingTags }) {\n if (loading) {\n return (\n <div className=\"flex items-center justify-center py-20\">\n <div className=\"animate-spin rounded-full h-8 w-8 border-b-2 border-indigo-600\"></div>\n </div>\n );\n }\n\n if (!payments || payments.length === 0) {\n return (\n <div className=\"flex flex-col items-center justify-center py-20 text-gray-400\">\n <Inbox className=\"w-12 h-12 mb-3\" />\n <p className=\"text-lg font-medium\">No transactions found</p>\n <p className=\"text-sm\">Try adjusting your filters, ingest a payment SMS, or upload a CSV.</p>\n </div>\n );\n }\n\n return (\n <div className=\"space-y-4\">\n {payments.map(payment => (\n <PaymentCard\n key={payment.id}\n payment={payment}\n onSend={onSend}\n onSkip={onSkip}\n onAddTag={onAddTag}\n onRemoveTag={onRemoveTag}\n existingTags={existingTags}\n />\n ))}\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"All files are written. Now building:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build finance-hub Docker images","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cd /volume2/docker/finance/finance-hub && docker compose build 2>&1","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":24,"on_screen":false,"help_text":"Copy code","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"OUT","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Exit code 1\ntime=\"2026-05-08T21:48:56+03:00\" level=warning msg=\"The \\\"DB_PASSWORD\\\" variable is not set. Defaulting to a blank string.\"\ntime=\"2026-05-08T21:48:56+03:00\" level=warning msg=\"The \\\"DB_PASSWORD\\\" variable is not set. Defaulting to a blank string.\"\ntime=\"2026-05-08T21:48:56+03:00\" level=warning msg=\"The \\\"NOTIFIER_URL\\\" variable is not set. Defaulting to a blank string.\"\ntime=\"2026-05-08T21:48:56+03:00\" level=warning msg=\"The \\\"NOTIFY_DEFAULT_PHONE\\\" variable is not set. Defaulting to a blank string.\"\ntime=\"2026-05-08T21:48:56+03:00\" level=warning msg=\"/volume2/docker/finance/finance-hub/docker-compose.yml: `version` is obsolete\"\npermission denied while trying to connect to the Docker daemon socket at unix:///var/run/docker.sock: Head \"http://%2Fvar%2Frun%2Fdocker.sock/_ping\": dial unix /var/run/docker.sock: connect: permission denied","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build finance-hub Docker images with sudo","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cd /volume2/docker/finance/finance-hub && sudo docker compose build 2>&1","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":24,"on_screen":false,"help_text":"Copy code","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"OUT","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Exit code 1\nsudo: a terminal is required to read the password; either use the -S option to read from standard input or configure an askpass helper\nsudo: a password is required","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check user groups and docker socket permissions","depth":24,"on_screen":false,"role_description":"text"}]...
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6809041617504496635
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G)
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
report(1).csv, Editor Group 1
report(2).csv, Editor Group 1
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
Design new payment-logge…, Editor Group 2
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Design new payment-logger and dsk-uploader hybrid app
Session history
New session
Message actions
payments.js
payments.js
ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.
Thinking
Thinking
I'll explore all three reference projects in parallel to understand their structure before planning.
Agent:
Explore payment-logger app structure and functionality
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How data flows (ingest, storage, retrieval)
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.
Agent:
Explore dsk-uploader app structure and functionality
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How file uploads work - what files, what format, how parsed
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.
Agent:
Explore auth folder and authentik integration
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. What auth system is being used (Authentik)
2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?
3. Middleware - how is auth enforced on routes?
4. Any frontend auth flow - login redirect, token handling, protected routes
5. Environment variables related to auth
6. Docker/deployment setup for the auth service itself
7. Any example of how other apps integrate with this auth
Report with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.
Message actions
payments.js
payments.js
continue
Thinking
Thinking
Launching parallel exploration of all three reference projects.
Agent:
Explore payment-logger app structure
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How data is ingested (look at /ingest route especially)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore dsk-uploader app structure
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How file uploads work (what format, what processing happens)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore auth project structure
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. What authentication system is used (authentik integration details)
3. How OAuth/OIDC flow works
4. Any middleware or helper functions for protecting routes
5. Session management approach
6. How frontend handles auth state
7. Any example of how other apps integrate with this auth system
8. Docker setup and environment variables
Please read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.
Thinking
Thinking
Now I have a complete picture of all three. Let me design the plan.
Agent:
Design combined app architecture
IN
Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:
---
## App 1: payments-logger (Node.js)
- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI
- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS
- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage
- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)
- **Schema** (PostgreSQL via Prisma):
- `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at
- `tags` table: id, name, color — M2M with payments via `_PaymentToTag`
- `users` table: id, username, hashed_password (this will be REMOVED)
- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system
- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance
## App 2: dsk-uploader (Python/Flask)
- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database
- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5
- **Auth**: None (open)
- **CSV format** (DSK Bank Bulgarian format, columns):
- `Дата` (date, DD.MM.YYYY)
- `Вид на трансакцията` (transaction type, Bulgarian)
- `Основание` (reason/description — contains card number regex: `^\d{6}x{6}\d{4}$`)
- `Дебит BGN` (debit amount, may be empty)
- `Кредит BGN` (credit amount, may be empty)
- `Наредител/Получател` (orderer/recipient name)
- `Номер сметка на наредителя / получателя` (account number)
- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers
- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)
## App 3: auth (Authentik)
- **Mode**: Proxy mode via NPM (forward auth)
- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:
- `X-authentik-username`
- `X-authentik-email`
- `X-authentik-groups`
- **No code integration needed** in the app itself — just trust these headers from NPM
- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`
---
## What the New Combined App Must Do
1. **Single PostgreSQL database** for all transactions
2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST
3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema
4. **Unified UI** — show all payments in one table regardless of source
5. **Source indicator** in UI — badge showing "INGEST", "UPLOAD", or "BOTH" (if duplicate detection added)
6. **Source filter** in FilterBar — filter by All/Ingest/Upload
7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM
8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination
9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL
---
## Technical Constraints
- Keep Node.js backend (not Python) — extend payments-logger's stack
- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)
- File upload: use `multer` npm middleware
- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)
- Add `source` enum field (INGEST/UPLOAD) to payments schema
- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is
- Remove `users` table from schema
---
## Please Design
1. Complete folder structure for the new app (suggest name: "finance-hub" or similar — note this is a placeholder, user will confirm)
2. Prisma schema with new fields (`source`, `currency`)
3. All backend API routes
4. CSV parser design in Node.js (port of the Python logic)
5. Authentik auth middleware
6. Frontend component structure (React) — what's reused from payments-logger, what's new
7. Docker Compose setup
8. Environment variables needed
9. Step-by-step implementation order
10. Verification checklist
Be specific about file paths and code structure. This will be used to write actual implementation code.
Thinking
Thinking
Good plan. Let me ask the one thing I need before writing the final plan.
AskUserQuestion
OUT
User has answered your questions: "What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding."="finance-hub". You can now continue with the user's answers in mind.
Thinking
Thinking
Writing the final plan now.
Thinking
Thinking
Write
ets-create-a-new-generic-sun.md
ets-create-a-new-generic-sun.md
326 lines
# finance-hub — Implementation Plan
## Context
Two separate finance apps exist as references and will be retired:
- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.
- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.
The new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).
---
## Tech Stack
| Layer | Choice | Rationale |
|-------|--------|-----------|
| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |
| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |
| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |
| Database | PostgreSQL 16 | Same as payments-logger |
| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |
| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |
| Container | Docker Compose | Same pattern as both reference apps |
**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage.
**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references.
**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.
---
## Folder Structure
```
/volume2/docker/finance/finance-hub/
├── docker-compose.yml
├── .env
├── .env.example
├── .gitignore
├── backend/
│ ├── Dockerfile
│ ├── package.json
│ ├── prisma/
│ │ ├── schema.prisma
│ │ └── migrations/
│ │ ├── migration_lock.toml
│ │ └── 20260508_init/
│ │ └── migration.sql
│ └── src/
│ ├── index.js ← entry point (Authentik middleware wired here)
│ ├── auth.js ← Authentik header middleware (replaces JWT auth)
│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)
│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)
│ └── routes/
│ ├── payments.js ← existing routes + source/currency additions
│ └── upload.js ← NEW: POST /api/upload/csv
└── frontend/
├── Dockerfile
├── package.json
├── vite.config.js
├── tailwind.config.js
├── postcss.config.js
├── index.html
└── src/
├── main.jsx ← remove AuthProvider wrapper
├── index.css
├── App.jsx ← remove auth state, add Upload tab toggle
└── components/
├── FilterBar.jsx ← add source filter select
├── PaymentTable.jsx ← add Source badge column + currency display
├── PaymentCard.jsx ← minor source badge addition
├── PaymentList.jsx ← unchanged
└── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI
```
---
## Database Schema (Prisma)
File: `backend/prisma/schema.prisma`
```prisma
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
}
model Payment {
id Int @id @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
auth.js
auth.js
27 lines
const PUBLIC_PATHS = new Set([
'/api/health',
'/api/payments/ingest',
]);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) {
return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });
}
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '')
.split(',')
.map(g => g.trim())
.filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
Write
parser.js
parser.js
104 lines
/**
* Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)
*
* Supported formats:
*
* POS / INTERNET / ECOM / P2P payment:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM withdrawal:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM utility payment (amount may include fee as AMOUNT/FEE):
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.
*/
const LOCAL_TZ = process.env.TZ || 'Europe/Sofia';
/**
* Convert a local-timezone date/time to a UTC Date object.
* Uses Intl to resolve the actual UTC offset (DST-aware).
*/
function localToUtc(year, month, day, hour, minute) {
const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));
const formatter = new Intl.DateTimeFormat('en-US', {
timeZone: LOCAL_TZ,
year: 'numeric', month: '2-digit', day: '2-digit',
hour: '2-digit', minute: '2-digit', second: '2-digit',
hour12: false,
});
const parts = {};
formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });
const localAtNaive = new Date(Date.UTC(
parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),
parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),
));
const offsetMs = localAtNaive.getTime() - naive.getTime();
return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);
}
function parsePaymentSms(message) {
const result = {
rawMessage: message,
date: null,
type: null,
card: null,
recipient: null,
amount: null,
balance: null,
};
// Date and time: "Na DD/MM/YYYY v HH:MM"
const dateMatch = message.match(/Na (\d{2})\/(\d{2})\/(\d{4}) v (\d{2}):(\d{2})/i);
if (dateMatch) {
const [, day, month, year, hour, minute] = dateMatch;
result.date = localToUtc(
parseInt(year), parseInt(month), parseInt(day),
parseInt(hour), parseInt(minute),
);
}
// Card mask: "s karta 400915***4447" or "s karta 483890***7162"
const cardMatch = message.match(/s karta\s+([\d*]+)/i);
if (cardMatch) {
result.card = cardMatch[1];
}
// Transaction type: supports both prepositions
// "na POS" / "na ATM" / "na INTERNET" etc. (payment)
// "ot ATM" (withdrawal)
const typeMatch = message.match(/(?:na|ot)\s+(POS|ATM|INTERNET|ECOM|P2P)\b/i);
if (typeMatch) {
result.type = typeMatch[1].toUpperCase();
}
// Recipient address: "s adres: MERCHANT" or "s adres:MERCHANT" (no space variant)
const recipientMatch = message.match(/s adres:\s*([^.]+)\./i);
if (recipientMatch) {
result.recipient = recipientMatch[1].trim();
}
// Amount: handles both verbs and the AMOUNT/FEE suffix format
// "sa plateni 7.78 EUR"
// "sa iztegleni 400.00 EUR"
// "sa plateni 0.50 EUR/0.50 EUR" → captures 0.50 (the charged amount, ignoring fee)
const amountMatch = message.match(/sa (?:plateni|iztegleni)\s+([\d.,]+)\s+[A-Z]{3}/i);
if (amountMatch) {
result.amount = parseFloat(amountMatch[1].replace(',', '.'));
}
// Balance: "Nalichni: 2583.07 EUR."
const balanceMatch = message.match(/Nalichni:\s*([\d.,]+)\s+[A-Z]{3}/i);
if (balanceMatch) {
result.balance = parseFloat(balanceMatch[1].replace(',', '.'));
}
return result;
}
module.exports = { parsePaymentSms };
Write
csvParser.js
csvParser.js
175 lines
/**
* DSK Bank CSV parser — Node.js port of dskuploader.py
*
* DSK Bank exports use Windows-1251 (cp1251) encoding.
* Each row maps to a Payment record with source=UPLOAD, currency=BGN.
*/
const { parse } = require('csv-parse');
const iconv = require('iconv-lite');
const SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';
const CARD_REGEX = /^\d{6}x{6}\d{4}$/;
const POS_REGEX = /^\s*ПЛАЩАНЕ\s+НА\s+ПОС\s+\d{2}\.\d{2}\.\d{4}\s+\d{2}:\d{2}/;
const COL = {
DATE: 'Дата',
TYPE: 'Вид на трансакцията',
REASON: 'Основание',
DEBIT: 'Дебит BGN',
CREDIT: 'Кредит BGN',
PAYEE: 'Наредител/Получател',
ACCT: 'Номер сметка на наредителя / получателя',
};
const TAG_RULES = [
['reason', 'ЗАПЛАТА', 'Salary'],
['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],
['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],
['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],
['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],
['payee', 'VIVACOM', 'Subscriptions'],
['payee', 'Google', 'Subscriptions'],
['payee', 'SkyShowtime', 'Subscriptions'],
['payee', 'NETFLIX', 'Subscriptions'],
['payee', 'LUKOIL', 'Bills'],
['payee', 'CityGate', 'Bills'],
['payee', 'CBA', 'Groceries'],
['payee', 'FANTASTICO', 'Groceries'],
['payee', 'LIDL', 'Groceries'],
];
function parseNum(val) {
if (val == null || val === '') return null;
if (typeof val === 'number') return isNaN(val) ? null : val;
const s = String(val).trim().replace(/\xa0/g, '').replace(/ /g, '').replace(',', '.');
const n = parseFloat(s);
return isNaN(n) ? null : n;
}
function parseDate(val) {
if (!val) return null;
const s = String(val).trim();
const m = s.match(/^(\d{2})\.(\d{2})\.(\d{4})$/);
if (m) {
return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));
}
return null;
}
function processReasonAndCard(reason) {
if (!reason || typeof reason !== 'string') return { reason: '', card: null };
const parts = reason.trim().split(' ');
let card = null;
let cleanReason = reason.trim();
if (parts[0] && CARD_REGEX.test(parts[0])) {
card = parts[0];
cleanReason = parts.slice(1).join(' ').trim();
}
if (POS_REGEX.test(cleanReason)) {
const posParts = cleanReason.split('<br/>');
try {
const dateTime = posParts[0].split('ПОС ')[1];
cleanReason = `POS PAYMENT ${dateTime}`;
} catch (_) { /* keep original */ }
}
return { reason: cleanReason.replace(/\s+/g, ' ').trim(), card };
}
function generateTags(fields) {
const tags = new Set();
for (const [field, keyword, tagName] of TAG_RULES) {
if ((fields[field] || '').includes(keyword)) {
tags.add(tagName);
}
}
return Array.from(tags);
}
function processRow(row) {
const transactionType = (row[COL.TYPE] || '').trim();
if (transactionType === SKIP_TYPE) return null;
const { reason, card } = processReasonAndCard(row[COL.REASON]);
const payee = (row[COL.PAYEE] || '...
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Explorer (⇧⌘E)
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Claude Code
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EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
report(1).csv, Editor Group 1
report(2).csv, Editor Group 1
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
Design new payment-logge…, Editor Group 2
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Design new payment-logger and dsk-uploader hybrid app
Session history
New session
Message actions
payments.js
payments.js
ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.
Thinking
Thinking
I'll explore all three reference projects in parallel to understand their structure before planning.
Agent:
Explore payment-logger app structure and functionality
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How data flows (ingest, storage, retrieval)
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.
Agent:
Explore dsk-uploader app structure and functionality
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How file uploads work - what files, what format, how parsed
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.
Agent:
Explore auth folder and authentik integration
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. What auth system is being used (Authentik)
2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?
3. Middleware - how is auth enforced on routes?
4. Any frontend auth flow - login redirect, token handling, protected routes
5. Environment variables related to auth
6. Docker/deployment setup for the auth service itself
7. Any example of how other apps integrate with this auth
Report with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.
Message actions
payments.js
payments.js
continue
Thinking
Thinking
Launching parallel exploration of all three reference projects.
Agent:
Explore payment-logger app structure
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How data is ingested (look at /ingest route especially)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore dsk-uploader app structure
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How file uploads work (what format, what processing happens)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore auth project structure
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. What authentication system is used (authentik integration details)
3. How OAuth/OIDC flow works
4. Any middleware or helper functions for protecting routes
5. Session management approach
6. How frontend handles auth state
7. Any example of how other apps integrate with this auth system
8. Docker setup and environment variables
Please read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.
Thinking
Thinking
Now I have a complete picture of all three. Let me design the plan.
Agent:
Design combined app architecture
IN
Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:
---
## App 1: payments-logger (Node.js)
- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI
- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS
- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage
- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)
- **Schema** (PostgreSQL via Prisma):
- `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at
- `tags` table: id, name, color — M2M with payments via `_PaymentToTag`
- `users` table: id, username, hashed_password (this will be REMOVED)
- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system
- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance
## App 2: dsk-uploader (Python/Flask)
- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database
- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5
- **Auth**: None (open)
- **CSV format** (DSK Bank Bulgarian format, columns):
- `Дата` (date, DD.MM.YYYY)
- `Вид на трансакцията` (transaction type, Bulgarian)
- `Основание` (reason/description — contains card number regex: `^\d{6}x{6}\d{4}$`)
- `Дебит BGN` (debit amount, may be empty)
- `Кредит BGN` (credit amount, may be empty)
- `Наредител/Получател` (orderer/recipient name)
- `Номер сметка на наредителя / получателя` (account number)
- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers
- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)
## App 3: auth (Authentik)
- **Mode**: Proxy mode via NPM (forward auth)
- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:
- `X-authentik-username`
- `X-authentik-email`
- `X-authentik-groups`
- **No code integration needed** in the app itself — just trust these headers from NPM
- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`
---
## What the New Combined App Must Do
1. **Single PostgreSQL database** for all transactions
2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST
3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema
4. **Unified UI** — show all payments in one table regardless of source
5. **Source indicator** in UI — badge showing "INGEST", "UPLOAD", or "BOTH" (if duplicate detection added)
6. **Source filter** in FilterBar — filter by All/Ingest/Upload
7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM
8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination
9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL
---
## Technical Constraints
- Keep Node.js backend (not Python) — extend payments-logger's stack
- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)
- File upload: use `multer` npm middleware
- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)
- Add `source` enum field (INGEST/UPLOAD) to payments schema
- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is
- Remove `users` table from schema
---
## Please Design
1. Complete folder structure for the new app (suggest name: "finance-hub" or similar — note this is a placeholder, user will confirm)
2. Prisma schema with new fields (`source`, `currency`)
3. All backend API routes
4. CSV parser design in Node.js (port of the Python logic)
5. Authentik auth middleware
6. Frontend component structure (React) — what's reused from payments-logger, what's new
7. Docker Compose setup
8. Environment variables needed
9. Step-by-step implementation order
10. Verification checklist
Be specific about file paths and code structure. This will be used to write actual implementation code.
Thinking
Thinking
Good plan. Let me ask the one thing I need before writing the final plan.
AskUserQuestion
OUT
User has answered your questions: "What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding."="finance-hub". You can now continue with the user's answers in mind.
Thinking
Thinking
Writing the final plan now.
Thinking
Thinking
Write
ets-create-a-new-generic-sun.md
ets-create-a-new-generic-sun.md
326 lines
# finance-hub — Implementation Plan
## Context
Two separate finance apps exist as references and will be retired:
- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.
- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.
The new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).
---
## Tech Stack
| Layer | Choice | Rationale |
|-------|--------|-----------|
| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |
| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |
| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |
| Database | PostgreSQL 16 | Same as payments-logger |
| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |
| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |
| Container | Docker Compose | Same pattern as both reference apps |
**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage.
**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references.
**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.
---
## Folder Structure
```
/volume2/docker/finance/finance-hub/
├── docker-compose.yml
├── .env
├── .env.example
├── .gitignore
├── backend/
│ ├── Dockerfile
│ ├── package.json
│ ├── prisma/
│ │ ├── schema.prisma
│ │ └── migrations/
│ │ ├── migration_lock.toml
│ │ └── 20260508_init/
│ │ └── migration.sql
│ └── src/
│ ├── index.js ← entry point (Authentik middleware wired here)
│ ├── auth.js ← Authentik header middleware (replaces JWT auth)
│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)
│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)
│ └── routes/
│ ├── payments.js ← existing routes + source/currency additions
│ └── upload.js ← NEW: POST /api/upload/csv
└── frontend/
├── Dockerfile
├── package.json
├── vite.config.js
├── tailwind.config.js
├── postcss.config.js
├── index.html
└── src/
├── main.jsx ← remove AuthProvider wrapper
├── index.css
├── App.jsx ← remove auth state, add Upload tab toggle
└── components/
├── FilterBar.jsx ← add source filter select
├── PaymentTable.jsx ← add Source badge column + currency display
├── PaymentCard.jsx ← minor source badge addition
├── PaymentList.jsx ← unchanged
└── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI
```
---
## Database Schema (Prisma)
File: `backend/prisma/schema.prisma`
```prisma
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
}
model Payment {
id Int @id @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
auth.js
auth.js
27 lines
const PUBLIC_PATHS = new Set([
'/api/health',
'/api/payments/ingest',
]);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) {
return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });
}
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '')
.split(',')
.map(g => g.trim())
.filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
Write
parser.js
parser.js
104 lines
/**
* Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)
*
* Supported formats:
*
* POS / INTERNET / ECOM / P2P payment:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM withdrawal:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM utility payment (amount may include fee as AMOUNT/FEE):
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.
*/
const LOCAL_TZ = process.env.TZ || 'Europe/Sofia';
/**
* Convert a local-timezone date/time to a UTC Date object.
* Uses Intl to resolve the actual UTC offset (DST-aware).
*/
function localToUtc(year, month, day, hour, minute) {
const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));
const formatter = new Intl.DateTimeFormat('en-US', {
timeZone: LOCAL_TZ,
year: 'numeric', month: '2-digit', day: '2-digit',
hour: '2-digit', minute: '2-digit', second: '2-digit',
hour12: false,
});
const parts = {};
formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });
const localAtNaive = new Date(Date.UTC(
parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),
parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),
));
const offsetMs = localAtNaive.getTime() - naive.getTime();
return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);
}
function parsePaymentSms(message) {
const result = {
rawMessage: message,
date: null,
type: null,
card: null,
recipient: null,
amount: null,
balance: null,
};
// Date and time: "Na DD/MM/YYYY v HH:MM"
const dateMatch = message.match(/Na (\d{2})\/(\d{2})\/(\d{4}) v (\d{2}):(\d{2})/i);
if (dateMatch) {
const [, day, month, year, hour, minute] = dateMatch;
result.date = localToUtc(
parseInt(year), parseInt(month), parseInt(day),
parseInt(hour), parseInt(minute),
);
}
// Card mask: "s karta 400915***4447" or "s karta 483890***7162"
const cardMatch = message.match(/s karta\s+([\d*]+)/i);
if (cardMatch) {
result.card = cardMatch[1];
}
// Transaction type: supports both prepositions
// "na POS" / "na ATM" / "na INTERNET" etc. (payment)
// "ot ATM" (withdrawal)
const typeMatch = message.match(/(?:na|ot)\s+(POS|ATM|INTERNET|ECOM|P2P)\b/i);
if (typeMatch) {
result.type = typeMatch[1].toUpperCase();
}
// Recipient address: "s adres: MERCHANT" or "s adres:MERCHANT" (no space variant)
const recipientMatch = message.match(/s adres:\s*([^.]+)\./i);
if (recipientMatch) {
result.recipient = recipientMatch[1].trim();
}
// Amount: handles both verbs and the AMOUNT/FEE suffix format
// "sa plateni 7.78 EUR"
// "sa iztegleni 400.00 EUR"
// "sa plateni 0.50 EUR/0.50 EUR" → captures 0.50 (the charged amount, ignoring fee)
const amountMatch = message.match(/sa (?:plateni|iztegleni)\s+([\d.,]+)\s+[A-Z]{3}/i);
if (amountMatch) {
result.amount = parseFloat(amountMatch[1].replace(',', '.'));
}
// Balance: "Nalichni: 2583.07 EUR."
const balanceMatch = message.match(/Nalichni:\s*([\d.,]+)\s+[A-Z]{3}/i);
if (balanceMatch) {
result.balance = parseFloat(balanceMatch[1].replace(',', '.'));
}
return result;
}
module.exports = { parsePaymentSms };
Write
csvParser.js
csvParser.js
175 lines
/**
* DSK Bank CSV parser — Node.js port of dskuploader.py
*
* DSK Bank exports use Windows-1251 (cp1251) encoding.
* Each row maps to a Payment record with source=UPLOAD, currency=BGN.
*/
const { parse } = require('csv-parse');
const iconv = require('iconv-lite');
const SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';
const CARD_REGEX = /^\d{6}x{6}\d{4}$/;
const POS_REGEX = /^\s*ПЛАЩАНЕ\s+НА\s+ПОС\s+\d{2}\.\d{2}\.\d{4}\s+\d{2}:\d{2}/;
const COL = {
DATE: 'Дата',
TYPE: 'Вид на трансакцията',
REASON: 'Основание',
DEBIT: 'Дебит BGN',
CREDIT: 'Кредит BGN',
PAYEE: 'Наредител/Получател',
ACCT: 'Номер сметка на наредителя / получателя',
};
const TAG_RULES = [
['reason', 'ЗАПЛАТА', 'Salary'],
['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],
['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],
['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],
['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],
['payee', 'VIVACOM', 'Subscriptions'],
['payee', 'Google', 'Subscriptions'],
['payee', 'SkyShowtime', 'Subscriptions'],
['payee', 'NETFLIX', 'Subscriptions'],
['payee', 'LUKOIL', 'Bills'],
['payee', 'CityGate', 'Bills'],
['payee', 'CBA', 'Groceries'],
['payee', 'FANTASTICO', 'Groceries'],
['payee', 'LIDL', 'Groceries'],
];
function parseNum(val) {
if (val == null || val === '') return null;
if (typeof val === 'number') return isNaN(val) ? null : val;
const s = String(val).trim().replace(/\xa0/g, '').replace(/ /g, '').replace(',', '.');
const n = parseFloat(s);
return isNaN(n) ? null : n;
}
function parseDate(val) {
if (!val) return null;
const s = String(val).trim();
const m = s.match(/^(\d{2})\.(\d{2})\.(\d{4})$/);
if (m) {
return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));
}
return null;
}
function processReasonAndCard(reason) {
if (!reason || typeof reason !== 'string') return { reason: '', card: null };
const parts = reason.trim().split(' ');
let card = null;
let cleanReason = reason.trim();
if (parts[0] && CARD_REGEX.test(parts[0])) {
card = parts[0];
cleanReason = parts.slice(1).join(' ').trim();
}
if (POS_REGEX.test(cleanReason)) {
const posParts = cleanReason.split('<br/>');
try {
const dateTime = posParts[0].split('ПОС ')[1];
cleanReason = `POS PAYMENT ${dateTime}`;
} catch (_) { /* keep original */ }
}
return { reason: cleanReason.replace(/\s+/g, ' ').trim(), card };
}
function generateTags(fields) {
const tags = new Set();
for (const [field, keyword, tagName] of TAG_RULES) {
if ((fields[field] || '').includes(keyword)) {
tags.add(tagName);
}
}
return Array.from(tags);
}
function processRow(row) {
const transactionType = (row[COL.TYPE] || '').trim();
if (transactionType === SKIP_TYPE) return null;
const { reason, card } = processReasonAndCard(row[COL.REASON]);
const payee = (row[COL.PAYEE] || '...
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4","depth":16,"bounds":{"left":0.85837764,"top":0.98244214,"width":0.022273935,"height":0.01755786},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Ln 1, Col 1","depth":16,"bounds":{"left":0.8327792,"top":0.98244214,"width":0.023936171,"height":0.01755786},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Info: Setting up SSH Host nas: Setting up SSH tunnel","depth":12,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Design new payment-logger and dsk-uploader hybrid app","depth":19,"bounds":{"left":0.56017286,"top":0.08060654,"width":0.099734046,"height":0.022346368},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Session 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actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"payments.js","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"I'll explore all three reference projects in parallel to understand their structure before planning.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How data flows (ingest, storage, retrieval)\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How file uploads work - what files, what format, how parsed\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth folder and authentik integration","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. What auth system is being used (Authentik)\n2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?\n3. Middleware - how is auth enforced on routes?\n4. Any frontend auth flow - login redirect, token handling, protected routes\n5. Environment variables related to auth\n6. Docker/deployment setup for the auth service itself\n7. Any example of how other apps integrate with this auth\n\nReport with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"payments.js","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"continue","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Launching parallel exploration of all three reference projects.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How data is ingested (look at /ingest route especially)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How file uploads work (what format, what processing happens)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth project structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. What authentication system is used (authentik integration details)\n3. How OAuth/OIDC flow works\n4. Any middleware or helper functions for protecting routes\n5. Session management approach\n6. How frontend handles auth state\n7. Any example of how other apps integrate with this auth system\n8. Docker setup and environment variables\n\nPlease read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now I have a complete picture of all three. Let me design the plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design combined app architecture","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:\n\n---\n\n## App 1: payments-logger (Node.js)\n- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI\n- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS\n- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage\n- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)\n- **Schema** (PostgreSQL via Prisma):\n - `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at\n - `tags` table: id, name, color — M2M with payments via `_PaymentToTag`\n - `users` table: id, username, hashed_password (this will be REMOVED)\n- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system\n- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance\n\n## App 2: dsk-uploader (Python/Flask)\n- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database\n- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5\n- **Auth**: None (open)\n- **CSV format** (DSK Bank Bulgarian format, columns):\n - `Дата` (date, DD.MM.YYYY)\n - `Вид на трансакцията` (transaction type, Bulgarian)\n - `Основание` (reason/description — contains card number regex: `^\\d{6}x{6}\\d{4}$`)\n - `Дебит BGN` (debit amount, may be empty)\n - `Кредит BGN` (credit amount, may be empty)\n - `Наредител/Получател` (orderer/recipient name)\n - `Номер сметка на наредителя / получателя` (account number)\n- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers\n- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)\n\n## App 3: auth (Authentik)\n- **Mode**: Proxy mode via NPM (forward auth)\n- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:\n - `X-authentik-username` \n - `X-authentik-email`\n - `X-authentik-groups`\n- **No code integration needed** in the app itself — just trust these headers from NPM\n- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`\n\n---\n\n## What the New Combined App Must Do\n\n1. **Single PostgreSQL database** for all transactions\n2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST\n3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema\n4. **Unified UI** — show all payments in one table regardless of source\n5. **Source indicator** in UI — badge showing \"INGEST\", \"UPLOAD\", or \"BOTH\" (if duplicate detection added)\n6. **Source filter** in FilterBar — filter by All/Ingest/Upload\n7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM\n8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination\n9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL\n\n---\n\n## Technical Constraints\n\n- Keep Node.js backend (not Python) — extend payments-logger's stack\n- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)\n- File upload: use `multer` npm middleware\n- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)\n- Add `source` enum field (INGEST/UPLOAD) to payments schema\n- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is\n- Remove `users` table from schema\n\n---\n\n## Please Design\n\n1. Complete folder structure for the new app (suggest name: \"finance-hub\" or similar — note this is a placeholder, user will confirm)\n2. Prisma schema with new fields (`source`, `currency`)\n3. All backend API routes\n4. CSV parser design in Node.js (port of the Python logic)\n5. Authentik auth middleware\n6. Frontend component structure (React) — what's reused from payments-logger, what's new\n7. Docker Compose setup\n8. Environment variables needed\n9. Step-by-step implementation order\n10. Verification checklist\n\nBe specific about file paths and code structure. This will be used to write actual implementation code.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good plan. Let me ask the one thing I need before writing the final plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"AskUserQuestion","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"OUT","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"User has answered your questions: \"What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding.\"=\"finance-hub\". You can now continue with the user's answers in mind.","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Writing the final plan now.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"326 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# finance-hub — Implementation Plan\n\n## Context\n\nTwo separate finance apps exist as references and will be retired:\n- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.\n- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.\n\nThe new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).\n\n---\n\n## Tech Stack\n\n| Layer | Choice | Rationale |\n|-------|--------|-----------|\n| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |\n| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |\n| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |\n| Database | PostgreSQL 16 | Same as payments-logger |\n| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |\n| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |\n| Container | Docker Compose | Same pattern as both reference apps |\n\n**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage. \n**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references. \n**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.\n\n---\n\n## Folder Structure\n\n```\n/volume2/docker/finance/finance-hub/\n├── docker-compose.yml\n├── .env\n├── .env.example\n├── .gitignore\n├── backend/\n│ ├── Dockerfile\n│ ├── package.json\n│ ├── prisma/\n│ │ ├── schema.prisma\n│ │ └── migrations/\n│ │ ├── migration_lock.toml\n│ │ └── 20260508_init/\n│ │ └── migration.sql\n│ └── src/\n│ ├── index.js ← entry point (Authentik middleware wired here)\n│ ├── auth.js ← Authentik header middleware (replaces JWT auth)\n│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)\n│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)\n│ └── routes/\n│ ├── payments.js ← existing routes + source/currency additions\n│ └── upload.js ← NEW: POST /api/upload/csv\n└── frontend/\n ├── Dockerfile\n ├── package.json\n ├── vite.config.js\n ├── tailwind.config.js\n ├── postcss.config.js\n ├── index.html\n └── src/\n ├── main.jsx ← remove AuthProvider wrapper\n ├── index.css\n ├── App.jsx ← remove auth state, add Upload tab toggle\n └── components/\n ├── FilterBar.jsx ← add source filter select\n ├── PaymentTable.jsx ← add Source badge column + currency display\n ├── PaymentCard.jsx ← minor source badge addition\n ├── PaymentList.jsx ← unchanged\n └── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI\n```\n\n---\n\n## Database Schema (Prisma)\n\nFile: `backend/prisma/schema.prisma`\n\n```prisma\ngenerator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status { UNPROCESSED SENT SKIPPED }\nenum Source { INGEST UPLOAD }\n```\n\n**Key decisions:**\n- No `User` model — Authentik owns identity.\n- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.\n- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.\n- `balance` is always null for CSV rows (DSK export does not include running balance).\n- Fresh consolidated migration — no data migration from reference apps required.\n\n---\n\n## API Routes\n\n| Method | Path | Auth | Description |\n|--------|------|------|-------------|\n| GET | /api/health | public | Health check |\n| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |\n| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |\n| GET | /api/payments/meta/tags | required | All tags |\n| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |\n| GET | /api/payments/:id | required | Single payment |\n| PATCH | /api/payments/:id | required | Update status |\n| DELETE | /api/payments/:id | required | Delete |\n| POST | /api/payments/:id/send | required | Send notification |\n| POST | /api/payments/:id/skip | required | Skip |\n| POST | /api/payments/:id/tags | required | Add/upsert tag |\n| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |\n| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |\n\n---\n\n## Key Implementation Details\n\n### auth.js (replaces entire old auth module)\n```js\nconst PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n const username = req.headers['x-authentik-username'];\n if (!username) return res.status(401).json({ error: 'Unauthorized' });\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),\n };\n next();\n}\nmodule.exports = { authentikMiddleware };\n```\n\n### csvParser.js (port of dskuploader.py)\n- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8\n- `csv-parse` parses the decoded text with `columns: true`\n- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`\n- Card extraction: regex `/^\\d{6}x{6}\\d{4}$/` on first token of `Основание`\n- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`\n- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`\n- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`\n\n### payments.js changes from payments-logger\n1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call\n2. Add `source` to the `GET /` where clause filter\n3. Add `sources` to `meta/filters` response\n4. Currency-aware amount formatting in notification message\n5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)\n\n### upload.js (new)\n- `multer` memory storage, max 10 files × 10 MB\n- Calls `parseDskCsv(buffer)` per file\n- Upserts tags via `prisma.tag.upsert` then connects\n- Returns `{ imported, skipped, errors, payments[] }`\n\n### Frontend changes\n- **Delete**: `auth.js`, `AuthProvider.jsx`\n- **main.jsx**: Remove `<AuthProvider>` wrapper\n- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add \"Payments\" / \"Upload CSV\" tab toggle\n- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols\n- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell\n- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`\n\n---\n\n## Docker Compose\n\n```yaml\nservices:\n db:\n image: postgres:16-alpine\n environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: ${DB_PASSWORD}, POSTGRES_DB: finance_hub }\n volumes: [pgdata:/var/lib/postgresql/data]\n healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }\n\n backend:\n build: ./backend\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports: [\"${BACKEND_PORT:-3001}:3001\"]\n depends_on: { db: { condition: service_healthy } }\n\n frontend:\n build: ./frontend\n ports: [\"${FRONTEND_PORT:-5175}:5173\"]\n depends_on: [backend]\n\nvolumes: { pgdata: }\n```\n\n**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.\n\n---\n\n## Environment Variables (.env)\n\n```bash\nDB_PASSWORD=change_me\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\nTZ=Europe/Sofia\nBACKEND_PORT=3001\nFRONTEND_PORT=5175\n```\n\nRemoved vs payments-logger: `JWT_SECRET`, `JWT_EXPIRE_MINUTES`.\n\n---\n\n## Implementation Order\n\n1. Create folder structure and write `docker-compose.yml`, `.env.example`, `.gitignore`\n2. Write `backend/prisma/schema.prisma` and migration SQL\n3. Write `backend/package.json` (add `csv-parse`, `iconv-lite`, `multer`; remove `bcryptjs`, `jose`)\n4. Write `backend/Dockerfile`\n5. Write `backend/src/auth.js` (Authentik middleware)\n6. Copy `backend/src/parser.js` verbatim from payments-logger\n7. Write `backend/src/csvParser.js` (Python port)\n8. Write `backend/src/routes/upload.js`\n9. Write `backend/src/routes/payments.js` (from payments-logger + 5 changes listed above)\n10. Write `backend/src/index.js`\n11. Copy frontend base from payments-logger; delete `auth.js` + `AuthProvider.jsx`\n12. Update `main.jsx`, `App.jsx`, `FilterBar.jsx`, `PaymentTable.jsx`\n13. Write `frontend/src/components/UploadPanel.jsx`\n14. Update `frontend/vite.config.js`\n15. `docker compose build && docker compose up -d`\n16. Run verification checklist\n\n---\n\n## Verification\n\n**Schema**\n- `payments` table has `source`, `currency`, `debit_bgn`, `credit_bgn`, `transaction_type`, `payer_account`\n- No `users` table; `Source` enum exists\n\n**Auth**\n- `GET /api/payments` → 401 without `x-authentik-username` header\n- `POST /api/payments/ingest` → 201 without any header\n- `curl -H \"x-authentik-username: test\" localhost:3001/api/payments` → 200\n\n**SMS Ingest**\n- DSK POS SMS → `source=INGEST`, `currency=EUR`, correct amount/card/recipient\n- Apple Wallet structured body → `type=WALLET`, `source=INGEST`\n- Rate limiter → 429 after 200 req/min\n\n**CSV Upload**\n- Single DSK CSV → rows with `source=UPLOAD`, `currency=BGN`\n- Multiple CSVs in one request → all merged\n- `ТРАНСФЕР СОБСТВЕНИ СМЕТКИ` rows counted in `skipped`, not imported\n- Card regex match from `Основание` column\n- Auto-tags applied (ЗАПЛАТА→Salary, LIDL→Groceries)\n- cp1251 file imports correctly\n\n**UI**\n- Source badge visible in payment table (SMS indigo, CSV emerald)\n- Source dropdown in FilterBar filters correctly\n- Amount shows correct currency per row\n- Upload Panel: drag-and-drop works, result summary shows counts\n- Logout redirects to Authentik sign_out\n- No login form shown (Authentik handles it at NPM level)\n- Tags, send, skip, delete all still work\n\n## Reference Files\n\n- `/volume2/docker/finance/payments-logger/backend/src/routes/payments.js`\n- `/volume2/docker/finance/payments-logger/backend/src/parser.js`\n- `/volume2/docker/finance/payments-logger/backend/src/index.js`\n- `/volume2/docker/finance/payments-logger/backend/src/auth.js`\n- `/volume2/docker/finance/payments-logger/backend/prisma/schema.prisma`\n- `/volume2/docker/finance/payments-logger/frontend/src/App.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/PaymentTable.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/FilterBar.jsx`\n- `/volume2/docker/finance/dsk-uploader/dskuploader.py`\n- `/volume2/docker/finance/auth/docker-compose.yml`","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Claude’s Plan","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Stayed in plan mode","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good question. Here's the full breakdown:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Backend Tech Stack — Options","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Backend Tech Stack — Options","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Why:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"payments-logger is already Node.js/Express/Prisma. The new app is 80% payments-logger with CSV upload added on top. Keeping the same stack means:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"verbatim, zero rewrite","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy the entire","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"routes/payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with minimal edits","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Same Prisma schema workflow, same migrations, same Docker image","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The CSV parsing logic (the only Python-specific thing) ports cleanly to","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"csv-parse","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— it's just regex + string manipulation, nothing pandas-specific","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Trade-off:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Have to port the Python CSV parsing to JS. It's ~150 lines and mostly string manipulation — straightforward.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option B: Python + FastAPI + SQLAlchemy","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option B: Python + FastAPI + SQLAlchemy","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rewrite everything in Python. dsk-uploader is Python, so CSV parsing is already done.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep the dsk-uploader CSV logic as-is (no porting). Python has better data science libraries if you later add analytics.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Lose the entire payments-logger backend (routes, parser, Prisma schema) — full rewrite. FastAPI + SQLAlchemy is a different mental model than Express + Prisma. Frontend stays React anyway, so the stack split doesn't simplify anything.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"More work overall, gains almost nothing.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep Node.js as the main API, add a separate Python FastAPI service just for CSV parsing. They share the DB.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Zero porting — Python CSV code used as-is.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two backend services to maintain, deploy, and keep in sync. Inter-service HTTP calls. Two Dockerfiles. For ~150 lines of CSV logic, this is massively over-engineered.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Not worth it.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Extend dsk-uploader into a full payments app.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pandas for CSV, no porting.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Jinja2 templates instead of React (or add React separately). Would need to reimplement the entire payments-logger (SMS parser, notification system, tag management, pagination/filtering). Flask's Jinja templating is far less capable than the existing React UI. The React frontend is the stronger UI foundation.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Worst of all options — rebuild the harder parts (UI, SMS parser, notification) for no gain.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Summary","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Summary","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"CSV porting effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"App rewrite effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Result 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Everything else in the plan reuses payments-logger code directly. That's why Node.js is the clear winner here.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Want to adjust the stack, or shall I proceed with Option A?","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ok sounds good. Implement all you suggested","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Starting implementation. Let me first read all the reference files I'll need to copy from.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"payments.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"App.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"App.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"FilterBar.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"FilterBar.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentTable.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentTable.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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payments-logger.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.css","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.css","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"vite.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"vite.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"tailwind.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"tailwind.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"postcss.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"postcss.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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components.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentCard.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentCard.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentList.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentList.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"schema.prisma","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"schema.prisma","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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Let me set up the todo list and start building.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create finance-hub directory structure","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"mkdir -p /volume2/docker/finance/finance-hub/backend/src/routes \\\n /volume2/docker/finance/finance-hub/backend/prisma/migrations/20260508_init \\\n /volume2/docker/finance/finance-hub/frontend/src/components && echo \"done\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":24,"on_screen":false,"help_text":"Copy code","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"OUT","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"done","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"docker-compose.yml","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"docker-compose.yml","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"45 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"version: '3.8'\n\nservices:\n db:\n image: postgres:16-alpine\n restart: unless-stopped\n environment:\n POSTGRES_USER: finance\n POSTGRES_PASSWORD: ${DB_PASSWORD}\n POSTGRES_DB: finance_hub\n volumes:\n - pgdata:/var/lib/postgresql/data\n healthcheck:\n test: [\"CMD-SHELL\", \"pg_isready -U finance -d finance_hub\"]\n interval: 5s\n timeout: 5s\n retries: 5\n\n backend:\n build: ./backend\n restart: unless-stopped\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports:\n - \"${BACKEND_PORT:-3001}:3001\"\n depends_on:\n db:\n condition: service_healthy\n\n frontend:\n build: ./frontend\n restart: unless-stopped\n ports:\n - \"${FRONTEND_PORT:-5175}:5173\"\n depends_on:\n - backend\n\nvolumes:\n pgdata:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".env.example","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".env.example","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"15 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Database\nDB_PASSWORD=change_me_strong_password\n\n# Notifier service (for SMS payment notifications)\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\n\n# Timezone (used by SMS parser for Bulgarian bank timestamps)\nTZ=Europe/Sofia\n\n# Ports (optional — defaults shown)\nBACKEND_PORT=3001\nFRONTEND_PORT=5175","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".gitignore","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".gitignore","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"5 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env\nnode_modules/\ndist/\n*.log","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"schema.prisma","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"schema.prisma","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"54 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"generator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status {\n UNPROCESSED\n SENT\n SKIPPED\n}\n\nenum Source {\n INGEST\n UPLOAD\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration.sql","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration.sql","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"55 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- CreateEnum\nCREATE TYPE \"Status\" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');\nCREATE TYPE \"Source\" AS ENUM ('INGEST', 'UPLOAD');\n\n-- CreateTable\nCREATE TABLE \"payments\" (\n \"id\" SERIAL PRIMARY KEY,\n \"raw_message\" TEXT NOT NULL,\n \"date\" TIMESTAMP(3),\n \"type\" TEXT,\n \"card\" TEXT,\n \"recipient\" TEXT,\n \"amount\" DOUBLE PRECISION,\n \"currency\" TEXT DEFAULT 'EUR',\n \"balance\" DOUBLE PRECISION,\n \"source\" \"Source\" NOT NULL DEFAULT 'INGEST',\n \"status\" \"Status\" NOT NULL DEFAULT 'UNPROCESSED',\n \"notified_at\" TIMESTAMP(3),\n \"notify_phone\" TEXT,\n \"debit_bgn\" DOUBLE PRECISION,\n \"credit_bgn\" DOUBLE PRECISION,\n \"transaction_type\" TEXT,\n \"payer_account\" TEXT,\n \"created_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,\n \"updated_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP\n);\n\n-- CreateTable\nCREATE TABLE \"tags\" (\n \"id\" SERIAL PRIMARY KEY,\n \"name\" TEXT NOT NULL,\n \"color\" TEXT NOT NULL DEFAULT '#6b7280'\n);\n\n-- CreateUniqueIndex\nCREATE UNIQUE INDEX \"tags_name_key\" ON \"tags\"(\"name\");\n\n-- CreateTable (M2M join)\nCREATE TABLE \"_PaymentToTag\" (\n \"A\" INTEGER NOT NULL,\n \"B\" INTEGER NOT NULL,\n CONSTRAINT \"_PaymentToTag_AB_pkey\" PRIMARY KEY (\"A\", \"B\")\n);\n\nCREATE INDEX \"_PaymentToTag_B_index\" ON \"_PaymentToTag\"(\"B\");\n\n-- AddForeignKey\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_A_fkey\"\n FOREIGN KEY (\"A\") REFERENCES \"payments\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;\n\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_B_fkey\"\n FOREIGN KEY (\"B\") REFERENCES \"tags\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration_lock.toml","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration_lock.toml","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"4 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Please do not edit this file manually\n# It should be added in your version-control system (e.g., Git)\nprovider = \"postgresql\"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"26 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"{\n \"name\": \"finance-hub-backend\",\n \"version\": \"1.0.0\",\n \"main\": \"src/index.js\",\n \"scripts\": {\n \"start\": \"node src/index.js\",\n \"dev\": \"nodemon src/index.js\",\n \"prisma:generate\": \"prisma generate\",\n \"prisma:migrate\": \"prisma migrate deploy\"\n },\n \"dependencies\": {\n \"@prisma/client\": \"^5.22.0\",\n \"cors\": \"^2.8.5\",\n \"csv-parse\": \"^5.5.6\",\n \"express\": \"^4.21.1\",\n \"express-rate-limit\": \"^7.4.0\",\n \"iconv-lite\": \"^0.6.3\",\n \"morgan\": \"^1.10.0\",\n \"multer\": \"^1.4.5-lts.1\"\n },\n \"devDependencies\": {\n \"nodemon\": \"^3.1.7\",\n \"prisma\": \"^5.22.0\"\n }\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"18 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"FROM node:20-alpine\n\nRUN apk add --no-cache openssl\n\nWORKDIR /app\n\nCOPY package.json package-lock.json* ./\nRUN npm install\n\nCOPY prisma ./prisma\nRUN npx prisma generate\n\nCOPY src ./src\n\nEXPOSE 3001\n\nCMD [\"sh\", \"-c\", \"npx prisma migrate deploy && node src/index.js\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"auth.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"auth.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"27 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const PUBLIC_PATHS = new Set([\n '/api/health',\n '/api/payments/ingest',\n]);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n\n const username = req.headers['x-authentik-username'];\n if (!username) {\n return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });\n }\n\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '')\n .split(',')\n .map(g => g.trim())\n .filter(Boolean),\n };\n\n next();\n}\n\nmodule.exports = { authentikMiddleware };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"104 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/**\n * Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)\n *\n * Supported formats:\n *\n * POS / INTERNET / ECOM / P2P payment:\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.\n *\n * ATM withdrawal:\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.\n *\n * ATM utility payment (amount may include fee as AMOUNT/FEE):\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.\n */\n\nconst LOCAL_TZ = process.env.TZ || 'Europe/Sofia';\n\n/**\n * Convert a local-timezone date/time to a UTC Date object.\n * Uses Intl to resolve the actual UTC offset (DST-aware).\n */\nfunction localToUtc(year, month, day, hour, minute) {\n const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));\n\n const formatter = new Intl.DateTimeFormat('en-US', {\n timeZone: LOCAL_TZ,\n year: 'numeric', month: '2-digit', day: '2-digit',\n hour: '2-digit', minute: '2-digit', second: '2-digit',\n hour12: false,\n });\n\n const parts = {};\n formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });\n\n const localAtNaive = new Date(Date.UTC(\n parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),\n parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),\n ));\n\n const offsetMs = localAtNaive.getTime() - naive.getTime();\n return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);\n}\n\nfunction parsePaymentSms(message) {\n const result = {\n rawMessage: message,\n date: null,\n type: null,\n card: null,\n recipient: null,\n amount: null,\n balance: null,\n };\n\n // Date and time: \"Na DD/MM/YYYY v HH:MM\"\n const dateMatch = message.match(/Na (\\d{2})\\/(\\d{2})\\/(\\d{4}) v (\\d{2}):(\\d{2})/i);\n if (dateMatch) {\n const [, day, month, year, hour, minute] = dateMatch;\n result.date = localToUtc(\n parseInt(year), parseInt(month), parseInt(day),\n parseInt(hour), parseInt(minute),\n );\n }\n\n // Card mask: \"s karta 400915***4447\" or \"s karta 483890***7162\"\n const cardMatch = message.match(/s karta\\s+([\\d*]+)/i);\n if (cardMatch) {\n result.card = cardMatch[1];\n }\n\n // Transaction type: supports both prepositions\n // \"na POS\" / \"na ATM\" / \"na INTERNET\" etc. (payment)\n // \"ot ATM\" (withdrawal)\n const typeMatch = message.match(/(?:na|ot)\\s+(POS|ATM|INTERNET|ECOM|P2P)\\b/i);\n if (typeMatch) {\n result.type = typeMatch[1].toUpperCase();\n }\n\n // Recipient address: \"s adres: MERCHANT\" or \"s adres:MERCHANT\" (no space variant)\n const recipientMatch = message.match(/s adres:\\s*([^.]+)\\./i);\n if (recipientMatch) {\n result.recipient = recipientMatch[1].trim();\n }\n\n // Amount: handles both verbs and the AMOUNT/FEE suffix format\n // \"sa plateni 7.78 EUR\"\n // \"sa iztegleni 400.00 EUR\"\n // \"sa plateni 0.50 EUR/0.50 EUR\" → captures 0.50 (the charged amount, ignoring fee)\n const amountMatch = message.match(/sa (?:plateni|iztegleni)\\s+([\\d.,]+)\\s+[A-Z]{3}/i);\n if (amountMatch) {\n result.amount = parseFloat(amountMatch[1].replace(',', '.'));\n }\n\n // Balance: \"Nalichni: 2583.07 EUR.\"\n const balanceMatch = message.match(/Nalichni:\\s*([\\d.,]+)\\s+[A-Z]{3}/i);\n if (balanceMatch) {\n result.balance = parseFloat(balanceMatch[1].replace(',', '.'));\n }\n\n return result;\n}\n\nmodule.exports = { parsePaymentSms };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"csvParser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"csvParser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"175 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/**\n * DSK Bank CSV parser — Node.js port of dskuploader.py\n *\n * DSK Bank exports use Windows-1251 (cp1251) encoding.\n * Each row maps to a Payment record with source=UPLOAD, currency=BGN.\n */\n\nconst { parse } = require('csv-parse');\nconst iconv = require('iconv-lite');\n\nconst SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';\nconst CARD_REGEX = /^\\d{6}x{6}\\d{4}$/;\nconst POS_REGEX = /^\\s*ПЛАЩАНЕ\\s+НА\\s+ПОС\\s+\\d{2}\\.\\d{2}\\.\\d{4}\\s+\\d{2}:\\d{2}/;\n\nconst COL = {\n DATE: 'Дата',\n TYPE: 'Вид на трансакцията',\n REASON: 'Основание',\n DEBIT: 'Дебит BGN',\n CREDIT: 'Кредит BGN',\n PAYEE: 'Наредител/Получател',\n ACCT: 'Номер сметка на наредителя / получателя',\n};\n\nconst TAG_RULES = [\n ['reason', 'ЗАПЛАТА', 'Salary'],\n ['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],\n ['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],\n ['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],\n ['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],\n ['payee', 'VIVACOM', 'Subscriptions'],\n ['payee', 'Google', 'Subscriptions'],\n ['payee', 'SkyShowtime', 'Subscriptions'],\n ['payee', 'NETFLIX', 'Subscriptions'],\n ['payee', 'LUKOIL', 'Bills'],\n ['payee', 'CityGate', 'Bills'],\n ['payee', 'CBA', 'Groceries'],\n ['payee', 'FANTASTICO', 'Groceries'],\n ['payee', 'LIDL', 'Groceries'],\n];\n\nfunction parseNum(val) {\n if (val == null || val === '') return null;\n if (typeof val === 'number') return isNaN(val) ? null : val;\n const s = String(val).trim().replace(/\\xa0/g, '').replace(/ /g, '').replace(',', '.');\n const n = parseFloat(s);\n return isNaN(n) ? null : n;\n}\n\nfunction parseDate(val) {\n if (!val) return null;\n const s = String(val).trim();\n const m = s.match(/^(\\d{2})\\.(\\d{2})\\.(\\d{4})$/);\n if (m) {\n return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));\n }\n return null;\n}\n\nfunction processReasonAndCard(reason) {\n if (!reason || typeof reason !== 'string') return { reason: '', card: null };\n\n const parts = reason.trim().split(' ');\n let card = null;\n let cleanReason = reason.trim();\n\n if (parts[0] && CARD_REGEX.test(parts[0])) {\n card = parts[0];\n cleanReason = parts.slice(1).join(' ').trim();\n }\n\n if (POS_REGEX.test(cleanReason)) {\n const posParts = cleanReason.split('<br/>');\n try {\n const dateTime = posParts[0].split('ПОС ')[1];\n cleanReason = `POS PAYMENT ${dateTime}`;\n } catch (_) { /* keep original */ }\n }\n\n return { reason: cleanReason.replace(/\\s+/g, ' ').trim(), card };\n}\n\nfunction generateTags(fields) {\n const tags = new Set();\n for (const [field, keyword, tagName] of TAG_RULES) {\n if ((fields[field] || '').includes(keyword)) {\n tags.add(tagName);\n }\n }\n return Array.from(tags);\n}\n\nfunction processRow(row) {\n const transactionType = (row[COL.TYPE] || '').trim();\n if (transactionType === SKIP_TYPE) return null;\n\n const { reason, card } = processReasonAndCard(row[COL.REASON]);\n const payee = (row[COL.PAYEE] || '').trim();\n const payerAccount = (row[COL.ACCT] || '').trim();\n const debitBgn = parseNum(row[COL.DEBIT]);\n const creditBgn = parseNum(row[COL.CREDIT]);\n const date = parseDate(row[COL.DATE]);\n\n const autoTags = generateTags({ reason, transactionType, payee, debitBgn, creditBgn });\n\n const amount = debitBgn ?? creditBgn ?? null;\n\n const rawMessage = [\n row[COL.DATE] && `Date: ${row[COL.DATE]}`,\n transactionType && `Type: ${transactionType}`,\n payee && `Payee: ${payee}`,\n debitBgn != null && `Debit: ${debitBgn} BGN`,\n creditBgn != null && `Credit: ${creditBgn} BGN`,\n ].filter(Boolean).join(' | ');\n\n return {\n rawMessage,\n date,\n type: null,\n card,\n recipient: payee || null,\n amount,\n currency: 'BGN',\n balance: null,\n source: 'UPLOAD',\n debitBgn,\n creditBgn,\n transactionType: transactionType || null,\n payerAccount: payerAccount || null,\n autoTags,\n };\n}\n\n/**\n * Parse a Buffer containing a DSK Bank CSV (cp1251 or UTF-8).\n * Returns { rows, skipped, errors }.\n */\nasync function parseDskCsv(buffer) {\n // Try cp1251 first (DSK Bank export encoding), fall back to UTF-8\n let text = iconv.decode(buffer, 'cp1251');\n if (!text.includes(COL.DATE)) {\n text = buffer.toString('utf-8');\n }\n\n return new Promise((resolve, reject) => {\n const rows = [];\n const errors = [];\n let skipped = 0;\n\n const parser = parse(text, {\n columns: true,\n skip_empty_lines: true,\n trim: true,\n relax_column_count: true,\n });\n\n parser.on('readable', () => {\n let record;\n while ((record = parser.read()) !== null) {\n try {\n const row = processRow(record);\n if (row === null) { skipped++; } else { rows.push(row); }\n } catch (err) {\n errors.push(err.message);\n }\n }\n });\n\n parser.on('error', reject);\n parser.on('end', () => resolve({ rows, skipped, errors }));\n });\n}\n\nmodule.exports = { parseDskCsv };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"39 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst cors = require('cors');\nconst morgan = require('morgan');\nconst rateLimit = require('express-rate-limit');\nconst { authentikMiddleware } = require('./auth');\nconst paymentsRouter = require('./routes/payments');\nconst uploadRouter = require('./routes/upload');\n\nconst app = express();\nconst PORT = process.env.PORT || 3001;\n\napp.use(cors());\napp.use(express.json({ limit: '16kb' }));\napp.use(morgan('combined'));\n\n// Rate-limit the public ingest endpoint before auth middleware\nconst ingestLimiter = rateLimit({\n windowMs: 60 * 1000,\n max: 200,\n standardHeaders: true,\n legacyHeaders: false,\n message: { error: 'Too many requests, slow down' },\n});\napp.use('/api/payments/ingest', ingestLimiter);\n\n// Authentik header auth (skips /api/health and /api/payments/ingest)\napp.use(authentikMiddleware);\n\napp.get('/api/health', (_req, res) => {\n res.json({ status: 'ok', timestamp: new Date().toISOString() });\n});\n\napp.use('/api/payments', paymentsRouter);\napp.use('/api/upload', uploadRouter);\n\napp.listen(PORT, '0.0.0.0', () => {\n console.log(`Finance Hub API running on port ${PORT}`);\n});","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"payments.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"399 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst { PrismaClient } = require('@prisma/client');\nconst { parsePaymentSms } = require('../parser');\n\nconst router = express.Router();\nconst prisma = new PrismaClient();\n\nconst NOTIFIER_URL = process.env.NOTIFIER_URL;\nconst NOTIFIER_CHANNEL = process.env.NOTIFIER_CHANNEL || 'viber';\nconst DEFAULT_PHONE = process.env.NOTIFY_DEFAULT_PHONE;\n\n// ── Helpers ───────────────────────────────────────────────────────────────────\n\nfunction parseId(raw) {\n const id = parseInt(raw, 10);\n return Number.isFinite(id) ? id : null;\n}\n\nfunction formatNotifyMessage(payment) {\n const currency = payment.currency || 'EUR';\n const parts = [];\n if (payment.amount != null) parts.push(`Amount: ${payment.amount.toFixed(2)} ${currency}`);\n if (payment.recipient) parts.push(`At: ${payment.recipient}`);\n if (payment.balance != null) parts.push(`Balance: ${payment.balance.toFixed(2)} ${currency}`);\n if (payment.date) parts.push(`Date: ${new Date(payment.date).toLocaleString('en-GB')}`);\n return parts.join('\\n');\n}\n\nasync function sendNotification(payment) {\n if (!NOTIFIER_URL) {\n console.warn('[NOTIFY] NOTIFIER_URL not set — skipping notification');\n return;\n }\n\n const phone = payment.notifyPhone || DEFAULT_PHONE;\n if (!phone) {\n console.warn('[NOTIFY] No phone number for payment #' + payment.id + ' and NOTIFY_DEFAULT_PHONE not set');\n return;\n }\n\n const body = {\n phone,\n notification: NOTIFIER_CHANNEL,\n message: formatNotifyMessage(payment),\n };\n\n const res = await fetch(NOTIFIER_URL, {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify(body),\n });\n\n if (!res.ok) {\n const text = await res.text().catch(() => '');\n throw new Error(`Notifier responded ${res.status}: ${text}`);\n }\n}\n\n// ── Ingest a payment (public — no auth) ──────────────────────────────────────\n//\n// Two modes:\n//\n// SMS mode (default):\n// { \"message\": \"<raw SMS text>\", \"notifyPhone\": \"...\" }\n//\n// Structured mode (Apple Wallet / manual):\n// { \"ingestMode\": \"apple_wallet\", \"amount\": 7.78, \"recipient\": \"Apple Store\",\n// \"type\": \"WALLET\", \"card\": \"••••4447\", \"date\": \"2026-02-22T10:30:00Z\" }\n//\nrouter.post('/ingest', async (req, res) => {\n try {\n const { message, notifyPhone, ingestMode } = req.body;\n\n let data;\n\n if (ingestMode === 'apple_wallet' || (!message && req.body.amount != null)) {\n // ── Structured / Apple Wallet mode ──────────────────────────────────────\n const { amount, recipient, type, card, date, balance } = req.body;\n if (amount == null || !recipient) {\n return res.status(400).json({ error: 'amount and recipient are required for structured ingest' });\n }\n\n const rawMessage = [\n `Source: ${ingestMode || 'structured'}`,\n `Amount: ${amount}`,\n recipient && `Recipient: ${recipient}`,\n type && `Type: ${type}`,\n card && `Card: ${card}`,\n ].filter(Boolean).join(' | ');\n\n data = {\n rawMessage,\n date: date ? new Date(date) : new Date(),\n type: type || 'WALLET',\n card: card || null,\n recipient,\n amount: parseFloat(amount),\n currency: 'EUR',\n balance: balance != null ? parseFloat(balance) : null,\n source: 'INGEST',\n notifyPhone: notifyPhone || null,\n };\n\n } else {\n // ── SMS mode ─────────────────────────────────────────────────────────────\n if (!message) {\n return res.status(400).json({ error: 'message is required' });\n }\n if (typeof message !== 'string' || message.length > 2000) {\n return res.status(400).json({ error: 'message must be a string under 2000 characters' });\n }\n\n const parsed = parsePaymentSms(message);\n data = {\n rawMessage: parsed.rawMessage,\n date: parsed.date,\n type: parsed.type,\n card: parsed.card,\n recipient: parsed.recipient,\n amount: parsed.amount,\n currency: 'EUR',\n balance: parsed.balance,\n source: 'INGEST',\n notifyPhone: notifyPhone || null,\n };\n }\n\n const payment = await prisma.payment.create({\n data,\n include: { tags: true },\n });\n\n res.status(201).json(payment);\n } catch (err) {\n console.error('Ingest error:', err);\n res.status(500).json({ error: 'Failed to ingest payment' });\n }\n});\n\n// ── List payments with filtering ──────────────────────────────────────────────\nrouter.get('/', async (req, res) => {\n try {\n const {\n status,\n type,\n tag,\n source,\n recipient,\n dateFrom,\n dateTo,\n search,\n sortBy = 'createdAt',\n sortDir = 'desc',\n page = 1,\n } = req.query;\n\n const limit = Math.min(parseInt(req.query.limit, 10) || 50, 200);\n\n const where = {};\n\n if (status) where.status = status;\n if (type) where.type = type;\n if (source) where.source = source;\n if (recipient) where.recipient = { contains: recipient, mode: 'insensitive' };\n if (tag) where.tags = { some: { name: tag } };\n if (search) {\n where.OR = [\n { rawMessage: { contains: search, mode: 'insensitive' } },\n { recipient: { contains: search, mode: 'insensitive' } },\n ];\n }\n if (dateFrom || dateTo) {\n where.date = {};\n if (dateFrom) where.date.gte = new Date(dateFrom);\n if (dateTo) where.date.lte = new Date(dateTo);\n }\n\n const allowedSortFields = ['date', 'amount', 'balance', 'recipient', 'type', 'source', 'createdAt', 'status'];\n const orderField = allowedSortFields.includes(sortBy) ? sortBy : 'createdAt';\n const orderDir = sortDir === 'asc' ? 'asc' : 'desc';\n\n const skip = (parseInt(page, 10) - 1) * limit;\n\n const [payments, total] = await Promise.all([\n prisma.payment.findMany({\n where,\n include: { tags: true },\n orderBy: { [orderField]: orderDir },\n skip,\n take: limit,\n }),\n prisma.payment.count({ where }),\n ]);\n\n res.json({ payments, total, page: parseInt(page, 10), limit });\n } catch (err) {\n console.error('List error:', err);\n res.status(500).json({ error: 'Failed to list payments' });\n }\n});\n\n// ── Get filter options ────────────────────────────────────────────────────────\nrouter.get('/meta/filters', async (_req, res) => {\n try {\n const [types, recipients, tags, sources] = await Promise.all([\n prisma.payment.findMany({ distinct: ['type'], select: { type: true }, where: { type: { not: null } } }),\n prisma.payment.findMany({ distinct: ['recipient'], select: { recipient: true }, where: { recipient: { not: null } } }),\n prisma.tag.findMany({ orderBy: { name: 'asc' } }),\n prisma.payment.findMany({ distinct: ['source'], select: { source: true } }),\n ]);\n\n res.json({\n types: types.map(t => t.type),\n recipients: recipients.map(r => r.recipient),\n tags,\n sources: sources.map(s => s.source),\n });\n } catch (err) {\n res.status(500).json({ error: 'Failed to get filters' });\n }\n});\n\n// ── Get all tags ──────────────────────────────────────────────────────────────\nrouter.get('/meta/tags', async (_req, res) => {\n try {\n const tags = await prisma.tag.findMany({ orderBy: { name: 'asc' } });\n res.json(tags);\n } catch (err) {\n res.status(500).json({ error: 'Failed to list tags' });\n }\n});\n\n// ── Get single payment ────────────────────────────────────────────────────────\nrouter.get('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({\n where: { id },\n include: { tags: true },\n });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n res.json(payment);\n } catch (err) {\n console.error('Get error:', err);\n res.status(500).json({ error: 'Failed to get payment' });\n }\n});\n\n// ── Update payment metadata (status) ─────────────────────────────────────────\nrouter.patch('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const { status } = req.body;\n const data = {};\n\n if (status) {\n const validStatuses = ['UNPROCESSED', 'SENT', 'SKIPPED'];\n if (!validStatuses.includes(status)) {\n return res.status(400).json({ error: `Invalid status. Must be one of: ${validStatuses.join(', ')}` });\n }\n data.status = status;\n }\n\n if (Object.keys(data).length === 0) {\n return res.status(400).json({ error: 'No valid fields to update' });\n }\n\n const updated = await prisma.payment.update({\n where: { id },\n data,\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n if (err.code === 'P2025') return res.status(404).json({ error: 'Not found' });\n console.error('Update error:', err);\n res.status(500).json({ error: 'Failed to update payment' });\n }\n});\n\n// ── Delete payment ───────────────────────────────────────────────────────────\nrouter.delete('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n await prisma.payment.delete({ where: { id } });\n res.json({ success: true });\n } catch (err) {\n if (err.code === 'P2025') return res.status(404).json({ error: 'Not found' });\n console.error('Delete error:', err);\n res.status(500).json({ error: 'Failed to delete payment' });\n }\n});\n\n// ── Send notification (mark as SENT + call notifier service) ─────────────────\nrouter.post('/:id/send', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({ where: { id } });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n if (payment.status !== 'UNPROCESSED') {\n return res.status(409).json({ error: `Payment is already ${payment.status.toLowerCase()}` });\n }\n\n await sendNotification(payment);\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { status: 'SENT', notifiedAt: new Date() },\n include: { tags: true },\n });\n\n res.json(updated);\n } catch (err) {\n console.error('Send error:', err);\n res.status(500).json({ error: 'Failed to send notification' });\n }\n});\n\n// ── Skip notification (mark as SKIPPED) ──────────────────────────────────────\nrouter.post('/:id/skip', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({ where: { id } });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n if (payment.status !== 'UNPROCESSED') {\n return res.status(409).json({ error: `Payment is already ${payment.status.toLowerCase()}` });\n }\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { status: 'SKIPPED' },\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n console.error('Skip error:', err);\n res.status(500).json({ error: 'Failed to skip payment' });\n }\n});\n\n// ── Add tag to payment ────────────────────────────────────────────────────────\nrouter.post('/:id/tags', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const { name, color } = req.body;\n if (!name) return res.status(400).json({ error: 'tag name is required' });\n\n const tag = await prisma.tag.upsert({\n where: { name },\n update: {},\n create: { name, color: color || '#6b7280' },\n });\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { tags: { connect: { id: tag.id } } },\n include: { tags: true },\n });\n\n res.json(updated);\n } catch (err) {\n console.error('Tag error:', err);\n res.status(500).json({ error: 'Failed to add tag' });\n }\n});\n\n// ── Remove tag from payment ───────────────────────────────────────────────────\nrouter.delete('/:id/tags/:tagId', async (req, res) => {\n const id = parseId(req.params.id);\n const tagId = parseId(req.params.tagId);\n if (id === null || tagId === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const updated = await prisma.payment.update({\n where: { id },\n data: { tags: { disconnect: { id: tagId } } },\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n console.error('Remove tag error:', err);\n res.status(500).json({ error: 'Failed to remove tag' });\n }\n});\n\nmodule.exports = router;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"upload.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"upload.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"89 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst multer = require('multer');\nconst { PrismaClient } = require('@prisma/client');\nconst { parseDskCsv } = require('../csvParser');\n\nconst router = express.Router();\nconst prisma = new PrismaClient();\n\nconst upload = multer({\n storage: multer.memoryStorage(),\n limits: { fileSize: 10 * 1024 * 1024, files: 10 },\n fileFilter: (_req, file, cb) => {\n if (file.mimetype === 'text/csv' || file.originalname.toLowerCase().endsWith('.csv')) {\n cb(null, true);\n } else {\n cb(new Error('Only CSV files are accepted'));\n }\n },\n});\n\n// POST /api/upload/csv\n// Accepts 1-10 CSV files, parses them, stores to DB with source=UPLOAD.\n// Returns { imported, skipped, errors, payments[] }\nrouter.post('/csv', upload.array('files', 10), async (req, res) => {\n if (!req.files || req.files.length === 0) {\n return res.status(400).json({ error: 'No files uploaded' });\n }\n\n const allRows = [];\n const allErrors = [];\n let totalSkipped = 0;\n\n for (const file of req.files) {\n try {\n const { rows, skipped, errors } = await parseDskCsv(file.buffer);\n allRows.push(...rows);\n totalSkipped += skipped;\n allErrors.push(...errors.map(e => `${file.originalname}: ${e}`));\n } catch (err) {\n allErrors.push(`${file.originalname}: ${err.message}`);\n }\n }\n\n if (allRows.length === 0) {\n return res.status(422).json({\n error: 'No importable rows found',\n skipped: totalSkipped,\n errors: allErrors,\n });\n }\n\n const created = [];\n\n for (const row of allRows) {\n const { autoTags, ...paymentData } = row;\n try {\n const tagConnects = [];\n for (const tagName of autoTags) {\n const tag = await prisma.tag.upsert({\n where: { name: tagName },\n update: {},\n create: { name: tagName, color: '#6b7280' },\n });\n tagConnects.push({ id: tag.id });\n }\n\n const payment = await prisma.payment.create({\n data: {\n ...paymentData,\n ...(tagConnects.length ? { tags: { connect: tagConnects } } : {}),\n },\n include: { tags: true },\n });\n created.push(payment);\n } catch (err) {\n allErrors.push(`Row insert failed: ${err.message}`);\n }\n }\n\n res.status(201).json({\n imported: created.length,\n skipped: totalSkipped,\n errors: allErrors,\n payments: created,\n });\n});\n\nmodule.exports = router;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now writing all frontend config files:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"24 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"{\n \"name\": \"finance-hub-frontend\",\n \"version\": \"1.0.0\",\n \"type\": \"module\",\n \"scripts\": {\n \"dev\": \"vite\",\n \"build\": \"vite build\",\n \"preview\": \"vite preview\"\n },\n \"dependencies\": {\n \"lucide-react\": \"^0.460.0\",\n \"react\": \"^18.3.1\",\n \"react-dom\": \"^18.3.1\"\n },\n \"devDependencies\": {\n \"@types/react\": \"^18.3.12\",\n \"@vitejs/plugin-react\": \"^4.3.4\",\n \"autoprefixer\": \"^10.4.20\",\n \"postcss\": \"^8.4.49\",\n \"tailwindcss\": \"^3.4.15\",\n \"vite\": \"^6.0.1\"\n }\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"FROM node:20-alpine\n\nWORKDIR /app\n\nCOPY package.json package-lock.json* ./\nRUN npm install\n\nCOPY . .\n\nEXPOSE 5173\n\nCMD [\"npm\", \"run\", \"dev\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"vite.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"vite.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"18 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import { defineConfig } from 'vite';\nimport react from '@vitejs/plugin-react';\n\nexport default defineConfig({\n plugins: [react()],\n server: {\n host: '0.0.0.0',\n port: 5173,\n allowedHosts: ['finance-hub.lakylak.xyz'],\n proxy: {\n '/api': {\n target: 'http://backend:3001',\n changeOrigin: true,\n },\n },\n },\n});","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"tailwind.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"tailwind.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"12 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/** @type {import('tailwindcss').Config} */\nexport default {\n content: [\n \"./index.html\",\n \"./src/**/*.{js,ts,jsx,tsx}\",\n ],\n theme: {\n extend: {},\n },\n plugins: [],\n};","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"postcss.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"postcss.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"7 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"export default {\n plugins: {\n tailwindcss: {},\n autoprefixer: {},\n },\n};","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.html","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.html","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"14 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"<!DOCTYPE html>\n<html lang=\"en\">\n <head>\n <meta charset=\"UTF-8\" />\n <meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\" />\n <title>Finance Hub</title>\n <link rel=\"icon\" type=\"image/svg+xml\" href=\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 100 100'><text y='.9em' font-size='90'>💰</text></svg>\" />\n </head>\n <body class=\"bg-gray-50 min-h-screen\">\n <div id=\"root\"></div>\n <script type=\"module\" src=\"/src/main.jsx\"></script>\n </body>\n</html>","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.css","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.css","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"4 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"@tailwind base;\n@tailwind components;\n@tailwind utilities;","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now writing all React components:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"11 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React from 'react';\nimport ReactDOM from 'react-dom/client';\nimport App from './App';\nimport './index.css';\n\nReactDOM.createRoot(document.getElementById('root')).render(\n <React.StrictMode>\n <App />\n </React.StrictMode>\n);","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"App.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"App.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"257 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState, useEffect, useCallback } from 'react';\nimport { LayoutDashboard, Upload, RefreshCw, LogOut } from 'lucide-react';\nimport FilterBar from './components/FilterBar';\nimport PaymentTable from './components/PaymentTable';\nimport UploadPanel from './components/UploadPanel';\n\nconst API_BASE = '/api/payments';\n\nexport default function App() {\n const [activeTab, setActiveTab] = useState('payments');\n const [payments, setPayments] = useState([]);\n const [total, setTotal] = useState(0);\n const [page, setPage] = useState(1);\n const [filters, setFilters] = useState({});\n const [sortBy, setSortBy] = useState('createdAt');\n const [sortDir, setSortDir] = useState('desc');\n const [filterOptions, setFilterOptions] = useState({ types: [], recipients: [], tags: [], sources: [] });\n const [loading, setLoading] = useState(false);\n\n const fetchPayments = useCallback(async () => {\n setLoading(true);\n try {\n const params = new URLSearchParams();\n params.set('page', page);\n params.set('limit', 50);\n params.set('sortBy', sortBy);\n params.set('sortDir', sortDir);\n Object.entries(filters).forEach(([key, val]) => {\n if (val) params.set(key, val);\n });\n const res = await fetch(`${API_BASE}?${params}`);\n const data = await res.json();\n setPayments(data.payments || []);\n setTotal(data.total || 0);\n } catch (err) {\n console.error('Failed to fetch payments:', err);\n } finally {\n setLoading(false);\n }\n }, [page, filters, sortBy, sortDir]);\n\n const fetchFilterOptions = useCallback(async () => {\n try {\n const res = await fetch(`${API_BASE}/meta/filters`);\n const data = await res.json();\n setFilterOptions(data);\n } catch (err) {\n console.error('Failed to fetch filter options:', err);\n }\n }, []);\n\n useEffect(() => {\n fetchPayments();\n }, [fetchPayments]);\n\n useEffect(() => {\n fetchFilterOptions();\n }, [fetchFilterOptions]);\n\n // Refresh payments list after a successful CSV upload\n const handleUploadSuccess = () => {\n fetchPayments();\n fetchFilterOptions();\n setActiveTab('payments');\n };\n\n const handleAction = async (id, action) => {\n try {\n await fetch(`${API_BASE}/${id}/${action}`, { method: 'POST' });\n fetchPayments();\n fetchFilterOptions();\n } catch (err) {\n console.error(`Failed to ${action} payment:`, err);\n }\n };\n\n const handleAddTag = async (id, tagName, tagColor) => {\n try {\n await fetch(`${API_BASE}/${id}/tags`, {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify({ name: tagName, color: tagColor }),\n });\n fetchPayments();\n fetchFilterOptions();\n } catch (err) {\n console.error('Failed to add tag:', err);\n }\n };\n\n const handleRemoveTag = async (paymentId, tagId) => {\n try {\n await fetch(`${API_BASE}/${paymentId}/tags/${tagId}`, { method: 'DELETE' });\n fetchPayments();\n } catch (err) {\n console.error('Failed to remove tag:', err);\n }\n };\n\n const handleDelete = async (id) => {\n try {\n await fetch(`${API_BASE}/${id}`, { method: 'DELETE' });\n fetchPayments();\n fetchFilterOptions();\n } catch (err) {\n console.error('Failed to delete payment:', err);\n }\n };\n\n const handleUpdateStatus = async (id, status) => {\n try {\n await fetch(`${API_BASE}/${id}`, {\n method: 'PATCH',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify({ status }),\n });\n fetchPayments();\n } catch (err) {\n console.error('Failed to update status:', err);\n }\n };\n\n const handleFilterChange = (newFilters) => {\n setFilters(newFilters);\n setPage(1);\n };\n\n const handleSort = (field) => {\n if (sortBy === field) {\n setSortDir(d => d === 'asc' ? 'desc' : 'asc');\n } else {\n setSortBy(field);\n setSortDir('desc');\n }\n setPage(1);\n };\n\n const totalPages = Math.ceil(total / 50);\n\n return (\n <div className=\"min-h-screen bg-gray-50\">\n <header className=\"bg-white border-b border-gray-200 shadow-sm\">\n <div className=\"max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-4\">\n <div className=\"flex items-center justify-between\">\n <div className=\"flex items-center gap-3\">\n <div className=\"bg-indigo-600 p-2 rounded-lg\">\n <LayoutDashboard className=\"w-6 h-6 text-white\" />\n </div>\n <div>\n <h1 className=\"text-xl font-bold text-gray-900\">Finance Hub</h1>\n <p className=\"text-sm text-gray-500\">{total} transaction{total !== 1 ? 's' : ''} total</p>\n </div>\n </div>\n\n <div className=\"flex items-center gap-2\">\n {/* Tab switcher */}\n <div className=\"flex items-center rounded-lg border border-gray-200 bg-gray-50 p-1 gap-1\">\n <button\n onClick={() => setActiveTab('payments')}\n className={`flex items-center gap-1.5 px-3 py-1.5 text-sm font-medium rounded-md transition-colors ${\n activeTab === 'payments'\n ? 'bg-white text-indigo-700 shadow-sm'\n : 'text-gray-600 hover:text-gray-900'\n }`}\n >\n <LayoutDashboard className=\"w-4 h-4\" />\n Payments\n </button>\n <button\n onClick={() => setActiveTab('upload')}\n className={`flex items-center gap-1.5 px-3 py-1.5 text-sm font-medium rounded-md transition-colors ${\n activeTab === 'upload'\n ? 'bg-white text-emerald-700 shadow-sm'\n : 'text-gray-600 hover:text-gray-900'\n }`}\n >\n <Upload className=\"w-4 h-4\" />\n Upload CSV\n </button>\n </div>\n\n {activeTab === 'payments' && (\n <button\n onClick={() => { fetchPayments(); fetchFilterOptions(); }}\n className=\"flex items-center gap-2 px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 transition-colors\"\n >\n <RefreshCw className={`w-4 h-4 ${loading ? 'animate-spin' : ''}`} />\n Refresh\n </button>\n )}\n\n <button\n onClick={() => { window.location.href = '/outpost.goauthentik.io/sign_out'; }}\n className=\"flex items-center gap-2 px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 transition-colors\"\n title=\"Sign out\"\n >\n <LogOut className=\"w-4 h-4\" />\n </button>\n </div>\n </div>\n </div>\n </header>\n\n <main className=\"max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-6\">\n {activeTab === 'payments' ? (\n <>\n <FilterBar\n filters={filters}\n filterOptions={filterOptions}\n onFilterChange={handleFilterChange}\n />\n\n <PaymentTable\n payments={payments}\n loading={loading}\n sortBy={sortBy}\n sortDir={sortDir}\n onSort={handleSort}\n onSend={(id) => handleAction(id, 'send')}\n onSkip={(id) => handleAction(id, 'skip')}\n onAddTag={handleAddTag}\n onRemoveTag={handleRemoveTag}\n onDelete={handleDelete}\n onUpdateStatus={handleUpdateStatus}\n existingTags={filterOptions.tags}\n />\n\n {totalPages > 1 && (\n <div className=\"flex items-center justify-center gap-2 mt-6\">\n <button\n onClick={() => setPage(p => Math.max(1, p - 1))}\n disabled={page === 1}\n className=\"px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 disabled:opacity-50 disabled:cursor-not-allowed\"\n >\n Previous\n </button>\n <span className=\"text-sm text-gray-600\">\n Page {page} of {totalPages}\n </span>\n <button\n onClick={() => setPage(p => Math.min(totalPages, p + 1))}\n disabled={page === totalPages}\n className=\"px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 disabled:opacity-50 disabled:cursor-not-allowed\"\n >\n Next\n </button>\n </div>\n )}\n </>\n ) : (\n <UploadPanel onUploadSuccess={handleUploadSuccess} />\n )}\n </main>\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"FilterBar.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"FilterBar.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"167 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState, useEffect } from 'react';\nimport { Search, Filter, X, Calendar, ChevronDown, ChevronUp } from 'lucide-react';\n\nconst STATUS_OPTIONS = [\n { value: '', label: 'All Statuses' },\n { value: 'UNPROCESSED', label: 'Unprocessed' },\n { value: 'SENT', label: 'Sent' },\n { value: 'SKIPPED', label: 'Skipped' },\n];\n\nconst SOURCE_OPTIONS = [\n { value: '', label: 'All Sources' },\n { value: 'INGEST', label: 'SMS Ingest' },\n { value: 'UPLOAD', label: 'CSV Upload' },\n];\n\nexport default function FilterBar({ filters, filterOptions, onFilterChange }) {\n const [search, setSearch] = useState(filters.search || '');\n const [isOpen, setIsOpen] = useState(() => window.innerWidth >= 768);\n\n useEffect(() => {\n const mq = window.matchMedia('(min-width: 768px)');\n const handler = (e) => setIsOpen(e.matches);\n mq.addEventListener('change', handler);\n return () => mq.removeEventListener('change', handler);\n }, []);\n\n const handleSearchSubmit = (e) => {\n e.preventDefault();\n onFilterChange({ ...filters, search: search || undefined });\n };\n\n const handleSelectChange = (key, value) => {\n const newFilters = { ...filters };\n if (value) {\n newFilters[key] = value;\n } else {\n delete newFilters[key];\n }\n onFilterChange(newFilters);\n };\n\n const clearFilters = () => {\n setSearch('');\n onFilterChange({});\n };\n\n const activeFilterCount = Object.keys(filters).length;\n const hasActiveFilters = activeFilterCount > 0;\n\n return (\n <div className=\"bg-white rounded-xl border border-gray-200 shadow-sm p-4 mb-6\">\n <button\n onClick={() => setIsOpen(!isOpen)}\n className=\"w-full flex items-center gap-2\"\n >\n <Filter className=\"w-4 h-4 text-gray-500\" />\n <span className=\"text-sm font-medium text-gray-700\">Filters</span>\n {hasActiveFilters && (\n <span className=\"inline-flex items-center justify-center w-5 h-5 text-xs font-bold text-white bg-indigo-600 rounded-full\">\n {activeFilterCount}\n </span>\n )}\n {hasActiveFilters && (\n <span\n onClick={(e) => { e.stopPropagation(); clearFilters(); }}\n className=\"ml-1 flex items-center gap-1 text-xs text-red-600 hover:text-red-700\"\n >\n <X className=\"w-3 h-3\" />\n Clear\n </span>\n )}\n <span className=\"ml-auto\">\n {isOpen\n ? <ChevronUp className=\"w-4 h-4 text-gray-400\" />\n : <ChevronDown className=\"w-4 h-4 text-gray-400\" />\n }\n </span>\n </button>\n\n {isOpen && (\n <div className=\"space-y-3 mt-3 pt-3 border-t border-gray-100\">\n <div className=\"grid grid-cols-1 sm:grid-cols-2 lg:grid-cols-5 gap-3\">\n <form onSubmit={handleSearchSubmit} className=\"relative\">\n <Search className=\"absolute left-3 top-1/2 -translate-y-1/2 w-4 h-4 text-gray-400\" />\n <input\n type=\"text\"\n placeholder=\"Search...\"\n value={search}\n onChange={(e) => setSearch(e.target.value)}\n onBlur={() => onFilterChange({ ...filters, search: search || undefined })}\n className=\"w-full pl-9 pr-3 py-2 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none\"\n />\n </form>\n\n <select\n value={filters.source || ''}\n onChange={(e) => handleSelectChange('source', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n {SOURCE_OPTIONS.map(opt => (\n <option key={opt.value} value={opt.value}>{opt.label}</option>\n ))}\n </select>\n\n <select\n value={filters.status || ''}\n onChange={(e) => handleSelectChange('status', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n {STATUS_OPTIONS.map(opt => (\n <option key={opt.value} value={opt.value}>{opt.label}</option>\n ))}\n </select>\n\n <select\n value={filters.type || ''}\n onChange={(e) => handleSelectChange('type', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n <option value=\"\">All Types</option>\n {(filterOptions.types || []).map(t => (\n <option key={t} value={t}>{t}</option>\n ))}\n </select>\n\n <select\n value={filters.tag || ''}\n onChange={(e) => handleSelectChange('tag', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n <option value=\"\">All Tags</option>\n {(filterOptions.tags || []).map(t => (\n <option key={t.id} value={t.name}>{t.name}</option>\n ))}\n </select>\n </div>\n\n <div className=\"grid grid-cols-1 sm:grid-cols-2 gap-3\">\n <div className=\"relative\">\n <Calendar className=\"absolute left-3 top-1/2 -translate-y-1/2 w-4 h-4 text-gray-400\" />\n <input\n type=\"date\"\n placeholder=\"From date\"\n value={filters.dateFrom || ''}\n onChange={(e) => handleSelectChange('dateFrom', e.target.value)}\n className=\"w-full pl-9 pr-3 py-2 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none\"\n />\n </div>\n\n <div className=\"relative\">\n <Calendar className=\"absolute left-3 top-1/2 -translate-y-1/2 w-4 h-4 text-gray-400\" />\n <input\n type=\"date\"\n placeholder=\"To date\"\n value={filters.dateTo || ''}\n onChange={(e) => handleSelectChange('dateTo', e.target.value)}\n className=\"w-full pl-9 pr-3 py-2 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none\"\n />\n </div>\n </div>\n </div>\n )}\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentTable.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentTable.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"339 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState } from 'react';\nimport {\n ArrowUpDown, ArrowUp, ArrowDown,\n Send, XCircle, CheckCircle, MinusCircle, Clock,\n Inbox, Plus, X, ChevronDown, ChevronUp, Trash2,\n} from 'lucide-react';\n\nconst STATUS_CONFIG = {\n UNPROCESSED: { label: 'Unprocessed', icon: Clock, color: 'bg-amber-100 text-amber-700' },\n SENT: { label: 'Sent', icon: CheckCircle, color: 'bg-green-100 text-green-700' },\n SKIPPED: { label: 'Skipped', icon: MinusCircle, color: 'bg-gray-100 text-gray-500' },\n};\n\nconst TAG_COLORS = [\n '#ef4444', '#f97316', '#eab308', '#22c55e', '#06b6d4',\n '#3b82f6', '#8b5cf6', '#ec4899', '#6b7280',\n];\n\nconst COLUMNS = [\n { key: 'date', label: 'Date & Time', sortable: true },\n { key: 'source', label: 'Source', sortable: true },\n { key: 'type', label: 'Type', sortable: true },\n { key: 'recipient', label: 'Recipient', sortable: true },\n { key: 'amount', label: 'Amount', sortable: true },\n { key: 'balance', label: 'Balance', sortable: true },\n { key: 'status', label: 'Status', sortable: true },\n { key: 'tags', label: 'Tags', sortable: false },\n { key: 'actions', label: 'Actions', sortable: false },\n];\n\nfunction SortIcon({ column, sortBy, sortDir }) {\n if (sortBy !== column) return <ArrowUpDown className=\"w-3 h-3 text-gray-400\" />;\n return sortDir === 'asc'\n ? <ArrowUp className=\"w-3 h-3 text-indigo-600\" />\n : <ArrowDown className=\"w-3 h-3 text-indigo-600\" />;\n}\n\nfunction SourceBadge({ source }) {\n if (source === 'UPLOAD') {\n return (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-emerald-50 text-emerald-700\">\n CSV\n </span>\n );\n }\n return (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-indigo-50 text-indigo-700\">\n SMS\n </span>\n );\n}\n\nfunction TagCell({ payment, onAddTag, onRemoveTag, existingTags }) {\n const [open, setOpen] = useState(false);\n const [newTagName, setNewTagName] = useState('');\n const [newTagColor, setNewTagColor] = useState('#3b82f6');\n\n const paymentTags = payment.tags || [];\n const availableTags = existingTags.filter(t => !paymentTags.some(pt => pt.id === t.id));\n\n const handleAdd = (e) => {\n e.preventDefault();\n if (newTagName.trim()) {\n onAddTag(payment.id, newTagName.trim(), newTagColor);\n setNewTagName('');\n setOpen(false);\n }\n };\n\n return (\n <div className=\"flex flex-wrap items-center gap-1\">\n {paymentTags.map(tag => (\n <span\n key={tag.id}\n className=\"inline-flex items-center gap-0.5 px-1.5 py-0.5 text-xs font-medium rounded-full text-white\"\n style={{ backgroundColor: tag.color }}\n >\n {tag.name}\n <button onClick={() => onRemoveTag(payment.id, tag.id)} className=\"hover:opacity-75\">\n <X className=\"w-2.5 h-2.5\" />\n </button>\n </span>\n ))}\n <div className=\"relative\">\n <button\n onClick={() => setOpen(!open)}\n className=\"inline-flex items-center gap-0.5 px-1.5 py-0.5 text-xs text-gray-500 border border-dashed border-gray-300 rounded-full hover:border-gray-400\"\n >\n <Plus className=\"w-2.5 h-2.5\" />\n </button>\n {open && (\n <div className=\"absolute z-20 top-full left-0 mt-1 bg-white border border-gray-200 rounded-lg shadow-lg p-2 w-56\">\n <form onSubmit={handleAdd} className=\"flex items-center gap-1 mb-2\">\n <input\n type=\"text\"\n value={newTagName}\n onChange={(e) => setNewTagName(e.target.value)}\n placeholder=\"New tag\"\n autoFocus\n className=\"flex-1 px-2 py-1 text-xs border border-gray-300 rounded focus:ring-1 focus:ring-indigo-500 outline-none\"\n />\n <button type=\"submit\" className=\"text-xs text-indigo-600 font-medium hover:text-indigo-700 whitespace-nowrap\">Add</button>\n </form>\n <div className=\"flex gap-1 mb-2\">\n {TAG_COLORS.map(c => (\n <button\n key={c}\n type=\"button\"\n onClick={() => setNewTagColor(c)}\n className={`w-4 h-4 rounded-full border-2 ${newTagColor === c ? 'border-gray-800' : 'border-transparent'}`}\n style={{ backgroundColor: c }}\n />\n ))}\n </div>\n {availableTags.length > 0 && (\n <div className=\"border-t border-gray-100 pt-1 flex flex-wrap gap-1\">\n {availableTags.map(tag => (\n <button\n key={tag.id}\n onClick={() => { onAddTag(payment.id, tag.name, tag.color); setOpen(false); }}\n className=\"px-1.5 py-0.5 text-xs rounded-full border border-gray-200 text-gray-600 hover:bg-gray-100\"\n >\n {tag.name}\n </button>\n ))}\n </div>\n )}\n </div>\n )}\n </div>\n </div>\n );\n}\n\nfunction ExpandedRow({ payment }) {\n return (\n <tr className=\"bg-gray-50\">\n <td colSpan={COLUMNS.length} className=\"px-4 py-3\">\n <div className=\"text-xs text-gray-500 uppercase tracking-wide mb-1\">Original Message / Raw Data</div>\n <p className=\"text-sm text-gray-700 whitespace-pre-wrap break-words\">{payment.rawMessage}</p>\n {payment.debitBgn != null && (\n <p className=\"text-xs text-gray-500 mt-1\">Debit: {payment.debitBgn.toFixed(2)} BGN</p>\n )}\n {payment.creditBgn != null && (\n <p className=\"text-xs text-gray-500 mt-0.5\">Credit: {payment.creditBgn.toFixed(2)} BGN</p>\n )}\n {payment.transactionType && (\n <p className=\"text-xs text-gray-500 mt-0.5\">Transaction type: {payment.transactionType}</p>\n )}\n {payment.payerAccount && (\n <p className=\"text-xs text-gray-500 mt-0.5\">Account: {payment.payerAccount}</p>\n )}\n {payment.notifiedAt && (\n <p className=\"text-xs text-green-600 mt-2\">\n Notified on {new Date(payment.notifiedAt).toLocaleString('en-GB')}\n {payment.notifyPhone && ` to ${payment.notifyPhone}`}\n </p>\n )}\n </td>\n </tr>\n );\n}\n\nfunction StatusCell({ payment, onUpdateStatus }) {\n const [open, setOpen] = useState(false);\n const statusCfg = STATUS_CONFIG[payment.status] || STATUS_CONFIG.UNPROCESSED;\n const StatusIcon = statusCfg.icon;\n\n return (\n <div className=\"relative\">\n <button\n onClick={() => setOpen(!open)}\n className={`inline-flex items-center gap-1 px-2 py-0.5 text-xs font-medium rounded-full cursor-pointer ${statusCfg.color}`}\n >\n <StatusIcon className=\"w-3 h-3\" />\n {statusCfg.label}\n </button>\n {open && (\n <div className=\"absolute z-20 top-full left-0 mt-1 bg-white border border-gray-200 rounded-lg shadow-lg py-1 w-36\">\n {Object.entries(STATUS_CONFIG).map(([key, cfg]) => {\n const Icon = cfg.icon;\n return (\n <button\n key={key}\n onClick={() => { onUpdateStatus(payment.id, key); setOpen(false); }}\n className={`w-full flex items-center gap-2 px-3 py-1.5 text-xs hover:bg-gray-50 ${payment.status === key ? 'font-bold' : ''}`}\n >\n <Icon className=\"w-3 h-3\" />\n {cfg.label}\n </button>\n );\n })}\n </div>\n )}\n </div>\n );\n}\n\nexport default function PaymentTable({\n payments, loading, sortBy, sortDir, onSort,\n onSend, onSkip, onAddTag, onRemoveTag, onDelete, onUpdateStatus, existingTags,\n}) {\n const [expandedId, setExpandedId] = useState(null);\n\n if (loading) {\n return (\n <div className=\"flex items-center justify-center py-20\">\n <div className=\"animate-spin rounded-full h-8 w-8 border-b-2 border-indigo-600\"></div>\n </div>\n );\n }\n\n if (!payments || payments.length === 0) {\n return (\n <div className=\"flex flex-col items-center justify-center py-20 text-gray-400\">\n <Inbox className=\"w-12 h-12 mb-3\" />\n <p className=\"text-lg font-medium\">No transactions found</p>\n <p className=\"text-sm\">Try adjusting your filters, ingest a payment SMS, or upload a CSV.</p>\n </div>\n );\n }\n\n const formatDate = (d) => {\n if (!d) return '—';\n return new Date(d).toLocaleDateString('en-GB', {\n day: '2-digit', month: 'short', year: 'numeric', hour: '2-digit', minute: '2-digit',\n });\n };\n\n const formatAmount = (v, currency) =>\n v != null ? `${v.toFixed(2)} ${currency || 'EUR'}` : '—';\n\n return (\n <div className=\"bg-white rounded-xl border border-gray-200 shadow-sm overflow-hidden\">\n <div className=\"overflow-x-auto\">\n <table className=\"w-full text-sm\">\n <thead>\n <tr className=\"bg-gray-50 border-b border-gray-200\">\n {COLUMNS.map(col => (\n <th\n key={col.key}\n className={`px-4 py-3 text-left text-xs font-semibold text-gray-600 uppercase tracking-wider ${col.sortable ? 'cursor-pointer select-none hover:bg-gray-100' : ''}`}\n onClick={() => col.sortable && onSort(col.key)}\n >\n <span className=\"inline-flex items-center gap-1\">\n {col.label}\n {col.sortable && <SortIcon column={col.key} sortBy={sortBy} sortDir={sortDir} />}\n </span>\n </th>\n ))}\n </tr>\n </thead>\n <tbody className=\"divide-y divide-gray-100\">\n {payments.map(p => {\n const isExpanded = expandedId === p.id;\n return (\n <React.Fragment key={p.id}>\n <tr className=\"hover:bg-gray-50 transition-colors\">\n <td className=\"px-4 py-3 whitespace-nowrap text-gray-700\">{formatDate(p.date)}</td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n <SourceBadge source={p.source} />\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n {p.type ? (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-blue-50 text-blue-700\">{p.type}</span>\n ) : (p.transactionType ? (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-gray-100 text-gray-600 max-w-24 truncate block\" title={p.transactionType}>{p.transactionType}</span>\n ) : '—')}\n </td>\n <td className=\"px-4 py-3 text-gray-700 max-w-xs truncate\" title={p.recipient || ''}>\n <div className=\"flex items-center gap-1\">\n <span className=\"truncate\">{p.recipient || '—'}</span>\n <button\n onClick={() => setExpandedId(isExpanded ? null : p.id)}\n className=\"flex-shrink-0 text-gray-400 hover:text-gray-600\"\n title=\"Show raw data\"\n >\n {isExpanded ? <ChevronUp className=\"w-3.5 h-3.5\" /> : <ChevronDown className=\"w-3.5 h-3.5\" />}\n </button>\n </div>\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap font-medium text-gray-900\">\n {formatAmount(p.amount, p.currency)}\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap text-gray-600\">\n {formatAmount(p.balance, p.currency)}\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n <StatusCell payment={p} onUpdateStatus={onUpdateStatus} />\n </td>\n <td className=\"px-4 py-3\">\n <TagCell\n payment={p}\n onAddTag={onAddTag}\n onRemoveTag={onRemoveTag}\n existingTags={existingTags}\n />\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n <div className=\"flex items-center gap-1.5\">\n {p.status === 'UNPROCESSED' && (\n <>\n <button\n onClick={() => onSend(p.id)}\n className=\"inline-flex items-center gap-1 px-2.5 py-1 text-xs font-medium text-white bg-indigo-600 rounded-md hover:bg-indigo-700 transition-colors\"\n >\n <Send className=\"w-3 h-3\" />\n Send\n </button>\n <button\n onClick={() => onSkip(p.id)}\n className=\"inline-flex items-center gap-1 px-2.5 py-1 text-xs font-medium text-gray-600 bg-white border border-gray-300 rounded-md hover:bg-gray-50 transition-colors\"\n >\n <XCircle className=\"w-3 h-3\" />\n Skip\n </button>\n </>\n )}\n <button\n onClick={() => { if (window.confirm('Delete this transaction?')) onDelete(p.id); }}\n className=\"inline-flex items-center gap-1 px-2 py-1 text-xs font-medium text-red-600 bg-white border border-red-200 rounded-md hover:bg-red-50 transition-colors\"\n title=\"Delete transaction\"\n >\n <Trash2 className=\"w-3 h-3\" />\n </button>\n </div>\n </td>\n </tr>\n {isExpanded && <ExpandedRow payment={p} />}\n </React.Fragment>\n );\n })}\n </tbody>\n </table>\n </div>\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"UploadPanel.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"UploadPanel.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"192 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState, useRef } from 'react';\nimport { Upload, FileText, CheckCircle, AlertCircle, X, ArrowLeft } from 'lucide-react';\n\nexport default function UploadPanel({ onUploadSuccess }) {\n const [files, setFiles] = useState([]);\n const [loading, setLoading] = useState(false);\n const [result, setResult] = useState(null);\n const [error, setError] = useState(null);\n const [dragging, setDragging] = useState(false);\n const fileInputRef = useRef();\n\n const addFiles = (incoming) => {\n const csvFiles = Array.from(incoming).filter(f =>\n f.name.toLowerCase().endsWith('.csv')\n );\n setFiles(prev => {\n const existingNames = new Set(prev.map(f => f.name));\n return [...prev, ...csvFiles.filter(f => !existingNames.has(f.name))];\n });\n };\n\n const handleDrop = (e) => {\n e.preventDefault();\n setDragging(false);\n addFiles(e.dataTransfer.files);\n };\n\n const handleFileSelect = (e) => {\n addFiles(e.target.files);\n e.target.value = '';\n };\n\n const removeFile = (idx) => setFiles(prev => prev.filter((_, i) => i !== idx));\n\n const handleUpload = async () => {\n if (!files.length) return;\n setLoading(true);\n setError(null);\n setResult(null);\n\n const formData = new FormData();\n files.forEach(f => formData.append('files', f));\n\n try {\n const res = await fetch('/api/upload/csv', { method: 'POST', body: formData });\n const data = await res.json();\n if (!res.ok) throw new Error(data.error || 'Upload failed');\n setResult(data);\n setFiles([]);\n } catch (err) {\n setError(err.message);\n } finally {\n setLoading(false);\n }\n };\n\n return (\n <div className=\"max-w-2xl mx-auto\">\n <div className=\"mb-6\">\n <h2 className=\"text-lg font-semibold text-gray-900\">Upload DSK Bank CSV</h2>\n <p className=\"text-sm text-gray-500 mt-1\">\n Import transactions from DSK Bank CSV exports. Multiple files are merged automatically.\n Internal transfers are skipped. Tags are auto-assigned based on payee and description.\n </p>\n </div>\n\n {/* Drop zone */}\n <div\n onDrop={handleDrop}\n onDragOver={(e) => { e.preventDefault(); setDragging(true); }}\n onDragLeave={() => setDragging(false)}\n onClick={() => fileInputRef.current.click()}\n className={`border-2 border-dashed rounded-xl p-12 text-center cursor-pointer transition-colors ${\n dragging\n ? 'border-emerald-400 bg-emerald-50'\n : 'border-gray-300 hover:border-emerald-400 hover:bg-emerald-50'\n }`}\n >\n <Upload className={`w-10 h-10 mx-auto mb-3 ${dragging ? 'text-emerald-500' : 'text-gray-400'}`} />\n <p className=\"text-sm font-medium text-gray-700\">Drop DSK Bank CSV files here</p>\n <p className=\"text-xs text-gray-500 mt-1\">or click to select files — multiple files supported</p>\n <input\n ref={fileInputRef}\n type=\"file\"\n multiple\n accept=\".csv\"\n className=\"hidden\"\n onChange={handleFileSelect}\n />\n </div>\n\n {/* File list */}\n {files.length > 0 && (\n <div className=\"mt-4 space-y-2\">\n {files.map((f, i) => (\n <div key={i} className=\"flex items-center gap-2 bg-white rounded-lg border border-gray-200 px-3 py-2\">\n <FileText className=\"w-4 h-4 text-gray-400 flex-shrink-0\" />\n <span className=\"text-sm text-gray-700 flex-1 truncate\">{f.name}</span>\n <span className=\"text-xs text-gray-400 flex-shrink-0\">{(f.size / 1024).toFixed(1)} KB</span>\n <button\n onClick={(e) => { e.stopPropagation(); removeFile(i); }}\n className=\"text-gray-400 hover:text-gray-600 flex-shrink-0\"\n >\n <X className=\"w-4 h-4\" />\n </button>\n </div>\n ))}\n\n <button\n onClick={handleUpload}\n disabled={loading}\n className=\"w-full py-2.5 text-sm font-medium text-white bg-emerald-600 rounded-lg hover:bg-emerald-700 disabled:opacity-50 disabled:cursor-not-allowed transition-colors mt-2\"\n >\n {loading\n ? 'Importing…'\n : `Import ${files.length} file${files.length !== 1 ? 's' : ''}`\n }\n </button>\n </div>\n )}\n\n {/* Success result */}\n {result && (\n <div className=\"mt-6 bg-green-50 border border-green-200 rounded-xl p-5\">\n <div className=\"flex items-center gap-2 mb-3\">\n <CheckCircle className=\"w-5 h-5 text-green-600 flex-shrink-0\" />\n <span className=\"font-medium text-green-800\">Import complete</span>\n </div>\n <div className=\"grid grid-cols-3 gap-3 text-center mb-3\">\n <div className=\"bg-white rounded-lg border border-green-100 py-2 px-3\">\n <p className=\"text-2xl font-bold text-green-700\">{result.imported}</p>\n <p className=\"text-xs text-gray-500\">Imported</p>\n </div>\n <div className=\"bg-white rounded-lg border border-green-100 py-2 px-3\">\n <p className=\"text-2xl font-bold text-gray-500\">{result.skipped}</p>\n <p className=\"text-xs text-gray-500\">Skipped</p>\n </div>\n <div className=\"bg-white rounded-lg border border-green-100 py-2 px-3\">\n <p className=\"text-2xl font-bold text-amber-600\">{result.errors?.length ?? 0}</p>\n <p className=\"text-xs text-gray-500\">Warnings</p>\n </div>\n </div>\n <p className=\"text-xs text-gray-500 mb-3\">\n Skipped rows are internal bank transfers (ТРАНСФЕР СОБСТВЕНИ СМЕТКИ).\n </p>\n {result.errors?.length > 0 && (\n <details className=\"mb-3\">\n <summary className=\"text-xs text-amber-700 cursor-pointer hover:text-amber-800\">\n Show {result.errors.length} warning{result.errors.length !== 1 ? 's' : ''}\n </summary>\n <ul className=\"mt-2 text-xs text-amber-600 space-y-0.5 max-h-32 overflow-y-auto\">\n {result.errors.map((e, i) => <li key={i} className=\"font-mono\">{e}</li>)}\n </ul>\n </details>\n )}\n <button\n onClick={onUploadSuccess}\n className=\"flex items-center gap-1.5 text-sm font-medium text-green-700 hover:text-green-800\"\n >\n <ArrowLeft className=\"w-4 h-4\" />\n View imported transactions\n </button>\n </div>\n )}\n\n {/* Error */}\n {error && (\n <div className=\"mt-4 bg-red-50 border border-red-200 rounded-xl p-4 flex items-start gap-3\">\n <AlertCircle className=\"w-5 h-5 text-red-500 flex-shrink-0 mt-0.5\" />\n <div>\n <p className=\"text-sm font-medium text-red-800\">Upload failed</p>\n <p className=\"text-sm text-red-700 mt-0.5\">{error}</p>\n </div>\n </div>\n )}\n\n {/* Info box */}\n {!result && !error && (\n <div className=\"mt-6 bg-blue-50 border border-blue-100 rounded-xl p-4\">\n <p className=\"text-xs font-medium text-blue-800 mb-1\">Expected CSV format (DSK Bank export)</p>\n <p className=\"text-xs text-blue-700 font-mono\">\n Дата, Вид на трансакцията, Основание, Дебит BGN, Кредит BGN, Наредител/Получател, Номер сметка...\n </p>\n <p className=\"text-xs text-blue-600 mt-2\">\n Both UTF-8 and Windows-1251 encodings are supported. Tags are auto-applied based on payee and description keywords.\n </p>\n </div>\n )}\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentCard.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentCard.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"186 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState } from 'react';\nimport {\n Send, XCircle, CheckCircle, MinusCircle, Clock,\n CreditCard, Tag, Plus, X,\n} from 'lucide-react';\n\nconst STATUS_CONFIG = {\n UNPROCESSED: { label: 'Unprocessed', icon: Clock, color: 'bg-amber-100 text-amber-700 border-amber-200' },\n SENT: { label: 'Sent', icon: CheckCircle, color: 'bg-green-100 text-green-700 border-green-200' },\n SKIPPED: { label: 'Skipped', icon: MinusCircle, color: 'bg-gray-100 text-gray-500 border-gray-200' },\n};\n\nconst TAG_COLORS = [\n '#ef4444', '#f97316', '#eab308', '#22c55e', '#06b6d4',\n '#3b82f6', '#8b5cf6', '#ec4899', '#6b7280',\n];\n\nexport default function PaymentCard({ payment, onSend, onSkip, onAddTag, onRemoveTag, existingTags }) {\n const [showTagInput, setShowTagInput] = useState(false);\n const [newTagName, setNewTagName] = useState('');\n const [newTagColor, setNewTagColor] = useState('#3b82f6');\n\n const statusCfg = STATUS_CONFIG[payment.status] || STATUS_CONFIG.UNPROCESSED;\n const StatusIcon = statusCfg.icon;\n\n const handleAddTag = (e) => {\n e.preventDefault();\n if (newTagName.trim()) {\n onAddTag(payment.id, newTagName.trim(), newTagColor);\n setNewTagName('');\n setShowTagInput(false);\n }\n };\n\n const paymentTags = payment.tags || [];\n const availableTags = existingTags.filter(t => !paymentTags.some(pt => pt.id === t.id));\n\n const formattedDate = payment.date\n ? new Date(payment.date).toLocaleDateString('en-GB', {\n day: '2-digit', month: 'short', year: 'numeric', hour: '2-digit', minute: '2-digit',\n })\n : 'N/A';\n\n const currency = payment.currency || 'EUR';\n\n return (\n <div className=\"bg-white rounded-xl border border-gray-200 shadow-sm hover:shadow-md transition-shadow p-4\">\n <div className=\"flex items-start justify-between gap-3 mb-3\">\n <div className=\"flex-1 min-w-0\">\n <div className=\"flex items-center gap-2 mb-1\">\n <span className={`inline-flex items-center gap-1 px-2 py-0.5 text-xs font-medium rounded-full border ${statusCfg.color}`}>\n <StatusIcon className=\"w-3 h-3\" />\n {statusCfg.label}\n </span>\n {payment.source === 'UPLOAD' ? (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-emerald-50 text-emerald-700\">CSV</span>\n ) : (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-indigo-50 text-indigo-700\">SMS</span>\n )}\n </div>\n <p className=\"text-sm text-gray-600 break-words leading-relaxed\">{payment.rawMessage}</p>\n </div>\n </div>\n\n <div className=\"grid grid-cols-2 sm:grid-cols-4 gap-3 mb-3 text-sm\">\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Amount</span>\n <p className=\"font-semibold text-gray-900\">\n {payment.amount != null ? `${payment.amount.toFixed(2)} ${currency}` : 'N/A'}\n </p>\n </div>\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Date</span>\n <p className=\"text-gray-700\">{formattedDate}</p>\n </div>\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Card</span>\n <p className=\"text-gray-700 flex items-center gap-1\">\n <CreditCard className=\"w-3 h-3 text-gray-400\" />\n {payment.card || 'N/A'}\n </p>\n </div>\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Balance</span>\n <p className=\"text-gray-700\">\n {payment.balance != null ? `${payment.balance.toFixed(2)} ${currency}` : 'N/A'}\n </p>\n </div>\n </div>\n\n {/* Tags */}\n <div className=\"flex flex-wrap items-center gap-1.5 mb-3\">\n <Tag className=\"w-3 h-3 text-gray-400\" />\n {paymentTags.map(tag => (\n <span\n key={tag.id}\n className=\"inline-flex items-center gap-1 px-2 py-0.5 text-xs font-medium rounded-full text-white\"\n style={{ backgroundColor: tag.color }}\n >\n {tag.name}\n <button onClick={() => onRemoveTag(payment.id, tag.id)} className=\"hover:opacity-75\">\n <X className=\"w-3 h-3\" />\n </button>\n </span>\n ))}\n {!showTagInput ? (\n <button\n onClick={() => setShowTagInput(true)}\n className=\"inline-flex items-center gap-0.5 px-2 py-0.5 text-xs text-gray-500 border border-dashed border-gray-300 rounded-full hover:border-gray-400 hover:text-gray-600\"\n >\n <Plus className=\"w-3 h-3\" />\n Tag\n </button>\n ) : (\n <form onSubmit={handleAddTag} className=\"inline-flex items-center gap-1\">\n <input\n type=\"text\"\n value={newTagName}\n onChange={(e) => setNewTagName(e.target.value)}\n placeholder=\"Tag name\"\n autoFocus\n className=\"w-24 px-2 py-0.5 text-xs border border-gray-300 rounded-md focus:ring-1 focus:ring-indigo-500 outline-none\"\n />\n <div className=\"flex gap-0.5\">\n {TAG_COLORS.map(c => (\n <button\n key={c}\n type=\"button\"\n onClick={() => setNewTagColor(c)}\n className={`w-4 h-4 rounded-full border-2 ${newTagColor === c ? 'border-gray-800' : 'border-transparent'}`}\n style={{ backgroundColor: c }}\n />\n ))}\n </div>\n <button type=\"submit\" className=\"text-xs text-indigo-600 font-medium hover:text-indigo-700\">Add</button>\n <button type=\"button\" onClick={() => setShowTagInput(false)} className=\"text-xs text-gray-400 hover:text-gray-600\">\n <X className=\"w-3 h-3\" />\n </button>\n </form>\n )}\n {showTagInput && availableTags.length > 0 && (\n <div className=\"flex flex-wrap gap-1 ml-1\">\n {availableTags.slice(0, 5).map(tag => (\n <button\n key={tag.id}\n onClick={() => { onAddTag(payment.id, tag.name, tag.color); setShowTagInput(false); }}\n className=\"px-2 py-0.5 text-xs rounded-full border border-gray-200 text-gray-600 hover:bg-gray-100\"\n >\n {tag.name}\n </button>\n ))}\n </div>\n )}\n </div>\n\n {payment.status === 'UNPROCESSED' && (\n <div className=\"flex items-center gap-2 pt-3 border-t border-gray-100\">\n <button\n onClick={() => onSend(payment.id)}\n className=\"flex items-center gap-1.5 px-4 py-2 text-sm font-medium text-white bg-indigo-600 rounded-lg hover:bg-indigo-700 transition-colors\"\n >\n <Send className=\"w-4 h-4\" />\n Send\n </button>\n <button\n onClick={() => onSkip(payment.id)}\n className=\"flex items-center gap-1.5 px-4 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 transition-colors\"\n >\n <XCircle className=\"w-4 h-4\" />\n Do Not Send\n </button>\n </div>\n )}\n\n {payment.status === 'SENT' && payment.notifiedAt && (\n <div className=\"pt-3 border-t border-gray-100\">\n <p className=\"text-xs text-green-600\">\n Notified on {new Date(payment.notifiedAt).toLocaleString('en-GB')}\n {payment.notifyPhone && ` to ${payment.notifyPhone}`}\n </p>\n </div>\n )}\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentList.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentList.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"40 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React from 'react';\nimport { Inbox } from 'lucide-react';\nimport PaymentCard from './PaymentCard';\n\nexport default function PaymentList({ payments, loading, onSend, onSkip, onAddTag, onRemoveTag, existingTags }) {\n if (loading) {\n return (\n <div className=\"flex items-center justify-center py-20\">\n <div className=\"animate-spin rounded-full h-8 w-8 border-b-2 border-indigo-600\"></div>\n </div>\n );\n }\n\n if (!payments || payments.length === 0) {\n return (\n <div className=\"flex flex-col items-center justify-center py-20 text-gray-400\">\n <Inbox className=\"w-12 h-12 mb-3\" />\n <p className=\"text-lg font-medium\">No transactions found</p>\n <p className=\"text-sm\">Try adjusting your filters, ingest a payment SMS, or upload a CSV.</p>\n </div>\n );\n }\n\n return (\n <div className=\"space-y-4\">\n {payments.map(payment => (\n <PaymentCard\n key={payment.id}\n payment={payment}\n onSend={onSend}\n onSkip={onSkip}\n onAddTag={onAddTag}\n onRemoveTag={onRemoveTag}\n existingTags={existingTags}\n />\n ))}\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"}]...
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Explorer (⇧⌘E)
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2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
report(1).csv, Editor Group 1
report(2).csv, Editor Group 1
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
Design new payment-logge…, Editor Group 2
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Ln 1, Col 1
Info: Setting up SSH Host nas: Setting up SSH tunnel
Design new payment-logger and dsk-uploader hybrid app
Session history
New session
Message actions
payments.js
payments.js
ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.
Thinking
Thinking
I'll explore all three reference projects in parallel to understand their structure before planning.
Agent:
Explore payment-logger app structure and functionality
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How data flows (ingest, storage, retrieval)
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.
Agent:
Explore dsk-uploader app structure and functionality
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How file uploads work - what files, what format, how parsed
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.
Agent:
Explore auth folder and authentik integration
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. What auth system is being used (Authentik)
2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?
3. Middleware - how is auth enforced on routes?
4. Any frontend auth flow - login redirect, token handling, protected routes
5. Environment variables related to auth
6. Docker/deployment setup for the auth service itself
7. Any example of how other apps integrate with this auth
Report with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.
Message actions
payments.js
payments.js
continue
Thinking
Thinking
Launching parallel exploration of all three reference projects.
Agent:
Explore payment-logger app structure
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How data is ingested (look at /ingest route especially)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore dsk-uploader app structure
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How file uploads work (what format, what processing happens)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore auth project structure
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. What authentication system is used (authentik integration details)
3. How OAuth/OIDC flow works
4. Any middleware or helper functions for protecting routes
5. Session management approach
6. How frontend handles auth state
7. Any example of how other apps integrate with this auth system
8. Docker setup and environment variables
Please read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.
Thinking
Thinking
Now I have a complete picture of all three. Let me design the plan.
Agent:
Design combined app architecture
IN
Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:
---
## App 1: payments-logger (Node.js)
- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI
- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS
- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage
- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)
- **Schema** (PostgreSQL via Prisma):
- `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at
- `tags` table: id, name, color — M2M with payments via `_PaymentToTag`
- `users` table: id, username, hashed_password (this will be REMOVED)
- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system
- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance
## App 2: dsk-uploader (Python/Flask)
- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database
- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5
- **Auth**: None (open)
- **CSV format** (DSK Bank Bulgarian format, columns):
- `Дата` (date, DD.MM.YYYY)
- `Вид на трансакцията` (transaction type, Bulgarian)
- `Основание` (reason/description — contains card number regex: `^\d{6}x{6}\d{4}$`)
- `Дебит BGN` (debit amount, may be empty)
- `Кредит BGN` (credit amount, may be empty)
- `Наредител/Получател` (orderer/recipient name)
- `Номер сметка на наредителя / получателя` (account number)
- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers
- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)
## App 3: auth (Authentik)
- **Mode**: Proxy mode via NPM (forward auth)
- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:
- `X-authentik-username`
- `X-authentik-email`
- `X-authentik-groups`
- **No code integration needed** in the app itself — just trust these headers from NPM
- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`
---
## What the New Combined App Must Do
1. **Single PostgreSQL database** for all transactions
2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST
3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema
4. **Unified UI** — show all payments in one table regardless of source
5. **Source indicator** in UI — badge showing "INGEST", "UPLOAD", or "BOTH" (if duplicate detection added)
6. **Source filter** in FilterBar — filter by All/Ingest/Upload
7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM
8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination
9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL
---
## Technical Constraints
- Keep Node.js backend (not Python) — extend payments-logger's stack
- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)
- File upload: use `multer` npm middleware
- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)
- Add `source` enum field (INGEST/UPLOAD) to payments schema
- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is
- Remove `users` table from schema
---
## Please Design
1. Complete folder structure for the new app (suggest name: "finance-hub" or similar — note this is a placeholder, user will confirm)
2. Prisma schema with new fields (`source`, `currency`)
3. All backend API routes
4. CSV parser design in Node.js (port of the Python logic)
5. Authentik auth middleware
6. Frontend component structure (React) — what's reused from payments-logger, what's new
7. Docker Compose setup
8. Environment variables needed
9. Step-by-step implementation order
10. Verification checklist
Be specific about file paths and code structure. This will be used to write actual implementation code.
Thinking
Thinking
Good plan. Let me ask the one thing I need before writing the final plan.
AskUserQuestion
OUT
User has answered your questions: "What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding."="finance-hub". You can now continue with the user's answers in mind.
Thinking
Thinking
Writing the final plan now.
Thinking
Thinking
Write
ets-create-a-new-generic-sun.md
ets-create-a-new-generic-sun.md
326 lines
# finance-hub — Implementation Plan
## Context
Two separate finance apps exist as references and will be retired:
- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.
- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.
The new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).
---
## Tech Stack
| Layer | Choice | Rationale |
|-------|--------|-----------|
| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |
| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |
| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |
| Database | PostgreSQL 16 | Same as payments-logger |
| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |
| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |
| Container | Docker Compose | Same pattern as both reference apps |
**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage.
**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references.
**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.
---
## Folder Structure
```
/volume2/docker/finance/finance-hub/
├── docker-compose.yml
├── .env
├── .env.example
├── .gitignore
├── backend/
│ ├── Dockerfile
│ ├── package.json
│ ├── prisma/
│ │ ├── schema.prisma
│ │ └── migrations/
│ │ ├── migration_lock.toml
│ │ └── 20260508_init/
│ │ └── migration.sql
│ └── src/
│ ├── index.js ← entry point (Authentik middleware wired here)
│ ├── auth.js ← Authentik header middleware (replaces JWT auth)
│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)
│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)
│ └── routes/
│ ├── payments.js ← existing routes + source/currency additions
│ └── upload.js ← NEW: POST /api/upload/csv
└── frontend/
├── Dockerfile
├── package.json
├── vite.config.js
├── tailwind.config.js
├── postcss.config.js
├── index.html
└── src/
├── main.jsx ← remove AuthProvider wrapper
├── index.css
├── App.jsx ← remove auth state, add Upload tab toggle
└── components/
├── FilterBar.jsx ← add source filter select
├── PaymentTable.jsx ← add Source badge column + currency display
├── PaymentCard.jsx ← minor source badge addition
├── PaymentList.jsx ← unchanged
└── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI
```
---
## Database Schema (Prisma)
File: `backend/prisma/schema.prisma`
```prisma
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
}
model Payment {
id Int @id @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
auth.js
auth.js
27 lines
const PUBLIC_PATHS = new Set([
'/api/health',
'/api/payments/ingest',
]);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) {
return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });
}
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '')
.split(',')
.map(g => g.trim())
.filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
Write
parser.js
parser.js
104 lines
/**
* Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)
*
* Supported formats:
*
* POS / INTERNET / ECOM / P2P payment:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM withdrawal:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM utility payment (amount may include fee as AMOUNT/FEE):
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.
*/
const LOCAL_TZ = process.env.TZ || 'Europe/Sofia';
/**
* Convert a local-timezone date/time to a UTC Date object.
* Uses Intl to resolve the actual UTC offset (DST-aware).
*/
function localToUtc(year, month, day, hour, minute) {
const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));
const formatter = new Intl.DateTimeFormat('en-US', {
timeZone: LOCAL_TZ,
year: 'numeric', month: '2-digit', day: '2-digit',
hour: '2-digit', minute: '2-digit', second: '2-digit',
hour12: false,
});
const parts = {};
formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });
const localAtNaive = new Date(Date.UTC(
parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),
parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),
));
const offsetMs = localAtNaive.getTime() - naive.getTime();
return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);
}
function parsePaymentSms(message) {
const result = {
rawMessage: message,
date: null,
type: null,
card: null,
recipient: null,
amount: null,
balance: null,
};
// Date and time: "Na DD/MM/YYYY v HH:MM"
const dateMatch = message.match(/Na (\d{2})\/(\d{2})\/(\d{4}) v (\d{2}):(\d{2})/i);
if (dateMatch) {
const [, day, month, year, hour, minute] = dateMatch;
result.date = localToUtc(
parseInt(year), parseInt(month), parseInt(day),
parseInt(hour), parseInt(minute),
);
}
// Card mask: "s karta 400915***4447" or "s karta 483890***7162"
const cardMatch = message.match(/s karta\s+([\d*]+)/i);
if (cardMatch) {
result.card = cardMatch[1];
}
// Transaction type: supports both prepositions
// "na POS" / "na ATM" / "na INTERNET" etc. (payment)
// "ot ATM" (withdrawal)
const typeMatch = message.match(/(?:na|ot)\s+(POS|ATM|INTERNET|ECOM|P2P)\b/i);
if (typeMatch) {
result.type = typeMatch[1].toUpperCase();
}
// Recipient address: "s adres: MERCHANT" or "s adres:MERCHANT" (no space variant)
const recipientMatch = message.match(/s adres:\s*([^.]+)\./i);
if (recipientMatch) {
result.recipient = recipientMatch[1].trim();
}
// Amount: handles both verbs and the AMOUNT/FEE suffix format
// "sa plateni 7.78 EUR"
// "sa iztegleni 400.00 EUR"
// "sa plateni 0.50 EUR/0.50 EUR" → captures 0.50 (the charged amount, ignoring fee)
const amountMatch = message.match(/sa (?:plateni|iztegleni)\s+([\d.,]+)\s+[A-Z]{3}/i);
if (amountMatch) {
result.amount = parseFloat(amountMatch[1].replace(',', '.'));
}
// Balance: "Nalichni: 2583.07 EUR."
const balanceMatch = message.match(/Nalichni:\s*([\d.,]+)\s+[A-Z]{3}/i);
if (balanceMatch) {
result.balance = parseFloat(balanceMatch[1].replace(',', '.'));
}
return result;
}
module.exports = { parsePaymentSms };
Write
csvParser.js
csvParser.js
175 lines
/**
* DSK Bank CSV parser — Node.js port of dskuploader.py
*
* DSK Bank exports use Windows-1251 (cp1251) encoding.
* Each row maps to a Payment record with source=UPLOAD, currency=BGN.
*/
const { parse } = require('csv-parse');
const iconv = require('iconv-lite');
const SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';
const CARD_REGEX = /^\d{6}x{6}\d{4}$/;
const POS_REGEX = /^\s*ПЛАЩАНЕ\s+НА\s+ПОС\s+\d{2}\.\d{2}\.\d{4}\s+\d{2}:\d{2}/;
const COL = {
DATE: 'Дата',
TYPE: 'Вид на трансакцията',
REASON: 'Основание',
DEBIT: 'Дебит BGN',
CREDIT: 'Кредит BGN',
PAYEE: 'Наредител/Получател',
ACCT: 'Номер сметка на наредителя / получателя',
};
const TAG_RULES = [
['reason', 'ЗАПЛАТА', 'Salary'],
['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],
['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],
['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],
['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],
['payee', 'VIVACOM', 'Subscriptions'],
['payee', 'Google', 'Subscriptions'],
['payee', 'SkyShowtime', 'Subscriptions'],
['payee', 'NETFLIX', 'Subscriptions'],
['payee', 'LUKOIL', 'Bills'],
['payee', 'CityGate', 'Bills'],
['payee', 'CBA', 'Groceries'],
['payee', 'FANTASTICO', 'Groceries'],
['payee', 'LIDL', 'Groceries'],
];
function parseNum(val) {
if (val == null || val === '') return null;
if (typeof val === 'number') return isNaN(val) ? null : val;
const s = String(val).trim().replace(/\xa0/g, '').replace(/ /g, '').replace(',', '.');
const n = parseFloat(s);
return isNaN(n) ? null : n;
}
function parseDate(val) {
if (!val) return null;
const s = String(val).trim();
const m = s.match(/^(\d{2})\.(\d{2})\.(\d{4})$/);
if (m) {
return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));
}
return null;
}
function processReasonAndCard(reason) {
if (!reason || typeof reason !== 'string') return { reason: '', card: null };
const parts = reason.trim().split(' ');
let card = null;
let cleanReason = reason.trim();
if (parts[0] && CARD_REGEX.test(parts[0])) {
card = parts[0];
cleanReason = parts.slice(1).join(' ').trim();
}
if (POS_REGEX.test(cleanReason)) {
const posParts = cleanReason.split('<br/>');
try {
const dateTime = posParts[0].split('ПОС ')[1];
cleanReason = `POS PAYMENT ${dateTime}`;
} catch (_) { /* keep original */ }
}
return { reason: cleanReason.replace(/\s+/g, ' ').trim(), card };
}
function generateTags(fields) {
const tags = new Set();
for (const [field, keyword, tagName] of TAG_RULES) {
if ((fields[field] || '').includes(keyword)) {
tags.add(tagName);
}
}
return Array.from(tags);
}
function processRow(row) {
const transactionType = (row[COL.TYPE] || '').trim();
if (transactionType === SKIP_TYPE) return null;
const { reason, card } = processReasonAndCard(row[COL.REASON]);
const payee = (row[COL.PAYEE] || '...
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Explorer (⇧⌘E)
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EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
report(1).csv, Editor Group 1
report(2).csv, Editor Group 1
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
Design new payment-logge…, Editor Group 2
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Info: Setting up SSH Host nas: Setting up SSH tunnel
Design new payment-logger and dsk-uploader hybrid app
Session history
New session
Message actions
payments.js
payments.js
ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.
Thinking
Thinking
I'll explore all three reference projects in parallel to understand their structure before planning.
Agent:
Explore payment-logger app structure and functionality
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How data flows (ingest, storage, retrieval)
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.
Agent:
Explore dsk-uploader app structure and functionality
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How file uploads work - what files, what format, how parsed
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.
Agent:
Explore auth folder and authentik integration
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. What auth system is being used (Authentik)
2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?
3. Middleware - how is auth enforced on routes?
4. Any frontend auth flow - login redirect, token handling, protected routes
5. Environment variables related to auth
6. Docker/deployment setup for the auth service itself
7. Any example of how other apps integrate with this auth
Report with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.
Message actions
payments.js
payments.js
continue
Thinking
Thinking
Launching parallel exploration of all three reference projects.
Agent:
Explore payment-logger app structure
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How data is ingested (look at /ingest route especially)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore dsk-uploader app structure
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How file uploads work (what format, what processing happens)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore auth project structure
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. What authentication system is used (authentik integration details)
3. How OAuth/OIDC flow works
4. Any middleware or helper functions for protecting routes
5. Session management approach
6. How frontend handles auth state
7. Any example of how other apps integrate with this auth system
8. Docker setup and environment variables
Please read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.
Thinking
Thinking
Now I have a complete picture of all three. Let me design the plan.
Agent:
Design combined app architecture
IN
Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:
---
## App 1: payments-logger (Node.js)
- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI
- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS
- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage
- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)
- **Schema** (PostgreSQL via Prisma):
- `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at
- `tags` table: id, name, color — M2M with payments via `_PaymentToTag`
- `users` table: id, username, hashed_password (this will be REMOVED)
- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system
- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance
## App 2: dsk-uploader (Python/Flask)
- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database
- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5
- **Auth**: None (open)
- **CSV format** (DSK Bank Bulgarian format, columns):
- `Дата` (date, DD.MM.YYYY)
- `Вид на трансакцията` (transaction type, Bulgarian)
- `Основание` (reason/description — contains card number regex: `^\d{6}x{6}\d{4}$`)
- `Дебит BGN` (debit amount, may be empty)
- `Кредит BGN` (credit amount, may be empty)
- `Наредител/Получател` (orderer/recipient name)
- `Номер сметка на наредителя / получателя` (account number)
- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers
- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)
## App 3: auth (Authentik)
- **Mode**: Proxy mode via NPM (forward auth)
- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:
- `X-authentik-username`
- `X-authentik-email`
- `X-authentik-groups`
- **No code integration needed** in the app itself — just trust these headers from NPM
- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`
---
## What the New Combined App Must Do
1. **Single PostgreSQL database** for all transactions
2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST
3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema
4. **Unified UI** — show all payments in one table regardless of source
5. **Source indicator** in UI — badge showing "INGEST", "UPLOAD", or "BOTH" (if duplicate detection added)
6. **Source filter** in FilterBar — filter by All/Ingest/Upload
7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM
8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination
9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL
---
## Technical Constraints
- Keep Node.js backend (not Python) — extend payments-logger's stack
- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)
- File upload: use `multer` npm middleware
- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)
- Add `source` enum field (INGEST/UPLOAD) to payments schema
- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is
- Remove `users` table from schema
---
## Please Design
1. Complete folder structure for the new app (suggest name: "finance-hub" or similar — note this is a placeholder, user will confirm)
2. Prisma schema with new fields (`source`, `currency`)
3. All backend API routes
4. CSV parser design in Node.js (port of the Python logic)
5. Authentik auth middleware
6. Frontend component structure (React) — what's reused from payments-logger, what's new
7. Docker Compose setup
8. Environment variables needed
9. Step-by-step implementation order
10. Verification checklist
Be specific about file paths and code structure. This will be used to write actual implementation code.
Thinking
Thinking
Good plan. Let me ask the one thing I need before writing the final plan.
AskUserQuestion
OUT
User has answered your questions: "What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding."="finance-hub". You can now continue with the user's answers in mind.
Thinking
Thinking
Writing the final plan now.
Thinking
Thinking
Write
ets-create-a-new-generic-sun.md
ets-create-a-new-generic-sun.md
326 lines
# finance-hub — Implementation Plan
## Context
Two separate finance apps exist as references and will be retired:
- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.
- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.
The new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).
---
## Tech Stack
| Layer | Choice | Rationale |
|-------|--------|-----------|
| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |
| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |
| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |
| Database | PostgreSQL 16 | Same as payments-logger |
| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |
| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |
| Container | Docker Compose | Same pattern as both reference apps |
**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage.
**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references.
**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.
---
## Folder Structure
```
/volume2/docker/finance/finance-hub/
├── docker-compose.yml
├── .env
├── .env.example
├── .gitignore
├── backend/
│ ├── Dockerfile
│ ├── package.json
│ ├── prisma/
│ │ ├── schema.prisma
│ │ └── migrations/
│ │ ├── migration_lock.toml
│ │ └── 20260508_init/
│ │ └── migration.sql
│ └── src/
│ ├── index.js ← entry point (Authentik middleware wired here)
│ ├── auth.js ← Authentik header middleware (replaces JWT auth)
│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)
│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)
│ └── routes/
│ ├── payments.js ← existing routes + source/currency additions
│ └── upload.js ← NEW: POST /api/upload/csv
└── frontend/
├── Dockerfile
├── package.json
├── vite.config.js
├── tailwind.config.js
├── postcss.config.js
├── index.html
└── src/
├── main.jsx ← remove AuthProvider wrapper
├── index.css
├── App.jsx ← remove auth state, add Upload tab toggle
└── components/
├── FilterBar.jsx ← add source filter select
├── PaymentTable.jsx ← add Source badge column + currency display
├── PaymentCard.jsx ← minor source badge addition
├── PaymentList.jsx ← unchanged
└── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI
```
---
## Database Schema (Prisma)
File: `backend/prisma/schema.prisma`
```prisma
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
}
model Payment {
id Int @id @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)...
|
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history","depth":19,"bounds":{"left":0.97839093,"top":0.08060654,"width":0.00930851,"height":0.022346368},"on_screen":true,"help_text":"Session history","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"New session","depth":19,"bounds":{"left":0.9890292,"top":0.08060654,"width":0.00930851,"height":0.022346368},"on_screen":true,"help_text":"New session","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"payments.js","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"I'll explore all three reference projects in parallel to understand their structure before planning.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How data flows (ingest, storage, retrieval)\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How file uploads work - what files, what format, how parsed\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth folder and authentik integration","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. What auth system is being used (Authentik)\n2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?\n3. Middleware - how is auth enforced on routes?\n4. Any frontend auth flow - login redirect, token handling, protected routes\n5. Environment variables related to auth\n6. Docker/deployment setup for the auth service itself\n7. Any example of how other apps integrate with this auth\n\nReport with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"payments.js","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"continue","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Launching parallel exploration of all three reference projects.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How data is ingested (look at /ingest route especially)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How file uploads work (what format, what processing happens)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth project structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. What authentication system is used (authentik integration details)\n3. How OAuth/OIDC flow works\n4. Any middleware or helper functions for protecting routes\n5. Session management approach\n6. How frontend handles auth state\n7. Any example of how other apps integrate with this auth system\n8. Docker setup and environment variables\n\nPlease read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now I have a complete picture of all three. Let me design the plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design combined app architecture","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:\n\n---\n\n## App 1: payments-logger (Node.js)\n- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI\n- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS\n- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage\n- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)\n- **Schema** (PostgreSQL via Prisma):\n - `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at\n - `tags` table: id, name, color — M2M with payments via `_PaymentToTag`\n - `users` table: id, username, hashed_password (this will be REMOVED)\n- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system\n- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance\n\n## App 2: dsk-uploader (Python/Flask)\n- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database\n- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5\n- **Auth**: None (open)\n- **CSV format** (DSK Bank Bulgarian format, columns):\n - `Дата` (date, DD.MM.YYYY)\n - `Вид на трансакцията` (transaction type, Bulgarian)\n - `Основание` (reason/description — contains card number regex: `^\\d{6}x{6}\\d{4}$`)\n - `Дебит BGN` (debit amount, may be empty)\n - `Кредит BGN` (credit amount, may be empty)\n - `Наредител/Получател` (orderer/recipient name)\n - `Номер сметка на наредителя / получателя` (account number)\n- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers\n- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)\n\n## App 3: auth (Authentik)\n- **Mode**: Proxy mode via NPM (forward auth)\n- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:\n - `X-authentik-username` \n - `X-authentik-email`\n - `X-authentik-groups`\n- **No code integration needed** in the app itself — just trust these headers from NPM\n- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`\n\n---\n\n## What the New Combined App Must Do\n\n1. **Single PostgreSQL database** for all transactions\n2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST\n3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema\n4. **Unified UI** — show all payments in one table regardless of source\n5. **Source indicator** in UI — badge showing \"INGEST\", \"UPLOAD\", or \"BOTH\" (if duplicate detection added)\n6. **Source filter** in FilterBar — filter by All/Ingest/Upload\n7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM\n8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination\n9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL\n\n---\n\n## Technical Constraints\n\n- Keep Node.js backend (not Python) — extend payments-logger's stack\n- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)\n- File upload: use `multer` npm middleware\n- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)\n- Add `source` enum field (INGEST/UPLOAD) to payments schema\n- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is\n- Remove `users` table from schema\n\n---\n\n## Please Design\n\n1. Complete folder structure for the new app (suggest name: \"finance-hub\" or similar — note this is a placeholder, user will confirm)\n2. Prisma schema with new fields (`source`, `currency`)\n3. All backend API routes\n4. CSV parser design in Node.js (port of the Python logic)\n5. Authentik auth middleware\n6. Frontend component structure (React) — what's reused from payments-logger, what's new\n7. Docker Compose setup\n8. Environment variables needed\n9. Step-by-step implementation order\n10. Verification checklist\n\nBe specific about file paths and code structure. This will be used to write actual implementation code.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good plan. Let me ask the one thing I need before writing the final plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"AskUserQuestion","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"OUT","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"User has answered your questions: \"What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding.\"=\"finance-hub\". You can now continue with the user's answers in mind.","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Writing the final plan now.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"326 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# finance-hub — Implementation Plan\n\n## Context\n\nTwo separate finance apps exist as references and will be retired:\n- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.\n- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.\n\nThe new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).\n\n---\n\n## Tech Stack\n\n| Layer | Choice | Rationale |\n|-------|--------|-----------|\n| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |\n| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |\n| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |\n| Database | PostgreSQL 16 | Same as payments-logger |\n| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |\n| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |\n| Container | Docker Compose | Same pattern as both reference apps |\n\n**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage. \n**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references. \n**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.\n\n---\n\n## Folder Structure\n\n```\n/volume2/docker/finance/finance-hub/\n├── docker-compose.yml\n├── .env\n├── .env.example\n├── .gitignore\n├── backend/\n│ ├── Dockerfile\n│ ├── package.json\n│ ├── prisma/\n│ │ ├── schema.prisma\n│ │ └── migrations/\n│ │ ├── migration_lock.toml\n│ │ └── 20260508_init/\n│ │ └── migration.sql\n│ └── src/\n│ ├── index.js ← entry point (Authentik middleware wired here)\n│ ├── auth.js ← Authentik header middleware (replaces JWT auth)\n│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)\n│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)\n│ └── routes/\n│ ├── payments.js ← existing routes + source/currency additions\n│ └── upload.js ← NEW: POST /api/upload/csv\n└── frontend/\n ├── Dockerfile\n ├── package.json\n ├── vite.config.js\n ├── tailwind.config.js\n ├── postcss.config.js\n ├── index.html\n └── src/\n ├── main.jsx ← remove AuthProvider wrapper\n ├── index.css\n ├── App.jsx ← remove auth state, add Upload tab toggle\n └── components/\n ├── FilterBar.jsx ← add source filter select\n ├── PaymentTable.jsx ← add Source badge column + currency display\n ├── PaymentCard.jsx ← minor source badge addition\n ├── PaymentList.jsx ← unchanged\n └── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI\n```\n\n---\n\n## Database Schema (Prisma)\n\nFile: `backend/prisma/schema.prisma`\n\n```prisma\ngenerator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status { UNPROCESSED SENT SKIPPED }\nenum Source { INGEST UPLOAD }\n```\n\n**Key decisions:**\n- No `User` model — Authentik owns identity.\n- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.\n- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.\n- `balance` is always null for CSV rows (DSK export does not include running balance).\n- Fresh consolidated migration — no data migration from reference apps required.\n\n---\n\n## API Routes\n\n| Method | Path | Auth | Description |\n|--------|------|------|-------------|\n| GET | /api/health | public | Health check |\n| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |\n| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |\n| GET | /api/payments/meta/tags | required | All tags |\n| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |\n| GET | /api/payments/:id | required | Single payment |\n| PATCH | /api/payments/:id | required | Update status |\n| DELETE | /api/payments/:id | required | Delete |\n| POST | /api/payments/:id/send | required | Send notification |\n| POST | /api/payments/:id/skip | required | Skip |\n| POST | /api/payments/:id/tags | required | Add/upsert tag |\n| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |\n| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |\n\n---\n\n## Key Implementation Details\n\n### auth.js (replaces entire old auth module)\n```js\nconst PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n const username = req.headers['x-authentik-username'];\n if (!username) return res.status(401).json({ error: 'Unauthorized' });\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),\n };\n next();\n}\nmodule.exports = { authentikMiddleware };\n```\n\n### csvParser.js (port of dskuploader.py)\n- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8\n- `csv-parse` parses the decoded text with `columns: true`\n- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`\n- Card extraction: regex `/^\\d{6}x{6}\\d{4}$/` on first token of `Основание`\n- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`\n- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`\n- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`\n\n### payments.js changes from payments-logger\n1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call\n2. Add `source` to the `GET /` where clause filter\n3. Add `sources` to `meta/filters` response\n4. Currency-aware amount formatting in notification message\n5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)\n\n### upload.js (new)\n- `multer` memory storage, max 10 files × 10 MB\n- Calls `parseDskCsv(buffer)` per file\n- Upserts tags via `prisma.tag.upsert` then connects\n- Returns `{ imported, skipped, errors, payments[] }`\n\n### Frontend changes\n- **Delete**: `auth.js`, `AuthProvider.jsx`\n- **main.jsx**: Remove `<AuthProvider>` wrapper\n- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add \"Payments\" / \"Upload CSV\" tab toggle\n- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols\n- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell\n- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`\n\n---\n\n## Docker Compose\n\n```yaml\nservices:\n db:\n image: postgres:16-alpine\n environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: ${DB_PASSWORD}, POSTGRES_DB: finance_hub }\n volumes: [pgdata:/var/lib/postgresql/data]\n healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }\n\n backend:\n build: ./backend\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports: [\"${BACKEND_PORT:-3001}:3001\"]\n depends_on: { db: { condition: service_healthy } }\n\n frontend:\n build: ./frontend\n ports: [\"${FRONTEND_PORT:-5175}:5173\"]\n depends_on: [backend]\n\nvolumes: { pgdata: }\n```\n\n**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.\n\n---\n\n## Environment Variables (.env)\n\n```bash\nDB_PASSWORD=change_me\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\nTZ=Europe/Sofia\nBACKEND_PORT=3001\nFRONTEND_PORT=5175\n```\n\nRemoved vs payments-logger: `JWT_SECRET`, `JWT_EXPIRE_MINUTES`.\n\n---\n\n## Implementation Order\n\n1. Create folder structure and write `docker-compose.yml`, `.env.example`, `.gitignore`\n2. Write `backend/prisma/schema.prisma` and migration SQL\n3. Write `backend/package.json` (add `csv-parse`, `iconv-lite`, `multer`; remove `bcryptjs`, `jose`)\n4. Write `backend/Dockerfile`\n5. Write `backend/src/auth.js` (Authentik middleware)\n6. Copy `backend/src/parser.js` verbatim from payments-logger\n7. Write `backend/src/csvParser.js` (Python port)\n8. Write `backend/src/routes/upload.js`\n9. Write `backend/src/routes/payments.js` (from payments-logger + 5 changes listed above)\n10. Write `backend/src/index.js`\n11. Copy frontend base from payments-logger; delete `auth.js` + `AuthProvider.jsx`\n12. Update `main.jsx`, `App.jsx`, `FilterBar.jsx`, `PaymentTable.jsx`\n13. Write `frontend/src/components/UploadPanel.jsx`\n14. Update `frontend/vite.config.js`\n15. `docker compose build && docker compose up -d`\n16. Run verification checklist\n\n---\n\n## Verification\n\n**Schema**\n- `payments` table has `source`, `currency`, `debit_bgn`, `credit_bgn`, `transaction_type`, `payer_account`\n- No `users` table; `Source` enum exists\n\n**Auth**\n- `GET /api/payments` → 401 without `x-authentik-username` header\n- `POST /api/payments/ingest` → 201 without any header\n- `curl -H \"x-authentik-username: test\" localhost:3001/api/payments` → 200\n\n**SMS Ingest**\n- DSK POS SMS → `source=INGEST`, `currency=EUR`, correct amount/card/recipient\n- Apple Wallet structured body → `type=WALLET`, `source=INGEST`\n- Rate limiter → 429 after 200 req/min\n\n**CSV Upload**\n- Single DSK CSV → rows with `source=UPLOAD`, `currency=BGN`\n- Multiple CSVs in one request → all merged\n- `ТРАНСФЕР СОБСТВЕНИ СМЕТКИ` rows counted in `skipped`, not imported\n- Card regex match from `Основание` column\n- Auto-tags applied (ЗАПЛАТА→Salary, LIDL→Groceries)\n- cp1251 file imports correctly\n\n**UI**\n- Source badge visible in payment table (SMS indigo, CSV emerald)\n- Source dropdown in FilterBar filters correctly\n- Amount shows correct currency per row\n- Upload Panel: drag-and-drop works, result summary shows counts\n- Logout redirects to Authentik sign_out\n- No login form shown (Authentik handles it at NPM level)\n- Tags, send, skip, delete all still work\n\n## Reference Files\n\n- `/volume2/docker/finance/payments-logger/backend/src/routes/payments.js`\n- `/volume2/docker/finance/payments-logger/backend/src/parser.js`\n- `/volume2/docker/finance/payments-logger/backend/src/index.js`\n- `/volume2/docker/finance/payments-logger/backend/src/auth.js`\n- `/volume2/docker/finance/payments-logger/backend/prisma/schema.prisma`\n- `/volume2/docker/finance/payments-logger/frontend/src/App.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/PaymentTable.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/FilterBar.jsx`\n- `/volume2/docker/finance/dsk-uploader/dskuploader.py`\n- `/volume2/docker/finance/auth/docker-compose.yml`","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Claude’s Plan","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Stayed in plan mode","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good question. Here's the full breakdown:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Backend Tech Stack — Options","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Backend Tech Stack — Options","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Why:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"payments-logger is already Node.js/Express/Prisma. The new app is 80% payments-logger with CSV upload added on top. Keeping the same stack means:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"verbatim, zero rewrite","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy the entire","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"routes/payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with minimal edits","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Same Prisma schema workflow, same migrations, same Docker image","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The CSV parsing logic (the only Python-specific thing) ports cleanly to","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"csv-parse","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— it's just regex + string manipulation, nothing pandas-specific","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Trade-off:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Have to port the Python CSV parsing to JS. It's ~150 lines and mostly string manipulation — straightforward.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option B: Python + FastAPI + SQLAlchemy","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option B: Python + FastAPI + SQLAlchemy","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rewrite everything in Python. dsk-uploader is Python, so CSV parsing is already done.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep the dsk-uploader CSV logic as-is (no porting). Python has better data science libraries if you later add analytics.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Lose the entire payments-logger backend (routes, parser, Prisma schema) — full rewrite. FastAPI + SQLAlchemy is a different mental model than Express + Prisma. Frontend stays React anyway, so the stack split doesn't simplify anything.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"More work overall, gains almost nothing.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep Node.js as the main API, add a separate Python FastAPI service just for CSV parsing. They share the DB.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Zero porting — Python CSV code used as-is.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two backend services to maintain, deploy, and keep in sync. Inter-service HTTP calls. Two Dockerfiles. For ~150 lines of CSV logic, this is massively over-engineered.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Not worth it.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Extend dsk-uploader into a full payments app.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pandas for CSV, no porting.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Jinja2 templates instead of React (or add React separately). 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The React frontend is the stronger UI foundation.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Worst of all options — rebuild the harder parts (UI, SMS parser, notification) for no gain.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Summary","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Summary","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"CSV porting effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"App rewrite effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Result 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Everything else in the plan reuses payments-logger code directly. That's why Node.js is the clear winner here.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Want to adjust the stack, or shall I proceed with Option A?","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ok sounds good. Implement all you suggested","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Starting implementation. Let me first read all the reference files I'll need to copy from.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"payments.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"App.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"App.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"FilterBar.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"FilterBar.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentTable.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentTable.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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payments-logger.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.css","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.css","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"vite.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"vite.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"tailwind.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"tailwind.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"postcss.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"postcss.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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components.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentCard.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentCard.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentList.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentList.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"schema.prisma","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"schema.prisma","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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Let me set up the todo list and start building.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create finance-hub directory structure","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"mkdir -p /volume2/docker/finance/finance-hub/backend/src/routes \\\n /volume2/docker/finance/finance-hub/backend/prisma/migrations/20260508_init \\\n /volume2/docker/finance/finance-hub/frontend/src/components && echo \"done\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":24,"on_screen":false,"help_text":"Copy 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POSTGRES_USER: finance\n POSTGRES_PASSWORD: ${DB_PASSWORD}\n POSTGRES_DB: finance_hub\n volumes:\n - pgdata:/var/lib/postgresql/data\n healthcheck:\n test: [\"CMD-SHELL\", \"pg_isready -U finance -d finance_hub\"]\n interval: 5s\n timeout: 5s\n retries: 5\n\n backend:\n build: ./backend\n restart: unless-stopped\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports:\n - \"${BACKEND_PORT:-3001}:3001\"\n depends_on:\n db:\n condition: service_healthy\n\n frontend:\n build: ./frontend\n restart: unless-stopped\n ports:\n - \"${FRONTEND_PORT:-5175}:5173\"\n depends_on:\n - backend\n\nvolumes:\n pgdata:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".env.example","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".env.example","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"15 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Database\nDB_PASSWORD=change_me_strong_password\n\n# Notifier service (for SMS payment notifications)\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\n\n# Timezone (used by SMS parser for Bulgarian bank timestamps)\nTZ=Europe/Sofia\n\n# Ports (optional — defaults shown)\nBACKEND_PORT=3001\nFRONTEND_PORT=5175","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".gitignore","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".gitignore","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"5 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env\nnode_modules/\ndist/\n*.log","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"schema.prisma","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"schema.prisma","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"54 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"generator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status {\n UNPROCESSED\n SENT\n SKIPPED\n}\n\nenum Source {\n INGEST\n UPLOAD\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration.sql","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration.sql","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"55 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- CreateEnum\nCREATE TYPE \"Status\" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');\nCREATE TYPE \"Source\" AS ENUM ('INGEST', 'UPLOAD');\n\n-- CreateTable\nCREATE TABLE \"payments\" (\n \"id\" SERIAL PRIMARY KEY,\n \"raw_message\" TEXT NOT NULL,\n \"date\" TIMESTAMP(3),\n \"type\" TEXT,\n \"card\" TEXT,\n \"recipient\" TEXT,\n \"amount\" DOUBLE PRECISION,\n \"currency\" TEXT DEFAULT 'EUR',\n \"balance\" DOUBLE PRECISION,\n \"source\" \"Source\" NOT NULL DEFAULT 'INGEST',\n \"status\" \"Status\" NOT NULL DEFAULT 'UNPROCESSED',\n \"notified_at\" TIMESTAMP(3),\n \"notify_phone\" TEXT,\n \"debit_bgn\" DOUBLE PRECISION,\n \"credit_bgn\" DOUBLE PRECISION,\n \"transaction_type\" TEXT,\n \"payer_account\" TEXT,\n \"created_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,\n \"updated_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP\n);\n\n-- CreateTable\nCREATE TABLE \"tags\" (\n \"id\" SERIAL PRIMARY KEY,\n \"name\" TEXT NOT NULL,\n \"color\" TEXT NOT NULL DEFAULT '#6b7280'\n);\n\n-- CreateUniqueIndex\nCREATE UNIQUE INDEX \"tags_name_key\" ON \"tags\"(\"name\");\n\n-- CreateTable (M2M join)\nCREATE TABLE \"_PaymentToTag\" (\n \"A\" INTEGER NOT NULL,\n \"B\" INTEGER NOT NULL,\n CONSTRAINT \"_PaymentToTag_AB_pkey\" PRIMARY KEY (\"A\", \"B\")\n);\n\nCREATE INDEX \"_PaymentToTag_B_index\" ON \"_PaymentToTag\"(\"B\");\n\n-- AddForeignKey\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_A_fkey\"\n FOREIGN KEY (\"A\") REFERENCES \"payments\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;\n\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_B_fkey\"\n FOREIGN KEY (\"B\") REFERENCES \"tags\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration_lock.toml","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration_lock.toml","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"4 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Please do not edit this file manually\n# It should be added in your version-control system (e.g., Git)\nprovider = \"postgresql\"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"26 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"{\n \"name\": \"finance-hub-backend\",\n \"version\": \"1.0.0\",\n \"main\": \"src/index.js\",\n \"scripts\": {\n \"start\": \"node src/index.js\",\n \"dev\": \"nodemon src/index.js\",\n \"prisma:generate\": \"prisma generate\",\n \"prisma:migrate\": \"prisma migrate deploy\"\n },\n \"dependencies\": {\n \"@prisma/client\": \"^5.22.0\",\n \"cors\": \"^2.8.5\",\n \"csv-parse\": \"^5.5.6\",\n \"express\": \"^4.21.1\",\n \"express-rate-limit\": \"^7.4.0\",\n \"iconv-lite\": \"^0.6.3\",\n \"morgan\": \"^1.10.0\",\n \"multer\": \"^1.4.5-lts.1\"\n },\n \"devDependencies\": {\n \"nodemon\": \"^3.1.7\",\n \"prisma\": \"^5.22.0\"\n }\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"18 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"FROM node:20-alpine\n\nRUN apk add --no-cache openssl\n\nWORKDIR /app\n\nCOPY package.json package-lock.json* ./\nRUN npm install\n\nCOPY prisma ./prisma\nRUN npx prisma generate\n\nCOPY src ./src\n\nEXPOSE 3001\n\nCMD [\"sh\", \"-c\", \"npx prisma migrate deploy && node src/index.js\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"}]...
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Claude Code
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EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
report(1).csv, Editor Group 1
report(2).csv, Editor Group 1
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
Design new payment-logge…, Editor Group 2
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Ln 9, Col 45
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Design new payment-logger and dsk-uploader hybrid app
Session history
New session
Message actions
payments.js
payments.js
ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.
Thinking
Thinking
I'll explore all three reference projects in parallel to understand their structure before planning.
Agent:
Explore payment-logger app structure and functionality
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How data flows (ingest, storage, retrieval)
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.
Agent:
Explore dsk-uploader app structure and functionality
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How file uploads work - what files, what format, how parsed
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.
Agent:
Explore auth folder and authentik integration
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. What auth system is being used (Authentik)
2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?
3. Middleware - how is auth enforced on routes?
4. Any frontend auth flow - login redirect, token handling, protected routes
5. Environment variables related to auth
6. Docker/deployment setup for the auth service itself
7. Any example of how other apps integrate with this auth
Report with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.
Message actions
payments.js
payments.js
continue
Thinking
Thinking
Launching parallel exploration of all three reference projects.
Agent:
Explore payment-logger app structure
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How data is ingested (look at /ingest route especially)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore dsk-uploader app structure
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How file uploads work (what format, what processing happens)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore auth project structure
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. What authentication system is used (authentik integration details)
3. How OAuth/OIDC flow works
4. Any middleware or helper functions for protecting routes
5. Session management approach
6. How frontend handles auth state
7. Any example of how other apps integrate with this auth system
8. Docker setup and environment variables
Please read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.
Thinking
Thinking
Now I have a complete picture of all three. Let me design the plan.
Agent:
Design combined app architecture
IN
Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:
---
## App 1: payments-logger (Node.js)
- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI
- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS
- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage
- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)
- **Schema** (PostgreSQL via Prisma):
- `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at
- `tags` table: id, name, color — M2M with payments via `_PaymentToTag`
- `users` table: id, username, hashed_password (this will be REMOVED)
- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system
- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance
## App 2: dsk-uploader (Python/Flask)
- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database
- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5
- **Auth**: None (open)
- **CSV format** (DSK Bank Bulgarian format, columns):
- `Дата` (date, DD.MM.YYYY)
- `Вид на трансакцията` (transaction type, Bulgarian)
- `Основание` (reason/description — contains card number regex: `^\d{6}x{6}\d{4}$`)
- `Дебит BGN` (debit amount, may be empty)
- `Кредит BGN` (credit amount, may be empty)
- `Наредител/Получател` (orderer/recipient name)
- `Номер сметка на наредителя / получателя` (account number)
- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers
- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)
## App 3: auth (Authentik)
- **Mode**: Proxy mode via NPM (forward auth)
- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:
- `X-authentik-username`
- `X-authentik-email`
- `X-authentik-groups`
- **No code integration needed** in the app itself — just trust these headers from NPM
- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`
---
## What the New Combined App Must Do
1. **Single PostgreSQL database** for all transactions
2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST
3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema
4. **Unified UI** — show all payments in one table regardless of source
5. **Source indicator** in UI — badge showing "INGEST", "UPLOAD", or "BOTH" (if duplicate detection added)
6. **Source filter** in FilterBar — filter by All/Ingest/Upload
7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM
8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination
9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL
---
## Technical Constraints
- Keep Node.js backend (not Python) — extend payments-logger's stack
- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)
- File upload: use `multer` npm middleware
- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)
- Add `source` enum field (INGEST/UPLOAD) to payments schema
- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is
- Remove `users` table from schema
---
## Please Design
1. Complete folder structure for the new app (suggest name: "finance-hub" or similar — note this is a placeholder, user will confirm)
2. Prisma schema with new fields (`source`, `currency`)
3. All backend API routes
4. CSV parser design in Node.js (port of the Python logic)
5. Authentik auth middleware
6. Frontend component structure (React) — what's reused from payments-logger, what's new
7. Docker Compose setup
8. Environment variables needed
9. Step-by-step implementation order
10. Verification checklist
Be specific about file paths and code structure. This will be used to write actual implementation code.
Thinking
Thinking
Good plan. Let me ask the one thing I need before writing the final plan.
AskUserQuestion
OUT
User has answered your questions: "What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding."="finance-hub". You can now continue with the user's answers in mind.
Thinking
Thinking
Writing the final plan now.
Thinking
Thinking
Write
ets-create-a-new-generic-sun.md
ets-create-a-new-generic-sun.md
326 lines
# finance-hub — Implementation Plan
## Context
Two separate finance apps exist as references and will be retired:
- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.
- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.
The new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).
---
## Tech Stack
| Layer | Choice | Rationale |
|-------|--------|-----------|
| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |
| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |
| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |
| Database | PostgreSQL 16 | Same as payments-logger |
| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |
| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |
| Container | Docker Compose | Same pattern as both reference apps |
**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage.
**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references.
**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.
---
## Folder Structure
```
/volume2/docker/finance/finance-hub/
├── docker-compose.yml
├── .env
├── .env.example
├── .gitignore
├── backend/
│ ├── Dockerfile
│ ├── package.json
│ ├── prisma/
│ │ ├── schema.prisma
│ │ └── migrations/
│ │ ├── migration_lock.toml
│ │ └── 20260508_init/
│ │ └── migration.sql
│ └── src/
│ ├── index.js ← entry point (Authentik middleware wired here)
│ ├── auth.js ← Authentik header middleware (replaces JWT auth)
│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)
│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)
│ └── routes/
│ ├── payments.js ← existing routes + source/currency additions
│ └── upload.js ← NEW: POST /api/upload/csv
└── frontend/
├── Dockerfile
├── package.json
├── vite.config.js
├── tailwind.config.js
├── postcss.config.js
├── index.html
└── src/
├── main.jsx ← remove AuthProvider wrapper
├── index.css
├── App.jsx ← remove auth state, add Upload tab toggle
└── components/
├── FilterBar.jsx ← add source filter select
├── PaymentTable.jsx ← add Source badge column + currency display
├── PaymentCard.jsx ← minor source badge addition
├── PaymentList.jsx ← unchanged
└── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI
```
---
## Database Schema (Prisma)
File: `backend/prisma/schema.prisma`
```prisma
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
}
model Payment {
id Int @id @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)...
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
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Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
report(1).csv, Editor Group 1
report(2).csv, Editor Group 1
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
Design new payment-logge…, Editor Group 2
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remote SSH: nas
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Ln 9, Col 45
Info: Setting up SSH Host nas: Setting up SSH tunnel
Design new payment-logger and dsk-uploader hybrid app
Session history
New session
Message actions
payments.js
payments.js
ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.
Thinking
Thinking
I'll explore all three reference projects in parallel to understand their structure before planning.
Agent:
Explore payment-logger app structure and functionality
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How data flows (ingest, storage, retrieval)
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.
Agent:
Explore dsk-uploader app structure and functionality
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How file uploads work - what files, what format, how parsed
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.
Agent:
Explore auth folder and authentik integration
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. What auth system is being used (Authentik)
2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?
3. Middleware - how is auth enforced on routes?
4. Any frontend auth flow - login redirect, token handling, protected routes
5. Environment variables related to auth
6. Docker/deployment setup for the auth service itself
7. Any example of how other apps integrate with this auth
Report with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.
Message actions
payments.js
payments.js
continue
Thinking
Thinking
Launching parallel exploration of all three reference projects.
Agent:
Explore payment-logger app structure
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How data is ingested (look at /ingest route especially)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore dsk-uploader app structure
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How file uploads work (what format, what processing happens)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore auth project structure
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. What authentication system is used (authentik integration details)
3. How OAuth/OIDC flow works
4. Any middleware or helper functions for protecting routes
5. Session management approach
6. How frontend handles auth state
7. Any example of how other apps integrate with this auth system
8. Docker setup and environment variables
Please read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.
Thinking
Thinking
Now I have a complete picture of all three. Let me design the plan.
Agent:
Design combined app architecture
IN
Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:
---
## App 1: payments-logger (Node.js)
- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI
- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS
- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage
- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)
- **Schema** (PostgreSQL via Prisma):
- `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at
- `tags` table: id, name, color — M2M with payments via `_PaymentToTag`
- `users` table: id, username, hashed_password (this will be REMOVED)
- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system
- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance
## App 2: dsk-uploader (Python/Flask)
- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database
- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5
- **Auth**: None (open)
- **CSV format** (DSK Bank Bulgarian format, columns):
- `Дата` (date, DD.MM.YYYY)
- `Вид на трансакцията` (transaction type, Bulgarian)
- `Основание` (reason/description — contains card number regex: `^\d{6}x{6}\d{4}$`)
- `Дебит BGN` (debit amount, may be empty)
- `Кредит BGN` (credit amount, may be empty)
- `Наредител/Получател` (orderer/recipient name)
- `Номер сметка на наредителя / получателя` (account number)
- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers
- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)
## App 3: auth (Authentik)
- **Mode**: Proxy mode via NPM (forward auth)
- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:
- `X-authentik-username`
- `X-authentik-email`
- `X-authentik-groups`
- **No code integration needed** in the app itself — just trust these headers from NPM
- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`
---
## What the New Combined App Must Do
1. **Single PostgreSQL database** for all transactions
2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST
3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema
4. **Unified UI** — show all payments in one table regardless of source
5. **Source indicator** in UI — badge showing "INGEST", "UPLOAD", or "BOTH" (if duplicate detection added)
6. **Source filter** in FilterBar — filter by All/Ingest/Upload
7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM
8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination
9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL
---
## Technical Constraints
- Keep Node.js backend (not Python) — extend payments-logger's stack
- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)
- File upload: use `multer` npm middleware
- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)
- Add `source` enum field (INGEST/UPLOAD) to payments schema
- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is
- Remove `users` table from schema
---
## Please Design
1. Complete folder structure for the new app (suggest name: "finance-hub" or similar — note this is a placeholder, user will confirm)
2. Prisma schema with new fields (`source`, `currency`)
3. All backend API routes
4. CSV parser design in Node.js (port of the Python logic)
5. Authentik auth middleware
6. Frontend component structure (React) — what's reused from payments-logger, what's new
7. Docker Compose setup
8. Environment variables needed
9. Step-by-step implementation order
10. Verification checklist
Be specific about file paths and code structure. This will be used to write actual implementation code.
Thinking
Thinking
Good plan. Let me ask the one thing I need before writing the final plan.
AskUserQuestion
OUT
User has answered your questions: "What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding."="finance-hub". You can now continue with the user's answers in mind.
Thinking
Thinking
Writing the final plan now.
Thinking
Thinking
Write
ets-create-a-new-generic-sun.md
ets-create-a-new-generic-sun.md
326 lines
# finance-hub — Implementation Plan
## Context
Two separate finance apps exist as references and will be retired:
- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.
- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.
The new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).
---
## Tech Stack
| Layer | Choice | Rationale |
|-------|--------|-----------|
| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |
| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |
| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |
| Database | PostgreSQL 16 | Same as payments-logger |
| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |
| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |
| Container | Docker Compose | Same pattern as both reference apps |
**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage.
**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references.
**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.
---
## Folder Structure
```
/volume2/docker/finance/finance-hub/
├── docker-compose.yml
├── .env
├── .env.example
├── .gitignore
├── backend/
│ ├── Dockerfile
│ ├── package.json
│ ├── prisma/
│ │ ├── schema.prisma
│ │ └── migrations/
│ │ ├── migration_lock.toml
│ │ └── 20260508_init/
│ │ └── migration.sql
│ └── src/
│ ├── index.js ← entry point (Authentik middleware wired here)
│ ├── auth.js ← Authentik header middleware (replaces JWT auth)
│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)
│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)
│ └── routes/
│ ├── payments.js ← existing routes + source/currency additions
│ └── upload.js ← NEW: POST /api/upload/csv
└── frontend/
├── Dockerfile
├── package.json
├── vite.config.js
├── tailwind.config.js
├── postcss.config.js
├── index.html
└── src/
├── main.jsx ← remove AuthProvider wrapper
├── index.css
├── App.jsx ← remove auth state, add Upload tab toggle
└── components/
├── FilterBar.jsx ← add source filter select
├── PaymentTable.jsx ← add Source badge column + currency display
├── PaymentCard.jsx ← minor source badge addition
├── PaymentList.jsx ← unchanged
└── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI
```
---
## Database Schema (Prisma)
File: `backend/prisma/schema.prisma`
```prisma
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
}
model Payment {
id Int @id @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
auth.js
auth.js
27 lines
const PUBLIC_PATHS = new Set([
'/api/health',
'/api/payments/ingest',
]);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) {
return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });
}
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '')
.split(',')
.map(g => g.trim())
.filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
Write
parser.js
parser.js
104 lines
/**
* Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)
*
* Supported formats:
*
* POS / INTERNET / ECOM / P2P payment:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM withdrawal:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM utility payment (amount may include fee as AMOUNT/FEE):
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.
*/
const LOCAL_TZ = process.env.TZ || 'Europe/Sofia';
/**
* Convert a local-timezone date/time to a UTC Date object.
* Uses Intl to resolve the actual UTC offset (DST-aware).
*/
function localToUtc(year, month, day, hour, minute) {
const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));
const formatter = new Intl.DateTimeFormat('en-US', {
timeZone: LOCAL_TZ,
year: 'numeric', month: '2-digit', day: '2-digit',
hour: '2-digit', minute: '2-digit', second: '2-digit',
hour12: false,
});
const parts = {};
formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });
const localAtNaive = new Date(Date.UTC(
parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),
parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),
));
const offsetMs = localAtNaive.getTime() - naive.getTime();
return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);
}
function parsePaymentSms(message) {
const result = {
rawMessage: message,
date: null,
type: null,
card: null,
recipient: null,
amount: null,
balance: null,
};
// Date and time: "Na DD/MM/YYYY v HH:MM"
const dateMatch = message.match(/Na (\d{2})\/(\d{2})\/(\d{4}) v (\d{2}):(\d{2})/i);
if (dateMatch) {
const [, day, month, year, hour, minute] = dateMatch;
result.date = localToUtc(
parseInt(year), parseInt(month), parseInt(day),
parseInt(hour), parseInt(minute),
);
}
// Card mask: "s karta 400915***4447" or "s karta 483890***7162"
const cardMatch = message.match(/s karta\s+([\d*]+)/i);
if (cardMatch) {
result.card = cardMatch[1];
}
// Transaction type: supports both prepositions
// "na POS" / "na ATM" / "na INTERNET" etc. (payment)
// "ot ATM" (withdrawal)
const typeMatch = message.match(/(?:na|ot)\s+(POS|ATM|INTERNET|ECOM|P2P)\b/i);
if (typeMatch) {
result.type = typeMatch[1].toUpperCase();
}
// Recipient address: "s adres: MERCHANT" or "s adres:MERCHANT" (no space variant)
const recipientMatch = message.match(/s adres:\s*([^.]+)\./i);
if (recipientMatch) {
result.recipient = recipientMatch[1].trim();
}
// Amount: handles both verbs and the AMOUNT/FEE suffix format
// "sa plateni 7.78 EUR"
// "sa iztegleni 400.00 EUR"
// "sa plateni 0.50 EUR/0.50 EUR" → captures 0.50 (the charged amount, ignoring fee)
const amountMatch = message.match(/sa (?:plateni|iztegleni)\s+([\d.,]+)\s+[A-Z]{3}/i);
if (amountMatch) {
result.amount = parseFloat(amountMatch[1].replace(',', '.'));
}
// Balance: "Nalichni: 2583.07 EUR."
const balanceMatch = message.match(/Nalichni:\s*([\d.,]+)\s+[A-Z]{3}/i);
if (balanceMatch) {
result.balance = parseFloat(balanceMatch[1].replace(',', '.'));
}
return result;
}
module.exports = { parsePaymentSms };
Write
csvParser.js
csvParser.js
175 lines
/**
* DSK Bank CSV parser — Node.js port of dskuploader.py
*
* DSK Bank exports use Windows-1251 (cp1251) encoding.
* Each row maps to a Payment record with source=UPLOAD, currency=BGN.
*/
const { parse } = require('csv-parse');
const iconv = require('iconv-lite');
const SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';
const CARD_REGEX = /^\d{6}x{6}\d{4}$/;
const POS_REGEX = /^\s*ПЛАЩАНЕ\s+НА\s+ПОС\s+\d{2}\.\d{2}\.\d{4}\s+\d{2}:\d{2}/;
const COL = {
DATE: 'Дата',
TYPE: 'Вид на трансакцията',
REASON: 'Основание',
DEBIT: 'Дебит BGN',
CREDIT: 'Кредит BGN',
PAYEE: 'Наредител/Получател',
ACCT: 'Номер сметка на наредителя / получателя',
};
const TAG_RULES = [
['reason', 'ЗАПЛАТА', 'Salary'],
['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],
['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],
['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],
['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],
['payee', 'VIVACOM', 'Subscriptions'],
['payee', 'Google', 'Subscriptions'],
['payee', 'SkyShowtime', 'Subscriptions'],
['payee', 'NETFLIX', 'Subscriptions'],
['payee', 'LUKOIL', 'Bills'],
['payee', 'CityGate', 'Bills'],
['payee', 'CBA', 'Groceries'],
['payee', 'FANTASTICO', 'Groceries'],
['payee', 'LIDL', 'Groceries'],
];
function parseNum(val) {
if (val == null || val === '') return null;
if (typeof val === 'number') return isNaN(val) ? null : val;
const s = String(val).trim().replace(/\xa0/g, '').replace(/ /g, '').replace(',', '.');
const n = parseFloat(s);
return isNaN(n) ? null : n;
}
function parseDate(val) {
if (!val) return null;
const s = String(val).trim();
const m = s.match(/^(\d{2})\.(\d{2})\.(\d{4})$/);
if (m) {
return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));
}
return null;
}
function processReasonAndCard(reason) {
if (!reason || typeof reason !== 'string') return { reason: '', card: null };
const parts = reason.trim().split(' ');
let card = null;
let cleanReason = reason.trim();
if (parts[0] && CARD_REGEX.test(parts[0])) {
card = parts[0];
cleanReason = parts.slice(1).join(' ').trim();
}
if (POS_REGEX.test(cleanReason)) {
const posParts = cleanReason.split('<br/>');
try {
const dateTime = posParts[0].split('ПОС ')[1];
cleanReason = `POS PAYMENT ${dateTime}`;
} catch (_) { /* keep original */ }
}
return { reason: cleanReason.replace(/\s+/g, ' ').trim(), card };
}
function generateTags(fields) {
const tags = new Set();
for (const [field, keyword, tagName] of TAG_RULES) {
if ((fields[field] || '').includes(keyword)) {
tags.add(tagName);
}
}
return Array.from(tags);
}
function processRow(row) {
const transactionType = (row[COL.TYPE] || '').trim();
if (transactionType === SKIP_TYPE) return null;
const { reason, card } = processReasonAndCard(row[COL.REASON]);
const payee = (row[COL.PAYEE] || ...
|
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45","depth":16,"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Info: Setting up SSH Host nas: Setting up SSH tunnel","depth":12,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Design new payment-logger and dsk-uploader hybrid app","depth":19,"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Session history","depth":19,"on_screen":true,"help_text":"Session history","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"New session","depth":19,"on_screen":true,"help_text":"New session","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"payments.js","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"I'll explore all three reference projects in parallel to understand their structure before planning.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How data flows (ingest, storage, retrieval)\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How file uploads work - what files, what format, how parsed\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth folder and authentik integration","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. What auth system is being used (Authentik)\n2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?\n3. Middleware - how is auth enforced on routes?\n4. Any frontend auth flow - login redirect, token handling, protected routes\n5. Environment variables related to auth\n6. Docker/deployment setup for the auth service itself\n7. Any example of how other apps integrate with this auth\n\nReport with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"payments.js","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"continue","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Launching parallel exploration of all three reference projects.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How data is ingested (look at /ingest route especially)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How file uploads work (what format, what processing happens)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth project structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. What authentication system is used (authentik integration details)\n3. How OAuth/OIDC flow works\n4. Any middleware or helper functions for protecting routes\n5. Session management approach\n6. How frontend handles auth state\n7. Any example of how other apps integrate with this auth system\n8. Docker setup and environment variables\n\nPlease read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now I have a complete picture of all three. Let me design the plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design combined app architecture","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:\n\n---\n\n## App 1: payments-logger (Node.js)\n- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI\n- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS\n- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage\n- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)\n- **Schema** (PostgreSQL via Prisma):\n - `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at\n - `tags` table: id, name, color — M2M with payments via `_PaymentToTag`\n - `users` table: id, username, hashed_password (this will be REMOVED)\n- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system\n- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance\n\n## App 2: dsk-uploader (Python/Flask)\n- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database\n- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5\n- **Auth**: None (open)\n- **CSV format** (DSK Bank Bulgarian format, columns):\n - `Дата` (date, DD.MM.YYYY)\n - `Вид на трансакцията` (transaction type, Bulgarian)\n - `Основание` (reason/description — contains card number regex: `^\\d{6}x{6}\\d{4}$`)\n - `Дебит BGN` (debit amount, may be empty)\n - `Кредит BGN` (credit amount, may be empty)\n - `Наредител/Получател` (orderer/recipient name)\n - `Номер сметка на наредителя / получателя` (account number)\n- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers\n- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)\n\n## App 3: auth (Authentik)\n- **Mode**: Proxy mode via NPM (forward auth)\n- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:\n - `X-authentik-username` \n - `X-authentik-email`\n - `X-authentik-groups`\n- **No code integration needed** in the app itself — just trust these headers from NPM\n- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`\n\n---\n\n## What the New Combined App Must Do\n\n1. **Single PostgreSQL database** for all transactions\n2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST\n3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema\n4. **Unified UI** — show all payments in one table regardless of source\n5. **Source indicator** in UI — badge showing \"INGEST\", \"UPLOAD\", or \"BOTH\" (if duplicate detection added)\n6. **Source filter** in FilterBar — filter by All/Ingest/Upload\n7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM\n8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination\n9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL\n\n---\n\n## Technical Constraints\n\n- Keep Node.js backend (not Python) — extend payments-logger's stack\n- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)\n- File upload: use `multer` npm middleware\n- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)\n- Add `source` enum field (INGEST/UPLOAD) to payments schema\n- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is\n- Remove `users` table from schema\n\n---\n\n## Please Design\n\n1. Complete folder structure for the new app (suggest name: \"finance-hub\" or similar — note this is a placeholder, user will confirm)\n2. Prisma schema with new fields (`source`, `currency`)\n3. All backend API routes\n4. CSV parser design in Node.js (port of the Python logic)\n5. Authentik auth middleware\n6. Frontend component structure (React) — what's reused from payments-logger, what's new\n7. Docker Compose setup\n8. Environment variables needed\n9. Step-by-step implementation order\n10. Verification checklist\n\nBe specific about file paths and code structure. This will be used to write actual implementation code.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good plan. Let me ask the one thing I need before writing the final plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"AskUserQuestion","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"OUT","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"User has answered your questions: \"What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding.\"=\"finance-hub\". You can now continue with the user's answers in mind.","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Writing the final plan now.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"326 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# finance-hub — Implementation Plan\n\n## Context\n\nTwo separate finance apps exist as references and will be retired:\n- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.\n- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.\n\nThe new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).\n\n---\n\n## Tech Stack\n\n| Layer | Choice | Rationale |\n|-------|--------|-----------|\n| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |\n| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |\n| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |\n| Database | PostgreSQL 16 | Same as payments-logger |\n| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |\n| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |\n| Container | Docker Compose | Same pattern as both reference apps |\n\n**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage. \n**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references. \n**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.\n\n---\n\n## Folder Structure\n\n```\n/volume2/docker/finance/finance-hub/\n├── docker-compose.yml\n├── .env\n├── .env.example\n├── .gitignore\n├── backend/\n│ ├── Dockerfile\n│ ├── package.json\n│ ├── prisma/\n│ │ ├── schema.prisma\n│ │ └── migrations/\n│ │ ├── migration_lock.toml\n│ │ └── 20260508_init/\n│ │ └── migration.sql\n│ └── src/\n│ ├── index.js ← entry point (Authentik middleware wired here)\n│ ├── auth.js ← Authentik header middleware (replaces JWT auth)\n│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)\n│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)\n│ └── routes/\n│ ├── payments.js ← existing routes + source/currency additions\n│ └── upload.js ← NEW: POST /api/upload/csv\n└── frontend/\n ├── Dockerfile\n ├── package.json\n ├── vite.config.js\n ├── tailwind.config.js\n ├── postcss.config.js\n ├── index.html\n └── src/\n ├── main.jsx ← remove AuthProvider wrapper\n ├── index.css\n ├── App.jsx ← remove auth state, add Upload tab toggle\n └── components/\n ├── FilterBar.jsx ← add source filter select\n ├── PaymentTable.jsx ← add Source badge column + currency display\n ├── PaymentCard.jsx ← minor source badge addition\n ├── PaymentList.jsx ← unchanged\n └── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI\n```\n\n---\n\n## Database Schema (Prisma)\n\nFile: `backend/prisma/schema.prisma`\n\n```prisma\ngenerator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status { UNPROCESSED SENT SKIPPED }\nenum Source { INGEST UPLOAD }\n```\n\n**Key decisions:**\n- No `User` model — Authentik owns identity.\n- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.\n- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.\n- `balance` is always null for CSV rows (DSK export does not include running balance).\n- Fresh consolidated migration — no data migration from reference apps required.\n\n---\n\n## API Routes\n\n| Method | Path | Auth | Description |\n|--------|------|------|-------------|\n| GET | /api/health | public | Health check |\n| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |\n| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |\n| GET | /api/payments/meta/tags | required | All tags |\n| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |\n| GET | /api/payments/:id | required | Single payment |\n| PATCH | /api/payments/:id | required | Update status |\n| DELETE | /api/payments/:id | required | Delete |\n| POST | /api/payments/:id/send | required | Send notification |\n| POST | /api/payments/:id/skip | required | Skip |\n| POST | /api/payments/:id/tags | required | Add/upsert tag |\n| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |\n| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |\n\n---\n\n## Key Implementation Details\n\n### auth.js (replaces entire old auth module)\n```js\nconst PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n const username = req.headers['x-authentik-username'];\n if (!username) return res.status(401).json({ error: 'Unauthorized' });\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),\n };\n next();\n}\nmodule.exports = { authentikMiddleware };\n```\n\n### csvParser.js (port of dskuploader.py)\n- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8\n- `csv-parse` parses the decoded text with `columns: true`\n- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`\n- Card extraction: regex `/^\\d{6}x{6}\\d{4}$/` on first token of `Основание`\n- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`\n- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`\n- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`\n\n### payments.js changes from payments-logger\n1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call\n2. Add `source` to the `GET /` where clause filter\n3. Add `sources` to `meta/filters` response\n4. Currency-aware amount formatting in notification message\n5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)\n\n### upload.js (new)\n- `multer` memory storage, max 10 files × 10 MB\n- Calls `parseDskCsv(buffer)` per file\n- Upserts tags via `prisma.tag.upsert` then connects\n- Returns `{ imported, skipped, errors, payments[] }`\n\n### Frontend changes\n- **Delete**: `auth.js`, `AuthProvider.jsx`\n- **main.jsx**: Remove `<AuthProvider>` wrapper\n- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add \"Payments\" / \"Upload CSV\" tab toggle\n- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols\n- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell\n- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`\n\n---\n\n## Docker Compose\n\n```yaml\nservices:\n db:\n image: postgres:16-alpine\n environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: ${DB_PASSWORD}, POSTGRES_DB: finance_hub }\n volumes: [pgdata:/var/lib/postgresql/data]\n healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }\n\n backend:\n build: ./backend\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports: [\"${BACKEND_PORT:-3001}:3001\"]\n depends_on: { db: { condition: service_healthy } }\n\n frontend:\n build: ./frontend\n ports: [\"${FRONTEND_PORT:-5175}:5173\"]\n depends_on: [backend]\n\nvolumes: { pgdata: }\n```\n\n**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.\n\n---\n\n## Environment Variables (.env)\n\n```bash\nDB_PASSWORD=change_me\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\nTZ=Europe/Sofia\nBACKEND_PORT=3001\nFRONTEND_PORT=5175\n```\n\nRemoved vs payments-logger: `JWT_SECRET`, `JWT_EXPIRE_MINUTES`.\n\n---\n\n## Implementation Order\n\n1. Create folder structure and write `docker-compose.yml`, `.env.example`, `.gitignore`\n2. Write `backend/prisma/schema.prisma` and migration SQL\n3. Write `backend/package.json` (add `csv-parse`, `iconv-lite`, `multer`; remove `bcryptjs`, `jose`)\n4. Write `backend/Dockerfile`\n5. Write `backend/src/auth.js` (Authentik middleware)\n6. Copy `backend/src/parser.js` verbatim from payments-logger\n7. Write `backend/src/csvParser.js` (Python port)\n8. Write `backend/src/routes/upload.js`\n9. Write `backend/src/routes/payments.js` (from payments-logger + 5 changes listed above)\n10. Write `backend/src/index.js`\n11. Copy frontend base from payments-logger; delete `auth.js` + `AuthProvider.jsx`\n12. Update `main.jsx`, `App.jsx`, `FilterBar.jsx`, `PaymentTable.jsx`\n13. Write `frontend/src/components/UploadPanel.jsx`\n14. Update `frontend/vite.config.js`\n15. `docker compose build && docker compose up -d`\n16. Run verification checklist\n\n---\n\n## Verification\n\n**Schema**\n- `payments` table has `source`, `currency`, `debit_bgn`, `credit_bgn`, `transaction_type`, `payer_account`\n- No `users` table; `Source` enum exists\n\n**Auth**\n- `GET /api/payments` → 401 without `x-authentik-username` header\n- `POST /api/payments/ingest` → 201 without any header\n- `curl -H \"x-authentik-username: test\" localhost:3001/api/payments` → 200\n\n**SMS Ingest**\n- DSK POS SMS → `source=INGEST`, `currency=EUR`, correct amount/card/recipient\n- Apple Wallet structured body → `type=WALLET`, `source=INGEST`\n- Rate limiter → 429 after 200 req/min\n\n**CSV Upload**\n- Single DSK CSV → rows with `source=UPLOAD`, `currency=BGN`\n- Multiple CSVs in one request → all merged\n- `ТРАНСФЕР СОБСТВЕНИ СМЕТКИ` rows counted in `skipped`, not imported\n- Card regex match from `Основание` column\n- Auto-tags applied (ЗАПЛАТА→Salary, LIDL→Groceries)\n- cp1251 file imports correctly\n\n**UI**\n- Source badge visible in payment table (SMS indigo, CSV emerald)\n- Source dropdown in FilterBar filters correctly\n- Amount shows correct currency per row\n- Upload Panel: drag-and-drop works, result summary shows counts\n- Logout redirects to Authentik sign_out\n- No login form shown (Authentik handles it at NPM level)\n- Tags, send, skip, delete all still work\n\n## Reference Files\n\n- `/volume2/docker/finance/payments-logger/backend/src/routes/payments.js`\n- `/volume2/docker/finance/payments-logger/backend/src/parser.js`\n- `/volume2/docker/finance/payments-logger/backend/src/index.js`\n- `/volume2/docker/finance/payments-logger/backend/src/auth.js`\n- `/volume2/docker/finance/payments-logger/backend/prisma/schema.prisma`\n- `/volume2/docker/finance/payments-logger/frontend/src/App.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/PaymentTable.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/FilterBar.jsx`\n- `/volume2/docker/finance/dsk-uploader/dskuploader.py`\n- `/volume2/docker/finance/auth/docker-compose.yml`","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Claude’s Plan","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Stayed in plan mode","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good question. Here's the full breakdown:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Backend Tech Stack — Options","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Backend Tech Stack — Options","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Why:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"payments-logger is already Node.js/Express/Prisma. The new app is 80% payments-logger with CSV upload added on top. Keeping the same stack means:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"verbatim, zero rewrite","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy the entire","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"routes/payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with minimal edits","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Same Prisma schema workflow, same migrations, same Docker image","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The CSV parsing logic (the only Python-specific thing) ports cleanly to","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"csv-parse","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— it's just regex + string manipulation, nothing pandas-specific","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Trade-off:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Have to port the Python CSV parsing to JS. It's ~150 lines and mostly string manipulation — straightforward.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option B: Python + FastAPI + SQLAlchemy","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option B: Python + FastAPI + SQLAlchemy","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rewrite everything in Python. dsk-uploader is Python, so CSV parsing is already done.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep the dsk-uploader CSV logic as-is (no porting). Python has better data science libraries if you later add analytics.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Lose the entire payments-logger backend (routes, parser, Prisma schema) — full rewrite. FastAPI + SQLAlchemy is a different mental model than Express + Prisma. Frontend stays React anyway, so the stack split doesn't simplify anything.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"More work overall, gains almost nothing.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep Node.js as the main API, add a separate Python FastAPI service just for CSV parsing. They share the DB.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Zero porting — Python CSV code used as-is.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two backend services to maintain, deploy, and keep in sync. Inter-service HTTP calls. Two Dockerfiles. For ~150 lines of CSV logic, this is massively over-engineered.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Not worth it.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Extend dsk-uploader into a full payments app.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pandas for CSV, no porting.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Jinja2 templates instead of React (or add React separately). 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The React frontend is the stronger UI foundation.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Worst of all options — rebuild the harder parts (UI, SMS parser, notification) for no gain.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Summary","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Summary","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"CSV porting effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"App rewrite effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Result 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Everything else in the plan reuses payments-logger code directly. That's why Node.js is the clear winner here.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Want to adjust the stack, or shall I proceed with Option A?","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ok sounds good. Implement all you suggested","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Starting implementation. Let me first read all the reference files I'll need to copy from.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"payments.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"App.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"App.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"FilterBar.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"FilterBar.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentTable.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentTable.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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payments-logger.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.css","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.css","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"vite.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"vite.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"tailwind.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"tailwind.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"postcss.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"postcss.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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components.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentCard.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentCard.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentList.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentList.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"schema.prisma","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"schema.prisma","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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Let me set up the todo list and start building.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create finance-hub directory structure","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"mkdir -p /volume2/docker/finance/finance-hub/backend/src/routes \\\n /volume2/docker/finance/finance-hub/backend/prisma/migrations/20260508_init \\\n /volume2/docker/finance/finance-hub/frontend/src/components && echo \"done\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":24,"on_screen":false,"help_text":"Copy 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POSTGRES_USER: finance\n POSTGRES_PASSWORD: ${DB_PASSWORD}\n POSTGRES_DB: finance_hub\n volumes:\n - pgdata:/var/lib/postgresql/data\n healthcheck:\n test: [\"CMD-SHELL\", \"pg_isready -U finance -d finance_hub\"]\n interval: 5s\n timeout: 5s\n retries: 5\n\n backend:\n build: ./backend\n restart: unless-stopped\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports:\n - \"${BACKEND_PORT:-3001}:3001\"\n depends_on:\n db:\n condition: service_healthy\n\n frontend:\n build: ./frontend\n restart: unless-stopped\n ports:\n - \"${FRONTEND_PORT:-5175}:5173\"\n depends_on:\n - backend\n\nvolumes:\n pgdata:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".env.example","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".env.example","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"15 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Database\nDB_PASSWORD=change_me_strong_password\n\n# Notifier service (for SMS payment notifications)\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\n\n# Timezone (used by SMS parser for Bulgarian bank timestamps)\nTZ=Europe/Sofia\n\n# Ports (optional — defaults shown)\nBACKEND_PORT=3001\nFRONTEND_PORT=5175","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".gitignore","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".gitignore","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"5 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env\nnode_modules/\ndist/\n*.log","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"schema.prisma","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"schema.prisma","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"54 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"generator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status {\n UNPROCESSED\n SENT\n SKIPPED\n}\n\nenum Source {\n INGEST\n UPLOAD\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration.sql","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration.sql","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"55 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- CreateEnum\nCREATE TYPE \"Status\" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');\nCREATE TYPE \"Source\" AS ENUM ('INGEST', 'UPLOAD');\n\n-- CreateTable\nCREATE TABLE \"payments\" (\n \"id\" SERIAL PRIMARY KEY,\n \"raw_message\" TEXT NOT NULL,\n \"date\" TIMESTAMP(3),\n \"type\" TEXT,\n \"card\" TEXT,\n \"recipient\" TEXT,\n \"amount\" DOUBLE PRECISION,\n \"currency\" TEXT DEFAULT 'EUR',\n \"balance\" DOUBLE PRECISION,\n \"source\" \"Source\" NOT NULL DEFAULT 'INGEST',\n \"status\" \"Status\" NOT NULL DEFAULT 'UNPROCESSED',\n \"notified_at\" TIMESTAMP(3),\n \"notify_phone\" TEXT,\n \"debit_bgn\" DOUBLE PRECISION,\n \"credit_bgn\" DOUBLE PRECISION,\n \"transaction_type\" TEXT,\n \"payer_account\" TEXT,\n \"created_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,\n \"updated_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP\n);\n\n-- CreateTable\nCREATE TABLE \"tags\" (\n \"id\" SERIAL PRIMARY KEY,\n \"name\" TEXT NOT NULL,\n \"color\" TEXT NOT NULL DEFAULT '#6b7280'\n);\n\n-- CreateUniqueIndex\nCREATE UNIQUE INDEX \"tags_name_key\" ON \"tags\"(\"name\");\n\n-- CreateTable (M2M join)\nCREATE TABLE \"_PaymentToTag\" (\n \"A\" INTEGER NOT NULL,\n \"B\" INTEGER NOT NULL,\n CONSTRAINT \"_PaymentToTag_AB_pkey\" PRIMARY KEY (\"A\", \"B\")\n);\n\nCREATE INDEX \"_PaymentToTag_B_index\" ON \"_PaymentToTag\"(\"B\");\n\n-- AddForeignKey\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_A_fkey\"\n FOREIGN KEY (\"A\") REFERENCES \"payments\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;\n\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_B_fkey\"\n FOREIGN KEY (\"B\") REFERENCES \"tags\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration_lock.toml","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration_lock.toml","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"4 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Please do not edit this file manually\n# It should be added in your version-control system (e.g., Git)\nprovider = \"postgresql\"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"26 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"{\n \"name\": \"finance-hub-backend\",\n \"version\": \"1.0.0\",\n \"main\": \"src/index.js\",\n \"scripts\": {\n \"start\": \"node src/index.js\",\n \"dev\": \"nodemon src/index.js\",\n \"prisma:generate\": \"prisma generate\",\n \"prisma:migrate\": \"prisma migrate deploy\"\n },\n \"dependencies\": {\n \"@prisma/client\": \"^5.22.0\",\n \"cors\": \"^2.8.5\",\n \"csv-parse\": \"^5.5.6\",\n \"express\": \"^4.21.1\",\n \"express-rate-limit\": \"^7.4.0\",\n \"iconv-lite\": \"^0.6.3\",\n \"morgan\": \"^1.10.0\",\n \"multer\": \"^1.4.5-lts.1\"\n },\n \"devDependencies\": {\n \"nodemon\": \"^3.1.7\",\n \"prisma\": \"^5.22.0\"\n }\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"18 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"FROM node:20-alpine\n\nRUN apk add --no-cache openssl\n\nWORKDIR /app\n\nCOPY package.json package-lock.json* ./\nRUN npm install\n\nCOPY prisma ./prisma\nRUN npx prisma generate\n\nCOPY src ./src\n\nEXPOSE 3001\n\nCMD [\"sh\", \"-c\", \"npx prisma migrate deploy && node src/index.js\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"auth.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"auth.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"27 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const PUBLIC_PATHS = new Set([\n '/api/health',\n '/api/payments/ingest',\n]);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n\n const username = req.headers['x-authentik-username'];\n if (!username) {\n return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });\n }\n\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '')\n .split(',')\n .map(g => g.trim())\n .filter(Boolean),\n };\n\n next();\n}\n\nmodule.exports = { authentikMiddleware };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"104 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/**\n * Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)\n *\n * Supported formats:\n *\n * POS / INTERNET / ECOM / P2P payment:\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.\n *\n * ATM withdrawal:\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.\n *\n * ATM utility payment (amount may include fee as AMOUNT/FEE):\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.\n */\n\nconst LOCAL_TZ = process.env.TZ || 'Europe/Sofia';\n\n/**\n * Convert a local-timezone date/time to a UTC Date object.\n * Uses Intl to resolve the actual UTC offset (DST-aware).\n */\nfunction localToUtc(year, month, day, hour, minute) {\n const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));\n\n const formatter = new Intl.DateTimeFormat('en-US', {\n timeZone: LOCAL_TZ,\n year: 'numeric', month: '2-digit', day: '2-digit',\n hour: '2-digit', minute: '2-digit', second: '2-digit',\n hour12: false,\n });\n\n const parts = {};\n formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });\n\n const localAtNaive = new Date(Date.UTC(\n parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),\n parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),\n ));\n\n const offsetMs = localAtNaive.getTime() - naive.getTime();\n return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);\n}\n\nfunction parsePaymentSms(message) {\n const result = {\n rawMessage: message,\n date: null,\n type: null,\n card: null,\n recipient: null,\n amount: null,\n balance: null,\n };\n\n // Date and time: \"Na DD/MM/YYYY v HH:MM\"\n const dateMatch = message.match(/Na (\\d{2})\\/(\\d{2})\\/(\\d{4}) v (\\d{2}):(\\d{2})/i);\n if (dateMatch) {\n const [, day, month, year, hour, minute] = dateMatch;\n result.date = localToUtc(\n parseInt(year), parseInt(month), parseInt(day),\n parseInt(hour), parseInt(minute),\n );\n }\n\n // Card mask: \"s karta 400915***4447\" or \"s karta 483890***7162\"\n const cardMatch = message.match(/s karta\\s+([\\d*]+)/i);\n if (cardMatch) {\n result.card = cardMatch[1];\n }\n\n // Transaction type: supports both prepositions\n // \"na POS\" / \"na ATM\" / \"na INTERNET\" etc. (payment)\n // \"ot ATM\" (withdrawal)\n const typeMatch = message.match(/(?:na|ot)\\s+(POS|ATM|INTERNET|ECOM|P2P)\\b/i);\n if (typeMatch) {\n result.type = typeMatch[1].toUpperCase();\n }\n\n // Recipient address: \"s adres: MERCHANT\" or \"s adres:MERCHANT\" (no space variant)\n const recipientMatch = message.match(/s adres:\\s*([^.]+)\\./i);\n if (recipientMatch) {\n result.recipient = recipientMatch[1].trim();\n }\n\n // Amount: handles both verbs and the AMOUNT/FEE suffix format\n // \"sa plateni 7.78 EUR\"\n // \"sa iztegleni 400.00 EUR\"\n // \"sa plateni 0.50 EUR/0.50 EUR\" → captures 0.50 (the charged amount, ignoring fee)\n const amountMatch = message.match(/sa (?:plateni|iztegleni)\\s+([\\d.,]+)\\s+[A-Z]{3}/i);\n if (amountMatch) {\n result.amount = parseFloat(amountMatch[1].replace(',', '.'));\n }\n\n // Balance: \"Nalichni: 2583.07 EUR.\"\n const balanceMatch = message.match(/Nalichni:\\s*([\\d.,]+)\\s+[A-Z]{3}/i);\n if (balanceMatch) {\n result.balance = parseFloat(balanceMatch[1].replace(',', '.'));\n }\n\n return result;\n}\n\nmodule.exports = { parsePaymentSms };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"csvParser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"csvParser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"175 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/**\n * DSK Bank CSV parser — Node.js port of dskuploader.py\n *\n * DSK Bank exports use Windows-1251 (cp1251) encoding.\n * Each row maps to a Payment record with source=UPLOAD, currency=BGN.\n */\n\nconst { parse } = require('csv-parse');\nconst iconv = require('iconv-lite');\n\nconst SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';\nconst CARD_REGEX = /^\\d{6}x{6}\\d{4}$/;\nconst POS_REGEX = /^\\s*ПЛАЩАНЕ\\s+НА\\s+ПОС\\s+\\d{2}\\.\\d{2}\\.\\d{4}\\s+\\d{2}:\\d{2}/;\n\nconst COL = {\n DATE: 'Дата',\n TYPE: 'Вид на трансакцията',\n REASON: 'Основание',\n DEBIT: 'Дебит BGN',\n CREDIT: 'Кредит BGN',\n PAYEE: 'Наредител/Получател',\n ACCT: 'Номер сметка на наредителя / получателя',\n};\n\nconst TAG_RULES = [\n ['reason', 'ЗАПЛАТА', 'Salary'],\n ['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],\n ['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],\n ['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],\n ['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],\n ['payee', 'VIVACOM', 'Subscriptions'],\n ['payee', 'Google', 'Subscriptions'],\n ['payee', 'SkyShowtime', 'Subscriptions'],\n ['payee', 'NETFLIX', 'Subscriptions'],\n ['payee', 'LUKOIL', 'Bills'],\n ['payee', 'CityGate', 'Bills'],\n ['payee', 'CBA', 'Groceries'],\n ['payee', 'FANTASTICO', 'Groceries'],\n ['payee', 'LIDL', 'Groceries'],\n];\n\nfunction parseNum(val) {\n if (val == null || val === '') return null;\n if (typeof val === 'number') return isNaN(val) ? null : val;\n const s = String(val).trim().replace(/\\xa0/g, '').replace(/ /g, '').replace(',', '.');\n const n = parseFloat(s);\n return isNaN(n) ? null : n;\n}\n\nfunction parseDate(val) {\n if (!val) return null;\n const s = String(val).trim();\n const m = s.match(/^(\\d{2})\\.(\\d{2})\\.(\\d{4})$/);\n if (m) {\n return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));\n }\n return null;\n}\n\nfunction processReasonAndCard(reason) {\n if (!reason || typeof reason !== 'string') return { reason: '', card: null };\n\n const parts = reason.trim().split(' ');\n let card = null;\n let cleanReason = reason.trim();\n\n if (parts[0] && CARD_REGEX.test(parts[0])) {\n card = parts[0];\n cleanReason = parts.slice(1).join(' ').trim();\n }\n\n if (POS_REGEX.test(cleanReason)) {\n const posParts = cleanReason.split('<br/>');\n try {\n const dateTime = posParts[0].split('ПОС ')[1];\n cleanReason = `POS PAYMENT ${dateTime}`;\n } catch (_) { /* keep original */ }\n }\n\n return { reason: cleanReason.replace(/\\s+/g, ' ').trim(), card };\n}\n\nfunction generateTags(fields) {\n const tags = new Set();\n for (const [field, keyword, tagName] of TAG_RULES) {\n if ((fields[field] || '').includes(keyword)) {\n tags.add(tagName);\n }\n }\n return Array.from(tags);\n}\n\nfunction processRow(row) {\n const transactionType = (row[COL.TYPE] || '').trim();\n if (transactionType === SKIP_TYPE) return null;\n\n const { reason, card } = processReasonAndCard(row[COL.REASON]);\n const payee = (row[COL.PAYEE] || '').trim();\n const payerAccount = (row[COL.ACCT] || '').trim();\n const debitBgn = parseNum(row[COL.DEBIT]);\n const creditBgn = parseNum(row[COL.CREDIT]);\n const date = parseDate(row[COL.DATE]);\n\n const autoTags = generateTags({ reason, transactionType, payee, debitBgn, creditBgn });\n\n const amount = debitBgn ?? creditBgn ?? null;\n\n const rawMessage = [\n row[COL.DATE] && `Date: ${row[COL.DATE]}`,\n transactionType && `Type: ${transactionType}`,\n payee && `Payee: ${payee}`,\n debitBgn != null && `Debit: ${debitBgn} BGN`,\n creditBgn != null && `Credit: ${creditBgn} BGN`,\n ].filter(Boolean).join(' | ');\n\n return {\n rawMessage,\n date,\n type: null,\n card,\n recipient: payee || null,\n amount,\n currency: 'BGN',\n balance: null,\n source: 'UPLOAD',\n debitBgn,\n creditBgn,\n transactionType: transactionType || null,\n payerAccount: payerAccount || null,\n autoTags,\n };\n}\n\n/**\n * Parse a Buffer containing a DSK Bank CSV (cp1251 or UTF-8).\n * Returns { rows, skipped, errors }.\n */\nasync function parseDskCsv(buffer) {\n // Try cp1251 first (DSK Bank export encoding), fall back to UTF-8\n let text = iconv.decode(buffer, 'cp1251');\n if (!text.includes(COL.DATE)) {\n text = buffer.toString('utf-8');\n }\n\n return new Promise((resolve, reject) => {\n const rows = [];\n const errors = [];\n let skipped = 0;\n\n const parser = parse(text, {\n columns: true,\n skip_empty_lines: true,\n trim: true,\n relax_column_count: true,\n });\n\n parser.on('readable', () => {\n let record;\n while ((record = parser.read()) !== null) {\n try {\n const row = processRow(record);\n if (row === null) { skipped++; } else { rows.push(row); }\n } catch (err) {\n errors.push(err.message);\n }\n }\n });\n\n parser.on('error', reject);\n parser.on('end', () => resolve({ rows, skipped, errors }));\n });\n}\n\nmodule.exports = { parseDskCsv };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"39 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst cors = require('cors');\nconst morgan = require('morgan');\nconst rateLimit = require('express-rate-limit');\nconst { authentikMiddleware } = require('./auth');\nconst paymentsRouter = require('./routes/payments');\nconst uploadRouter = require('./routes/upload');\n\nconst app = express();\nconst PORT = process.env.PORT || 3001;\n\napp.use(cors());\napp.use(express.json({ limit: '16kb' }));\napp.use(morgan('combined'));\n\n// Rate-limit the public ingest endpoint before auth middleware\nconst ingestLimiter = rateLimit({\n windowMs: 60 * 1000,\n max: 200,\n standardHeaders: true,\n legacyHeaders: false,\n message: { error: 'Too many requests, slow down' },\n});\napp.use('/api/payments/ingest', ingestLimiter);\n\n// Authentik header auth (skips /api/health and /api/payments/ingest)\napp.use(authentikMiddleware);\n\napp.get('/api/health', (_req, res) => {\n res.json({ status: 'ok', timestamp: new Date().toISOString() });\n});\n\napp.use('/api/payments', paymentsRouter);\napp.use('/api/upload', uploadRouter);\n\napp.listen(PORT, '0.0.0.0', () => {\n console.log(`Finance Hub API running on port ${PORT}`);\n});","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"}]...
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G)
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
report(1).csv, Editor Group 1
report(2).csv, Editor Group 1
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
Design new payment-logge…, Editor Group 2
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Design new payment-logger and dsk-uploader hybrid app
Session history
New session
Message actions
payments.js
payments.js
ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.
Thinking
Thinking
I'll explore all three reference projects in parallel to understand their structure before planning.
Agent:
Explore payment-logger app structure and functionality
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How data flows (ingest, storage, retrieval)
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.
Agent:
Explore dsk-uploader app structure and functionality
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How file uploads work - what files, what format, how parsed
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.
Agent:
Explore auth folder and authentik integration
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. What auth system is being used (Authentik)
2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?
3. Middleware - how is auth enforced on routes?
4. Any frontend auth flow - login redirect, token handling, protected routes
5. Environment variables related to auth
6. Docker/deployment setup for the auth service itself
7. Any example of how other apps integrate with this auth
Report with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.
Message actions
payments.js
payments.js
continue
Thinking
Thinking
Launching parallel exploration of all three reference projects.
Agent:
Explore payment-logger app structure
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How data is ingested (look at /ingest route especially)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore dsk-uploader app structure
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How file uploads work (what format, what processing happens)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore auth project structure
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. What authentication system is used (authentik integration details)
3. How OAuth/OIDC flow works
4. Any middleware or helper functions for protecting routes
5. Session management approach
6. How frontend handles auth state
7. Any example of how other apps integrate with this auth system
8. Docker setup and environment variables
Please read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.
Thinking
Thinking
Now I have a complete picture of all three. Let me design the plan.
Agent:
Design combined app architecture
IN
Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:
---
## App 1: payments-logger (Node.js)
- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI
- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS
- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage
- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)
- **Schema** (PostgreSQL via Prisma):
- `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at
- `tags` table: id, name, color — M2M with payments via `_PaymentToTag`
- `users` table: id, username, hashed_password (this will be REMOVED)
- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system
- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance
## App 2: dsk-uploader (Python/Flask)
- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database
- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5
- **Auth**: None (open)
- **CSV format** (DSK Bank Bulgarian format, columns):
- `Дата` (date, DD.MM.YYYY)
- `Вид на трансакцията` (transaction type, Bulgarian)
- `Основание` (reason/description — contains card number regex: `^\d{6}x{6}\d{4}$`)
- `Дебит BGN` (debit amount, may be empty)
- `Кредит BGN` (credit amount, may be empty)
- `Наредител/Получател` (orderer/recipient name)
- `Номер сметка на наредителя / получателя` (account number)
- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers
- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)
## App 3: auth (Authentik)
- **Mode**: Proxy mode via NPM (forward auth)
- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:
- `X-authentik-username`
- `X-authentik-email`
- `X-authentik-groups`
- **No code integration needed** in the app itself — just trust these headers from NPM
- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`
---
## What the New Combined App Must Do
1. **Single PostgreSQL database** for all transactions
2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST
3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema
4. **Unified UI** — show all payments in one table regardless of source
5. **Source indicator** in UI — badge showing "INGEST", "UPLOAD", or "BOTH" (if duplicate detection added)
6. **Source filter** in FilterBar — filter by All/Ingest/Upload
7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM
8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination
9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL
---
## Technical Constraints
- Keep Node.js backend (not Python) — extend payments-logger's stack
- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)
- File upload: use `multer` npm middleware
- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)
- Add `source` enum field (INGEST/UPLOAD) to payments schema
- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is
- Remove `users` table from schema
---
## Please Design
1. Complete folder structure for the new app (suggest name: "finance-hub" or similar — note this is a placeholder, user will confirm)
2. Prisma schema with new fields (`source`, `currency`)
3. All backend API routes
4. CSV parser design in Node.js (port of the Python logic)
5. Authentik auth middleware
6. Frontend component structure (React) — what's reused from payments-logger, what's new
7. Docker Compose setup
8. Environment variables needed
9. Step-by-step implementation order
10. Verification checklist
Be specific about file paths and code structure. This will be used to write actual implementation code.
Thinking
Thinking
Good plan. Let me ask the one thing I need before writing the final plan.
AskUserQuestion
OUT
User has answered your questions: "What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding."="finance-hub". You can now continue with the user's answers in mind.
Thinking
Thinking
Writing the final plan now.
Thinking
Thinking
Write
ets-create-a-new-generic-sun.md
ets-create-a-new-generic-sun.md
326 lines
# finance-hub — Implementation Plan
## Context
Two separate finance apps exist as references and will be retired:
- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.
- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.
The new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).
---
## Tech Stack
| Layer | Choice | Rationale |
|-------|--------|-----------|
| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |
| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |
| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |
| Database | PostgreSQL 16 | Same as payments-logger |
| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |
| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |
| Container | Docker Compose | Same pattern as both reference apps |
**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage.
**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references.
**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.
---
## Folder Structure
```
/volume2/docker/finance/finance-hub/
├── docker-compose.yml
├── .env
├── .env.example
├── .gitignore
├── backend/
│ ├── Dockerfile
│ ├── package.json
│ ├── prisma/
│ │ ├── schema.prisma
│ │ └── migrations/
│ │ ├── migration_lock.toml
│ │ └── 20260508_init/
│ │ └── migration.sql
│ └── src/
│ ├── index.js ← entry point (Authentik middleware wired here)
│ ├── auth.js ← Authentik header middleware (replaces JWT auth)
│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)
│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)
│ └── routes/
│ ├── payments.js ← existing routes + source/currency additions
│ └── upload.js ← NEW: POST /api/upload/csv
└── frontend/
├── Dockerfile
├── package.json
├── vite.config.js
├── tailwind.config.js
├── postcss.config.js
├── index.html
└── src/
├── main.jsx ← remove AuthProvider wrapper
├── index.css
├── App.jsx ← remove auth state, add Upload tab toggle
└── components/
├── FilterBar.jsx ← add source filter select
├── PaymentTable.jsx ← add Source badge column + currency display
├── PaymentCard.jsx ← minor source badge addition
├── PaymentList.jsx ← unchanged
└── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI
```
---
## Database Schema (Prisma)
File: `backend/prisma/schema.prisma`
```prisma
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
}
model Payment {
id Int @id @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
auth.js
auth.js
27 lines
const PUBLIC_PATHS = new Set([
'/api/health',
'/api/payments/ingest',
]);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) {
return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });
}
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '')
.split(',')
.map(g => g.trim())
.filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
Write
parser.js
parser.js
104 lines
/**
* Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)
*
* Supported formats:
*
* POS / INTERNET / ECOM / P2P payment:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM withdrawal:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM utility payment (amount may include fee as AMOUNT/FEE):
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.
*/
const LOCAL_TZ = process.env.TZ || 'Europe/Sofia';
/**
* Convert a local-timezone date/time to a UTC Date object.
* Uses Intl to resolve the actual UTC offset (DST-aware).
*/
function localToUtc(year, month, day, hour, minute) {
const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));
const formatter = new Intl.DateTimeFormat('en-US', {
timeZone: LOCAL_TZ,
year: 'numeric', month: '2-digit', day: '2-digit',
hour: '2-digit', minute: '2-digit', second: '2-digit',
hour12: false,
});
const parts = {};
formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });
const localAtNaive = new Date(Date.UTC(
parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),
parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),
));
const offsetMs = localAtNaive.getTime() - naive.getTime();
return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);
}
function parsePaymentSms(message) {
const result = {
rawMessage: message,
date: null,
type: null,
card: null,
recipient: null,
amount: null,
balance: null,
};
// Date and time: "Na DD/MM/YYYY v HH:MM"
const dateMatch = message.match(/Na (\d{2})\/(\d{2})\/(\d{4}) v (\d{2}):(\d{2})/i);
if (dateMatch) {
const [, day, month, year, hour, minute] = dateMatch;
result.date = localToUtc(
parseInt(year), parseInt(month), parseInt(day),
parseInt(hour), parseInt(minute),
);
}
// Card mask: "s karta 400915***4447" or "s karta 483890***7162"
const cardMatch = message.match(/s karta\s+([\d*]+)/i);
if (cardMatch) {
result.card = cardMatch[1];
}
// Transaction type: supports both prepositions
// "na POS" / "na ATM" / "na INTERNET" etc. (payment)
// "ot ATM" (withdrawal)
const typeMatch = message.match(/(?:na|ot)\s+(POS|ATM|INTERNET|ECOM|P2P)\b/i);
if (typeMatch) {
result.type = typeMatch[1].toUpperCase();
}
// Recipient address: "s adres: MERCHANT" or "s adres:MERCHANT" (no space variant)
const recipientMatch = message.match(/s adres:\s*([^.]+)\./i);
if (recipientMatch) {
result.recipient = recipientMatch[1].trim();
}
// Amount: handles both verbs and the AMOUNT/FEE suffix format
// "sa plateni 7.78 EUR"
// "sa iztegleni 400.00 EUR"
// "sa plateni 0.50 EUR/0.50 EUR" → captures 0.50 (the charged amount, ignoring fee)
const amountMatch = message.match(/sa (?:plateni|iztegleni)\s+([\d.,]+)\s+[A-Z]{3}/i);
if (amountMatch) {
result.amount = parseFloat(amountMatch[1].replace(',', '.'));
}
// Balance: "Nalichni: 2583.07 EUR."
const balanceMatch = message.match(/Nalichni:\s*([\d.,]+)\s+[A-Z]{3}/i);
if (balanceMatch) {
result.balance = parseFloat(balanceMatch[1].replace(',', '.'));
}
return result;
}
module.exports = { parsePaymentSms };
Write
csvParser.js
csvParser.js
175 lines
/**
* DSK Bank CSV parser — Node.js port of dskuploader.py
*
* DSK Bank exports use Windows-1251 (cp1251) encoding.
* Each row maps to a Payment record with source=UPLOAD, currency=BGN.
*/
const { parse } = require('csv-parse');
const iconv = require('iconv-lite');
const SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';
const CARD_REGEX = /^\d{6}x{6}\d{4}$/;
const POS_REGEX = /^\s*ПЛАЩАНЕ\s+НА\s+ПОС\s+\d{2}\.\d{2}\.\d{4}\s+\d{2}:\d{2}/;
const COL = {
DATE: 'Дата',
TYPE: 'Вид на трансакцията',
REASON: 'Основание',
DEBIT: 'Дебит BGN',
CREDIT: 'Кредит BGN',
PAYEE: 'Наредител/Получател',
ACCT: 'Номер сметка на наредителя / получателя',
};
const TAG_RULES = [
['reason', 'ЗАПЛАТА', 'Salary'],
['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],
['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],
['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],
['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],
['payee', 'VIVACOM', 'Subscriptions'],
['payee', 'Google', 'Subscriptions'],
['payee', 'SkyShowtime', 'Subscriptions'],
['payee', 'NETFLIX', 'Subscriptions'],
['payee', 'LUKOIL', 'Bills'],
['payee', 'CityGate', 'Bills'],
['payee', 'CBA', 'Groceries'],
['payee', 'FANTASTICO', 'Groceries'],
['payee', 'LIDL', 'Groceries'],
];
function parseNum(val) {
if (val == null || val === '') return null;
if (typeof val === 'number') return isNaN(val) ? null : val;
const s = String(val).trim().replace(/\xa0/g, '').replace(/ /g, '').replace(',', '.');
const n = parseFloat(s);
return isNaN(n) ? null : n;
}
function parseDate(val) {
if (!val) return null;
const s = String(val).trim();
const m = s.match(/^(\d{2})\.(\d{2})\.(\d{4})$/);
if (m) {
return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));
}
return null;
}
function processReasonAndCard(reason) {
if (!reason || typeof reason !== 'string') return { reason: '', card: null };
const parts = reason.trim().split(' ');
let card = null;
let cleanReason = reason.trim();
if (parts[0] && CARD_REGEX.test(parts[0])) {
card = parts[0];
cleanReason = parts.slice(1).join(' ').trim();
}
if (POS_REGEX.test(cleanReason)) {
const posParts = cleanReason.split('<br/>');
try {
const dateTime = posParts[0].split('ПОС ')[1];
cleanReason = `POS PAYMENT ${dateTime}`;
} catch (_) { /* keep original */ }
}
return { reason: cleanReason.replace(/\s+/g, ' ').trim(), card };
}
function generateTags(fields) {
const tags = new Set();
for (const [field, keyword, tagName] of TAG_RULES) {
if ((fields[field] || '').includes(keyword)) {
tags.add(tagName);
}
}
return Array.from(tags);
}
function processRow(row) {
const transactionType = (row[COL.TYPE] || '').trim();
if (transactionType === SKIP_TYPE) return null;
const { reason, card } = processReasonAndCard(row[COL.REASON]);
const payee = (row[COL.PAYEE] || ...
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report(2).csv — finance [SSH: nas]
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G)
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
report(1).csv, Editor Group 1
report(2).csv, Editor Group 1
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
Design new payment-logge…, Editor Group 2
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DEBUG CONSOLE
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remote SSH: nas
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Ln 9, Col 45
Info: Setting up SSH Host nas: Setting up SSH tunnel
Design new payment-logger and dsk-uploader hybrid app
Session history
New session
Message actions
payments.js
payments.js
ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.
Thinking
Thinking
I'll explore all three reference projects in parallel to understand their structure before planning.
Agent:
Explore payment-logger app structure and functionality
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How data flows (ingest, storage, retrieval)
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.
Agent:
Explore dsk-uploader app structure and functionality
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How file uploads work - what files, what format, how parsed
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.
Agent:
Explore auth folder and authentik integration
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. What auth system is being used (Authentik)
2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?
3. Middleware - how is auth enforced on routes?
4. Any frontend auth flow - login redirect, token handling, protected routes
5. Environment variables related to auth
6. Docker/deployment setup for the auth service itself
7. Any example of how other apps integrate with this auth
Report with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.
Message actions
payments.js
payments.js
continue
Thinking
Thinking
Launching parallel exploration of all three reference projects.
Agent:
Explore payment-logger app structure
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How data is ingested (look at /ingest route especially)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore dsk-uploader app structure
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How file uploads work (what format, what processing happens)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore auth project structure
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. What authentication system is used (authentik integration details)
3. How OAuth/OIDC flow works
4. Any middleware or helper functions for protecting routes
5. Session management approach
6. How frontend handles auth state
7. Any example of how other apps integrate with this auth system
8. Docker setup and environment variables
Please read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.
Thinking
Thinking
Now I have a complete picture of all three. Let me design the plan.
Agent:
Design combined app architecture
IN
Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:
---
## App 1: payments-logger (Node.js)
- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI
- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS
- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage
- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)
- **Schema** (PostgreSQL via Prisma):
- `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at
- `tags` table: id, name, color — M2M with payments via `_PaymentToTag`
- `users` table: id, username, hashed_password (this will be REMOVED)
- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system
- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance
## App 2: dsk-uploader (Python/Flask)
- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database
- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5
- **Auth**: None (open)
- **CSV format** (DSK Bank Bulgarian format, columns):
- `Дата` (date, DD.MM.YYYY)
- `Вид на трансакцията` (transaction type, Bulgarian)
- `Основание` (reason/description — contains card number regex: `^\d{6}x{6}\d{4}$`)
- `Дебит BGN` (debit amount, may be empty)
- `Кредит BGN` (credit amount, may be empty)
- `Наредител/Получател` (orderer/recipient name)
- `Номер сметка на наредителя / получателя` (account number)
- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers
- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)
## App 3: auth (Authentik)
- **Mode**: Proxy mode via NPM (forward auth)
- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:
- `X-authentik-username`
- `X-authentik-email`
- `X-authentik-groups`
- **No code integration needed** in the app itself — just trust these headers from NPM
- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`
---
## What the New Combined App Must Do
1. **Single PostgreSQL database** for all transactions
2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST
3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema
4. **Unified UI** — show all payments in one table regardless of source
5. **Source indicator** in UI — badge showing "INGEST", "UPLOAD", or "BOTH" (if duplicate detection added)
6. **Source filter** in FilterBar — filter by All/Ingest/Upload
7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM
8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination
9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL
---
## Technical Constraints
- Keep Node.js backend (not Python) — extend payments-logger's stack
- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)
- File upload: use `multer` npm middleware
- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)
- Add `source` enum field (INGEST/UPLOAD) to payments schema
- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is
- Remove `users` table from schema
---
## Please Design
1. Complete folder structure for the new app (suggest name: "finance-hub" or similar — note this is a placeholder, user will confirm)
2. Prisma schema with new fields (`source`, `currency`)
3. All backend API routes
4. CSV parser design in Node.js (port of the Python logic)
5. Authentik auth middleware
6. Frontend component structure (React) — what's reused from payments-logger, what's new
7. Docker Compose setup
8. Environment variables needed
9. Step-by-step implementation order
10. Verification checklist
Be specific about file paths and code structure. This will be used to write actual implementation code.
Thinking
Thinking
Good plan. Let me ask the one thing I need before writing the final plan.
AskUserQuestion
OUT
User has answered your questions: "What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding."="finance-hub". You can now continue with the user's answers in mind.
Thinking
Thinking
Writing the final plan now.
Thinking
Thinking
Write
ets-create-a-new-generic-sun.md
ets-create-a-new-generic-sun.md
326 lines
# finance-hub — Implementation Plan
## Context
Two separate finance apps exist as references and will be retired:
- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.
- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.
The new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).
---
## Tech Stack
| Layer | Choice | Rationale |
|-------|--------|-----------|
| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |
| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |
| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |
| Database | PostgreSQL 16 | Same as payments-logger |
| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |
| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |
| Container | Docker Compose | Same pattern as both reference apps |
**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage.
**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references.
**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.
---
## Folder Structure
```
/volume2/docker/finance/finance-hub/
├── docker-compose.yml
├── .env
├── .env.example
├── .gitignore
├── backend/
│ ├── Dockerfile
│ ├── package.json
│ ├── prisma/
│ │ ├── schema.prisma
│ │ └── migrations/
│ │ ├── migration_lock.toml
│ │ └── 20260508_init/
│ │ └── migration.sql
│ └── src/
│ ├── index.js ← entry point (Authentik middleware wired here)
│ ├── auth.js ← Authentik header middleware (replaces JWT auth)
│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)
│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)
│ └── routes/
│ ├── payments.js ← existing routes + source/currency additions
│ └── upload.js ← NEW: POST /api/upload/csv
└── frontend/
├── Dockerfile
├── package.json
├── vite.config.js
├── tailwind.config.js
├── postcss.config.js
├── index.html
└── src/
├── main.jsx ← remove AuthProvider wrapper
├── index.css
├── App.jsx ← remove auth state, add Upload tab toggle
└── components/
├── FilterBar.jsx ← add source filter select
├── PaymentTable.jsx ← add Source badge column + currency display
├── PaymentCard.jsx ← minor source badge addition
├── PaymentList.jsx ← unchanged
└── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI
```
---
## Database Schema (Prisma)
File: `backend/prisma/schema.prisma`
```prisma
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
}
model Payment {
id Int @id @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
auth.js
auth.js
27 lines
const PUBLIC_PATHS = new Set([
'/api/health',
'/api/payments/ingest',
]);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) {
return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });
}
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '')
.split(',')
.map(g => g.trim())
.filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
Write
parser.js
parser.js
104 lines
/**
* Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)
*
* Supported formats:
*
* POS / INTERNET / ECOM / P2P payment:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM withdrawal:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM utility payment (amount may include fee as AMOUNT/FEE):
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.
*/
const LOCAL_TZ = process.env.TZ || 'Europe/Sofia';
/**
* Convert a local-timezone date/time to a UTC Date object.
* Uses Intl to resolve the actual UTC offset (DST-aware).
*/
function localToUtc(year, month, day, hour, minute) {
const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));
const formatter = new Intl.DateTimeFormat('en-US', {
timeZone: LOCAL_TZ,
year: 'numeric', month: '2-digit', day: '2-digit',
hour: '2-digit', minute: '2-digit', second: '2-digit',
hour12: false,
});
const parts = {};
formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });
const localAtNaive = new Date(Date.UTC(
parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),
parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),
));
const offsetMs = localAtNaive.getTime() - naive.getTime();
return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);
}
function parsePaymentSms(message) {
const result = {
rawMessage: message,
date: null,
type: null,
card: null,
recipient: null,
amount: null,
balance: null,
};
// Date and time: "Na DD/MM/YYYY v HH:MM"
const dateMatch = message.match(/Na (\d{2})\/(\d{2})\/(\d{4}) v (\d{2}):(\d{2})/i);
if (dateMatch) {
const [, day, month, year, hour, minute] = dateMatch;
result.date = localToUtc(
parseInt(year), parseInt(month), parseInt(day),
parseInt(hour), parseInt(minute),
);
}
// Card mask: "s karta 400915***4447" or "s karta 483890***7162"
const cardMatch = message.match(/s karta\s+([\d*]+)/i);
if (cardMatch) {
result.card = cardMatch[1];
}
// Transaction type: supports both prepositions
// "na POS" / "na ATM" / "na INTERNET" etc. (payment)
// "ot ATM" (withdrawal)
const typeMatch = message.match(/(?:na|ot)\s+(POS|ATM|INTERNET|ECOM|P2P)\b/i);
if (typeMatch) {
result.type = typeMatch[1].toUpperCase();
}
// Recipient address: "s adres: MERCHANT" or "s adres:MERCHANT" (no space variant)
const recipientMatch = message.match(/s adres:\s*([^.]+)\./i);
if (recipientMatch) {
result.recipient = recipientMatch[1].trim();
}
// Amount: handles both verbs and the AMOUNT/FEE suffix format
// "sa plateni 7.78 EUR"
// "sa iztegleni 400.00 EUR"
// "sa plateni 0.50 EUR/0.50 EUR" → captures 0.50 (the charged amount, ignoring fee)
const amountMatch = message.match(/sa (?:plateni|iztegleni)\s+([\d.,]+)\s+[A-Z]{3}/i);
if (amountMatch) {
result.amount = parseFloat(amountMatch[1].replace(',', '.'));
}
// Balance: "Nalichni: 2583.07 EUR."
const balanceMatch = message.match(/Nalichni:\s*([\d.,]+)\s+[A-Z]{3}/i);
if (balanceMatch) {
result.balance = parseFloat(balanceMatch[1].replace(',', '.'));
}
return result;
}
module.exports = { parsePaymentSms };
Write
csvParser.js
csvParser.js
175 lines
/**
* DSK Bank CSV parser — Node.js port of dskuploader.py
*
* DSK Bank exports use Windows-1251 (cp1251) encoding.
* Each row maps to a Payment record with source=UPLOAD, currency=BGN.
*/
const { parse } = require('csv-parse');
const iconv = require('iconv-lite');
const SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';
const CARD_REGEX = /^\d{6}x{6}\d{4}$/;
const POS_REGEX = /^\s*ПЛАЩАНЕ\s+НА\s+ПОС\s+\d{2}\.\d{2}\.\d{4}\s+\d{2}:\d{2}/;
const COL = {
DATE: 'Дата',
TYPE: 'Вид на трансакцията',
REASON: 'Основание',
DEBIT: 'Дебит BGN',
CREDIT: 'Кредит BGN',
PAYEE: 'Наредител/Получател',
ACCT: 'Номер сметка на наредителя / получателя',
};
const TAG_RULES = [
['reason', 'ЗАПЛАТА', 'Salary'],
['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],
['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],
['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],
['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],
['payee', 'VIVACOM', 'Subscriptions'],
['payee', 'Google', 'Subscriptions'],
['payee', 'SkyShowtime', 'Subscriptions'],
['payee', 'NETFLIX', 'Subscriptions'],
['payee', 'LUKOIL', 'Bills'],
['payee', 'CityGate', 'Bills'],
['payee', 'CBA', 'Groceries'],
['payee', 'FANTASTICO', 'Groceries'],
['payee', 'LIDL', 'Groceries'],
];
function parseNum(val) {
if (val == null || val === '') return null;
if (typeof val === 'number') return isNaN(val) ? null : val;
const s = String(val).trim().replace(/\xa0/g, '').replace(/ /g, '').replace(',', '.');
const n = parseFloat(s);
return isNaN(n) ? null : n;
}
function parseDate(val) {
if (!val) return null;
const s = String(val).trim();
const m = s.match(/^(\d{2})\.(\d{2})\.(\d{4})$/);
if (m) {
return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));
}
return null;
}
function processReasonAndCard(reason) {
if (!reason || typeof reason !== 'string') return { reason: '', card: null };
const parts = reason.trim().split(' ');
let card = null;
let cleanReason = reason.trim();
if (parts[0] && CARD_REGEX.test(parts[0])) {
card = parts[0];
cleanReason = parts.slice(1).join(' ').trim();
}
if (POS_REGEX.test(cleanReason)) {
const posParts = cleanReason.split('<br/>');
try {
const dateTime = posParts[0].split('ПОС ')[1];
cleanReason = `POS PAYMENT ${dateTime}`;
} catch (_) { /* keep original */ }
}
return { reason: cleanReason.replace(/\s+/g, ' ').trim(), card };
}
function generateTags(fields) {
const tags = new Set();
for (const [field, keyword, tagName] of TAG_RULES) {
if ((fields[field] || '').includes(keyword)) {
tags.add(tagName);
}
}
return Array.from(tags);
}
function processRow(row) {
const transactionType = (row[COL.TYPE] || '').trim();
if (transactionType === SKIP_TYPE) return null;
const { reason, card } = processReasonAndCard(row[COL.REASON]);
const payee = (row[COL.PAYEE] || ...
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It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"I'll explore all three reference projects in parallel to understand their structure before planning.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How data flows (ingest, storage, retrieval)\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How file uploads work - what files, what format, how parsed\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth folder and authentik integration","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. What auth system is being used (Authentik)\n2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?\n3. Middleware - how is auth enforced on routes?\n4. Any frontend auth flow - login redirect, token handling, protected routes\n5. Environment variables related to auth\n6. Docker/deployment setup for the auth service itself\n7. Any example of how other apps integrate with this auth\n\nReport with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"payments.js","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"continue","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Launching parallel exploration of all three reference projects.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How data is ingested (look at /ingest route especially)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How file uploads work (what format, what processing happens)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth project structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. What authentication system is used (authentik integration details)\n3. How OAuth/OIDC flow works\n4. Any middleware or helper functions for protecting routes\n5. Session management approach\n6. How frontend handles auth state\n7. Any example of how other apps integrate with this auth system\n8. Docker setup and environment variables\n\nPlease read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now I have a complete picture of all three. Let me design the plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design combined app architecture","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:\n\n---\n\n## App 1: payments-logger (Node.js)\n- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI\n- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS\n- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage\n- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)\n- **Schema** (PostgreSQL via Prisma):\n - `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at\n - `tags` table: id, name, color — M2M with payments via `_PaymentToTag`\n - `users` table: id, username, hashed_password (this will be REMOVED)\n- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system\n- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance\n\n## App 2: dsk-uploader (Python/Flask)\n- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database\n- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5\n- **Auth**: None (open)\n- **CSV format** (DSK Bank Bulgarian format, columns):\n - `Дата` (date, DD.MM.YYYY)\n - `Вид на трансакцията` (transaction type, Bulgarian)\n - `Основание` (reason/description — contains card number regex: `^\\d{6}x{6}\\d{4}$`)\n - `Дебит BGN` (debit amount, may be empty)\n - `Кредит BGN` (credit amount, may be empty)\n - `Наредител/Получател` (orderer/recipient name)\n - `Номер сметка на наредителя / получателя` (account number)\n- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers\n- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)\n\n## App 3: auth (Authentik)\n- **Mode**: Proxy mode via NPM (forward auth)\n- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:\n - `X-authentik-username` \n - `X-authentik-email`\n - `X-authentik-groups`\n- **No code integration needed** in the app itself — just trust these headers from NPM\n- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`\n\n---\n\n## What the New Combined App Must Do\n\n1. **Single PostgreSQL database** for all transactions\n2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST\n3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema\n4. **Unified UI** — show all payments in one table regardless of source\n5. **Source indicator** in UI — badge showing \"INGEST\", \"UPLOAD\", or \"BOTH\" (if duplicate detection added)\n6. **Source filter** in FilterBar — filter by All/Ingest/Upload\n7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM\n8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination\n9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL\n\n---\n\n## Technical Constraints\n\n- Keep Node.js backend (not Python) — extend payments-logger's stack\n- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)\n- File upload: use `multer` npm middleware\n- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)\n- Add `source` enum field (INGEST/UPLOAD) to payments schema\n- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is\n- Remove `users` table from schema\n\n---\n\n## Please Design\n\n1. Complete folder structure for the new app (suggest name: \"finance-hub\" or similar — note this is a placeholder, user will confirm)\n2. Prisma schema with new fields (`source`, `currency`)\n3. All backend API routes\n4. CSV parser design in Node.js (port of the Python logic)\n5. Authentik auth middleware\n6. Frontend component structure (React) — what's reused from payments-logger, what's new\n7. Docker Compose setup\n8. Environment variables needed\n9. Step-by-step implementation order\n10. Verification checklist\n\nBe specific about file paths and code structure. This will be used to write actual implementation code.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good plan. Let me ask the one thing I need before writing the final plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"AskUserQuestion","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"OUT","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"User has answered your questions: \"What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding.\"=\"finance-hub\". You can now continue with the user's answers in mind.","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Writing the final plan now.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"326 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# finance-hub — Implementation Plan\n\n## Context\n\nTwo separate finance apps exist as references and will be retired:\n- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.\n- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.\n\nThe new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).\n\n---\n\n## Tech Stack\n\n| Layer | Choice | Rationale |\n|-------|--------|-----------|\n| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |\n| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |\n| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |\n| Database | PostgreSQL 16 | Same as payments-logger |\n| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |\n| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |\n| Container | Docker Compose | Same pattern as both reference apps |\n\n**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage. \n**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references. \n**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.\n\n---\n\n## Folder Structure\n\n```\n/volume2/docker/finance/finance-hub/\n├── docker-compose.yml\n├── .env\n├── .env.example\n├── .gitignore\n├── backend/\n│ ├── Dockerfile\n│ ├── package.json\n│ ├── prisma/\n│ │ ├── schema.prisma\n│ │ └── migrations/\n│ │ ├── migration_lock.toml\n│ │ └── 20260508_init/\n│ │ └── migration.sql\n│ └── src/\n│ ├── index.js ← entry point (Authentik middleware wired here)\n│ ├── auth.js ← Authentik header middleware (replaces JWT auth)\n│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)\n│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)\n│ └── routes/\n│ ├── payments.js ← existing routes + source/currency additions\n│ └── upload.js ← NEW: POST /api/upload/csv\n└── frontend/\n ├── Dockerfile\n ├── package.json\n ├── vite.config.js\n ├── tailwind.config.js\n ├── postcss.config.js\n ├── index.html\n └── src/\n ├── main.jsx ← remove AuthProvider wrapper\n ├── index.css\n ├── App.jsx ← remove auth state, add Upload tab toggle\n └── components/\n ├── FilterBar.jsx ← add source filter select\n ├── PaymentTable.jsx ← add Source badge column + currency display\n ├── PaymentCard.jsx ← minor source badge addition\n ├── PaymentList.jsx ← unchanged\n └── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI\n```\n\n---\n\n## Database Schema (Prisma)\n\nFile: `backend/prisma/schema.prisma`\n\n```prisma\ngenerator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status { UNPROCESSED SENT SKIPPED }\nenum Source { INGEST UPLOAD }\n```\n\n**Key decisions:**\n- No `User` model — Authentik owns identity.\n- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.\n- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.\n- `balance` is always null for CSV rows (DSK export does not include running balance).\n- Fresh consolidated migration — no data migration from reference apps required.\n\n---\n\n## API Routes\n\n| Method | Path | Auth | Description |\n|--------|------|------|-------------|\n| GET | /api/health | public | Health check |\n| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |\n| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |\n| GET | /api/payments/meta/tags | required | All tags |\n| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |\n| GET | /api/payments/:id | required | Single payment |\n| PATCH | /api/payments/:id | required | Update status |\n| DELETE | /api/payments/:id | required | Delete |\n| POST | /api/payments/:id/send | required | Send notification |\n| POST | /api/payments/:id/skip | required | Skip |\n| POST | /api/payments/:id/tags | required | Add/upsert tag |\n| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |\n| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |\n\n---\n\n## Key Implementation Details\n\n### auth.js (replaces entire old auth module)\n```js\nconst PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n const username = req.headers['x-authentik-username'];\n if (!username) return res.status(401).json({ error: 'Unauthorized' });\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),\n };\n next();\n}\nmodule.exports = { authentikMiddleware };\n```\n\n### csvParser.js (port of dskuploader.py)\n- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8\n- `csv-parse` parses the decoded text with `columns: true`\n- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`\n- Card extraction: regex `/^\\d{6}x{6}\\d{4}$/` on first token of `Основание`\n- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`\n- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`\n- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`\n\n### payments.js changes from payments-logger\n1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call\n2. Add `source` to the `GET /` where clause filter\n3. Add `sources` to `meta/filters` response\n4. Currency-aware amount formatting in notification message\n5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)\n\n### upload.js (new)\n- `multer` memory storage, max 10 files × 10 MB\n- Calls `parseDskCsv(buffer)` per file\n- Upserts tags via `prisma.tag.upsert` then connects\n- Returns `{ imported, skipped, errors, payments[] }`\n\n### Frontend changes\n- **Delete**: `auth.js`, `AuthProvider.jsx`\n- **main.jsx**: Remove `<AuthProvider>` wrapper\n- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add \"Payments\" / \"Upload CSV\" tab toggle\n- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols\n- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell\n- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`\n\n---\n\n## Docker Compose\n\n```yaml\nservices:\n db:\n image: postgres:16-alpine\n environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: ${DB_PASSWORD}, POSTGRES_DB: finance_hub }\n volumes: [pgdata:/var/lib/postgresql/data]\n healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }\n\n backend:\n build: ./backend\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports: [\"${BACKEND_PORT:-3001}:3001\"]\n depends_on: { db: { condition: service_healthy } }\n\n frontend:\n build: ./frontend\n ports: [\"${FRONTEND_PORT:-5175}:5173\"]\n depends_on: [backend]\n\nvolumes: { pgdata: }\n```\n\n**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.\n\n---\n\n## Environment Variables (.env)\n\n```bash\nDB_PASSWORD=change_me\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\nTZ=Europe/Sofia\nBACKEND_PORT=3001\nFRONTEND_PORT=5175\n```\n\nRemoved vs payments-logger: `JWT_SECRET`, `JWT_EXPIRE_MINUTES`.\n\n---\n\n## Implementation Order\n\n1. Create folder structure and write `docker-compose.yml`, `.env.example`, `.gitignore`\n2. Write `backend/prisma/schema.prisma` and migration SQL\n3. Write `backend/package.json` (add `csv-parse`, `iconv-lite`, `multer`; remove `bcryptjs`, `jose`)\n4. Write `backend/Dockerfile`\n5. Write `backend/src/auth.js` (Authentik middleware)\n6. Copy `backend/src/parser.js` verbatim from payments-logger\n7. Write `backend/src/csvParser.js` (Python port)\n8. Write `backend/src/routes/upload.js`\n9. Write `backend/src/routes/payments.js` (from payments-logger + 5 changes listed above)\n10. Write `backend/src/index.js`\n11. Copy frontend base from payments-logger; delete `auth.js` + `AuthProvider.jsx`\n12. Update `main.jsx`, `App.jsx`, `FilterBar.jsx`, `PaymentTable.jsx`\n13. Write `frontend/src/components/UploadPanel.jsx`\n14. Update `frontend/vite.config.js`\n15. `docker compose build && docker compose up -d`\n16. Run verification checklist\n\n---\n\n## Verification\n\n**Schema**\n- `payments` table has `source`, `currency`, `debit_bgn`, `credit_bgn`, `transaction_type`, `payer_account`\n- No `users` table; `Source` enum exists\n\n**Auth**\n- `GET /api/payments` → 401 without `x-authentik-username` header\n- `POST /api/payments/ingest` → 201 without any header\n- `curl -H \"x-authentik-username: test\" localhost:3001/api/payments` → 200\n\n**SMS Ingest**\n- DSK POS SMS → `source=INGEST`, `currency=EUR`, correct amount/card/recipient\n- Apple Wallet structured body → `type=WALLET`, `source=INGEST`\n- Rate limiter → 429 after 200 req/min\n\n**CSV Upload**\n- Single DSK CSV → rows with `source=UPLOAD`, `currency=BGN`\n- Multiple CSVs in one request → all merged\n- `ТРАНСФЕР СОБСТВЕНИ СМЕТКИ` rows counted in `skipped`, not imported\n- Card regex match from `Основание` column\n- Auto-tags applied (ЗАПЛАТА→Salary, LIDL→Groceries)\n- cp1251 file imports correctly\n\n**UI**\n- Source badge visible in payment table (SMS indigo, CSV emerald)\n- Source dropdown in FilterBar filters correctly\n- Amount shows correct currency per row\n- Upload Panel: drag-and-drop works, result summary shows counts\n- Logout redirects to Authentik sign_out\n- No login form shown (Authentik handles it at NPM level)\n- Tags, send, skip, delete all still work\n\n## Reference Files\n\n- `/volume2/docker/finance/payments-logger/backend/src/routes/payments.js`\n- `/volume2/docker/finance/payments-logger/backend/src/parser.js`\n- `/volume2/docker/finance/payments-logger/backend/src/index.js`\n- `/volume2/docker/finance/payments-logger/backend/src/auth.js`\n- `/volume2/docker/finance/payments-logger/backend/prisma/schema.prisma`\n- `/volume2/docker/finance/payments-logger/frontend/src/App.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/PaymentTable.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/FilterBar.jsx`\n- `/volume2/docker/finance/dsk-uploader/dskuploader.py`\n- `/volume2/docker/finance/auth/docker-compose.yml`","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Claude’s Plan","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Stayed in plan mode","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good question. Here's the full breakdown:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Backend Tech Stack — Options","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Backend Tech Stack — Options","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Why:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"payments-logger is already Node.js/Express/Prisma. The new app is 80% payments-logger with CSV upload added on top. Keeping the same stack means:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"verbatim, zero rewrite","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy the entire","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"routes/payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with minimal edits","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Same Prisma schema workflow, same migrations, same Docker image","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The CSV parsing logic (the only Python-specific thing) ports cleanly to","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"csv-parse","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— it's just regex + string manipulation, nothing pandas-specific","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Trade-off:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Have to port the Python CSV parsing to JS. It's ~150 lines and mostly string manipulation — straightforward.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option B: Python + FastAPI + SQLAlchemy","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option B: Python + FastAPI + SQLAlchemy","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rewrite everything in Python. dsk-uploader is Python, so CSV parsing is already done.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep the dsk-uploader CSV logic as-is (no porting). Python has better data science libraries if you later add analytics.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Lose the entire payments-logger backend (routes, parser, Prisma schema) — full rewrite. FastAPI + SQLAlchemy is a different mental model than Express + Prisma. Frontend stays React anyway, so the stack split doesn't simplify anything.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"More work overall, gains almost nothing.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep Node.js as the main API, add a separate Python FastAPI service just for CSV parsing. They share the DB.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Zero porting — Python CSV code used as-is.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two backend services to maintain, deploy, and keep in sync. Inter-service HTTP calls. Two Dockerfiles. For ~150 lines of CSV logic, this is massively over-engineered.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Not worth it.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Extend dsk-uploader into a full payments app.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pandas for CSV, no porting.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Jinja2 templates instead of React (or add React separately). Would need to reimplement the entire payments-logger (SMS parser, notification system, tag management, pagination/filtering). Flask's Jinja templating is far less capable than the existing React UI. The React frontend is the stronger UI foundation.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Worst of all options — rebuild the harder parts (UI, SMS parser, notification) for no gain.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Summary","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Summary","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"CSV porting effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"App rewrite effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Result 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Everything else in the plan reuses payments-logger code directly. That's why Node.js is the clear winner here.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Want to adjust the stack, or shall I proceed with Option A?","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ok sounds good. Implement all you suggested","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Starting implementation. Let me first read all the reference files I'll need to copy from.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"payments.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"App.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"App.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"FilterBar.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"FilterBar.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentTable.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentTable.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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payments-logger.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.css","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.css","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"vite.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"vite.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"tailwind.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"tailwind.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"postcss.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"postcss.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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components.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentCard.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentCard.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentList.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentList.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"schema.prisma","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"schema.prisma","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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Let me set up the todo list and start building.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create finance-hub directory structure","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"mkdir -p /volume2/docker/finance/finance-hub/backend/src/routes \\\n /volume2/docker/finance/finance-hub/backend/prisma/migrations/20260508_init \\\n /volume2/docker/finance/finance-hub/frontend/src/components && echo \"done\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":24,"on_screen":false,"help_text":"Copy code","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"OUT","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"done","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"docker-compose.yml","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"docker-compose.yml","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"45 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"version: '3.8'\n\nservices:\n db:\n image: postgres:16-alpine\n restart: unless-stopped\n environment:\n POSTGRES_USER: finance\n POSTGRES_PASSWORD: ${DB_PASSWORD}\n POSTGRES_DB: finance_hub\n volumes:\n - pgdata:/var/lib/postgresql/data\n healthcheck:\n test: [\"CMD-SHELL\", \"pg_isready -U finance -d finance_hub\"]\n interval: 5s\n timeout: 5s\n retries: 5\n\n backend:\n build: ./backend\n restart: unless-stopped\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports:\n - \"${BACKEND_PORT:-3001}:3001\"\n depends_on:\n db:\n condition: service_healthy\n\n frontend:\n build: ./frontend\n restart: unless-stopped\n ports:\n - \"${FRONTEND_PORT:-5175}:5173\"\n depends_on:\n - backend\n\nvolumes:\n pgdata:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".env.example","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".env.example","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"15 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Database\nDB_PASSWORD=change_me_strong_password\n\n# Notifier service (for SMS payment notifications)\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\n\n# Timezone (used by SMS parser for Bulgarian bank timestamps)\nTZ=Europe/Sofia\n\n# Ports (optional — defaults shown)\nBACKEND_PORT=3001\nFRONTEND_PORT=5175","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".gitignore","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".gitignore","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"5 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env\nnode_modules/\ndist/\n*.log","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"schema.prisma","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"schema.prisma","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"54 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"generator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status {\n UNPROCESSED\n SENT\n SKIPPED\n}\n\nenum Source {\n INGEST\n UPLOAD\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration.sql","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration.sql","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"55 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- CreateEnum\nCREATE TYPE \"Status\" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');\nCREATE TYPE \"Source\" AS ENUM ('INGEST', 'UPLOAD');\n\n-- CreateTable\nCREATE TABLE \"payments\" (\n \"id\" SERIAL PRIMARY KEY,\n \"raw_message\" TEXT NOT NULL,\n \"date\" TIMESTAMP(3),\n \"type\" TEXT,\n \"card\" TEXT,\n \"recipient\" TEXT,\n \"amount\" DOUBLE PRECISION,\n \"currency\" TEXT DEFAULT 'EUR',\n \"balance\" DOUBLE PRECISION,\n \"source\" \"Source\" NOT NULL DEFAULT 'INGEST',\n \"status\" \"Status\" NOT NULL DEFAULT 'UNPROCESSED',\n \"notified_at\" TIMESTAMP(3),\n \"notify_phone\" TEXT,\n \"debit_bgn\" DOUBLE PRECISION,\n \"credit_bgn\" DOUBLE PRECISION,\n \"transaction_type\" TEXT,\n \"payer_account\" TEXT,\n \"created_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,\n \"updated_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP\n);\n\n-- CreateTable\nCREATE TABLE \"tags\" (\n \"id\" SERIAL PRIMARY KEY,\n \"name\" TEXT NOT NULL,\n \"color\" TEXT NOT NULL DEFAULT '#6b7280'\n);\n\n-- CreateUniqueIndex\nCREATE UNIQUE INDEX \"tags_name_key\" ON \"tags\"(\"name\");\n\n-- CreateTable (M2M join)\nCREATE TABLE \"_PaymentToTag\" (\n \"A\" INTEGER NOT NULL,\n \"B\" INTEGER NOT NULL,\n CONSTRAINT \"_PaymentToTag_AB_pkey\" PRIMARY KEY (\"A\", \"B\")\n);\n\nCREATE INDEX \"_PaymentToTag_B_index\" ON \"_PaymentToTag\"(\"B\");\n\n-- AddForeignKey\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_A_fkey\"\n FOREIGN KEY (\"A\") REFERENCES \"payments\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;\n\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_B_fkey\"\n FOREIGN KEY (\"B\") REFERENCES \"tags\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration_lock.toml","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration_lock.toml","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"4 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Please do not edit this file manually\n# It should be added in your version-control system (e.g., Git)\nprovider = \"postgresql\"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"26 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"{\n \"name\": \"finance-hub-backend\",\n \"version\": \"1.0.0\",\n \"main\": \"src/index.js\",\n \"scripts\": {\n \"start\": \"node src/index.js\",\n \"dev\": \"nodemon src/index.js\",\n \"prisma:generate\": \"prisma generate\",\n \"prisma:migrate\": \"prisma migrate deploy\"\n },\n \"dependencies\": {\n \"@prisma/client\": \"^5.22.0\",\n \"cors\": \"^2.8.5\",\n \"csv-parse\": \"^5.5.6\",\n \"express\": \"^4.21.1\",\n \"express-rate-limit\": \"^7.4.0\",\n \"iconv-lite\": \"^0.6.3\",\n \"morgan\": \"^1.10.0\",\n \"multer\": \"^1.4.5-lts.1\"\n },\n \"devDependencies\": {\n \"nodemon\": \"^3.1.7\",\n \"prisma\": \"^5.22.0\"\n }\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"18 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"FROM node:20-alpine\n\nRUN apk add --no-cache openssl\n\nWORKDIR /app\n\nCOPY package.json package-lock.json* ./\nRUN npm install\n\nCOPY prisma ./prisma\nRUN npx prisma generate\n\nCOPY src ./src\n\nEXPOSE 3001\n\nCMD [\"sh\", \"-c\", \"npx prisma migrate deploy && node src/index.js\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"auth.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"auth.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"27 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const PUBLIC_PATHS = new Set([\n '/api/health',\n '/api/payments/ingest',\n]);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n\n const username = req.headers['x-authentik-username'];\n if (!username) {\n return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });\n }\n\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '')\n .split(',')\n .map(g => g.trim())\n .filter(Boolean),\n };\n\n next();\n}\n\nmodule.exports = { authentikMiddleware };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"104 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/**\n * Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)\n *\n * Supported formats:\n *\n * POS / INTERNET / ECOM / P2P payment:\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.\n *\n * ATM withdrawal:\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.\n *\n * ATM utility payment (amount may include fee as AMOUNT/FEE):\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.\n */\n\nconst LOCAL_TZ = process.env.TZ || 'Europe/Sofia';\n\n/**\n * Convert a local-timezone date/time to a UTC Date object.\n * Uses Intl to resolve the actual UTC offset (DST-aware).\n */\nfunction localToUtc(year, month, day, hour, minute) {\n const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));\n\n const formatter = new Intl.DateTimeFormat('en-US', {\n timeZone: LOCAL_TZ,\n year: 'numeric', month: '2-digit', day: '2-digit',\n hour: '2-digit', minute: '2-digit', second: '2-digit',\n hour12: false,\n });\n\n const parts = {};\n formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });\n\n const localAtNaive = new Date(Date.UTC(\n parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),\n parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),\n ));\n\n const offsetMs = localAtNaive.getTime() - naive.getTime();\n return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);\n}\n\nfunction parsePaymentSms(message) {\n const result = {\n rawMessage: message,\n date: null,\n type: null,\n card: null,\n recipient: null,\n amount: null,\n balance: null,\n };\n\n // Date and time: \"Na DD/MM/YYYY v HH:MM\"\n const dateMatch = message.match(/Na (\\d{2})\\/(\\d{2})\\/(\\d{4}) v (\\d{2}):(\\d{2})/i);\n if (dateMatch) {\n const [, day, month, year, hour, minute] = dateMatch;\n result.date = localToUtc(\n parseInt(year), parseInt(month), parseInt(day),\n parseInt(hour), parseInt(minute),\n );\n }\n\n // Card mask: \"s karta 400915***4447\" or \"s karta 483890***7162\"\n const cardMatch = message.match(/s karta\\s+([\\d*]+)/i);\n if (cardMatch) {\n result.card = cardMatch[1];\n }\n\n // Transaction type: supports both prepositions\n // \"na POS\" / \"na ATM\" / \"na INTERNET\" etc. (payment)\n // \"ot ATM\" (withdrawal)\n const typeMatch = message.match(/(?:na|ot)\\s+(POS|ATM|INTERNET|ECOM|P2P)\\b/i);\n if (typeMatch) {\n result.type = typeMatch[1].toUpperCase();\n }\n\n // Recipient address: \"s adres: MERCHANT\" or \"s adres:MERCHANT\" (no space variant)\n const recipientMatch = message.match(/s adres:\\s*([^.]+)\\./i);\n if (recipientMatch) {\n result.recipient = recipientMatch[1].trim();\n }\n\n // Amount: handles both verbs and the AMOUNT/FEE suffix format\n // \"sa plateni 7.78 EUR\"\n // \"sa iztegleni 400.00 EUR\"\n // \"sa plateni 0.50 EUR/0.50 EUR\" → captures 0.50 (the charged amount, ignoring fee)\n const amountMatch = message.match(/sa (?:plateni|iztegleni)\\s+([\\d.,]+)\\s+[A-Z]{3}/i);\n if (amountMatch) {\n result.amount = parseFloat(amountMatch[1].replace(',', '.'));\n }\n\n // Balance: \"Nalichni: 2583.07 EUR.\"\n const balanceMatch = message.match(/Nalichni:\\s*([\\d.,]+)\\s+[A-Z]{3}/i);\n if (balanceMatch) {\n result.balance = parseFloat(balanceMatch[1].replace(',', '.'));\n }\n\n return result;\n}\n\nmodule.exports = { parsePaymentSms };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"csvParser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"csvParser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"175 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/**\n * DSK Bank CSV parser — Node.js port of dskuploader.py\n *\n * DSK Bank exports use Windows-1251 (cp1251) encoding.\n * Each row maps to a Payment record with source=UPLOAD, currency=BGN.\n */\n\nconst { parse } = require('csv-parse');\nconst iconv = require('iconv-lite');\n\nconst SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';\nconst CARD_REGEX = /^\\d{6}x{6}\\d{4}$/;\nconst POS_REGEX = /^\\s*ПЛАЩАНЕ\\s+НА\\s+ПОС\\s+\\d{2}\\.\\d{2}\\.\\d{4}\\s+\\d{2}:\\d{2}/;\n\nconst COL = {\n DATE: 'Дата',\n TYPE: 'Вид на трансакцията',\n REASON: 'Основание',\n DEBIT: 'Дебит BGN',\n CREDIT: 'Кредит BGN',\n PAYEE: 'Наредител/Получател',\n ACCT: 'Номер сметка на наредителя / получателя',\n};\n\nconst TAG_RULES = [\n ['reason', 'ЗАПЛАТА', 'Salary'],\n ['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],\n ['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],\n ['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],\n ['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],\n ['payee', 'VIVACOM', 'Subscriptions'],\n ['payee', 'Google', 'Subscriptions'],\n ['payee', 'SkyShowtime', 'Subscriptions'],\n ['payee', 'NETFLIX', 'Subscriptions'],\n ['payee', 'LUKOIL', 'Bills'],\n ['payee', 'CityGate', 'Bills'],\n ['payee', 'CBA', 'Groceries'],\n ['payee', 'FANTASTICO', 'Groceries'],\n ['payee', 'LIDL', 'Groceries'],\n];\n\nfunction parseNum(val) {\n if (val == null || val === '') return null;\n if (typeof val === 'number') return isNaN(val) ? null : val;\n const s = String(val).trim().replace(/\\xa0/g, '').replace(/ /g, '').replace(',', '.');\n const n = parseFloat(s);\n return isNaN(n) ? null : n;\n}\n\nfunction parseDate(val) {\n if (!val) return null;\n const s = String(val).trim();\n const m = s.match(/^(\\d{2})\\.(\\d{2})\\.(\\d{4})$/);\n if (m) {\n return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));\n }\n return null;\n}\n\nfunction processReasonAndCard(reason) {\n if (!reason || typeof reason !== 'string') return { reason: '', card: null };\n\n const parts = reason.trim().split(' ');\n let card = null;\n let cleanReason = reason.trim();\n\n if (parts[0] && CARD_REGEX.test(parts[0])) {\n card = parts[0];\n cleanReason = parts.slice(1).join(' ').trim();\n }\n\n if (POS_REGEX.test(cleanReason)) {\n const posParts = cleanReason.split('<br/>');\n try {\n const dateTime = posParts[0].split('ПОС ')[1];\n cleanReason = `POS PAYMENT ${dateTime}`;\n } catch (_) { /* keep original */ }\n }\n\n return { reason: cleanReason.replace(/\\s+/g, ' ').trim(), card };\n}\n\nfunction generateTags(fields) {\n const tags = new Set();\n for (const [field, keyword, tagName] of TAG_RULES) {\n if ((fields[field] || '').includes(keyword)) {\n tags.add(tagName);\n }\n }\n return Array.from(tags);\n}\n\nfunction processRow(row) {\n const transactionType = (row[COL.TYPE] || '').trim();\n if (transactionType === SKIP_TYPE) return null;\n\n const { reason, card } = processReasonAndCard(row[COL.REASON]);\n const payee = (row[COL.PAYEE] || '').trim();\n const payerAccount = (row[COL.ACCT] || '').trim();\n const debitBgn = parseNum(row[COL.DEBIT]);\n const creditBgn = parseNum(row[COL.CREDIT]);\n const date = parseDate(row[COL.DATE]);\n\n const autoTags = generateTags({ reason, transactionType, payee, debitBgn, creditBgn });\n\n const amount = debitBgn ?? creditBgn ?? null;\n\n const rawMessage = [\n row[COL.DATE] && `Date: ${row[COL.DATE]}`,\n transactionType && `Type: ${transactionType}`,\n payee && `Payee: ${payee}`,\n debitBgn != null && `Debit: ${debitBgn} BGN`,\n creditBgn != null && `Credit: ${creditBgn} BGN`,\n ].filter(Boolean).join(' | ');\n\n return {\n rawMessage,\n date,\n type: null,\n card,\n recipient: payee || null,\n amount,\n currency: 'BGN',\n balance: null,\n source: 'UPLOAD',\n debitBgn,\n creditBgn,\n transactionType: transactionType || null,\n payerAccount: payerAccount || null,\n autoTags,\n };\n}\n\n/**\n * Parse a Buffer containing a DSK Bank CSV (cp1251 or UTF-8).\n * Returns { rows, skipped, errors }.\n */\nasync function parseDskCsv(buffer) {\n // Try cp1251 first (DSK Bank export encoding), fall back to UTF-8\n let text = iconv.decode(buffer, 'cp1251');\n if (!text.includes(COL.DATE)) {\n text = buffer.toString('utf-8');\n }\n\n return new Promise((resolve, reject) => {\n const rows = [];\n const errors = [];\n let skipped = 0;\n\n const parser = parse(text, {\n columns: true,\n skip_empty_lines: true,\n trim: true,\n relax_column_count: true,\n });\n\n parser.on('readable', () => {\n let record;\n while ((record = parser.read()) !== null) {\n try {\n const row = processRow(record);\n if (row === null) { skipped++; } else { rows.push(row); }\n } catch (err) {\n errors.push(err.message);\n }\n }\n });\n\n parser.on('error', reject);\n parser.on('end', () => resolve({ rows, skipped, errors }));\n });\n}\n\nmodule.exports = { parseDskCsv };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"39 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst cors = require('cors');\nconst morgan = require('morgan');\nconst rateLimit = require('express-rate-limit');\nconst { authentikMiddleware } = require('./auth');\nconst paymentsRouter = require('./routes/payments');\nconst uploadRouter = require('./routes/upload');\n\nconst app = express();\nconst PORT = process.env.PORT || 3001;\n\napp.use(cors());\napp.use(express.json({ limit: '16kb' }));\napp.use(morgan('combined'));\n\n// Rate-limit the public ingest endpoint before auth middleware\nconst ingestLimiter = rateLimit({\n windowMs: 60 * 1000,\n max: 200,\n standardHeaders: true,\n legacyHeaders: false,\n message: { error: 'Too many requests, slow down' },\n});\napp.use('/api/payments/ingest', ingestLimiter);\n\n// Authentik header auth (skips /api/health and /api/payments/ingest)\napp.use(authentikMiddleware);\n\napp.get('/api/health', (_req, res) => {\n res.json({ status: 'ok', timestamp: new Date().toISOString() });\n});\n\napp.use('/api/payments', paymentsRouter);\napp.use('/api/upload', uploadRouter);\n\napp.listen(PORT, '0.0.0.0', () => {\n console.log(`Finance Hub API running on port ${PORT}`);\n});","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"payments.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"399 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst { PrismaClient } = require('@prisma/client');\nconst { parsePaymentSms } = require('../parser');\n\nconst router = express.Router();\nconst prisma = new PrismaClient();\n\nconst NOTIFIER_URL = process.env.NOTIFIER_URL;\nconst NOTIFIER_CHANNEL = process.env.NOTIFIER_CHANNEL || 'viber';\nconst DEFAULT_PHONE = process.env.NOTIFY_DEFAULT_PHONE;\n\n// ── Helpers ───────────────────────────────────────────────────────────────────\n\nfunction parseId(raw) {\n const id = parseInt(raw, 10);\n return Number.isFinite(id) ? id : null;\n}\n\nfunction formatNotifyMessage(payment) {\n const currency = payment.currency || 'EUR';\n const parts = [];\n if (payment.amount != null) parts.push(`Amount: ${payment.amount.toFixed(2)} ${currency}`);\n if (payment.recipient) parts.push(`At: ${payment.recipient}`);\n if (payment.balance != null) parts.push(`Balance: ${payment.balance.toFixed(2)} ${currency}`);\n if (payment.date) parts.push(`Date: ${new Date(payment.date).toLocaleString('en-GB')}`);\n return parts.join('\\n');\n}\n\nasync function sendNotification(payment) {\n if (!NOTIFIER_URL) {\n console.warn('[NOTIFY] NOTIFIER_URL not set — skipping notification');\n return;\n }\n\n const phone = payment.notifyPhone || DEFAULT_PHONE;\n if (!phone) {\n console.warn('[NOTIFY] No phone number for payment #' + payment.id + ' and NOTIFY_DEFAULT_PHONE not set');\n return;\n }\n\n const body = {\n phone,\n notification: NOTIFIER_CHANNEL,\n message: formatNotifyMessage(payment),\n };\n\n const res = await fetch(NOTIFIER_URL, {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify(body),\n });\n\n if (!res.ok) {\n const text = await res.text().catch(() => '');\n throw new Error(`Notifier responded ${res.status}: ${text}`);\n }\n}\n\n// ── Ingest a payment (public — no auth) ──────────────────────────────────────\n//\n// Two modes:\n//\n// SMS mode (default):\n// { \"message\": \"<raw SMS text>\", \"notifyPhone\": \"...\" }\n//\n// Structured mode (Apple Wallet / manual):\n// { \"ingestMode\": \"apple_wallet\", \"amount\": 7.78, \"recipient\": \"Apple Store\",\n// \"type\": \"WALLET\", \"card\": \"••••4447\", \"date\": \"2026-02-22T10:30:00Z\" }\n//\nrouter.post('/ingest', async (req, res) => {\n try {\n const { message, notifyPhone, ingestMode } = req.body;\n\n let data;\n\n if (ingestMode === 'apple_wallet' || (!message && req.body.amount != null)) {\n // ── Structured / Apple Wallet mode ──────────────────────────────────────\n const { amount, recipient, type, card, date, balance } = req.body;\n if (amount == null || !recipient) {\n return res.status(400).json({ error: 'amount and recipient are required for structured ingest' });\n }\n\n const rawMessage = [\n `Source: ${ingestMode || 'structured'}`,\n `Amount: ${amount}`,\n recipient && `Recipient: ${recipient}`,\n type && `Type: ${type}`,\n card && `Card: ${card}`,\n ].filter(Boolean).join(' | ');\n\n data = {\n rawMessage,\n date: date ? new Date(date) : new Date(),\n type: type || 'WALLET',\n card: card || null,\n recipient,\n amount: parseFloat(amount),\n currency: 'EUR',\n balance: balance != null ? parseFloat(balance) : null,\n source: 'INGEST',\n notifyPhone: notifyPhone || null,\n };\n\n } else {\n // ── SMS mode ─────────────────────────────────────────────────────────────\n if (!message) {\n return res.status(400).json({ error: 'message is required' });\n }\n if (typeof message !== 'string' || message.length > 2000) {\n return res.status(400).json({ error: 'message must be a string under 2000 characters' });\n }\n\n const parsed = parsePaymentSms(message);\n data = {\n rawMessage: parsed.rawMessage,\n date: parsed.date,\n type: parsed.type,\n card: parsed.card,\n recipient: parsed.recipient,\n amount: parsed.amount,\n currency: 'EUR',\n balance: parsed.balance,\n source: 'INGEST',\n notifyPhone: notifyPhone || null,\n };\n }\n\n const payment = await prisma.payment.create({\n data,\n include: { tags: true },\n });\n\n res.status(201).json(payment);\n } catch (err) {\n console.error('Ingest error:', err);\n res.status(500).json({ error: 'Failed to ingest payment' });\n }\n});\n\n// ── List payments with filtering ──────────────────────────────────────────────\nrouter.get('/', async (req, res) => {\n try {\n const {\n status,\n type,\n tag,\n source,\n recipient,\n dateFrom,\n dateTo,\n search,\n sortBy = 'createdAt',\n sortDir = 'desc',\n page = 1,\n } = req.query;\n\n const limit = Math.min(parseInt(req.query.limit, 10) || 50, 200);\n\n const where = {};\n\n if (status) where.status = status;\n if (type) where.type = type;\n if (source) where.source = source;\n if (recipient) where.recipient = { contains: recipient, mode: 'insensitive' };\n if (tag) where.tags = { some: { name: tag } };\n if (search) {\n where.OR = [\n { rawMessage: { contains: search, mode: 'insensitive' } },\n { recipient: { contains: search, mode: 'insensitive' } },\n ];\n }\n if (dateFrom || dateTo) {\n where.date = {};\n if (dateFrom) where.date.gte = new Date(dateFrom);\n if (dateTo) where.date.lte = new Date(dateTo);\n }\n\n const allowedSortFields = ['date', 'amount', 'balance', 'recipient', 'type', 'source', 'createdAt', 'status'];\n const orderField = allowedSortFields.includes(sortBy) ? sortBy : 'createdAt';\n const orderDir = sortDir === 'asc' ? 'asc' : 'desc';\n\n const skip = (parseInt(page, 10) - 1) * limit;\n\n const [payments, total] = await Promise.all([\n prisma.payment.findMany({\n where,\n include: { tags: true },\n orderBy: { [orderField]: orderDir },\n skip,\n take: limit,\n }),\n prisma.payment.count({ where }),\n ]);\n\n res.json({ payments, total, page: parseInt(page, 10), limit });\n } catch (err) {\n console.error('List error:', err);\n res.status(500).json({ error: 'Failed to list payments' });\n }\n});\n\n// ── Get filter options ────────────────────────────────────────────────────────\nrouter.get('/meta/filters', async (_req, res) => {\n try {\n const [types, recipients, tags, sources] = await Promise.all([\n prisma.payment.findMany({ distinct: ['type'], select: { type: true }, where: { type: { not: null } } }),\n prisma.payment.findMany({ distinct: ['recipient'], select: { recipient: true }, where: { recipient: { not: null } } }),\n prisma.tag.findMany({ orderBy: { name: 'asc' } }),\n prisma.payment.findMany({ distinct: ['source'], select: { source: true } }),\n ]);\n\n res.json({\n types: types.map(t => t.type),\n recipients: recipients.map(r => r.recipient),\n tags,\n sources: sources.map(s => s.source),\n });\n } catch (err) {\n res.status(500).json({ error: 'Failed to get filters' });\n }\n});\n\n// ── Get all tags ──────────────────────────────────────────────────────────────\nrouter.get('/meta/tags', async (_req, res) => {\n try {\n const tags = await prisma.tag.findMany({ orderBy: { name: 'asc' } });\n res.json(tags);\n } catch (err) {\n res.status(500).json({ error: 'Failed to list tags' });\n }\n});\n\n// ── Get single payment ────────────────────────────────────────────────────────\nrouter.get('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({\n where: { id },\n include: { tags: true },\n });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n res.json(payment);\n } catch (err) {\n console.error('Get error:', err);\n res.status(500).json({ error: 'Failed to get payment' });\n }\n});\n\n// ── Update payment metadata (status) ─────────────────────────────────────────\nrouter.patch('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const { status } = req.body;\n const data = {};\n\n if (status) {\n const validStatuses = ['UNPROCESSED', 'SENT', 'SKIPPED'];\n if (!validStatuses.includes(status)) {\n return res.status(400).json({ error: `Invalid status. Must be one of: ${validStatuses.join(', ')}` });\n }\n data.status = status;\n }\n\n if (Object.keys(data).length === 0) {\n return res.status(400).json({ error: 'No valid fields to update' });\n }\n\n const updated = await prisma.payment.update({\n where: { id },\n data,\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n if (err.code === 'P2025') return res.status(404).json({ error: 'Not found' });\n console.error('Update error:', err);\n res.status(500).json({ error: 'Failed to update payment' });\n }\n});\n\n// ── Delete payment ───────────────────────────────────────────────────────────\nrouter.delete('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n await prisma.payment.delete({ where: { id } });\n res.json({ success: true });\n } catch (err) {\n if (err.code === 'P2025') return res.status(404).json({ error: 'Not found' });\n console.error('Delete error:', err);\n res.status(500).json({ error: 'Failed to delete payment' });\n }\n});\n\n// ── Send notification (mark as SENT + call notifier service) ─────────────────\nrouter.post('/:id/send', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({ where: { id } });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n if (payment.status !== 'UNPROCESSED') {\n return res.status(409).json({ error: `Payment is already ${payment.status.toLowerCase()}` });\n }\n\n await sendNotification(payment);\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { status: 'SENT', notifiedAt: new Date() },\n include: { tags: true },\n });\n\n res.json(updated);\n } catch (err) {\n console.error('Send error:', err);\n res.status(500).json({ error: 'Failed to send notification' });\n }\n});\n\n// ── Skip notification (mark as SKIPPED) ──────────────────────────────────────\nrouter.post('/:id/skip', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({ where: { id } });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n if (payment.status !== 'UNPROCESSED') {\n return res.status(409).json({ error: `Payment is already ${payment.status.toLowerCase()}` });\n }\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { status: 'SKIPPED' },\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n console.error('Skip error:', err);\n res.status(500).json({ error: 'Failed to skip payment' });\n }\n});\n\n// ── Add tag to payment ────────────────────────────────────────────────────────\nrouter.post('/:id/tags', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const { name, color } = req.body;\n if (!name) return res.status(400).json({ error: 'tag name is required' });\n\n const tag = await prisma.tag.upsert({\n where: { name },\n update: {},\n create: { name, color: color || '#6b7280' },\n });\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { tags: { connect: { id: tag.id } } },\n include: { tags: true },\n });\n\n res.json(updated);\n } catch (err) {\n console.error('Tag error:', err);\n res.status(500).json({ error: 'Failed to add tag' });\n }\n});\n\n// ── Remove tag from payment ───────────────────────────────────────────────────\nrouter.delete('/:id/tags/:tagId', async (req, res) => {\n const id = parseId(req.params.id);\n const tagId = parseId(req.params.tagId);\n if (id === null || tagId === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const updated = await prisma.payment.update({\n where: { id },\n data: { tags: { disconnect: { id: tagId } } },\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n console.error('Remove tag error:', err);\n res.status(500).json({ error: 'Failed to remove tag' });\n }\n});\n\nmodule.exports = router;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"upload.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"upload.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"89 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst multer = require('multer');\nconst { PrismaClient } = require('@prisma/client');\nconst { parseDskCsv } = require('../csvParser');\n\nconst router = express.Router();\nconst prisma = new PrismaClient();\n\nconst upload = multer({\n storage: multer.memoryStorage(),\n limits: { fileSize: 10 * 1024 * 1024, files: 10 },\n fileFilter: (_req, file, cb) => {\n if (file.mimetype === 'text/csv' || file.originalname.toLowerCase().endsWith('.csv')) {\n cb(null, true);\n } else {\n cb(new Error('Only CSV files are accepted'));\n }\n },\n});\n\n// POST /api/upload/csv\n// Accepts 1-10 CSV files, parses them, stores to DB with source=UPLOAD.\n// Returns { imported, skipped, errors, payments[] }\nrouter.post('/csv', upload.array('files', 10), async (req, res) => {\n if (!req.files || req.files.length === 0) {\n return res.status(400).json({ error: 'No files uploaded' });\n }\n\n const allRows = [];\n const allErrors = [];\n let totalSkipped = 0;\n\n for (const file of req.files) {\n try {\n const { rows, skipped, errors } = await parseDskCsv(file.buffer);\n allRows.push(...rows);\n totalSkipped += skipped;\n allErrors.push(...errors.map(e => `${file.originalname}: ${e}`));\n } catch (err) {\n allErrors.push(`${file.originalname}: ${err.message}`);\n }\n }\n\n if (allRows.length === 0) {\n return res.status(422).json({\n error: 'No importable rows found',\n skipped: totalSkipped,\n errors: allErrors,\n });\n }\n\n const created = [];\n\n for (const row of allRows) {\n const { autoTags, ...paymentData } = row;\n try {\n const tagConnects = [];\n for (const tagName of autoTags) {\n const tag = await prisma.tag.upsert({\n where: { name: tagName },\n update: {},\n create: { name: tagName, color: '#6b7280' },\n });\n tagConnects.push({ id: tag.id });\n }\n\n const payment = await prisma.payment.create({\n data: {\n ...paymentData,\n ...(tagConnects.length ? { tags: { connect: tagConnects } } : {}),\n },\n include: { tags: true },\n });\n created.push(payment);\n } catch (err) {\n allErrors.push(`Row insert failed: ${err.message}`);\n }\n }\n\n res.status(201).json({\n imported: created.length,\n skipped: totalSkipped,\n errors: allErrors,\n payments: created,\n });\n});\n\nmodule.exports = router;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now writing all frontend config files:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"24 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"{\n \"name\": \"finance-hub-frontend\",\n \"version\": \"1.0.0\",\n \"type\": \"module\",\n \"scripts\": {\n \"dev\": \"vite\",\n \"build\": \"vite build\",\n \"preview\": \"vite preview\"\n },\n \"dependencies\": {\n \"lucide-react\": \"^0.460.0\",\n \"react\": \"^18.3.1\",\n \"react-dom\": \"^18.3.1\"\n },\n \"devDependencies\": {\n \"@types/react\": \"^18.3.12\",\n \"@vitejs/plugin-react\": \"^4.3.4\",\n \"autoprefixer\": \"^10.4.20\",\n \"postcss\": \"^8.4.49\",\n \"tailwindcss\": \"^3.4.15\",\n \"vite\": \"^6.0.1\"\n }\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"FROM node:20-alpine\n\nWORKDIR /app\n\nCOPY package.json package-lock.json* ./\nRUN npm install\n\nCOPY . .\n\nEXPOSE 5173\n\nCMD [\"npm\", \"run\", \"dev\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"vite.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"vite.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"18 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import { defineConfig } from 'vite';\nimport react from '@vitejs/plugin-react';\n\nexport default defineConfig({\n plugins: [react()],\n server: {\n host: '0.0.0.0',\n port: 5173,\n allowedHosts: ['finance-hub.lakylak.xyz'],\n proxy: {\n '/api': {\n target: 'http://backend:3001',\n changeOrigin: true,\n },\n },\n },\n});","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"tailwind.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"tailwind.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"12 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/** @type {import('tailwindcss').Config} */\nexport default {\n content: [\n \"./index.html\",\n \"./src/**/*.{js,ts,jsx,tsx}\",\n ],\n theme: {\n extend: {},\n },\n plugins: [],\n};","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"postcss.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"postcss.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"7 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"export default {\n plugins: {\n tailwindcss: {},\n autoprefixer: {},\n },\n};","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.html","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.html","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"14 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"<!DOCTYPE html>\n<html lang=\"en\">\n <head>\n <meta charset=\"UTF-8\" />\n <meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\" />\n <title>Finance Hub</title>\n <link rel=\"icon\" type=\"image/svg+xml\" href=\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 100 100'><text y='.9em' font-size='90'>💰</text></svg>\" />\n </head>\n <body class=\"bg-gray-50 min-h-screen\">\n <div id=\"root\"></div>\n <script type=\"module\" src=\"/src/main.jsx\"></script>\n </body>\n</html>","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.css","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.css","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"4 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"@tailwind base;\n@tailwind components;\n@tailwind utilities;","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now writing all React components:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"11 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React from 'react';\nimport ReactDOM from 'react-dom/client';\nimport App from './App';\nimport './index.css';\n\nReactDOM.createRoot(document.getElementById('root')).render(\n <React.StrictMode>\n <App />\n </React.StrictMode>\n);","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"App.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"App.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"257 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState, useEffect, useCallback } from 'react';\nimport { LayoutDashboard, Upload, RefreshCw, LogOut } from 'lucide-react';\nimport FilterBar from './components/FilterBar';\nimport PaymentTable from './components/PaymentTable';\nimport UploadPanel from './components/UploadPanel';\n\nconst API_BASE = '/api/payments';\n\nexport default function App() {\n const [activeTab, setActiveTab] = useState('payments');\n const [payments, setPayments] = useState([]);\n const [total, setTotal] = useState(0);\n const [page, setPage] = useState(1);\n const [filters, setFilters] = useState({});\n const [sortBy, setSortBy] = useState('createdAt');\n const [sortDir, setSortDir] = useState('desc');\n const [filterOptions, setFilterOptions] = useState({ types: [], recipients: [], tags: [], sources: [] });\n const [loading, setLoading] = useState(false);\n\n const fetchPayments = useCallback(async () => {\n setLoading(true);\n try {\n const params = new URLSearchParams();\n params.set('page', page);\n params.set('limit', 50);\n params.set('sortBy', sortBy);\n params.set('sortDir', sortDir);\n Object.entries(filters).forEach(([key, val]) => {\n if (val) params.set(key, val);\n });\n const res = await fetch(`${API_BASE}?${params}`);\n const data = await res.json();\n setPayments(data.payments || []);\n setTotal(data.total || 0);\n } catch (err) {\n console.error('Failed to fetch payments:', err);\n } finally {\n setLoading(false);\n }\n }, [page, filters, sortBy, sortDir]);\n\n const fetchFilterOptions = useCallback(async () => {\n try {\n const res = await fetch(`${API_BASE}/meta/filters`);\n const data = await res.json();\n setFilterOptions(data);\n } catch (err) {\n console.error('Failed to fetch filter options:', err);\n }\n }, []);\n\n useEffect(() => {\n fetchPayments();\n }, [fetchPayments]);\n\n useEffect(() => {\n fetchFilterOptions();\n }, [fetchFilterOptions]);\n\n // Refresh payments list after a successful CSV upload\n const handleUploadSuccess = () => {\n fetchPayments();\n fetchFilterOptions();\n setActiveTab('payments');\n };\n\n const handleAction = async (id, action) => {\n try {\n await fetch(`${API_BASE}/${id}/${action}`, { method: 'POST' });\n fetchPayments();\n fetchFilterOptions();\n } catch (err) {\n console.error(`Failed to ${action} payment:`, err);\n }\n };\n\n const handleAddTag = async (id, tagName, tagColor) => {\n try {\n await fetch(`${API_BASE}/${id}/tags`, {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify({ name: tagName, color: tagColor }),\n });\n fetchPayments();\n fetchFilterOptions();\n } catch (err) {\n console.error('Failed to add tag:', err);\n }\n };\n\n const handleRemoveTag = async (paymentId, tagId) => {\n try {\n await fetch(`${API_BASE}/${paymentId}/tags/${tagId}`, { method: 'DELETE' });\n fetchPayments();\n } catch (err) {\n console.error('Failed to remove tag:', err);\n }\n };\n\n const handleDelete = async (id) => {\n try {\n await fetch(`${API_BASE}/${id}`, { method: 'DELETE' });\n fetchPayments();\n fetchFilterOptions();\n } catch (err) {\n console.error('Failed to delete payment:', err);\n }\n };\n\n const handleUpdateStatus = async (id, status) => {\n try {\n await fetch(`${API_BASE}/${id}`, {\n method: 'PATCH',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify({ status }),\n });\n fetchPayments();\n } catch (err) {\n console.error('Failed to update status:', err);\n }\n };\n\n const handleFilterChange = (newFilters) => {\n setFilters(newFilters);\n setPage(1);\n };\n\n const handleSort = (field) => {\n if (sortBy === field) {\n setSortDir(d => d === 'asc' ? 'desc' : 'asc');\n } else {\n setSortBy(field);\n setSortDir('desc');\n }\n setPage(1);\n };\n\n const totalPages = Math.ceil(total / 50);\n\n return (\n <div className=\"min-h-screen bg-gray-50\">\n <header className=\"bg-white border-b border-gray-200 shadow-sm\">\n <div className=\"max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-4\">\n <div className=\"flex items-center justify-between\">\n <div className=\"flex items-center gap-3\">\n <div className=\"bg-indigo-600 p-2 rounded-lg\">\n <LayoutDashboard className=\"w-6 h-6 text-white\" />\n </div>\n <div>\n <h1 className=\"text-xl font-bold text-gray-900\">Finance Hub</h1>\n <p className=\"text-sm text-gray-500\">{total} transaction{total !== 1 ? 's' : ''} total</p>\n </div>\n </div>\n\n <div className=\"flex items-center gap-2\">\n {/* Tab switcher */}\n <div className=\"flex items-center rounded-lg border border-gray-200 bg-gray-50 p-1 gap-1\">\n <button\n onClick={() => setActiveTab('payments')}\n className={`flex items-center gap-1.5 px-3 py-1.5 text-sm font-medium rounded-md transition-colors ${\n activeTab === 'payments'\n ? 'bg-white text-indigo-700 shadow-sm'\n : 'text-gray-600 hover:text-gray-900'\n }`}\n >\n <LayoutDashboard className=\"w-4 h-4\" />\n Payments\n </button>\n <button\n onClick={() => setActiveTab('upload')}\n className={`flex items-center gap-1.5 px-3 py-1.5 text-sm font-medium rounded-md transition-colors ${\n activeTab === 'upload'\n ? 'bg-white text-emerald-700 shadow-sm'\n : 'text-gray-600 hover:text-gray-900'\n }`}\n >\n <Upload className=\"w-4 h-4\" />\n Upload CSV\n </button>\n </div>\n\n {activeTab === 'payments' && (\n <button\n onClick={() => { fetchPayments(); fetchFilterOptions(); }}\n className=\"flex items-center gap-2 px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 transition-colors\"\n >\n <RefreshCw className={`w-4 h-4 ${loading ? 'animate-spin' : ''}`} />\n Refresh\n </button>\n )}\n\n <button\n onClick={() => { window.location.href = '/outpost.goauthentik.io/sign_out'; }}\n className=\"flex items-center gap-2 px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 transition-colors\"\n title=\"Sign out\"\n >\n <LogOut className=\"w-4 h-4\" />\n </button>\n </div>\n </div>\n </div>\n </header>\n\n <main className=\"max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-6\">\n {activeTab === 'payments' ? (\n <>\n <FilterBar\n filters={filters}\n filterOptions={filterOptions}\n onFilterChange={handleFilterChange}\n />\n\n <PaymentTable\n payments={payments}\n loading={loading}\n sortBy={sortBy}\n sortDir={sortDir}\n onSort={handleSort}\n onSend={(id) => handleAction(id, 'send')}\n onSkip={(id) => handleAction(id, 'skip')}\n onAddTag={handleAddTag}\n onRemoveTag={handleRemoveTag}\n onDelete={handleDelete}\n onUpdateStatus={handleUpdateStatus}\n existingTags={filterOptions.tags}\n />\n\n {totalPages > 1 && (\n <div className=\"flex items-center justify-center gap-2 mt-6\">\n <button\n onClick={() => setPage(p => Math.max(1, p - 1))}\n disabled={page === 1}\n className=\"px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 disabled:opacity-50 disabled:cursor-not-allowed\"\n >\n Previous\n </button>\n <span className=\"text-sm text-gray-600\">\n Page {page} of {totalPages}\n </span>\n <button\n onClick={() => setPage(p => Math.min(totalPages, p + 1))}\n disabled={page === totalPages}\n className=\"px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 disabled:opacity-50 disabled:cursor-not-allowed\"\n >\n Next\n </button>\n </div>\n )}\n </>\n ) : (\n <UploadPanel onUploadSuccess={handleUploadSuccess} />\n )}\n </main>\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"FilterBar.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"FilterBar.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"167 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState, useEffect } from 'react';\nimport { Search, Filter, X, Calendar, ChevronDown, ChevronUp } from 'lucide-react';\n\nconst STATUS_OPTIONS = [\n { value: '', label: 'All Statuses' },\n { value: 'UNPROCESSED', label: 'Unprocessed' },\n { value: 'SENT', label: 'Sent' },\n { value: 'SKIPPED', label: 'Skipped' },\n];\n\nconst SOURCE_OPTIONS = [\n { value: '', label: 'All Sources' },\n { value: 'INGEST', label: 'SMS Ingest' },\n { value: 'UPLOAD', label: 'CSV Upload' },\n];\n\nexport default function FilterBar({ filters, filterOptions, onFilterChange }) {\n const [search, setSearch] = useState(filters.search || '');\n const [isOpen, setIsOpen] = useState(() => window.innerWidth >= 768);\n\n useEffect(() => {\n const mq = window.matchMedia('(min-width: 768px)');\n const handler = (e) => setIsOpen(e.matches);\n mq.addEventListener('change', handler);\n return () => mq.removeEventListener('change', handler);\n }, []);\n\n const handleSearchSubmit = (e) => {\n e.preventDefault();\n onFilterChange({ ...filters, search: search || undefined });\n };\n\n const handleSelectChange = (key, value) => {\n const newFilters = { ...filters };\n if (value) {\n newFilters[key] = value;\n } else {\n delete newFilters[key];\n }\n onFilterChange(newFilters);\n };\n\n const clearFilters = () => {\n setSearch('');\n onFilterChange({});\n };\n\n const activeFilterCount = Object.keys(filters).length;\n const hasActiveFilters = activeFilterCount > 0;\n\n return (\n <div className=\"bg-white rounded-xl border border-gray-200 shadow-sm p-4 mb-6\">\n <button\n onClick={() => setIsOpen(!isOpen)}\n className=\"w-full flex items-center gap-2\"\n >\n <Filter className=\"w-4 h-4 text-gray-500\" />\n <span className=\"text-sm font-medium text-gray-700\">Filters</span>\n {hasActiveFilters && (\n <span className=\"inline-flex items-center justify-center w-5 h-5 text-xs font-bold text-white bg-indigo-600 rounded-full\">\n {activeFilterCount}\n </span>\n )}\n {hasActiveFilters && (\n <span\n onClick={(e) => { e.stopPropagation(); clearFilters(); }}\n className=\"ml-1 flex items-center gap-1 text-xs text-red-600 hover:text-red-700\"\n >\n <X className=\"w-3 h-3\" />\n Clear\n </span>\n )}\n <span className=\"ml-auto\">\n {isOpen\n ? <ChevronUp className=\"w-4 h-4 text-gray-400\" />\n : <ChevronDown className=\"w-4 h-4 text-gray-400\" />\n }\n </span>\n </button>\n\n {isOpen && (\n <div className=\"space-y-3 mt-3 pt-3 border-t border-gray-100\">\n <div className=\"grid grid-cols-1 sm:grid-cols-2 lg:grid-cols-5 gap-3\">\n <form onSubmit={handleSearchSubmit} className=\"relative\">\n <Search className=\"absolute left-3 top-1/2 -translate-y-1/2 w-4 h-4 text-gray-400\" />\n <input\n type=\"text\"\n placeholder=\"Search...\"\n value={search}\n onChange={(e) => setSearch(e.target.value)}\n onBlur={() => onFilterChange({ ...filters, search: search || undefined })}\n className=\"w-full pl-9 pr-3 py-2 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none\"\n />\n </form>\n\n <select\n value={filters.source || ''}\n onChange={(e) => handleSelectChange('source', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n {SOURCE_OPTIONS.map(opt => (\n <option key={opt.value} value={opt.value}>{opt.label}</option>\n ))}\n </select>\n\n <select\n value={filters.status || ''}\n onChange={(e) => handleSelectChange('status', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n {STATUS_OPTIONS.map(opt => (\n <option key={opt.value} value={opt.value}>{opt.label}</option>\n ))}\n </select>\n\n <select\n value={filters.type || ''}\n onChange={(e) => handleSelectChange('type', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n <option value=\"\">All Types</option>\n {(filterOptions.types || []).map(t => (\n <option key={t} value={t}>{t}</option>\n ))}\n </select>\n\n <select\n value={filters.tag || ''}\n onChange={(e) => handleSelectChange('tag', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n <option value=\"\">All Tags</option>\n {(filterOptions.tags || []).map(t => (\n <option key={t.id} value={t.name}>{t.name}</option>\n ))}\n </select>\n </div>\n\n <div className=\"grid grid-cols-1 sm:grid-cols-2 gap-3\">\n <div className=\"relative\">\n <Calendar className=\"absolute left-3 top-1/2 -translate-y-1/2 w-4 h-4 text-gray-400\" />\n <input\n type=\"date\"\n placeholder=\"From date\"\n value={filters.dateFrom || ''}\n onChange={(e) => handleSelectChange('dateFrom', e.target.value)}\n className=\"w-full pl-9 pr-3 py-2 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none\"\n />\n </div>\n\n <div className=\"relative\">\n <Calendar className=\"absolute left-3 top-1/2 -translate-y-1/2 w-4 h-4 text-gray-400\" />\n <input\n type=\"date\"\n placeholder=\"To date\"\n value={filters.dateTo || ''}\n onChange={(e) => handleSelectChange('dateTo', e.target.value)}\n className=\"w-full pl-9 pr-3 py-2 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none\"\n />\n </div>\n </div>\n </div>\n )}\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentTable.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentTable.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"339 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState } from 'react';\nimport {\n ArrowUpDown, ArrowUp, ArrowDown,\n Send, XCircle, CheckCircle, MinusCircle, Clock,\n Inbox, Plus, X, ChevronDown, ChevronUp, Trash2,\n} from 'lucide-react';\n\nconst STATUS_CONFIG = {\n UNPROCESSED: { label: 'Unprocessed', icon: Clock, color: 'bg-amber-100 text-amber-700' },\n SENT: { label: 'Sent', icon: CheckCircle, color: 'bg-green-100 text-green-700' },\n SKIPPED: { label: 'Skipped', icon: MinusCircle, color: 'bg-gray-100 text-gray-500' },\n};\n\nconst TAG_COLORS = [\n '#ef4444', '#f97316', '#eab308', '#22c55e', '#06b6d4',\n '#3b82f6', '#8b5cf6', '#ec4899', '#6b7280',\n];\n\nconst COLUMNS = [\n { key: 'date', label: 'Date & Time', sortable: true },\n { key: 'source', label: 'Source', sortable: true },\n { key: 'type', label: 'Type', sortable: true },\n { key: 'recipient', label: 'Recipient', sortable: true },\n { key: 'amount', label: 'Amount', sortable: true },\n { key: 'balance', label: 'Balance', sortable: true },\n { key: 'status', label: 'Status', sortable: true },\n { key: 'tags', label: 'Tags', sortable: false },\n { key: 'actions', label: 'Actions', sortable: false },\n];\n\nfunction SortIcon({ column, sortBy, sortDir }) {\n if (sortBy !== column) return <ArrowUpDown className=\"w-3 h-3 text-gray-400\" />;\n return sortDir === 'asc'\n ? <ArrowUp className=\"w-3 h-3 text-indigo-600\" />\n : <ArrowDown className=\"w-3 h-3 text-indigo-600\" />;\n}\n\nfunction SourceBadge({ source }) {\n if (source === 'UPLOAD') {\n return (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-emerald-50 text-emerald-700\">\n CSV\n </span>\n );\n }\n return (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-indigo-50 text-indigo-700\">\n SMS\n </span>\n );\n}\n\nfunction TagCell({ payment, onAddTag, onRemoveTag, existingTags }) {\n const [open, setOpen] = useState(false);\n const [newTagName, setNewTagName] = useState('');\n const [newTagColor, setNewTagColor] = useState('#3b82f6');\n\n const paymentTags = payment.tags || [];\n const availableTags = existingTags.filter(t => !paymentTags.some(pt => pt.id === t.id));\n\n const handleAdd = (e) => {\n e.preventDefault();\n if (newTagName.trim()) {\n onAddTag(payment.id, newTagName.trim(), newTagColor);\n setNewTagName('');\n setOpen(false);\n }\n };\n\n return (\n <div className=\"flex flex-wrap items-center gap-1\">\n {paymentTags.map(tag => (\n <span\n key={tag.id}\n className=\"inline-flex items-center gap-0.5 px-1.5 py-0.5 text-xs font-medium rounded-full text-white\"\n style={{ backgroundColor: tag.color }}\n >\n {tag.name}\n <button onClick={() => onRemoveTag(payment.id, tag.id)} className=\"hover:opacity-75\">\n <X className=\"w-2.5 h-2.5\" />\n </button>\n </span>\n ))}\n <div className=\"relative\">\n <button\n onClick={() => setOpen(!open)}\n className=\"inline-flex items-center gap-0.5 px-1.5 py-0.5 text-xs text-gray-500 border border-dashed border-gray-300 rounded-full hover:border-gray-400\"\n >\n <Plus className=\"w-2.5 h-2.5\" />\n </button>\n {open && (\n <div className=\"absolute z-20 top-full left-0 mt-1 bg-white border border-gray-200 rounded-lg shadow-lg p-2 w-56\">\n <form onSubmit={handleAdd} className=\"flex items-center gap-1 mb-2\">\n <input\n type=\"text\"\n value={newTagName}\n onChange={(e) => setNewTagName(e.target.value)}\n placeholder=\"New tag\"\n autoFocus\n className=\"flex-1 px-2 py-1 text-xs border border-gray-300 rounded focus:ring-1 focus:ring-indigo-500 outline-none\"\n />\n <button type=\"submit\" className=\"text-xs text-indigo-600 font-medium hover:text-indigo-700 whitespace-nowrap\">Add</button>\n </form>\n <div className=\"flex gap-1 mb-2\">\n {TAG_COLORS.map(c => (\n <button\n key={c}\n type=\"button\"\n onClick={() => setNewTagColor(c)}\n className={`w-4 h-4 rounded-full border-2 ${newTagColor === c ? 'border-gray-800' : 'border-transparent'}`}\n style={{ backgroundColor: c }}\n />\n ))}\n </div>\n {availableTags.length > 0 && (\n <div className=\"border-t border-gray-100 pt-1 flex flex-wrap gap-1\">\n {availableTags.map(tag => (\n <button\n key={tag.id}\n onClick={() => { onAddTag(payment.id, tag.name, tag.color); setOpen(false); }}\n className=\"px-1.5 py-0.5 text-xs rounded-full border border-gray-200 text-gray-600 hover:bg-gray-100\"\n >\n {tag.name}\n </button>\n ))}\n </div>\n )}\n </div>\n )}\n </div>\n </div>\n );\n}\n\nfunction ExpandedRow({ payment }) {\n return (\n <tr className=\"bg-gray-50\">\n <td colSpan={COLUMNS.length} className=\"px-4 py-3\">\n <div className=\"text-xs text-gray-500 uppercase tracking-wide mb-1\">Original Message / Raw Data</div>\n <p className=\"text-sm text-gray-700 whitespace-pre-wrap break-words\">{payment.rawMessage}</p>\n {payment.debitBgn != null && (\n <p className=\"text-xs text-gray-500 mt-1\">Debit: {payment.debitBgn.toFixed(2)} BGN</p>\n )}\n {payment.creditBgn != null && (\n <p className=\"text-xs text-gray-500 mt-0.5\">Credit: {payment.creditBgn.toFixed(2)} BGN</p>\n )}\n {payment.transactionType && (\n <p className=\"text-xs text-gray-500 mt-0.5\">Transaction type: {payment.transactionType}</p>\n )}\n {payment.payerAccount && (\n <p className=\"text-xs text-gray-500 mt-0.5\">Account: {payment.payerAccount}</p>\n )}\n {payment.notifiedAt && (\n <p className=\"text-xs text-green-600 mt-2\">\n Notified on {new Date(payment.notifiedAt).toLocaleString('en-GB')}\n {payment.notifyPhone && ` to ${payment.notifyPhone}`}\n </p>\n )}\n </td>\n </tr>\n );\n}\n\nfunction StatusCell({ payment, onUpdateStatus }) {\n const [open, setOpen] = useState(false);\n const statusCfg = STATUS_CONFIG[payment.status] || STATUS_CONFIG.UNPROCESSED;\n const StatusIcon = statusCfg.icon;\n\n return (\n <div className=\"relative\">\n <button\n onClick={() => setOpen(!open)}\n className={`inline-flex items-center gap-1 px-2 py-0.5 text-xs font-medium rounded-full cursor-pointer ${statusCfg.color}`}\n >\n <StatusIcon className=\"w-3 h-3\" />\n {statusCfg.label}\n </button>\n {open && (\n <div className=\"absolute z-20 top-full left-0 mt-1 bg-white border border-gray-200 rounded-lg shadow-lg py-1 w-36\">\n {Object.entries(STATUS_CONFIG).map(([key, cfg]) => {\n const Icon = cfg.icon;\n return (\n <button\n key={key}\n onClick={() => { onUpdateStatus(payment.id, key); setOpen(false); }}\n className={`w-full flex items-center gap-2 px-3 py-1.5 text-xs hover:bg-gray-50 ${payment.status === key ? 'font-bold' : ''}`}\n >\n <Icon className=\"w-3 h-3\" />\n {cfg.label}\n </button>\n );\n })}\n </div>\n )}\n </div>\n );\n}\n\nexport default function PaymentTable({\n payments, loading, sortBy, sortDir, onSort,\n onSend, onSkip, onAddTag, onRemoveTag, onDelete, onUpdateStatus, existingTags,\n}) {\n const [expandedId, setExpandedId] = useState(null);\n\n if (loading) {\n return (\n <div className=\"flex items-center justify-center py-20\">\n <div className=\"animate-spin rounded-full h-8 w-8 border-b-2 border-indigo-600\"></div>\n </div>\n );\n }\n\n if (!payments || payments.length === 0) {\n return (\n <div className=\"flex flex-col items-center justify-center py-20 text-gray-400\">\n <Inbox className=\"w-12 h-12 mb-3\" />\n <p className=\"text-lg font-medium\">No transactions found</p>\n <p className=\"text-sm\">Try adjusting your filters, ingest a payment SMS, or upload a CSV.</p>\n </div>\n );\n }\n\n const formatDate = (d) => {\n if (!d) return '—';\n return new Date(d).toLocaleDateString('en-GB', {\n day: '2-digit', month: 'short', year: 'numeric', hour: '2-digit', minute: '2-digit',\n });\n };\n\n const formatAmount = (v, currency) =>\n v != null ? `${v.toFixed(2)} ${currency || 'EUR'}` : '—';\n\n return (\n <div className=\"bg-white rounded-xl border border-gray-200 shadow-sm overflow-hidden\">\n <div className=\"overflow-x-auto\">\n <table className=\"w-full text-sm\">\n <thead>\n <tr className=\"bg-gray-50 border-b border-gray-200\">\n {COLUMNS.map(col => (\n <th\n key={col.key}\n className={`px-4 py-3 text-left text-xs font-semibold text-gray-600 uppercase tracking-wider ${col.sortable ? 'cursor-pointer select-none hover:bg-gray-100' : ''}`}\n onClick={() => col.sortable && onSort(col.key)}\n >\n <span className=\"inline-flex items-center gap-1\">\n {col.label}\n {col.sortable && <SortIcon column={col.key} sortBy={sortBy} sortDir={sortDir} />}\n </span>\n </th>\n ))}\n </tr>\n </thead>\n <tbody className=\"divide-y divide-gray-100\">\n {payments.map(p => {\n const isExpanded = expandedId === p.id;\n return (\n <React.Fragment key={p.id}>\n <tr className=\"hover:bg-gray-50 transition-colors\">\n <td className=\"px-4 py-3 whitespace-nowrap text-gray-700\">{formatDate(p.date)}</td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n <SourceBadge source={p.source} />\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n {p.type ? (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-blue-50 text-blue-700\">{p.type}</span>\n ) : (p.transactionType ? (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-gray-100 text-gray-600 max-w-24 truncate block\" title={p.transactionType}>{p.transactionType}</span>\n ) : '—')}\n </td>\n <td className=\"px-4 py-3 text-gray-700 max-w-xs truncate\" title={p.recipient || ''}>\n <div className=\"flex items-center gap-1\">\n <span className=\"truncate\">{p.recipient || '—'}</span>\n <button\n onClick={() => setExpandedId(isExpanded ? null : p.id)}\n className=\"flex-shrink-0 text-gray-400 hover:text-gray-600\"\n title=\"Show raw data\"\n >\n {isExpanded ? <ChevronUp className=\"w-3.5 h-3.5\" /> : <ChevronDown className=\"w-3.5 h-3.5\" />}\n </button>\n </div>\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap font-medium text-gray-900\">\n {formatAmount(p.amount, p.currency)}\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap text-gray-600\">\n {formatAmount(p.balance, p.currency)}\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n <StatusCell payment={p} onUpdateStatus={onUpdateStatus} />\n </td>\n <td className=\"px-4 py-3\">\n <TagCell\n payment={p}\n onAddTag={onAddTag}\n onRemoveTag={onRemoveTag}\n existingTags={existingTags}\n />\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n <div className=\"flex items-center gap-1.5\">\n {p.status === 'UNPROCESSED' && (\n <>\n <button\n onClick={() => onSend(p.id)}\n className=\"inline-flex items-center gap-1 px-2.5 py-1 text-xs font-medium text-white bg-indigo-600 rounded-md hover:bg-indigo-700 transition-colors\"\n >\n <Send className=\"w-3 h-3\" />\n Send\n </button>\n <button\n onClick={() => onSkip(p.id)}\n className=\"inline-flex items-center gap-1 px-2.5 py-1 text-xs font-medium text-gray-600 bg-white border border-gray-300 rounded-md hover:bg-gray-50 transition-colors\"\n >\n <XCircle className=\"w-3 h-3\" />\n Skip\n </button>\n </>\n )}\n <button\n onClick={() => { if (window.confirm('Delete this transaction?')) onDelete(p.id); }}\n className=\"inline-flex items-center gap-1 px-2 py-1 text-xs font-medium text-red-600 bg-white border border-red-200 rounded-md hover:bg-red-50 transition-colors\"\n title=\"Delete transaction\"\n >\n <Trash2 className=\"w-3 h-3\" />\n </button>\n </div>\n </td>\n </tr>\n {isExpanded && <ExpandedRow payment={p} />}\n </React.Fragment>\n );\n })}\n </tbody>\n </table>\n </div>\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"UploadPanel.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"UploadPanel.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"192 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState, useRef } from 'react';\nimport { Upload, FileText, CheckCircle, AlertCircle, X, ArrowLeft } from 'lucide-react';\n\nexport default function UploadPanel({ onUploadSuccess }) {\n const [files, setFiles] = useState([]);\n const [loading, setLoading] = useState(false);\n const [result, setResult] = useState(null);\n const [error, setError] = useState(null);\n const [dragging, setDragging] = useState(false);\n const fileInputRef = useRef();\n\n const addFiles = (incoming) => {\n const csvFiles = Array.from(incoming).filter(f =>\n f.name.toLowerCase().endsWith('.csv')\n );\n setFiles(prev => {\n const existingNames = new Set(prev.map(f => f.name));\n return [...prev, ...csvFiles.filter(f => !existingNames.has(f.name))];\n });\n };\n\n const handleDrop = (e) => {\n e.preventDefault();\n setDragging(false);\n addFiles(e.dataTransfer.files);\n };\n\n const handleFileSelect = (e) => {\n addFiles(e.target.files);\n e.target.value = '';\n };\n\n const removeFile = (idx) => setFiles(prev => prev.filter((_, i) => i !== idx));\n\n const handleUpload = async () => {\n if (!files.length) return;\n setLoading(true);\n setError(null);\n setResult(null);\n\n const formData = new FormData();\n files.forEach(f => formData.append('files', f));\n\n try {\n const res = await fetch('/api/upload/csv', { method: 'POST', body: formData });\n const data = await res.json();\n if (!res.ok) throw new Error(data.error || 'Upload failed');\n setResult(data);\n setFiles([]);\n } catch (err) {\n setError(err.message);\n } finally {\n setLoading(false);\n }\n };\n\n return (\n <div className=\"max-w-2xl mx-auto\">\n <div className=\"mb-6\">\n <h2 className=\"text-lg font-semibold text-gray-900\">Upload DSK Bank CSV</h2>\n <p className=\"text-sm text-gray-500 mt-1\">\n Import transactions from DSK Bank CSV exports. Multiple files are merged automatically.\n Internal transfers are skipped. Tags are auto-assigned based on payee and description.\n </p>\n </div>\n\n {/* Drop zone */}\n <div\n onDrop={handleDrop}\n onDragOver={(e) => { e.preventDefault(); setDragging(true); }}\n onDragLeave={() => setDragging(false)}\n onClick={() => fileInputRef.current.click()}\n className={`border-2 border-dashed rounded-xl p-12 text-center cursor-pointer transition-colors ${\n dragging\n ? 'border-emerald-400 bg-emerald-50'\n : 'border-gray-300 hover:border-emerald-400 hover:bg-emerald-50'\n }`}\n >\n <Upload className={`w-10 h-10 mx-auto mb-3 ${dragging ? 'text-emerald-500' : 'text-gray-400'}`} />\n <p className=\"text-sm font-medium text-gray-700\">Drop DSK Bank CSV files here</p>\n <p className=\"text-xs text-gray-500 mt-1\">or click to select files — multiple files supported</p>\n <input\n ref={fileInputRef}\n type=\"file\"\n multiple\n accept=\".csv\"\n className=\"hidden\"\n onChange={handleFileSelect}\n />\n </div>\n\n {/* File list */}\n {files.length > 0 && (\n <div className=\"mt-4 space-y-2\">\n {files.map((f, i) => (\n <div key={i} className=\"flex items-center gap-2 bg-white rounded-lg border border-gray-200 px-3 py-2\">\n <FileText className=\"w-4 h-4 text-gray-400 flex-shrink-0\" />\n <span className=\"text-sm text-gray-700 flex-1 truncate\">{f.name}</span>\n <span className=\"text-xs text-gray-400 flex-shrink-0\">{(f.size / 1024).toFixed(1)} KB</span>\n <button\n onClick={(e) => { e.stopPropagation(); removeFile(i); }}\n className=\"text-gray-400 hover:text-gray-600 flex-shrink-0\"\n >\n <X className=\"w-4 h-4\" />\n </button>\n </div>\n ))}\n\n <button\n onClick={handleUpload}\n disabled={loading}\n className=\"w-full py-2.5 text-sm font-medium text-white bg-emerald-600 rounded-lg hover:bg-emerald-700 disabled:opacity-50 disabled:cursor-not-allowed transition-colors mt-2\"\n >\n {loading\n ? 'Importing…'\n : `Import ${files.length} file${files.length !== 1 ? 's' : ''}`\n }\n </button>\n </div>\n )}\n\n {/* Success result */}\n {result && (\n <div className=\"mt-6 bg-green-50 border border-green-200 rounded-xl p-5\">\n <div className=\"flex items-center gap-2 mb-3\">\n <CheckCircle className=\"w-5 h-5 text-green-600 flex-shrink-0\" />\n <span className=\"font-medium text-green-800\">Import complete</span>\n </div>\n <div className=\"grid grid-cols-3 gap-3 text-center mb-3\">\n <div className=\"bg-white rounded-lg border border-green-100 py-2 px-3\">\n <p className=\"text-2xl font-bold text-green-700\">{result.imported}</p>\n <p className=\"text-xs text-gray-500\">Imported</p>\n </div>\n <div className=\"bg-white rounded-lg border border-green-100 py-2 px-3\">\n <p className=\"text-2xl font-bold text-gray-500\">{result.skipped}</p>\n <p className=\"text-xs text-gray-500\">Skipped</p>\n </div>\n <div className=\"bg-white rounded-lg border border-green-100 py-2 px-3\">\n <p className=\"text-2xl font-bold text-amber-600\">{result.errors?.length ?? 0}</p>\n <p className=\"text-xs text-gray-500\">Warnings</p>\n </div>\n </div>\n <p className=\"text-xs text-gray-500 mb-3\">\n Skipped rows are internal bank transfers (ТРАНСФЕР СОБСТВЕНИ СМЕТКИ).\n </p>\n {result.errors?.length > 0 && (\n <details className=\"mb-3\">\n <summary className=\"text-xs text-amber-700 cursor-pointer hover:text-amber-800\">\n Show {result.errors.length} warning{result.errors.length !== 1 ? 's' : ''}\n </summary>\n <ul className=\"mt-2 text-xs text-amber-600 space-y-0.5 max-h-32 overflow-y-auto\">\n {result.errors.map((e, i) => <li key={i} className=\"font-mono\">{e}</li>)}\n </ul>\n </details>\n )}\n <button\n onClick={onUploadSuccess}\n className=\"flex items-center gap-1.5 text-sm font-medium text-green-700 hover:text-green-800\"\n >\n <ArrowLeft className=\"w-4 h-4\" />\n View imported transactions\n </button>\n </div>\n )}\n\n {/* Error */}\n {error && (\n <div className=\"mt-4 bg-red-50 border border-red-200 rounded-xl p-4 flex items-start gap-3\">\n <AlertCircle className=\"w-5 h-5 text-red-500 flex-shrink-0 mt-0.5\" />\n <div>\n <p className=\"text-sm font-medium text-red-800\">Upload failed</p>\n <p className=\"text-sm text-red-700 mt-0.5\">{error}</p>\n </div>\n </div>\n )}\n\n {/* Info box */}\n {!result && !error && (\n <div className=\"mt-6 bg-blue-50 border border-blue-100 rounded-xl p-4\">\n <p className=\"text-xs font-medium text-blue-800 mb-1\">Expected CSV format (DSK Bank export)</p>\n <p className=\"text-xs text-blue-700 font-mono\">\n Дата, Вид на трансакцията, Основание, Дебит BGN, Кредит BGN, Наредител/Получател, Номер сметка...\n </p>\n <p className=\"text-xs text-blue-600 mt-2\">\n Both UTF-8 and Windows-1251 encodings are supported. Tags are auto-applied based on payee and description keywords.\n </p>\n </div>\n )}\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentCard.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentCard.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"186 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState } from 'react';\nimport {\n Send, XCircle, CheckCircle, MinusCircle, Clock,\n CreditCard, Tag, Plus, X,\n} from 'lucide-react';\n\nconst STATUS_CONFIG = {\n UNPROCESSED: { label: 'Unprocessed', icon: Clock, color: 'bg-amber-100 text-amber-700 border-amber-200' },\n SENT: { label: 'Sent', icon: CheckCircle, color: 'bg-green-100 text-green-700 border-green-200' },\n SKIPPED: { label: 'Skipped', icon: MinusCircle, color: 'bg-gray-100 text-gray-500 border-gray-200' },\n};\n\nconst TAG_COLORS = [\n '#ef4444', '#f97316', '#eab308', '#22c55e', '#06b6d4',\n '#3b82f6', '#8b5cf6', '#ec4899', '#6b7280',\n];\n\nexport default function PaymentCard({ payment, onSend, onSkip, onAddTag, onRemoveTag, existingTags }) {\n const [showTagInput, setShowTagInput] = useState(false);\n const [newTagName, setNewTagName] = useState('');\n const [newTagColor, setNewTagColor] = useState('#3b82f6');\n\n const statusCfg = STATUS_CONFIG[payment.status] || STATUS_CONFIG.UNPROCESSED;\n const StatusIcon = statusCfg.icon;\n\n const handleAddTag = (e) => {\n e.preventDefault();\n if (newTagName.trim()) {\n onAddTag(payment.id, newTagName.trim(), newTagColor);\n setNewTagName('');\n setShowTagInput(false);\n }\n };\n\n const paymentTags = payment.tags || [];\n const availableTags = existingTags.filter(t => !paymentTags.some(pt => pt.id === t.id));\n\n const formattedDate = payment.date\n ? new Date(payment.date).toLocaleDateString('en-GB', {\n day: '2-digit', month: 'short', year: 'numeric', hour: '2-digit', minute: '2-digit',\n })\n : 'N/A';\n\n const currency = payment.currency || 'EUR';\n\n return (\n <div className=\"bg-white rounded-xl border border-gray-200 shadow-sm hover:shadow-md transition-shadow p-4\">\n <div className=\"flex items-start justify-between gap-3 mb-3\">\n <div className=\"flex-1 min-w-0\">\n <div className=\"flex items-center gap-2 mb-1\">\n <span className={`inline-flex items-center gap-1 px-2 py-0.5 text-xs font-medium rounded-full border ${statusCfg.color}`}>\n <StatusIcon className=\"w-3 h-3\" />\n {statusCfg.label}\n </span>\n {payment.source === 'UPLOAD' ? (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-emerald-50 text-emerald-700\">CSV</span>\n ) : (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-indigo-50 text-indigo-700\">SMS</span>\n )}\n </div>\n <p className=\"text-sm text-gray-600 break-words leading-relaxed\">{payment.rawMessage}</p>\n </div>\n </div>\n\n <div className=\"grid grid-cols-2 sm:grid-cols-4 gap-3 mb-3 text-sm\">\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Amount</span>\n <p className=\"font-semibold text-gray-900\">\n {payment.amount != null ? `${payment.amount.toFixed(2)} ${currency}` : 'N/A'}\n </p>\n </div>\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Date</span>\n <p className=\"text-gray-700\">{formattedDate}</p>\n </div>\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Card</span>\n <p className=\"text-gray-700 flex items-center gap-1\">\n <CreditCard className=\"w-3 h-3 text-gray-400\" />\n {payment.card || 'N/A'}\n </p>\n </div>\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Balance</span>\n <p className=\"text-gray-700\">\n {payment.balance != null ? `${payment.balance.toFixed(2)} ${currency}` : 'N/A'}\n </p>\n </div>\n </div>\n\n {/* Tags */}\n <div className=\"flex flex-wrap items-center gap-1.5 mb-3\">\n <Tag className=\"w-3 h-3 text-gray-400\" />\n {paymentTags.map(tag => (\n <span\n key={tag.id}\n className=\"inline-flex items-center gap-1 px-2 py-0.5 text-xs font-medium rounded-full text-white\"\n style={{ backgroundColor: tag.color }}\n >\n {tag.name}\n <button onClick={() => onRemoveTag(payment.id, tag.id)} className=\"hover:opacity-75\">\n <X className=\"w-3 h-3\" />\n </button>\n </span>\n ))}\n {!showTagInput ? (\n <button\n onClick={() => setShowTagInput(true)}\n className=\"inline-flex items-center gap-0.5 px-2 py-0.5 text-xs text-gray-500 border border-dashed border-gray-300 rounded-full hover:border-gray-400 hover:text-gray-600\"\n >\n <Plus className=\"w-3 h-3\" />\n Tag\n </button>\n ) : (\n <form onSubmit={handleAddTag} className=\"inline-flex items-center gap-1\">\n <input\n type=\"text\"\n value={newTagName}\n onChange={(e) => setNewTagName(e.target.value)}\n placeholder=\"Tag name\"\n autoFocus\n className=\"w-24 px-2 py-0.5 text-xs border border-gray-300 rounded-md focus:ring-1 focus:ring-indigo-500 outline-none\"\n />\n <div className=\"flex gap-0.5\">\n {TAG_COLORS.map(c => (\n <button\n key={c}\n type=\"button\"\n onClick={() => setNewTagColor(c)}\n className={`w-4 h-4 rounded-full border-2 ${newTagColor === c ? 'border-gray-800' : 'border-transparent'}`}\n style={{ backgroundColor: c }}\n />\n ))}\n </div>\n <button type=\"submit\" className=\"text-xs text-indigo-600 font-medium hover:text-indigo-700\">Add</button>\n <button type=\"button\" onClick={() => setShowTagInput(false)} className=\"text-xs text-gray-400 hover:text-gray-600\">\n <X className=\"w-3 h-3\" />\n </button>\n </form>\n )}\n {showTagInput && availableTags.length > 0 && (\n <div className=\"flex flex-wrap gap-1 ml-1\">\n {availableTags.slice(0, 5).map(tag => (\n <button\n key={tag.id}\n onClick={() => { onAddTag(payment.id, tag.name, tag.color); setShowTagInput(false); }}\n className=\"px-2 py-0.5 text-xs rounded-full border border-gray-200 text-gray-600 hover:bg-gray-100\"\n >\n {tag.name}\n </button>\n ))}\n </div>\n )}\n </div>\n\n {payment.status === 'UNPROCESSED' && (\n <div className=\"flex items-center gap-2 pt-3 border-t border-gray-100\">\n <button\n onClick={() => onSend(payment.id)}\n className=\"flex items-center gap-1.5 px-4 py-2 text-sm font-medium text-white bg-indigo-600 rounded-lg hover:bg-indigo-700 transition-colors\"\n >\n <Send className=\"w-4 h-4\" />\n Send\n </button>\n <button\n onClick={() => onSkip(payment.id)}\n className=\"flex items-center gap-1.5 px-4 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 transition-colors\"\n >\n <XCircle className=\"w-4 h-4\" />\n Do Not Send\n </button>\n </div>\n )}\n\n {payment.status === 'SENT' && payment.notifiedAt && (\n <div className=\"pt-3 border-t border-gray-100\">\n <p className=\"text-xs text-green-600\">\n Notified on {new Date(payment.notifiedAt).toLocaleString('en-GB')}\n {payment.notifyPhone && ` to ${payment.notifyPhone}`}\n </p>\n </div>\n )}\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentList.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentList.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"40 lines","depth":24,"on_screen":false,"role_description":"text"}]...
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Explorer (⇧⌘E)
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Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
report(1).csv, Editor Group 1
report(2).csv, Editor Group 1
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
Design new payment-logge…, Editor Group 2
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Ln 9, Col 45
Info: Setting up SSH Host nas: Setting up SSH tunnel
Design new payment-logger and dsk-uploader hybrid app
Session history
New session
Message actions
payments.js
payments.js
ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.
Thinking
Thinking
I'll explore all three reference projects in parallel to understand their structure before planning.
Agent:
Explore payment-logger app structure and functionality
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How data flows (ingest, storage, retrieval)
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.
Agent:
Explore dsk-uploader app structure and functionality
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How file uploads work - what files, what format, how parsed
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.
Agent:
Explore auth folder and authentik integration
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. What auth system is being used (Authentik)
2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?
3. Middleware - how is auth enforced on routes?
4. Any frontend auth flow - login redirect, token handling, protected routes
5. Environment variables related to auth
6. Docker/deployment setup for the auth service itself
7. Any example of how other apps integrate with this auth
Report with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.
Message actions
payments.js
payments.js
continue
Thinking
Thinking
Launching parallel exploration of all three reference projects.
Agent:
Explore payment-logger app structure
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How data is ingested (look at /ingest route especially)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore dsk-uploader app structure
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How file uploads work (what format, what processing happens)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore auth project structure
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. What authentication system is used (authentik integration details)
3. How OAuth/OIDC flow works
4. Any middleware or helper functions for protecting routes
5. Session management approach
6. How frontend handles auth state
7. Any example of how other apps integrate with this auth system
8. Docker setup and environment variables
Please read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.
Thinking
Thinking
Now I have a complete picture of all three. Let me design the plan.
Agent:
Design combined app architecture
IN
Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:
---
## App 1: payments-logger (Node.js)
- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI
- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS
- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage
- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)
- **Schema** (PostgreSQL via Prisma):
- `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at
- `tags` table: id, name, color — M2M with payments via `_PaymentToTag`
- `users` table: id, username, hashed_password (this will be REMOVED)
- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system
- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance
## App 2: dsk-uploader (Python/Flask)
- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database
- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5
- **Auth**: None (open)
- **CSV format** (DSK Bank Bulgarian format, columns):
- `Дата` (date, DD.MM.YYYY)
- `Вид на трансакцията` (transaction type, Bulgarian)
- `Основание` (reason/description — contains card number regex: `^\d{6}x{6}\d{4}$`)
- `Дебит BGN` (debit amount, may be empty)
- `Кредит BGN` (credit amount, may be empty)
- `Наредител/Получател` (orderer/recipient name)
- `Номер сметка на наредителя / получателя` (account number)
- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers
- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)
## App 3: auth (Authentik)
- **Mode**: Proxy mode via NPM (forward auth)
- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:
- `X-authentik-username`
- `X-authentik-email`
- `X-authentik-groups`
- **No code integration needed** in the app itself — just trust these headers from NPM
- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`
---
## What the New Combined App Must Do
1. **Single PostgreSQL database** for all transactions
2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST
3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema
4. **Unified UI** — show all payments in one table regardless of source
5. **Source indicator** in UI — badge showing "INGEST", "UPLOAD", or "BOTH" (if duplicate detection added)
6. **Source filter** in FilterBar — filter by All/Ingest/Upload
7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM
8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination
9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL
---
## Technical Constraints
- Keep Node.js backend (not Python) — extend payments-logger's stack
- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)
- File upload: use `multer` npm middleware
- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)
- Add `source` enum field (INGEST/UPLOAD) to payments schema
- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is
- Remove `users` table from schema
---
## Please Design
1. Complete folder structure for the new app (suggest name: "finance-hub" or similar — note this is a placeholder, user will confirm)
2. Prisma schema with new fields (`source`, `currency`)
3. All backend API routes
4. CSV parser design in Node.js (port of the Python logic)
5. Authentik auth middleware
6. Frontend component structure (React) — what's reused from payments-logger, what's new
7. Docker Compose setup
8. Environment variables needed
9. Step-by-step implementation order
10. Verification checklist
Be specific about file paths and code structure. This will be used to write actual implementation code.
Thinking
Thinking
Good plan. Let me ask the one thing I need before writing the final plan.
AskUserQuestion
OUT
User has answered your questions: "What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding."="finance-hub". You can now continue with the user's answers in mind.
Thinking
Thinking
Writing the final plan now.
Thinking
Thinking
Write
ets-create-a-new-generic-sun.md
ets-create-a-new-generic-sun.md
326 lines
# finance-hub — Implementation Plan
## Context
Two separate finance apps exist as references and will be retired:
- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.
- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.
The new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).
---
## Tech Stack
| Layer | Choice | Rationale |
|-------|--------|-----------|
| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |
| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |
| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |
| Database | PostgreSQL 16 | Same as payments-logger |
| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |
| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |
| Container | Docker Compose | Same pattern as both reference apps |
**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage.
**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references.
**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.
---
## Folder Structure
```
/volume2/docker/finance/finance-hub/
├── docker-compose.yml
├── .env
├── .env.example
├── .gitignore
├── backend/
│ ├── Dockerfile
│ ├── package.json
│ ├── prisma/
│ │ ├── schema.prisma
│ │ └── migrations/
│ │ ├── migration_lock.toml
│ │ └── 20260508_init/
│ │ └── migration.sql
│ └── src/
│ ├── index.js ← entry point (Authentik middleware wired here)
│ ├── auth.js ← Authentik header middleware (replaces JWT auth)
│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)
│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)
│ └── routes/
│ ├── payments.js ← existing routes + source/currency additions
│ └── upload.js ← NEW: POST /api/upload/csv
└── frontend/
├── Dockerfile
├── package.json
├── vite.config.js
├── tailwind.config.js
├── postcss.config.js
├── index.html
└── src/
├── main.jsx ← remove AuthProvider wrapper
├── index.css
├── App.jsx ← remove auth state, add Upload tab toggle
└── components/
├── FilterBar.jsx ← add source filter select
├── PaymentTable.jsx ← add Source badge column + currency display
├── PaymentCard.jsx ← minor source badge addition
├── PaymentList.jsx ← unchanged
└── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI
```
---
## Database Schema (Prisma)
File: `backend/prisma/schema.prisma`
```prisma
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
}
model Payment {
id Int @id @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
auth.js
auth.js
27 lines
const PUBLIC_PATHS = new Set([
'/api/health',
'/api/payments/ingest',
]);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) {
return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });
}
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '')
.split(',')
.map(g => g.trim())
.filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
Write
parser.js
parser.js
104 lines
/**
* Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)
*
* Supported formats:
*
* POS / INTERNET / ECOM / P2P payment:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM withdrawal:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM utility payment (amount may include fee as AMOUNT/FEE):
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.
*/
const LOCAL_TZ = process.env.TZ || 'Europe/Sofia';
/**
* Convert a local-timezone date/time to a UTC Date object.
* Uses Intl to resolve the actual UTC offset (DST-aware).
*/
function localToUtc(year, month, day, hour, minute) {
const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));
const formatter = new Intl.DateTimeFormat('en-US', {
timeZone: LOCAL_TZ,
year: 'numeric', month: '2-digit', day: '2-digit',
hour: '2-digit', minute: '2-digit', second: '2-digit',
hour12: false,
});
const parts = {};
formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });
const localAtNaive = new Date(Date.UTC(
parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),
parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),
));
const offsetMs = localAtNaive.getTime() - naive.getTime();
return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);
}
function parsePaymentSms(message) {
const result = {
rawMessage: message,
date: null,
type: null,
card: null,
recipient: null,
amount: null,
balance: null,
};
// Date and time: "Na DD/MM/YYYY v HH:MM"
const dateMatch = message.match(/Na (\d{2})\/(\d{2})\/(\d{4}) v (\d{2}):(\d{2})/i);
if (dateMatch) {
const [, day, month, year, hour, minute] = dateMatch;
result.date = localToUtc(
parseInt(year), parseInt(month), parseInt(day),
parseInt(hour), parseInt(minute),
);
}
// Card mask: "s karta 400915***4447" or "s karta 483890***7162"
const cardMatch = message.match(/s karta\s+([\d*]+)/i);
if (cardMatch) {
result.card = cardMatch[1];
}
// Transaction type: supports both prepositions
// "na POS" / "na ATM" / "na INTERNET" etc. (payment)
// "ot ATM" (withdrawal)
const typeMatch = message.match(/(?:na|ot)\s+(POS|ATM|INTERNET|ECOM|P2P)\b/i);
if (typeMatch) {
result.type = typeMatch[1].toUpperCase();
}
// Recipient address: "s adres: MERCHANT" or "s adres:MERCHANT" (no space variant)
const recipientMatch = message.match(/s adres:\s*([^.]+)\./i);
if (recipientMatch) {
result.recipient = recipientMatch[1].trim();
}
// Amount: handles both verbs and the AMOUNT/FEE suffix format
// "sa plateni 7.78 EUR"
// "sa iztegleni 400.00 EUR"
// "sa plateni 0.50 EUR/0.50 EUR" → captures 0.50 (the charged amount, ignoring fee)
const amountMatch = message.match(/sa (?:plateni|iztegleni)\s+([\d.,]+)\s+[A-Z]{3}/i);
if (amountMatch) {
result.amount = parseFloat(amountMatch[1].replace(',', '.'));
}
// Balance: "Nalichni: 2583.07 EUR."
const balanceMatch = message.match(/Nalichni:\s*([\d.,]+)\s+[A-Z]{3}/i);
if (balanceMatch) {
result.balance = parseFloat(balanceMatch[1].replace(',', '.'));
}
return result;
}
module.exports = { parsePaymentSms };
Write
csvParser.js
csvParser.js
175 lines
/**
* DSK Bank CSV parser — Node.js port of dskuploader.py
*
* DSK Bank exports use Windows-1251 (cp1251) encoding.
* Each row maps to a Payment record with source=UPLOAD, currency=BGN.
*/
const { parse } = require('csv-parse');
const iconv = require('iconv-lite');
const SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';
const CARD_REGEX = /^\d{6}x{6}\d{4}$/;
const POS_REGEX = /^\s*ПЛАЩАНЕ\s+НА\s+ПОС\s+\d{2}\.\d{2}\.\d{4}\s+\d{2}:\d{2}/;
const COL = {
DATE: 'Дата',
TYPE: 'Вид на трансакцията',
REASON: 'Основание',
DEBIT: 'Дебит BGN',
CREDIT: 'Кредит BGN',
PAYEE: 'Наредител/Получател',
ACCT: 'Номер сметка на наредителя / получателя',
};
const TAG_RULES = [
['reason', 'ЗАПЛАТА', 'Salary'],
['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],
['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],
['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],
['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],
['payee', 'VIVACOM', 'Subscriptions'],
['payee', 'Google', 'Subscriptions'],
['payee', 'SkyShowtime', 'Subscriptions'],
['payee', 'NETFLIX', 'Subscriptions'],
['payee', 'LUKOIL', 'Bills'],
['payee', 'CityGate', 'Bills'],
['payee', 'CBA', 'Groceries'],
['payee', 'FANTASTICO', 'Groceries'],
['payee', 'LIDL', 'Groceries'],
];
function parseNum(val) {
if (val == null || val === '') return null;
if (typeof val === 'number') return isNaN(val) ? null : val;
const s = String(val).trim().replace(/\xa0/g, '').replace(/ /g, '').replace(',', '.');
const n = parseFloat(s);
return isNaN(n) ? null : n;
}
function parseDate(val) {
if (!val) return null;
const s = String(val).trim();
const m = s.match(/^(\d{2})\.(\d{2})\.(\d{4})$/);
if (m) {
return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));
}
return null;
}
function processReasonAndCard(reason) {
if (!reason || typeof reason !== 'string') return { reason: '', card: null };
const parts = reason.trim().split(' ');
let card = null;
let cleanReason = reason.trim();
if (parts[0] && CARD_REGEX.test(parts[0])) {
card = parts[0];
cleanReason = parts.slice(1).join(' ').trim();
}
if (POS_REGEX.test(cleanReason)) {
const posParts = cleanReason.split('<br/>');
try {
const dateTime = posParts[0].split('ПОС ')[1];
cleanReason = `POS PAYMENT ${dateTime}`;
} catch (_) { /* keep original */ }
}
return { reason: cleanReason.replace(/\s+/g, ' ').trim(), card };
}
function generateTags(fields) {
const tags = new Set();
for (const [field, keyword, tagName] of TAG_RULES) {
if ((fields[field] || '').includes(keyword)) {
tags.add(tagName);
}
}
return Array.from(tags);
}
function processRow(row) {
const transactionType = (row[COL.TYPE] || '').trim();
if (transactionType === SKIP_TYPE) return null;
const { reason, card } = processReasonAndCard(row[COL.REASON]);
const payee = (row[COL.PAYEE] || ...
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Explorer (⇧⌘E)
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EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
report(1).csv, Editor Group 1
report(2).csv, Editor Group 1
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
Design new payment-logge…, Editor Group 2
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Info: Setting up SSH Host nas: Setting up SSH tunnel
Design new payment-logger and dsk-uploader hybrid app
Session history
New session
Message actions
payments.js
payments.js
ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.
Thinking
Thinking
I'll explore all three reference projects in parallel to understand their structure before planning.
Agent:
Explore payment-logger app structure and functionality
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How data flows (ingest, storage, retrieval)
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.
Agent:
Explore dsk-uploader app structure and functionality
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How file uploads work - what files, what format, how parsed
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.
Agent:
Explore auth folder and authentik integration
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. What auth system is being used (Authentik)
2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?
3. Middleware - how is auth enforced on routes?
4. Any frontend auth flow - login redirect, token handling, protected routes
5. Environment variables related to auth
6. Docker/deployment setup for the auth service itself
7. Any example of how other apps integrate with this auth
Report with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.
Message actions
payments.js
payments.js
continue
Thinking
Thinking
Launching parallel exploration of all three reference projects.
Agent:
Explore payment-logger app structure
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How data is ingested (look at /ingest route especially)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore dsk-uploader app structure
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How file uploads work (what format, what processing happens)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore auth project structure
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. What authentication system is used (authentik integration details)
3. How OAuth/OIDC flow works
4. Any middleware or helper functions for protecting routes
5. Session management approach
6. How frontend handles auth state
7. Any example of how other apps integrate with this auth system
8. Docker setup and environment variables
Please read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.
Thinking
Thinking
Now I have a complete picture of all three. Let me design the plan.
Agent:
Design combined app architecture
IN
Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:
---
## App 1: payments-logger (Node.js)
- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI
- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS
- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage
- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)
- **Schema** (PostgreSQL via Prisma):
- `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at
- `tags` table: id, name, color — M2M with payments via `_PaymentToTag`
- `users` table: id, username, hashed_password (this will be REMOVED)
- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system
- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance
## App 2: dsk-uploader (Python/Flask)
- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database
- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5
- **Auth**: None (open)
- **CSV format** (DSK Bank Bulgarian format, columns):
- `Дата` (date, DD.MM.YYYY)
- `Вид на трансакцията` (transaction type, Bulgarian)
- `Основание` (reason/description — contains card number regex: `^\d{6}x{6}\d{4}$`)
- `Дебит BGN` (debit amount, may be empty)
- `Кредит BGN` (credit amount, may be empty)
- `Наредител/Получател` (orderer/recipient name)
- `Номер сметка на наредителя / получателя` (account number)
- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers
- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)
## App 3: auth (Authentik)
- **Mode**: Proxy mode via NPM (forward auth)
- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:
- `X-authentik-username`
- `X-authentik-email`
- `X-authentik-groups`
- **No code integration needed** in the app itself — just trust these headers from NPM
- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`
---
## What the New Combined App Must Do
1. **Single PostgreSQL database** for all transactions
2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST
3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema
4. **Unified UI** — show all payments in one table regardless of source
5. **Source indicator** in UI — badge showing "INGEST", "UPLOAD", or "BOTH" (if duplicate detection added)
6. **Source filter** in FilterBar — filter by All/Ingest/Upload
7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM
8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination
9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL
---
## Technical Constraints
- Keep Node.js backend (not Python) — extend payments-logger's stack
- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)
- File upload: use `multer` npm middleware
- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)
- Add `source` enum field (INGEST/UPLOAD) to payments schema
- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is
- Remove `users` table from schema
---
## Please Design
1. Complete folder structure for the new app (suggest name: "finance-hub" or similar — note this is a placeholder, user will confirm)
2. Prisma schema with new fields (`source`, `currency`)
3. All backend API routes
4. CSV parser design in Node.js (port of the Python logic)
5. Authentik auth middleware
6. Frontend component structure (React) — what's reused from payments-logger, what's new
7. Docker Compose setup
8. Environment variables needed
9. Step-by-step implementation order
10. Verification checklist
Be specific about file paths and code structure. This will be used to write actual implementation code.
Thinking
Thinking
Good plan. Let me ask the one thing I need before writing the final plan.
AskUserQuestion
OUT
User has answered your questions: "What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding."="finance-hub". You can now continue with the user's answers in mind.
Thinking
Thinking
Writing the final plan now.
Thinking
Thinking
Write
ets-create-a-new-generic-sun.md
ets-create-a-new-generic-sun.md
326 lines
# finance-hub — Implementation Plan
## Context
Two separate finance apps exist as references and will be retired:
- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.
- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.
The new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).
---
## Tech Stack
| Layer | Choice | Rationale |
|-------|--------|-----------|
| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |
| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |
| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |
| Database | PostgreSQL 16 | Same as payments-logger |
| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |
| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |
| Container | Docker Compose | Same pattern as both reference apps |
**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage.
**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references.
**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.
---
## Folder Structure
```
/volume2/docker/finance/finance-hub/
├── docker-compose.yml
├── .env
├── .env.example
├── .gitignore
├── backend/
│ ├── Dockerfile
│ ├── package.json
│ ├── prisma/
│ │ ├── schema.prisma
│ │ └── migrations/
│ │ ├── migration_lock.toml
│ │ └── 20260508_init/
│ │ └── migration.sql
│ └── src/
│ ├── index.js ← entry point (Authentik middleware wired here)
│ ├── auth.js ← Authentik header middleware (replaces JWT auth)
│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)
│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)
│ └── routes/
│ ├── payments.js ← existing routes + source/currency additions
│ └── upload.js ← NEW: POST /api/upload/csv
└── frontend/
├── Dockerfile
├── package.json
├── vite.config.js
├── tailwind.config.js
├── postcss.config.js
├── index.html
└── src/
├── main.jsx ← remove AuthProvider wrapper
├── index.css
├── App.jsx ← remove auth state, add Upload tab toggle
└── components/
├── FilterBar.jsx ← add source filter select
├── PaymentTable.jsx ← add Source badge column + currency display
├── PaymentCard.jsx ← minor source badge addition
├── PaymentList.jsx ← unchanged
└── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI
```
---
## Database Schema (Prisma)
File: `backend/prisma/schema.prisma`
```prisma
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
}
model Payment {
id Int @id @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
auth.js
auth.js
27 lines
const PUBLIC_PATHS = new Set([
'/api/health',
'/api/payments/ingest',
]);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) {
return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });
}
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '')
.split(',')
.map(g => g.trim())
.filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
Write
parser.js
parser.js
104 lines
/**
* Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)
*
* Supported formats:
*
* POS / INTERNET / ECOM / P2P payment:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM withdrawal:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM utility payment (amount may include fee as AMOUNT/FEE):
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.
*/
const LOCAL_TZ = process.env.TZ || 'Europe/Sofia';
/**
* Convert a local-timezone date/time to a UTC Date object.
* Uses Intl to resolve the actual UTC offset (DST-aware).
*/
function localToUtc(year, month, day, hour, minute) {
const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));
const formatter = new Intl.DateTimeFormat('en-US', {
timeZone: LOCAL_TZ,
year: 'numeric', month: '2-digit', day: '2-digit',
hour: '2-digit', minute: '2-digit', second: '2-digit',
hour12: false,
});
const parts = {};
formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });
const localAtNaive = new Date(Date.UTC(
parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),
parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),
));
const offsetMs = localAtNaive.getTime() - naive.getTime();
return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);
}
function parsePaymentSms(message) {
const result = {
rawMessage: message,
date: null,
type: null,
card: null,
recipient: null,
amount: null,
balance: null,
};
// Date and time: "Na DD/MM/YYYY v HH:MM"
const dateMatch = message.match(/Na (\d{2})\/(\d{2})\/(\d{4}) v (\d{2}):(\d{2})/i);
if (dateMatch) {
const [, day, month, year, hour, minute] = dateMatch;
result.date = localToUtc(
parseInt(year), parseInt(month), parseInt(day),
parseInt(hour), parseInt(minute),
);
}
// Card mask: "s karta 400915***4447" or "s karta 483890***7162"
const cardMatch = message.match(/s karta\s+([\d*]+)/i);
if (cardMatch) {
result.card = cardMatch[1];
}
// Transaction type: supports both prepositions
// "na POS" / "na ATM" / "na INTERNET" etc. (payment)
// "ot ATM" (withdrawal)
const typeMatch = message.match(/(?:na|ot)\s+(POS|ATM|INTERNET|ECOM|P2P)\b/i);
if (typeMatch) {
result.type = typeMatch[1].toUpperCase();
}
// Recipient address: "s adres: MERCHANT" or "s adres:MERCHANT" (no space variant)
const recipientMatch = message.match(/s adres:\s*([^.]+)\./i);
if (recipientMatch) {
result.recipient = recipientMatch[1].trim();
}
// Amount: handles both verbs and the AMOUNT/FEE suffix format
// "sa plateni 7.78 EUR"
// "sa iztegleni 400.00 EUR"
// "sa plateni 0.50 EUR/0.50 EUR" → captures 0.50 (the charged amount, ignoring fee)
const amountMatch = message.match(/sa (?:plateni|iztegleni)\s+([\d.,]+)\s+[A-Z]{3}/i);
if (amountMatch) {
result.amount = parseFloat(amountMatch[1].replace(',', '.'));
}
// Balance: "Nalichni: 2583.07 EUR."
const balanceMatch = message.match(/Nalichni:\s*([\d.,]+)\s+[A-Z]{3}/i);
if (balanceMatch) {
result.balance = parseFloat(balanceMatch[1].replace(',', '.'));
}
return result;
}
module.exports = { parsePaymentSms };
Write
csvParser.js
csvParser.js
175 lines
/**
* DSK Bank CSV parser — Node.js port of dskuploader.py
*
* DSK Bank exports use Windows-1251 (cp1251) encoding.
* Each row maps to a Payment record with source=UPLOAD, currency=BGN.
*/
const { parse } = require('csv-parse');
const iconv = require('iconv-lite');
const SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';
const CARD_REGEX = /^\d{6}x{6}\d{4}$/;
const POS_REGEX = /^\s*ПЛАЩАНЕ\s+НА\s+ПОС\s+\d{2}\.\d{2}\.\d{4}\s+\d{2}:\d{2}/;
const COL = {
DATE: 'Дата',
TYPE: 'Вид на трансакцията',
REASON: 'Основание',
DEBIT: 'Дебит BGN',
CREDIT: 'Кредит BGN',
PAYEE: 'Наредител/Получател',
ACCT: 'Номер сметка на наредителя / получателя',
};
const TAG_RULES = [
['reason', 'ЗАПЛАТА', 'Salary'],
['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],
['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],
['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],
['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],
['payee', 'VIVACOM', 'Subscriptions'],
['payee', 'Google', 'Subscriptions'],
['payee', 'SkyShowtime', 'Subscriptions'],
['payee', 'NETFLIX', 'Subscriptions'],
['payee', 'LUKOIL', 'Bills'],
['payee', 'CityGate', 'Bills'],
['payee', 'CBA', 'Groceries'],
['payee', 'FANTASTICO', 'Groceries'],
['payee', 'LIDL', 'Groceries'],
];
function parseNum(val) {
if (val == null || val === '') return null;
if (typeof val === 'number') return isNaN(val) ? null : val;
const s = String(val).trim().replace(/\xa0/g, '').replace(/ /g, '').replace(',', '.');
const n = parseFloat(s);
return isNaN(n) ? null : n;
}
function parseDate(val) {
if (!val) return null;
const s = String(val).trim();
const m = s.match(/^(\d{2})\.(\d{2})\.(\d{4})$/);
if (m) {
return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));
}
return null;
}
function processReasonAndCard(reason) {
if (!reason || typeof reason !== 'string') return { reason: '', card: null };
const parts = reason.trim().split(' ');
let card = null;
let cleanReason = reason.trim();
if (parts[0] && CARD_REGEX.test(parts[0])) {
card = parts[0];
cleanReason = parts.slice(1).join(' ').trim();
}
if (POS_REGEX.test(cleanReason)) {
const posParts = cleanReason.split('<br/>');
try {
const dateTime = posParts[0].split('ПОС ')[1];
cleanReason = `POS PAYMENT ${dateTime}`;
} catch (_) { /* keep original */ }
}
return { reason: cleanReason.replace(/\s+/g, ' ').trim(), card };
}
function generateTags(fields) {
const tags = new Set();
for (const [field, keyword, tagName] of TAG_RULES) {
if ((fields[field] || '').includes(keyword)) {
tags.add(tagName);
}
}
return Array.from(tags);
}
function processRow(row) {
const transactionType = (row[COL.TYPE] || '').trim();
if (transactionType === SKIP_TYPE) return null;
const { reason, card } = processReasonAndCard(row[COL.REASON]);
const payee = (row[COL.PAYEE] || ...
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It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"I'll explore all three reference projects in parallel to understand their structure before planning.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How data flows (ingest, storage, retrieval)\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How file uploads work - what files, what format, how parsed\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth folder and authentik integration","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. What auth system is being used (Authentik)\n2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?\n3. Middleware - how is auth enforced on routes?\n4. Any frontend auth flow - login redirect, token handling, protected routes\n5. Environment variables related to auth\n6. Docker/deployment setup for the auth service itself\n7. Any example of how other apps integrate with this auth\n\nReport with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"payments.js","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"continue","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Launching parallel exploration of all three reference projects.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How data is ingested (look at /ingest route especially)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How file uploads work (what format, what processing happens)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth project structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. What authentication system is used (authentik integration details)\n3. How OAuth/OIDC flow works\n4. Any middleware or helper functions for protecting routes\n5. Session management approach\n6. How frontend handles auth state\n7. Any example of how other apps integrate with this auth system\n8. Docker setup and environment variables\n\nPlease read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now I have a complete picture of all three. Let me design the plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design combined app architecture","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:\n\n---\n\n## App 1: payments-logger (Node.js)\n- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI\n- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS\n- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage\n- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)\n- **Schema** (PostgreSQL via Prisma):\n - `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at\n - `tags` table: id, name, color — M2M with payments via `_PaymentToTag`\n - `users` table: id, username, hashed_password (this will be REMOVED)\n- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system\n- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance\n\n## App 2: dsk-uploader (Python/Flask)\n- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database\n- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5\n- **Auth**: None (open)\n- **CSV format** (DSK Bank Bulgarian format, columns):\n - `Дата` (date, DD.MM.YYYY)\n - `Вид на трансакцията` (transaction type, Bulgarian)\n - `Основание` (reason/description — contains card number regex: `^\\d{6}x{6}\\d{4}$`)\n - `Дебит BGN` (debit amount, may be empty)\n - `Кредит BGN` (credit amount, may be empty)\n - `Наредител/Получател` (orderer/recipient name)\n - `Номер сметка на наредителя / получателя` (account number)\n- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers\n- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)\n\n## App 3: auth (Authentik)\n- **Mode**: Proxy mode via NPM (forward auth)\n- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:\n - `X-authentik-username` \n - `X-authentik-email`\n - `X-authentik-groups`\n- **No code integration needed** in the app itself — just trust these headers from NPM\n- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`\n\n---\n\n## What the New Combined App Must Do\n\n1. **Single PostgreSQL database** for all transactions\n2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST\n3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema\n4. **Unified UI** — show all payments in one table regardless of source\n5. **Source indicator** in UI — badge showing \"INGEST\", \"UPLOAD\", or \"BOTH\" (if duplicate detection added)\n6. **Source filter** in FilterBar — filter by All/Ingest/Upload\n7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM\n8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination\n9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL\n\n---\n\n## Technical Constraints\n\n- Keep Node.js backend (not Python) — extend payments-logger's stack\n- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)\n- File upload: use `multer` npm middleware\n- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)\n- Add `source` enum field (INGEST/UPLOAD) to payments schema\n- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is\n- Remove `users` table from schema\n\n---\n\n## Please Design\n\n1. Complete folder structure for the new app (suggest name: \"finance-hub\" or similar — note this is a placeholder, user will confirm)\n2. Prisma schema with new fields (`source`, `currency`)\n3. All backend API routes\n4. CSV parser design in Node.js (port of the Python logic)\n5. Authentik auth middleware\n6. Frontend component structure (React) — what's reused from payments-logger, what's new\n7. Docker Compose setup\n8. Environment variables needed\n9. Step-by-step implementation order\n10. Verification checklist\n\nBe specific about file paths and code structure. This will be used to write actual implementation code.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good plan. Let me ask the one thing I need before writing the final plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"AskUserQuestion","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"OUT","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"User has answered your questions: \"What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding.\"=\"finance-hub\". You can now continue with the user's answers in mind.","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Writing the final plan now.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"326 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# finance-hub — Implementation Plan\n\n## Context\n\nTwo separate finance apps exist as references and will be retired:\n- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.\n- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.\n\nThe new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).\n\n---\n\n## Tech Stack\n\n| Layer | Choice | Rationale |\n|-------|--------|-----------|\n| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |\n| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |\n| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |\n| Database | PostgreSQL 16 | Same as payments-logger |\n| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |\n| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |\n| Container | Docker Compose | Same pattern as both reference apps |\n\n**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage. \n**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references. \n**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.\n\n---\n\n## Folder Structure\n\n```\n/volume2/docker/finance/finance-hub/\n├── docker-compose.yml\n├── .env\n├── .env.example\n├── .gitignore\n├── backend/\n│ ├── Dockerfile\n│ ├── package.json\n│ ├── prisma/\n│ │ ├── schema.prisma\n│ │ └── migrations/\n│ │ ├── migration_lock.toml\n│ │ └── 20260508_init/\n│ │ └── migration.sql\n│ └── src/\n│ ├── index.js ← entry point (Authentik middleware wired here)\n│ ├── auth.js ← Authentik header middleware (replaces JWT auth)\n│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)\n│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)\n│ └── routes/\n│ ├── payments.js ← existing routes + source/currency additions\n│ └── upload.js ← NEW: POST /api/upload/csv\n└── frontend/\n ├── Dockerfile\n ├── package.json\n ├── vite.config.js\n ├── tailwind.config.js\n ├── postcss.config.js\n ├── index.html\n └── src/\n ├── main.jsx ← remove AuthProvider wrapper\n ├── index.css\n ├── App.jsx ← remove auth state, add Upload tab toggle\n └── components/\n ├── FilterBar.jsx ← add source filter select\n ├── PaymentTable.jsx ← add Source badge column + currency display\n ├── PaymentCard.jsx ← minor source badge addition\n ├── PaymentList.jsx ← unchanged\n └── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI\n```\n\n---\n\n## Database Schema (Prisma)\n\nFile: `backend/prisma/schema.prisma`\n\n```prisma\ngenerator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status { UNPROCESSED SENT SKIPPED }\nenum Source { INGEST UPLOAD }\n```\n\n**Key decisions:**\n- No `User` model — Authentik owns identity.\n- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.\n- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.\n- `balance` is always null for CSV rows (DSK export does not include running balance).\n- Fresh consolidated migration — no data migration from reference apps required.\n\n---\n\n## API Routes\n\n| Method | Path | Auth | Description |\n|--------|------|------|-------------|\n| GET | /api/health | public | Health check |\n| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |\n| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |\n| GET | /api/payments/meta/tags | required | All tags |\n| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |\n| GET | /api/payments/:id | required | Single payment |\n| PATCH | /api/payments/:id | required | Update status |\n| DELETE | /api/payments/:id | required | Delete |\n| POST | /api/payments/:id/send | required | Send notification |\n| POST | /api/payments/:id/skip | required | Skip |\n| POST | /api/payments/:id/tags | required | Add/upsert tag |\n| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |\n| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |\n\n---\n\n## Key Implementation Details\n\n### auth.js (replaces entire old auth module)\n```js\nconst PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n const username = req.headers['x-authentik-username'];\n if (!username) return res.status(401).json({ error: 'Unauthorized' });\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),\n };\n next();\n}\nmodule.exports = { authentikMiddleware };\n```\n\n### csvParser.js (port of dskuploader.py)\n- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8\n- `csv-parse` parses the decoded text with `columns: true`\n- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`\n- Card extraction: regex `/^\\d{6}x{6}\\d{4}$/` on first token of `Основание`\n- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`\n- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`\n- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`\n\n### payments.js changes from payments-logger\n1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call\n2. Add `source` to the `GET /` where clause filter\n3. Add `sources` to `meta/filters` response\n4. Currency-aware amount formatting in notification message\n5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)\n\n### upload.js (new)\n- `multer` memory storage, max 10 files × 10 MB\n- Calls `parseDskCsv(buffer)` per file\n- Upserts tags via `prisma.tag.upsert` then connects\n- Returns `{ imported, skipped, errors, payments[] }`\n\n### Frontend changes\n- **Delete**: `auth.js`, `AuthProvider.jsx`\n- **main.jsx**: Remove `<AuthProvider>` wrapper\n- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add \"Payments\" / \"Upload CSV\" tab toggle\n- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols\n- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell\n- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`\n\n---\n\n## Docker Compose\n\n```yaml\nservices:\n db:\n image: postgres:16-alpine\n environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: ${DB_PASSWORD}, POSTGRES_DB: finance_hub }\n volumes: [pgdata:/var/lib/postgresql/data]\n healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }\n\n backend:\n build: ./backend\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports: [\"${BACKEND_PORT:-3001}:3001\"]\n depends_on: { db: { condition: service_healthy } }\n\n frontend:\n build: ./frontend\n ports: [\"${FRONTEND_PORT:-5175}:5173\"]\n depends_on: [backend]\n\nvolumes: { pgdata: }\n```\n\n**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.\n\n---\n\n## Environment Variables (.env)\n\n```bash\nDB_PASSWORD=change_me\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\nTZ=Europe/Sofia\nBACKEND_PORT=3001\nFRONTEND_PORT=5175\n```\n\nRemoved vs payments-logger: `JWT_SECRET`, `JWT_EXPIRE_MINUTES`.\n\n---\n\n## Implementation Order\n\n1. Create folder structure and write `docker-compose.yml`, `.env.example`, `.gitignore`\n2. Write `backend/prisma/schema.prisma` and migration SQL\n3. Write `backend/package.json` (add `csv-parse`, `iconv-lite`, `multer`; remove `bcryptjs`, `jose`)\n4. Write `backend/Dockerfile`\n5. Write `backend/src/auth.js` (Authentik middleware)\n6. Copy `backend/src/parser.js` verbatim from payments-logger\n7. Write `backend/src/csvParser.js` (Python port)\n8. Write `backend/src/routes/upload.js`\n9. Write `backend/src/routes/payments.js` (from payments-logger + 5 changes listed above)\n10. Write `backend/src/index.js`\n11. Copy frontend base from payments-logger; delete `auth.js` + `AuthProvider.jsx`\n12. Update `main.jsx`, `App.jsx`, `FilterBar.jsx`, `PaymentTable.jsx`\n13. Write `frontend/src/components/UploadPanel.jsx`\n14. Update `frontend/vite.config.js`\n15. `docker compose build && docker compose up -d`\n16. Run verification checklist\n\n---\n\n## Verification\n\n**Schema**\n- `payments` table has `source`, `currency`, `debit_bgn`, `credit_bgn`, `transaction_type`, `payer_account`\n- No `users` table; `Source` enum exists\n\n**Auth**\n- `GET /api/payments` → 401 without `x-authentik-username` header\n- `POST /api/payments/ingest` → 201 without any header\n- `curl -H \"x-authentik-username: test\" localhost:3001/api/payments` → 200\n\n**SMS Ingest**\n- DSK POS SMS → `source=INGEST`, `currency=EUR`, correct amount/card/recipient\n- Apple Wallet structured body → `type=WALLET`, `source=INGEST`\n- Rate limiter → 429 after 200 req/min\n\n**CSV Upload**\n- Single DSK CSV → rows with `source=UPLOAD`, `currency=BGN`\n- Multiple CSVs in one request → all merged\n- `ТРАНСФЕР СОБСТВЕНИ СМЕТКИ` rows counted in `skipped`, not imported\n- Card regex match from `Основание` column\n- Auto-tags applied (ЗАПЛАТА→Salary, LIDL→Groceries)\n- cp1251 file imports correctly\n\n**UI**\n- Source badge visible in payment table (SMS indigo, CSV emerald)\n- Source dropdown in FilterBar filters correctly\n- Amount shows correct currency per row\n- Upload Panel: drag-and-drop works, result summary shows counts\n- Logout redirects to Authentik sign_out\n- No login form shown (Authentik handles it at NPM level)\n- Tags, send, skip, delete all still work\n\n## Reference Files\n\n- `/volume2/docker/finance/payments-logger/backend/src/routes/payments.js`\n- `/volume2/docker/finance/payments-logger/backend/src/parser.js`\n- `/volume2/docker/finance/payments-logger/backend/src/index.js`\n- `/volume2/docker/finance/payments-logger/backend/src/auth.js`\n- `/volume2/docker/finance/payments-logger/backend/prisma/schema.prisma`\n- `/volume2/docker/finance/payments-logger/frontend/src/App.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/PaymentTable.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/FilterBar.jsx`\n- `/volume2/docker/finance/dsk-uploader/dskuploader.py`\n- `/volume2/docker/finance/auth/docker-compose.yml`","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Claude’s Plan","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Stayed in plan mode","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good question. Here's the full breakdown:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Backend Tech Stack — Options","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Backend Tech Stack — Options","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Why:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"payments-logger is already Node.js/Express/Prisma. The new app is 80% payments-logger with CSV upload added on top. Keeping the same stack means:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"verbatim, zero rewrite","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy the entire","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"routes/payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with minimal edits","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Same Prisma schema workflow, same migrations, same Docker image","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The CSV parsing logic (the only Python-specific thing) ports cleanly to","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"csv-parse","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— it's just regex + string manipulation, nothing pandas-specific","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Trade-off:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Have to port the Python CSV parsing to JS. It's ~150 lines and mostly string manipulation — straightforward.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option B: Python + FastAPI + SQLAlchemy","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option B: Python + FastAPI + SQLAlchemy","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rewrite everything in Python. dsk-uploader is Python, so CSV parsing is already done.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep the dsk-uploader CSV logic as-is (no porting). Python has better data science libraries if you later add analytics.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Lose the entire payments-logger backend (routes, parser, Prisma schema) — full rewrite. FastAPI + SQLAlchemy is a different mental model than Express + Prisma. Frontend stays React anyway, so the stack split doesn't simplify anything.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"More work overall, gains almost nothing.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep Node.js as the main API, add a separate Python FastAPI service just for CSV parsing. They share the DB.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Zero porting — Python CSV code used as-is.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two backend services to maintain, deploy, and keep in sync. Inter-service HTTP calls. Two Dockerfiles. For ~150 lines of CSV logic, this is massively over-engineered.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Not worth it.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Extend dsk-uploader into a full payments app.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pandas for CSV, no porting.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Jinja2 templates instead of React (or add React separately). Would need to reimplement the entire payments-logger (SMS parser, notification system, tag management, pagination/filtering). Flask's Jinja templating is far less capable than the existing React UI. The React frontend is the stronger UI foundation.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Worst of all options — rebuild the harder parts (UI, SMS parser, notification) for no gain.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Summary","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Summary","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"CSV porting effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"App rewrite effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Result 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Everything else in the plan reuses payments-logger code directly. That's why Node.js is the clear winner here.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Want to adjust the stack, or shall I proceed with Option A?","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ok sounds good. Implement all you suggested","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Starting implementation. Let me first read all the reference files I'll need to copy from.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"payments.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"App.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"App.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"FilterBar.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"FilterBar.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentTable.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentTable.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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payments-logger.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.css","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.css","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"vite.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"vite.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"tailwind.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"tailwind.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"postcss.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"postcss.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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components.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentCard.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentCard.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentList.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentList.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"schema.prisma","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"schema.prisma","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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Let me set up the todo list and start building.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create finance-hub directory structure","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"mkdir -p /volume2/docker/finance/finance-hub/backend/src/routes \\\n /volume2/docker/finance/finance-hub/backend/prisma/migrations/20260508_init \\\n /volume2/docker/finance/finance-hub/frontend/src/components && echo \"done\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":24,"on_screen":false,"help_text":"Copy code","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"OUT","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"done","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"docker-compose.yml","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"docker-compose.yml","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"45 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"version: '3.8'\n\nservices:\n db:\n image: postgres:16-alpine\n restart: unless-stopped\n environment:\n POSTGRES_USER: finance\n POSTGRES_PASSWORD: ${DB_PASSWORD}\n POSTGRES_DB: finance_hub\n volumes:\n - pgdata:/var/lib/postgresql/data\n healthcheck:\n test: [\"CMD-SHELL\", \"pg_isready -U finance -d finance_hub\"]\n interval: 5s\n timeout: 5s\n retries: 5\n\n backend:\n build: ./backend\n restart: unless-stopped\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports:\n - \"${BACKEND_PORT:-3001}:3001\"\n depends_on:\n db:\n condition: service_healthy\n\n frontend:\n build: ./frontend\n restart: unless-stopped\n ports:\n - \"${FRONTEND_PORT:-5175}:5173\"\n depends_on:\n - backend\n\nvolumes:\n pgdata:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".env.example","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".env.example","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"15 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Database\nDB_PASSWORD=change_me_strong_password\n\n# Notifier service (for SMS payment notifications)\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\n\n# Timezone (used by SMS parser for Bulgarian bank timestamps)\nTZ=Europe/Sofia\n\n# Ports (optional — defaults shown)\nBACKEND_PORT=3001\nFRONTEND_PORT=5175","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".gitignore","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".gitignore","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"5 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env\nnode_modules/\ndist/\n*.log","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"schema.prisma","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"schema.prisma","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"54 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"generator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status {\n UNPROCESSED\n SENT\n SKIPPED\n}\n\nenum Source {\n INGEST\n UPLOAD\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration.sql","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration.sql","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"55 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- CreateEnum\nCREATE TYPE \"Status\" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');\nCREATE TYPE \"Source\" AS ENUM ('INGEST', 'UPLOAD');\n\n-- CreateTable\nCREATE TABLE \"payments\" (\n \"id\" SERIAL PRIMARY KEY,\n \"raw_message\" TEXT NOT NULL,\n \"date\" TIMESTAMP(3),\n \"type\" TEXT,\n \"card\" TEXT,\n \"recipient\" TEXT,\n \"amount\" DOUBLE PRECISION,\n \"currency\" TEXT DEFAULT 'EUR',\n \"balance\" DOUBLE PRECISION,\n \"source\" \"Source\" NOT NULL DEFAULT 'INGEST',\n \"status\" \"Status\" NOT NULL DEFAULT 'UNPROCESSED',\n \"notified_at\" TIMESTAMP(3),\n \"notify_phone\" TEXT,\n \"debit_bgn\" DOUBLE PRECISION,\n \"credit_bgn\" DOUBLE PRECISION,\n \"transaction_type\" TEXT,\n \"payer_account\" TEXT,\n \"created_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,\n \"updated_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP\n);\n\n-- CreateTable\nCREATE TABLE \"tags\" (\n \"id\" SERIAL PRIMARY KEY,\n \"name\" TEXT NOT NULL,\n \"color\" TEXT NOT NULL DEFAULT '#6b7280'\n);\n\n-- CreateUniqueIndex\nCREATE UNIQUE INDEX \"tags_name_key\" ON \"tags\"(\"name\");\n\n-- CreateTable (M2M join)\nCREATE TABLE \"_PaymentToTag\" (\n \"A\" INTEGER NOT NULL,\n \"B\" INTEGER NOT NULL,\n CONSTRAINT \"_PaymentToTag_AB_pkey\" PRIMARY KEY (\"A\", \"B\")\n);\n\nCREATE INDEX \"_PaymentToTag_B_index\" ON \"_PaymentToTag\"(\"B\");\n\n-- AddForeignKey\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_A_fkey\"\n FOREIGN KEY (\"A\") REFERENCES \"payments\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;\n\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_B_fkey\"\n FOREIGN KEY (\"B\") REFERENCES \"tags\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration_lock.toml","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration_lock.toml","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"4 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Please do not edit this file manually\n# It should be added in your version-control system (e.g., Git)\nprovider = \"postgresql\"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"26 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"{\n \"name\": \"finance-hub-backend\",\n \"version\": \"1.0.0\",\n \"main\": \"src/index.js\",\n \"scripts\": {\n \"start\": \"node src/index.js\",\n \"dev\": \"nodemon src/index.js\",\n \"prisma:generate\": \"prisma generate\",\n \"prisma:migrate\": \"prisma migrate deploy\"\n },\n \"dependencies\": {\n \"@prisma/client\": \"^5.22.0\",\n \"cors\": \"^2.8.5\",\n \"csv-parse\": \"^5.5.6\",\n \"express\": \"^4.21.1\",\n \"express-rate-limit\": \"^7.4.0\",\n \"iconv-lite\": \"^0.6.3\",\n \"morgan\": \"^1.10.0\",\n \"multer\": \"^1.4.5-lts.1\"\n },\n \"devDependencies\": {\n \"nodemon\": \"^3.1.7\",\n \"prisma\": \"^5.22.0\"\n }\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"18 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"FROM node:20-alpine\n\nRUN apk add --no-cache openssl\n\nWORKDIR /app\n\nCOPY package.json package-lock.json* ./\nRUN npm install\n\nCOPY prisma ./prisma\nRUN npx prisma generate\n\nCOPY src ./src\n\nEXPOSE 3001\n\nCMD [\"sh\", \"-c\", \"npx prisma migrate deploy && node src/index.js\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"auth.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"auth.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"27 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const PUBLIC_PATHS = new Set([\n '/api/health',\n '/api/payments/ingest',\n]);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n\n const username = req.headers['x-authentik-username'];\n if (!username) {\n return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });\n }\n\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '')\n .split(',')\n .map(g => g.trim())\n .filter(Boolean),\n };\n\n next();\n}\n\nmodule.exports = { authentikMiddleware };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"104 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/**\n * Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)\n *\n * Supported formats:\n *\n * POS / INTERNET / ECOM / P2P payment:\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.\n *\n * ATM withdrawal:\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.\n *\n * ATM utility payment (amount may include fee as AMOUNT/FEE):\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.\n */\n\nconst LOCAL_TZ = process.env.TZ || 'Europe/Sofia';\n\n/**\n * Convert a local-timezone date/time to a UTC Date object.\n * Uses Intl to resolve the actual UTC offset (DST-aware).\n */\nfunction localToUtc(year, month, day, hour, minute) {\n const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));\n\n const formatter = new Intl.DateTimeFormat('en-US', {\n timeZone: LOCAL_TZ,\n year: 'numeric', month: '2-digit', day: '2-digit',\n hour: '2-digit', minute: '2-digit', second: '2-digit',\n hour12: false,\n });\n\n const parts = {};\n formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });\n\n const localAtNaive = new Date(Date.UTC(\n parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),\n parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),\n ));\n\n const offsetMs = localAtNaive.getTime() - naive.getTime();\n return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);\n}\n\nfunction parsePaymentSms(message) {\n const result = {\n rawMessage: message,\n date: null,\n type: null,\n card: null,\n recipient: null,\n amount: null,\n balance: null,\n };\n\n // Date and time: \"Na DD/MM/YYYY v HH:MM\"\n const dateMatch = message.match(/Na (\\d{2})\\/(\\d{2})\\/(\\d{4}) v (\\d{2}):(\\d{2})/i);\n if (dateMatch) {\n const [, day, month, year, hour, minute] = dateMatch;\n result.date = localToUtc(\n parseInt(year), parseInt(month), parseInt(day),\n parseInt(hour), parseInt(minute),\n );\n }\n\n // Card mask: \"s karta 400915***4447\" or \"s karta 483890***7162\"\n const cardMatch = message.match(/s karta\\s+([\\d*]+)/i);\n if (cardMatch) {\n result.card = cardMatch[1];\n }\n\n // Transaction type: supports both prepositions\n // \"na POS\" / \"na ATM\" / \"na INTERNET\" etc. (payment)\n // \"ot ATM\" (withdrawal)\n const typeMatch = message.match(/(?:na|ot)\\s+(POS|ATM|INTERNET|ECOM|P2P)\\b/i);\n if (typeMatch) {\n result.type = typeMatch[1].toUpperCase();\n }\n\n // Recipient address: \"s adres: MERCHANT\" or \"s adres:MERCHANT\" (no space variant)\n const recipientMatch = message.match(/s adres:\\s*([^.]+)\\./i);\n if (recipientMatch) {\n result.recipient = recipientMatch[1].trim();\n }\n\n // Amount: handles both verbs and the AMOUNT/FEE suffix format\n // \"sa plateni 7.78 EUR\"\n // \"sa iztegleni 400.00 EUR\"\n // \"sa plateni 0.50 EUR/0.50 EUR\" → captures 0.50 (the charged amount, ignoring fee)\n const amountMatch = message.match(/sa (?:plateni|iztegleni)\\s+([\\d.,]+)\\s+[A-Z]{3}/i);\n if (amountMatch) {\n result.amount = parseFloat(amountMatch[1].replace(',', '.'));\n }\n\n // Balance: \"Nalichni: 2583.07 EUR.\"\n const balanceMatch = message.match(/Nalichni:\\s*([\\d.,]+)\\s+[A-Z]{3}/i);\n if (balanceMatch) {\n result.balance = parseFloat(balanceMatch[1].replace(',', '.'));\n }\n\n return result;\n}\n\nmodule.exports = { parsePaymentSms };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"csvParser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"csvParser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"175 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/**\n * DSK Bank CSV parser — Node.js port of dskuploader.py\n *\n * DSK Bank exports use Windows-1251 (cp1251) encoding.\n * Each row maps to a Payment record with source=UPLOAD, currency=BGN.\n */\n\nconst { parse } = require('csv-parse');\nconst iconv = require('iconv-lite');\n\nconst SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';\nconst CARD_REGEX = /^\\d{6}x{6}\\d{4}$/;\nconst POS_REGEX = /^\\s*ПЛАЩАНЕ\\s+НА\\s+ПОС\\s+\\d{2}\\.\\d{2}\\.\\d{4}\\s+\\d{2}:\\d{2}/;\n\nconst COL = {\n DATE: 'Дата',\n TYPE: 'Вид на трансакцията',\n REASON: 'Основание',\n DEBIT: 'Дебит BGN',\n CREDIT: 'Кредит BGN',\n PAYEE: 'Наредител/Получател',\n ACCT: 'Номер сметка на наредителя / получателя',\n};\n\nconst TAG_RULES = [\n ['reason', 'ЗАПЛАТА', 'Salary'],\n ['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],\n ['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],\n ['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],\n ['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],\n ['payee', 'VIVACOM', 'Subscriptions'],\n ['payee', 'Google', 'Subscriptions'],\n ['payee', 'SkyShowtime', 'Subscriptions'],\n ['payee', 'NETFLIX', 'Subscriptions'],\n ['payee', 'LUKOIL', 'Bills'],\n ['payee', 'CityGate', 'Bills'],\n ['payee', 'CBA', 'Groceries'],\n ['payee', 'FANTASTICO', 'Groceries'],\n ['payee', 'LIDL', 'Groceries'],\n];\n\nfunction parseNum(val) {\n if (val == null || val === '') return null;\n if (typeof val === 'number') return isNaN(val) ? null : val;\n const s = String(val).trim().replace(/\\xa0/g, '').replace(/ /g, '').replace(',', '.');\n const n = parseFloat(s);\n return isNaN(n) ? null : n;\n}\n\nfunction parseDate(val) {\n if (!val) return null;\n const s = String(val).trim();\n const m = s.match(/^(\\d{2})\\.(\\d{2})\\.(\\d{4})$/);\n if (m) {\n return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));\n }\n return null;\n}\n\nfunction processReasonAndCard(reason) {\n if (!reason || typeof reason !== 'string') return { reason: '', card: null };\n\n const parts = reason.trim().split(' ');\n let card = null;\n let cleanReason = reason.trim();\n\n if (parts[0] && CARD_REGEX.test(parts[0])) {\n card = parts[0];\n cleanReason = parts.slice(1).join(' ').trim();\n }\n\n if (POS_REGEX.test(cleanReason)) {\n const posParts = cleanReason.split('<br/>');\n try {\n const dateTime = posParts[0].split('ПОС ')[1];\n cleanReason = `POS PAYMENT ${dateTime}`;\n } catch (_) { /* keep original */ }\n }\n\n return { reason: cleanReason.replace(/\\s+/g, ' ').trim(), card };\n}\n\nfunction generateTags(fields) {\n const tags = new Set();\n for (const [field, keyword, tagName] of TAG_RULES) {\n if ((fields[field] || '').includes(keyword)) {\n tags.add(tagName);\n }\n }\n return Array.from(tags);\n}\n\nfunction processRow(row) {\n const transactionType = (row[COL.TYPE] || '').trim();\n if (transactionType === SKIP_TYPE) return null;\n\n const { reason, card } = processReasonAndCard(row[COL.REASON]);\n const payee = (row[COL.PAYEE] || '').trim();\n const payerAccount = (row[COL.ACCT] || '').trim();\n const debitBgn = parseNum(row[COL.DEBIT]);\n const creditBgn = parseNum(row[COL.CREDIT]);\n const date = parseDate(row[COL.DATE]);\n\n const autoTags = generateTags({ reason, transactionType, payee, debitBgn, creditBgn });\n\n const amount = debitBgn ?? creditBgn ?? null;\n\n const rawMessage = [\n row[COL.DATE] && `Date: ${row[COL.DATE]}`,\n transactionType && `Type: ${transactionType}`,\n payee && `Payee: ${payee}`,\n debitBgn != null && `Debit: ${debitBgn} BGN`,\n creditBgn != null && `Credit: ${creditBgn} BGN`,\n ].filter(Boolean).join(' | ');\n\n return {\n rawMessage,\n date,\n type: null,\n card,\n recipient: payee || null,\n amount,\n currency: 'BGN',\n balance: null,\n source: 'UPLOAD',\n debitBgn,\n creditBgn,\n transactionType: transactionType || null,\n payerAccount: payerAccount || null,\n autoTags,\n };\n}\n\n/**\n * Parse a Buffer containing a DSK Bank CSV (cp1251 or UTF-8).\n * Returns { rows, skipped, errors }.\n */\nasync function parseDskCsv(buffer) {\n // Try cp1251 first (DSK Bank export encoding), fall back to UTF-8\n let text = iconv.decode(buffer, 'cp1251');\n if (!text.includes(COL.DATE)) {\n text = buffer.toString('utf-8');\n }\n\n return new Promise((resolve, reject) => {\n const rows = [];\n const errors = [];\n let skipped = 0;\n\n const parser = parse(text, {\n columns: true,\n skip_empty_lines: true,\n trim: true,\n relax_column_count: true,\n });\n\n parser.on('readable', () => {\n let record;\n while ((record = parser.read()) !== null) {\n try {\n const row = processRow(record);\n if (row === null) { skipped++; } else { rows.push(row); }\n } catch (err) {\n errors.push(err.message);\n }\n }\n });\n\n parser.on('error', reject);\n parser.on('end', () => resolve({ rows, skipped, errors }));\n });\n}\n\nmodule.exports = { parseDskCsv };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"39 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst cors = require('cors');\nconst morgan = require('morgan');\nconst rateLimit = require('express-rate-limit');\nconst { authentikMiddleware } = require('./auth');\nconst paymentsRouter = require('./routes/payments');\nconst uploadRouter = require('./routes/upload');\n\nconst app = express();\nconst PORT = process.env.PORT || 3001;\n\napp.use(cors());\napp.use(express.json({ limit: '16kb' }));\napp.use(morgan('combined'));\n\n// Rate-limit the public ingest endpoint before auth middleware\nconst ingestLimiter = rateLimit({\n windowMs: 60 * 1000,\n max: 200,\n standardHeaders: true,\n legacyHeaders: false,\n message: { error: 'Too many requests, slow down' },\n});\napp.use('/api/payments/ingest', ingestLimiter);\n\n// Authentik header auth (skips /api/health and /api/payments/ingest)\napp.use(authentikMiddleware);\n\napp.get('/api/health', (_req, res) => {\n res.json({ status: 'ok', timestamp: new Date().toISOString() });\n});\n\napp.use('/api/payments', paymentsRouter);\napp.use('/api/upload', uploadRouter);\n\napp.listen(PORT, '0.0.0.0', () => {\n console.log(`Finance Hub API running on port ${PORT}`);\n});","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"payments.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"399 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst { PrismaClient } = require('@prisma/client');\nconst { parsePaymentSms } = require('../parser');\n\nconst router = express.Router();\nconst prisma = new PrismaClient();\n\nconst NOTIFIER_URL = process.env.NOTIFIER_URL;\nconst NOTIFIER_CHANNEL = process.env.NOTIFIER_CHANNEL || 'viber';\nconst DEFAULT_PHONE = process.env.NOTIFY_DEFAULT_PHONE;\n\n// ── Helpers ───────────────────────────────────────────────────────────────────\n\nfunction parseId(raw) {\n const id = parseInt(raw, 10);\n return Number.isFinite(id) ? id : null;\n}\n\nfunction formatNotifyMessage(payment) {\n const currency = payment.currency || 'EUR';\n const parts = [];\n if (payment.amount != null) parts.push(`Amount: ${payment.amount.toFixed(2)} ${currency}`);\n if (payment.recipient) parts.push(`At: ${payment.recipient}`);\n if (payment.balance != null) parts.push(`Balance: ${payment.balance.toFixed(2)} ${currency}`);\n if (payment.date) parts.push(`Date: ${new Date(payment.date).toLocaleString('en-GB')}`);\n return parts.join('\\n');\n}\n\nasync function sendNotification(payment) {\n if (!NOTIFIER_URL) {\n console.warn('[NOTIFY] NOTIFIER_URL not set — skipping notification');\n return;\n }\n\n const phone = payment.notifyPhone || DEFAULT_PHONE;\n if (!phone) {\n console.warn('[NOTIFY] No phone number for payment #' + payment.id + ' and NOTIFY_DEFAULT_PHONE not set');\n return;\n }\n\n const body = {\n phone,\n notification: NOTIFIER_CHANNEL,\n message: formatNotifyMessage(payment),\n };\n\n const res = await fetch(NOTIFIER_URL, {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify(body),\n });\n\n if (!res.ok) {\n const text = await res.text().catch(() => '');\n throw new Error(`Notifier responded ${res.status}: ${text}`);\n }\n}\n\n// ── Ingest a payment (public — no auth) ──────────────────────────────────────\n//\n// Two modes:\n//\n// SMS mode (default):\n// { \"message\": \"<raw SMS text>\", \"notifyPhone\": \"...\" }\n//\n// Structured mode (Apple Wallet / manual):\n// { \"ingestMode\": \"apple_wallet\", \"amount\": 7.78, \"recipient\": \"Apple Store\",\n// \"type\": \"WALLET\", \"card\": \"••••4447\", \"date\": \"2026-02-22T10:30:00Z\" }\n//\nrouter.post('/ingest', async (req, res) => {\n try {\n const { message, notifyPhone, ingestMode } = req.body;\n\n let data;\n\n if (ingestMode === 'apple_wallet' || (!message && req.body.amount != null)) {\n // ── Structured / Apple Wallet mode ──────────────────────────────────────\n const { amount, recipient, type, card, date, balance } = req.body;\n if (amount == null || !recipient) {\n return res.status(400).json({ error: 'amount and recipient are required for structured ingest' });\n }\n\n const rawMessage = [\n `Source: ${ingestMode || 'structured'}`,\n `Amount: ${amount}`,\n recipient && `Recipient: ${recipient}`,\n type && `Type: ${type}`,\n card && `Card: ${card}`,\n ].filter(Boolean).join(' | ');\n\n data = {\n rawMessage,\n date: date ? new Date(date) : new Date(),\n type: type || 'WALLET',\n card: card || null,\n recipient,\n amount: parseFloat(amount),\n currency: 'EUR',\n balance: balance != null ? parseFloat(balance) : null,\n source: 'INGEST',\n notifyPhone: notifyPhone || null,\n };\n\n } else {\n // ── SMS mode ─────────────────────────────────────────────────────────────\n if (!message) {\n return res.status(400).json({ error: 'message is required' });\n }\n if (typeof message !== 'string' || message.length > 2000) {\n return res.status(400).json({ error: 'message must be a string under 2000 characters' });\n }\n\n const parsed = parsePaymentSms(message);\n data = {\n rawMessage: parsed.rawMessage,\n date: parsed.date,\n type: parsed.type,\n card: parsed.card,\n recipient: parsed.recipient,\n amount: parsed.amount,\n currency: 'EUR',\n balance: parsed.balance,\n source: 'INGEST',\n notifyPhone: notifyPhone || null,\n };\n }\n\n const payment = await prisma.payment.create({\n data,\n include: { tags: true },\n });\n\n res.status(201).json(payment);\n } catch (err) {\n console.error('Ingest error:', err);\n res.status(500).json({ error: 'Failed to ingest payment' });\n }\n});\n\n// ── List payments with filtering ──────────────────────────────────────────────\nrouter.get('/', async (req, res) => {\n try {\n const {\n status,\n type,\n tag,\n source,\n recipient,\n dateFrom,\n dateTo,\n search,\n sortBy = 'createdAt',\n sortDir = 'desc',\n page = 1,\n } = req.query;\n\n const limit = Math.min(parseInt(req.query.limit, 10) || 50, 200);\n\n const where = {};\n\n if (status) where.status = status;\n if (type) where.type = type;\n if (source) where.source = source;\n if (recipient) where.recipient = { contains: recipient, mode: 'insensitive' };\n if (tag) where.tags = { some: { name: tag } };\n if (search) {\n where.OR = [\n { rawMessage: { contains: search, mode: 'insensitive' } },\n { recipient: { contains: search, mode: 'insensitive' } },\n ];\n }\n if (dateFrom || dateTo) {\n where.date = {};\n if (dateFrom) where.date.gte = new Date(dateFrom);\n if (dateTo) where.date.lte = new Date(dateTo);\n }\n\n const allowedSortFields = ['date', 'amount', 'balance', 'recipient', 'type', 'source', 'createdAt', 'status'];\n const orderField = allowedSortFields.includes(sortBy) ? sortBy : 'createdAt';\n const orderDir = sortDir === 'asc' ? 'asc' : 'desc';\n\n const skip = (parseInt(page, 10) - 1) * limit;\n\n const [payments, total] = await Promise.all([\n prisma.payment.findMany({\n where,\n include: { tags: true },\n orderBy: { [orderField]: orderDir },\n skip,\n take: limit,\n }),\n prisma.payment.count({ where }),\n ]);\n\n res.json({ payments, total, page: parseInt(page, 10), limit });\n } catch (err) {\n console.error('List error:', err);\n res.status(500).json({ error: 'Failed to list payments' });\n }\n});\n\n// ── Get filter options ────────────────────────────────────────────────────────\nrouter.get('/meta/filters', async (_req, res) => {\n try {\n const [types, recipients, tags, sources] = await Promise.all([\n prisma.payment.findMany({ distinct: ['type'], select: { type: true }, where: { type: { not: null } } }),\n prisma.payment.findMany({ distinct: ['recipient'], select: { recipient: true }, where: { recipient: { not: null } } }),\n prisma.tag.findMany({ orderBy: { name: 'asc' } }),\n prisma.payment.findMany({ distinct: ['source'], select: { source: true } }),\n ]);\n\n res.json({\n types: types.map(t => t.type),\n recipients: recipients.map(r => r.recipient),\n tags,\n sources: sources.map(s => s.source),\n });\n } catch (err) {\n res.status(500).json({ error: 'Failed to get filters' });\n }\n});\n\n// ── Get all tags ──────────────────────────────────────────────────────────────\nrouter.get('/meta/tags', async (_req, res) => {\n try {\n const tags = await prisma.tag.findMany({ orderBy: { name: 'asc' } });\n res.json(tags);\n } catch (err) {\n res.status(500).json({ error: 'Failed to list tags' });\n }\n});\n\n// ── Get single payment ────────────────────────────────────────────────────────\nrouter.get('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({\n where: { id },\n include: { tags: true },\n });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n res.json(payment);\n } catch (err) {\n console.error('Get error:', err);\n res.status(500).json({ error: 'Failed to get payment' });\n }\n});\n\n// ── Update payment metadata (status) ─────────────────────────────────────────\nrouter.patch('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const { status } = req.body;\n const data = {};\n\n if (status) {\n const validStatuses = ['UNPROCESSED', 'SENT', 'SKIPPED'];\n if (!validStatuses.includes(status)) {\n return res.status(400).json({ error: `Invalid status. Must be one of: ${validStatuses.join(', ')}` });\n }\n data.status = status;\n }\n\n if (Object.keys(data).length === 0) {\n return res.status(400).json({ error: 'No valid fields to update' });\n }\n\n const updated = await prisma.payment.update({\n where: { id },\n data,\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n if (err.code === 'P2025') return res.status(404).json({ error: 'Not found' });\n console.error('Update error:', err);\n res.status(500).json({ error: 'Failed to update payment' });\n }\n});\n\n// ── Delete payment ───────────────────────────────────────────────────────────\nrouter.delete('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n await prisma.payment.delete({ where: { id } });\n res.json({ success: true });\n } catch (err) {\n if (err.code === 'P2025') return res.status(404).json({ error: 'Not found' });\n console.error('Delete error:', err);\n res.status(500).json({ error: 'Failed to delete payment' });\n }\n});\n\n// ── Send notification (mark as SENT + call notifier service) ─────────────────\nrouter.post('/:id/send', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({ where: { id } });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n if (payment.status !== 'UNPROCESSED') {\n return res.status(409).json({ error: `Payment is already ${payment.status.toLowerCase()}` });\n }\n\n await sendNotification(payment);\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { status: 'SENT', notifiedAt: new Date() },\n include: { tags: true },\n });\n\n res.json(updated);\n } catch (err) {\n console.error('Send error:', err);\n res.status(500).json({ error: 'Failed to send notification' });\n }\n});\n\n// ── Skip notification (mark as SKIPPED) ──────────────────────────────────────\nrouter.post('/:id/skip', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({ where: { id } });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n if (payment.status !== 'UNPROCESSED') {\n return res.status(409).json({ error: `Payment is already ${payment.status.toLowerCase()}` });\n }\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { status: 'SKIPPED' },\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n console.error('Skip error:', err);\n res.status(500).json({ error: 'Failed to skip payment' });\n }\n});\n\n// ── Add tag to payment ────────────────────────────────────────────────────────\nrouter.post('/:id/tags', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const { name, color } = req.body;\n if (!name) return res.status(400).json({ error: 'tag name is required' });\n\n const tag = await prisma.tag.upsert({\n where: { name },\n update: {},\n create: { name, color: color || '#6b7280' },\n });\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { tags: { connect: { id: tag.id } } },\n include: { tags: true },\n });\n\n res.json(updated);\n } catch (err) {\n console.error('Tag error:', err);\n res.status(500).json({ error: 'Failed to add tag' });\n }\n});\n\n// ── Remove tag from payment ───────────────────────────────────────────────────\nrouter.delete('/:id/tags/:tagId', async (req, res) => {\n const id = parseId(req.params.id);\n const tagId = parseId(req.params.tagId);\n if (id === null || tagId === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const updated = await prisma.payment.update({\n where: { id },\n data: { tags: { disconnect: { id: tagId } } },\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n console.error('Remove tag error:', err);\n res.status(500).json({ error: 'Failed to remove tag' });\n }\n});\n\nmodule.exports = router;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"upload.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"upload.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"89 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst multer = require('multer');\nconst { PrismaClient } = require('@prisma/client');\nconst { parseDskCsv } = require('../csvParser');\n\nconst router = express.Router();\nconst prisma = new PrismaClient();\n\nconst upload = multer({\n storage: multer.memoryStorage(),\n limits: { fileSize: 10 * 1024 * 1024, files: 10 },\n fileFilter: (_req, file, cb) => {\n if (file.mimetype === 'text/csv' || file.originalname.toLowerCase().endsWith('.csv')) {\n cb(null, true);\n } else {\n cb(new Error('Only CSV files are accepted'));\n }\n },\n});\n\n// POST /api/upload/csv\n// Accepts 1-10 CSV files, parses them, stores to DB with source=UPLOAD.\n// Returns { imported, skipped, errors, payments[] }\nrouter.post('/csv', upload.array('files', 10), async (req, res) => {\n if (!req.files || req.files.length === 0) {\n return res.status(400).json({ error: 'No files uploaded' });\n }\n\n const allRows = [];\n const allErrors = [];\n let totalSkipped = 0;\n\n for (const file of req.files) {\n try {\n const { rows, skipped, errors } = await parseDskCsv(file.buffer);\n allRows.push(...rows);\n totalSkipped += skipped;\n allErrors.push(...errors.map(e => `${file.originalname}: ${e}`));\n } catch (err) {\n allErrors.push(`${file.originalname}: ${err.message}`);\n }\n }\n\n if (allRows.length === 0) {\n return res.status(422).json({\n error: 'No importable rows found',\n skipped: totalSkipped,\n errors: allErrors,\n });\n }\n\n const created = [];\n\n for (const row of allRows) {\n const { autoTags, ...paymentData } = row;\n try {\n const tagConnects = [];\n for (const tagName of autoTags) {\n const tag = await prisma.tag.upsert({\n where: { name: tagName },\n update: {},\n create: { name: tagName, color: '#6b7280' },\n });\n tagConnects.push({ id: tag.id });\n }\n\n const payment = await prisma.payment.create({\n data: {\n ...paymentData,\n ...(tagConnects.length ? { tags: { connect: tagConnects } } : {}),\n },\n include: { tags: true },\n });\n created.push(payment);\n } catch (err) {\n allErrors.push(`Row insert failed: ${err.message}`);\n }\n }\n\n res.status(201).json({\n imported: created.length,\n skipped: totalSkipped,\n errors: allErrors,\n payments: created,\n });\n});\n\nmodule.exports = router;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now writing all frontend config files:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"24 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"{\n \"name\": \"finance-hub-frontend\",\n \"version\": \"1.0.0\",\n \"type\": \"module\",\n \"scripts\": {\n \"dev\": \"vite\",\n \"build\": \"vite build\",\n \"preview\": \"vite preview\"\n },\n \"dependencies\": {\n \"lucide-react\": \"^0.460.0\",\n \"react\": \"^18.3.1\",\n \"react-dom\": \"^18.3.1\"\n },\n \"devDependencies\": {\n \"@types/react\": \"^18.3.12\",\n \"@vitejs/plugin-react\": \"^4.3.4\",\n \"autoprefixer\": \"^10.4.20\",\n \"postcss\": \"^8.4.49\",\n \"tailwindcss\": \"^3.4.15\",\n \"vite\": \"^6.0.1\"\n }\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"FROM node:20-alpine\n\nWORKDIR /app\n\nCOPY package.json package-lock.json* ./\nRUN npm install\n\nCOPY . .\n\nEXPOSE 5173\n\nCMD [\"npm\", \"run\", \"dev\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"vite.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"vite.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"18 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import { defineConfig } from 'vite';\nimport react from '@vitejs/plugin-react';\n\nexport default defineConfig({\n plugins: [react()],\n server: {\n host: '0.0.0.0',\n port: 5173,\n allowedHosts: ['finance-hub.lakylak.xyz'],\n proxy: {\n '/api': {\n target: 'http://backend:3001',\n changeOrigin: true,\n },\n },\n },\n});","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"tailwind.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"tailwind.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"12 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/** @type {import('tailwindcss').Config} */\nexport default {\n content: [\n \"./index.html\",\n \"./src/**/*.{js,ts,jsx,tsx}\",\n ],\n theme: {\n extend: {},\n },\n plugins: [],\n};","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"postcss.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"postcss.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"7 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"export default {\n plugins: {\n tailwindcss: {},\n autoprefixer: {},\n },\n};","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.html","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.html","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"14 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"<!DOCTYPE html>\n<html lang=\"en\">\n <head>\n <meta charset=\"UTF-8\" />\n <meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\" />\n <title>Finance Hub</title>\n <link rel=\"icon\" type=\"image/svg+xml\" href=\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 100 100'><text y='.9em' font-size='90'>💰</text></svg>\" />\n </head>\n <body class=\"bg-gray-50 min-h-screen\">\n <div id=\"root\"></div>\n <script type=\"module\" src=\"/src/main.jsx\"></script>\n </body>\n</html>","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.css","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.css","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"4 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"@tailwind base;\n@tailwind components;\n@tailwind utilities;","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now writing all React components:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"11 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React from 'react';\nimport ReactDOM from 'react-dom/client';\nimport App from './App';\nimport './index.css';\n\nReactDOM.createRoot(document.getElementById('root')).render(\n <React.StrictMode>\n <App />\n </React.StrictMode>\n);","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"App.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"App.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"257 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState, useEffect, useCallback } from 'react';\nimport { LayoutDashboard, Upload, RefreshCw, LogOut } from 'lucide-react';\nimport FilterBar from './components/FilterBar';\nimport PaymentTable from './components/PaymentTable';\nimport UploadPanel from './components/UploadPanel';\n\nconst API_BASE = '/api/payments';\n\nexport default function App() {\n const [activeTab, setActiveTab] = useState('payments');\n const [payments, setPayments] = useState([]);\n const [total, setTotal] = useState(0);\n const [page, setPage] = useState(1);\n const [filters, setFilters] = useState({});\n const [sortBy, setSortBy] = useState('createdAt');\n const [sortDir, setSortDir] = useState('desc');\n const [filterOptions, setFilterOptions] = useState({ types: [], recipients: [], tags: [], sources: [] });\n const [loading, setLoading] = useState(false);\n\n const fetchPayments = useCallback(async () => {\n setLoading(true);\n try {\n const params = new URLSearchParams();\n params.set('page', page);\n params.set('limit', 50);\n params.set('sortBy', sortBy);\n params.set('sortDir', sortDir);\n Object.entries(filters).forEach(([key, val]) => {\n if (val) params.set(key, val);\n });\n const res = await fetch(`${API_BASE}?${params}`);\n const data = await res.json();\n setPayments(data.payments || []);\n setTotal(data.total || 0);\n } catch (err) {\n console.error('Failed to fetch payments:', err);\n } finally {\n setLoading(false);\n }\n }, [page, filters, sortBy, sortDir]);\n\n const fetchFilterOptions = useCallback(async () => {\n try {\n const res = await fetch(`${API_BASE}/meta/filters`);\n const data = await res.json();\n setFilterOptions(data);\n } catch (err) {\n console.error('Failed to fetch filter options:', err);\n }\n }, []);\n\n useEffect(() => {\n fetchPayments();\n }, [fetchPayments]);\n\n useEffect(() => {\n fetchFilterOptions();\n }, [fetchFilterOptions]);\n\n // Refresh payments list after a successful CSV upload\n const handleUploadSuccess = () => {\n fetchPayments();\n fetchFilterOptions();\n setActiveTab('payments');\n };\n\n const handleAction = async (id, action) => {\n try {\n await fetch(`${API_BASE}/${id}/${action}`, { method: 'POST' });\n fetchPayments();\n fetchFilterOptions();\n } catch (err) {\n console.error(`Failed to ${action} payment:`, err);\n }\n };\n\n const handleAddTag = async (id, tagName, tagColor) => {\n try {\n await fetch(`${API_BASE}/${id}/tags`, {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify({ name: tagName, color: tagColor }),\n });\n fetchPayments();\n fetchFilterOptions();\n } catch (err) {\n console.error('Failed to add tag:', err);\n }\n };\n\n const handleRemoveTag = async (paymentId, tagId) => {\n try {\n await fetch(`${API_BASE}/${paymentId}/tags/${tagId}`, { method: 'DELETE' });\n fetchPayments();\n } catch (err) {\n console.error('Failed to remove tag:', err);\n }\n };\n\n const handleDelete = async (id) => {\n try {\n await fetch(`${API_BASE}/${id}`, { method: 'DELETE' });\n fetchPayments();\n fetchFilterOptions();\n } catch (err) {\n console.error('Failed to delete payment:', err);\n }\n };\n\n const handleUpdateStatus = async (id, status) => {\n try {\n await fetch(`${API_BASE}/${id}`, {\n method: 'PATCH',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify({ status }),\n });\n fetchPayments();\n } catch (err) {\n console.error('Failed to update status:', err);\n }\n };\n\n const handleFilterChange = (newFilters) => {\n setFilters(newFilters);\n setPage(1);\n };\n\n const handleSort = (field) => {\n if (sortBy === field) {\n setSortDir(d => d === 'asc' ? 'desc' : 'asc');\n } else {\n setSortBy(field);\n setSortDir('desc');\n }\n setPage(1);\n };\n\n const totalPages = Math.ceil(total / 50);\n\n return (\n <div className=\"min-h-screen bg-gray-50\">\n <header className=\"bg-white border-b border-gray-200 shadow-sm\">\n <div className=\"max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-4\">\n <div className=\"flex items-center justify-between\">\n <div className=\"flex items-center gap-3\">\n <div className=\"bg-indigo-600 p-2 rounded-lg\">\n <LayoutDashboard className=\"w-6 h-6 text-white\" />\n </div>\n <div>\n <h1 className=\"text-xl font-bold text-gray-900\">Finance Hub</h1>\n <p className=\"text-sm text-gray-500\">{total} transaction{total !== 1 ? 's' : ''} total</p>\n </div>\n </div>\n\n <div className=\"flex items-center gap-2\">\n {/* Tab switcher */}\n <div className=\"flex items-center rounded-lg border border-gray-200 bg-gray-50 p-1 gap-1\">\n <button\n onClick={() => setActiveTab('payments')}\n className={`flex items-center gap-1.5 px-3 py-1.5 text-sm font-medium rounded-md transition-colors ${\n activeTab === 'payments'\n ? 'bg-white text-indigo-700 shadow-sm'\n : 'text-gray-600 hover:text-gray-900'\n }`}\n >\n <LayoutDashboard className=\"w-4 h-4\" />\n Payments\n </button>\n <button\n onClick={() => setActiveTab('upload')}\n className={`flex items-center gap-1.5 px-3 py-1.5 text-sm font-medium rounded-md transition-colors ${\n activeTab === 'upload'\n ? 'bg-white text-emerald-700 shadow-sm'\n : 'text-gray-600 hover:text-gray-900'\n }`}\n >\n <Upload className=\"w-4 h-4\" />\n Upload CSV\n </button>\n </div>\n\n {activeTab === 'payments' && (\n <button\n onClick={() => { fetchPayments(); fetchFilterOptions(); }}\n className=\"flex items-center gap-2 px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 transition-colors\"\n >\n <RefreshCw className={`w-4 h-4 ${loading ? 'animate-spin' : ''}`} />\n Refresh\n </button>\n )}\n\n <button\n onClick={() => { window.location.href = '/outpost.goauthentik.io/sign_out'; }}\n className=\"flex items-center gap-2 px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 transition-colors\"\n title=\"Sign out\"\n >\n <LogOut className=\"w-4 h-4\" />\n </button>\n </div>\n </div>\n </div>\n </header>\n\n <main className=\"max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-6\">\n {activeTab === 'payments' ? (\n <>\n <FilterBar\n filters={filters}\n filterOptions={filterOptions}\n onFilterChange={handleFilterChange}\n />\n\n <PaymentTable\n payments={payments}\n loading={loading}\n sortBy={sortBy}\n sortDir={sortDir}\n onSort={handleSort}\n onSend={(id) => handleAction(id, 'send')}\n onSkip={(id) => handleAction(id, 'skip')}\n onAddTag={handleAddTag}\n onRemoveTag={handleRemoveTag}\n onDelete={handleDelete}\n onUpdateStatus={handleUpdateStatus}\n existingTags={filterOptions.tags}\n />\n\n {totalPages > 1 && (\n <div className=\"flex items-center justify-center gap-2 mt-6\">\n <button\n onClick={() => setPage(p => Math.max(1, p - 1))}\n disabled={page === 1}\n className=\"px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 disabled:opacity-50 disabled:cursor-not-allowed\"\n >\n Previous\n </button>\n <span className=\"text-sm text-gray-600\">\n Page {page} of {totalPages}\n </span>\n <button\n onClick={() => setPage(p => Math.min(totalPages, p + 1))}\n disabled={page === totalPages}\n className=\"px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 disabled:opacity-50 disabled:cursor-not-allowed\"\n >\n Next\n </button>\n </div>\n )}\n </>\n ) : (\n <UploadPanel onUploadSuccess={handleUploadSuccess} />\n )}\n </main>\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"FilterBar.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"FilterBar.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"167 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState, useEffect } from 'react';\nimport { Search, Filter, X, Calendar, ChevronDown, ChevronUp } from 'lucide-react';\n\nconst STATUS_OPTIONS = [\n { value: '', label: 'All Statuses' },\n { value: 'UNPROCESSED', label: 'Unprocessed' },\n { value: 'SENT', label: 'Sent' },\n { value: 'SKIPPED', label: 'Skipped' },\n];\n\nconst SOURCE_OPTIONS = [\n { value: '', label: 'All Sources' },\n { value: 'INGEST', label: 'SMS Ingest' },\n { value: 'UPLOAD', label: 'CSV Upload' },\n];\n\nexport default function FilterBar({ filters, filterOptions, onFilterChange }) {\n const [search, setSearch] = useState(filters.search || '');\n const [isOpen, setIsOpen] = useState(() => window.innerWidth >= 768);\n\n useEffect(() => {\n const mq = window.matchMedia('(min-width: 768px)');\n const handler = (e) => setIsOpen(e.matches);\n mq.addEventListener('change', handler);\n return () => mq.removeEventListener('change', handler);\n }, []);\n\n const handleSearchSubmit = (e) => {\n e.preventDefault();\n onFilterChange({ ...filters, search: search || undefined });\n };\n\n const handleSelectChange = (key, value) => {\n const newFilters = { ...filters };\n if (value) {\n newFilters[key] = value;\n } else {\n delete newFilters[key];\n }\n onFilterChange(newFilters);\n };\n\n const clearFilters = () => {\n setSearch('');\n onFilterChange({});\n };\n\n const activeFilterCount = Object.keys(filters).length;\n const hasActiveFilters = activeFilterCount > 0;\n\n return (\n <div className=\"bg-white rounded-xl border border-gray-200 shadow-sm p-4 mb-6\">\n <button\n onClick={() => setIsOpen(!isOpen)}\n className=\"w-full flex items-center gap-2\"\n >\n <Filter className=\"w-4 h-4 text-gray-500\" />\n <span className=\"text-sm font-medium text-gray-700\">Filters</span>\n {hasActiveFilters && (\n <span className=\"inline-flex items-center justify-center w-5 h-5 text-xs font-bold text-white bg-indigo-600 rounded-full\">\n {activeFilterCount}\n </span>\n )}\n {hasActiveFilters && (\n <span\n onClick={(e) => { e.stopPropagation(); clearFilters(); }}\n className=\"ml-1 flex items-center gap-1 text-xs text-red-600 hover:text-red-700\"\n >\n <X className=\"w-3 h-3\" />\n Clear\n </span>\n )}\n <span className=\"ml-auto\">\n {isOpen\n ? <ChevronUp className=\"w-4 h-4 text-gray-400\" />\n : <ChevronDown className=\"w-4 h-4 text-gray-400\" />\n }\n </span>\n </button>\n\n {isOpen && (\n <div className=\"space-y-3 mt-3 pt-3 border-t border-gray-100\">\n <div className=\"grid grid-cols-1 sm:grid-cols-2 lg:grid-cols-5 gap-3\">\n <form onSubmit={handleSearchSubmit} className=\"relative\">\n <Search className=\"absolute left-3 top-1/2 -translate-y-1/2 w-4 h-4 text-gray-400\" />\n <input\n type=\"text\"\n placeholder=\"Search...\"\n value={search}\n onChange={(e) => setSearch(e.target.value)}\n onBlur={() => onFilterChange({ ...filters, search: search || undefined })}\n className=\"w-full pl-9 pr-3 py-2 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none\"\n />\n </form>\n\n <select\n value={filters.source || ''}\n onChange={(e) => handleSelectChange('source', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n {SOURCE_OPTIONS.map(opt => (\n <option key={opt.value} value={opt.value}>{opt.label}</option>\n ))}\n </select>\n\n <select\n value={filters.status || ''}\n onChange={(e) => handleSelectChange('status', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n {STATUS_OPTIONS.map(opt => (\n <option key={opt.value} value={opt.value}>{opt.label}</option>\n ))}\n </select>\n\n <select\n value={filters.type || ''}\n onChange={(e) => handleSelectChange('type', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n <option value=\"\">All Types</option>\n {(filterOptions.types || []).map(t => (\n <option key={t} value={t}>{t}</option>\n ))}\n </select>\n\n <select\n value={filters.tag || ''}\n onChange={(e) => handleSelectChange('tag', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n <option value=\"\">All Tags</option>\n {(filterOptions.tags || []).map(t => (\n <option key={t.id} value={t.name}>{t.name}</option>\n ))}\n </select>\n </div>\n\n <div className=\"grid grid-cols-1 sm:grid-cols-2 gap-3\">\n <div className=\"relative\">\n <Calendar className=\"absolute left-3 top-1/2 -translate-y-1/2 w-4 h-4 text-gray-400\" />\n <input\n type=\"date\"\n placeholder=\"From date\"\n value={filters.dateFrom || ''}\n onChange={(e) => handleSelectChange('dateFrom', e.target.value)}\n className=\"w-full pl-9 pr-3 py-2 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none\"\n />\n </div>\n\n <div className=\"relative\">\n <Calendar className=\"absolute left-3 top-1/2 -translate-y-1/2 w-4 h-4 text-gray-400\" />\n <input\n type=\"date\"\n placeholder=\"To date\"\n value={filters.dateTo || ''}\n onChange={(e) => handleSelectChange('dateTo', e.target.value)}\n className=\"w-full pl-9 pr-3 py-2 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none\"\n />\n </div>\n </div>\n </div>\n )}\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentTable.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentTable.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"339 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState } from 'react';\nimport {\n ArrowUpDown, ArrowUp, ArrowDown,\n Send, XCircle, CheckCircle, MinusCircle, Clock,\n Inbox, Plus, X, ChevronDown, ChevronUp, Trash2,\n} from 'lucide-react';\n\nconst STATUS_CONFIG = {\n UNPROCESSED: { label: 'Unprocessed', icon: Clock, color: 'bg-amber-100 text-amber-700' },\n SENT: { label: 'Sent', icon: CheckCircle, color: 'bg-green-100 text-green-700' },\n SKIPPED: { label: 'Skipped', icon: MinusCircle, color: 'bg-gray-100 text-gray-500' },\n};\n\nconst TAG_COLORS = [\n '#ef4444', '#f97316', '#eab308', '#22c55e', '#06b6d4',\n '#3b82f6', '#8b5cf6', '#ec4899', '#6b7280',\n];\n\nconst COLUMNS = [\n { key: 'date', label: 'Date & Time', sortable: true },\n { key: 'source', label: 'Source', sortable: true },\n { key: 'type', label: 'Type', sortable: true },\n { key: 'recipient', label: 'Recipient', sortable: true },\n { key: 'amount', label: 'Amount', sortable: true },\n { key: 'balance', label: 'Balance', sortable: true },\n { key: 'status', label: 'Status', sortable: true },\n { key: 'tags', label: 'Tags', sortable: false },\n { key: 'actions', label: 'Actions', sortable: false },\n];\n\nfunction SortIcon({ column, sortBy, sortDir }) {\n if (sortBy !== column) return <ArrowUpDown className=\"w-3 h-3 text-gray-400\" />;\n return sortDir === 'asc'\n ? <ArrowUp className=\"w-3 h-3 text-indigo-600\" />\n : <ArrowDown className=\"w-3 h-3 text-indigo-600\" />;\n}\n\nfunction SourceBadge({ source }) {\n if (source === 'UPLOAD') {\n return (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-emerald-50 text-emerald-700\">\n CSV\n </span>\n );\n }\n return (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-indigo-50 text-indigo-700\">\n SMS\n </span>\n );\n}\n\nfunction TagCell({ payment, onAddTag, onRemoveTag, existingTags }) {\n const [open, setOpen] = useState(false);\n const [newTagName, setNewTagName] = useState('');\n const [newTagColor, setNewTagColor] = useState('#3b82f6');\n\n const paymentTags = payment.tags || [];\n const availableTags = existingTags.filter(t => !paymentTags.some(pt => pt.id === t.id));\n\n const handleAdd = (e) => {\n e.preventDefault();\n if (newTagName.trim()) {\n onAddTag(payment.id, newTagName.trim(), newTagColor);\n setNewTagName('');\n setOpen(false);\n }\n };\n\n return (\n <div className=\"flex flex-wrap items-center gap-1\">\n {paymentTags.map(tag => (\n <span\n key={tag.id}\n className=\"inline-flex items-center gap-0.5 px-1.5 py-0.5 text-xs font-medium rounded-full text-white\"\n style={{ backgroundColor: tag.color }}\n >\n {tag.name}\n <button onClick={() => onRemoveTag(payment.id, tag.id)} className=\"hover:opacity-75\">\n <X className=\"w-2.5 h-2.5\" />\n </button>\n </span>\n ))}\n <div className=\"relative\">\n <button\n onClick={() => setOpen(!open)}\n className=\"inline-flex items-center gap-0.5 px-1.5 py-0.5 text-xs text-gray-500 border border-dashed border-gray-300 rounded-full hover:border-gray-400\"\n >\n <Plus className=\"w-2.5 h-2.5\" />\n </button>\n {open && (\n <div className=\"absolute z-20 top-full left-0 mt-1 bg-white border border-gray-200 rounded-lg shadow-lg p-2 w-56\">\n <form onSubmit={handleAdd} className=\"flex items-center gap-1 mb-2\">\n <input\n type=\"text\"\n value={newTagName}\n onChange={(e) => setNewTagName(e.target.value)}\n placeholder=\"New tag\"\n autoFocus\n className=\"flex-1 px-2 py-1 text-xs border border-gray-300 rounded focus:ring-1 focus:ring-indigo-500 outline-none\"\n />\n <button type=\"submit\" className=\"text-xs text-indigo-600 font-medium hover:text-indigo-700 whitespace-nowrap\">Add</button>\n </form>\n <div className=\"flex gap-1 mb-2\">\n {TAG_COLORS.map(c => (\n <button\n key={c}\n type=\"button\"\n onClick={() => setNewTagColor(c)}\n className={`w-4 h-4 rounded-full border-2 ${newTagColor === c ? 'border-gray-800' : 'border-transparent'}`}\n style={{ backgroundColor: c }}\n />\n ))}\n </div>\n {availableTags.length > 0 && (\n <div className=\"border-t border-gray-100 pt-1 flex flex-wrap gap-1\">\n {availableTags.map(tag => (\n <button\n key={tag.id}\n onClick={() => { onAddTag(payment.id, tag.name, tag.color); setOpen(false); }}\n className=\"px-1.5 py-0.5 text-xs rounded-full border border-gray-200 text-gray-600 hover:bg-gray-100\"\n >\n {tag.name}\n </button>\n ))}\n </div>\n )}\n </div>\n )}\n </div>\n </div>\n );\n}\n\nfunction ExpandedRow({ payment }) {\n return (\n <tr className=\"bg-gray-50\">\n <td colSpan={COLUMNS.length} className=\"px-4 py-3\">\n <div className=\"text-xs text-gray-500 uppercase tracking-wide mb-1\">Original Message / Raw Data</div>\n <p className=\"text-sm text-gray-700 whitespace-pre-wrap break-words\">{payment.rawMessage}</p>\n {payment.debitBgn != null && (\n <p className=\"text-xs text-gray-500 mt-1\">Debit: {payment.debitBgn.toFixed(2)} BGN</p>\n )}\n {payment.creditBgn != null && (\n <p className=\"text-xs text-gray-500 mt-0.5\">Credit: {payment.creditBgn.toFixed(2)} BGN</p>\n )}\n {payment.transactionType && (\n <p className=\"text-xs text-gray-500 mt-0.5\">Transaction type: {payment.transactionType}</p>\n )}\n {payment.payerAccount && (\n <p className=\"text-xs text-gray-500 mt-0.5\">Account: {payment.payerAccount}</p>\n )}\n {payment.notifiedAt && (\n <p className=\"text-xs text-green-600 mt-2\">\n Notified on {new Date(payment.notifiedAt).toLocaleString('en-GB')}\n {payment.notifyPhone && ` to ${payment.notifyPhone}`}\n </p>\n )}\n </td>\n </tr>\n );\n}\n\nfunction StatusCell({ payment, onUpdateStatus }) {\n const [open, setOpen] = useState(false);\n const statusCfg = STATUS_CONFIG[payment.status] || STATUS_CONFIG.UNPROCESSED;\n const StatusIcon = statusCfg.icon;\n\n return (\n <div className=\"relative\">\n <button\n onClick={() => setOpen(!open)}\n className={`inline-flex items-center gap-1 px-2 py-0.5 text-xs font-medium rounded-full cursor-pointer ${statusCfg.color}`}\n >\n <StatusIcon className=\"w-3 h-3\" />\n {statusCfg.label}\n </button>\n {open && (\n <div className=\"absolute z-20 top-full left-0 mt-1 bg-white border border-gray-200 rounded-lg shadow-lg py-1 w-36\">\n {Object.entries(STATUS_CONFIG).map(([key, cfg]) => {\n const Icon = cfg.icon;\n return (\n <button\n key={key}\n onClick={() => { onUpdateStatus(payment.id, key); setOpen(false); }}\n className={`w-full flex items-center gap-2 px-3 py-1.5 text-xs hover:bg-gray-50 ${payment.status === key ? 'font-bold' : ''}`}\n >\n <Icon className=\"w-3 h-3\" />\n {cfg.label}\n </button>\n );\n })}\n </div>\n )}\n </div>\n );\n}\n\nexport default function PaymentTable({\n payments, loading, sortBy, sortDir, onSort,\n onSend, onSkip, onAddTag, onRemoveTag, onDelete, onUpdateStatus, existingTags,\n}) {\n const [expandedId, setExpandedId] = useState(null);\n\n if (loading) {\n return (\n <div className=\"flex items-center justify-center py-20\">\n <div className=\"animate-spin rounded-full h-8 w-8 border-b-2 border-indigo-600\"></div>\n </div>\n );\n }\n\n if (!payments || payments.length === 0) {\n return (\n <div className=\"flex flex-col items-center justify-center py-20 text-gray-400\">\n <Inbox className=\"w-12 h-12 mb-3\" />\n <p className=\"text-lg font-medium\">No transactions found</p>\n <p className=\"text-sm\">Try adjusting your filters, ingest a payment SMS, or upload a CSV.</p>\n </div>\n );\n }\n\n const formatDate = (d) => {\n if (!d) return '—';\n return new Date(d).toLocaleDateString('en-GB', {\n day: '2-digit', month: 'short', year: 'numeric', hour: '2-digit', minute: '2-digit',\n });\n };\n\n const formatAmount = (v, currency) =>\n v != null ? `${v.toFixed(2)} ${currency || 'EUR'}` : '—';\n\n return (\n <div className=\"bg-white rounded-xl border border-gray-200 shadow-sm overflow-hidden\">\n <div className=\"overflow-x-auto\">\n <table className=\"w-full text-sm\">\n <thead>\n <tr className=\"bg-gray-50 border-b border-gray-200\">\n {COLUMNS.map(col => (\n <th\n key={col.key}\n className={`px-4 py-3 text-left text-xs font-semibold text-gray-600 uppercase tracking-wider ${col.sortable ? 'cursor-pointer select-none hover:bg-gray-100' : ''}`}\n onClick={() => col.sortable && onSort(col.key)}\n >\n <span className=\"inline-flex items-center gap-1\">\n {col.label}\n {col.sortable && <SortIcon column={col.key} sortBy={sortBy} sortDir={sortDir} />}\n </span>\n </th>\n ))}\n </tr>\n </thead>\n <tbody className=\"divide-y divide-gray-100\">\n {payments.map(p => {\n const isExpanded = expandedId === p.id;\n return (\n <React.Fragment key={p.id}>\n <tr className=\"hover:bg-gray-50 transition-colors\">\n <td className=\"px-4 py-3 whitespace-nowrap text-gray-700\">{formatDate(p.date)}</td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n <SourceBadge source={p.source} />\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n {p.type ? (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-blue-50 text-blue-700\">{p.type}</span>\n ) : (p.transactionType ? (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-gray-100 text-gray-600 max-w-24 truncate block\" title={p.transactionType}>{p.transactionType}</span>\n ) : '—')}\n </td>\n <td className=\"px-4 py-3 text-gray-700 max-w-xs truncate\" title={p.recipient || ''}>\n <div className=\"flex items-center gap-1\">\n <span className=\"truncate\">{p.recipient || '—'}</span>\n <button\n onClick={() => setExpandedId(isExpanded ? null : p.id)}\n className=\"flex-shrink-0 text-gray-400 hover:text-gray-600\"\n title=\"Show raw data\"\n >\n {isExpanded ? <ChevronUp className=\"w-3.5 h-3.5\" /> : <ChevronDown className=\"w-3.5 h-3.5\" />}\n </button>\n </div>\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap font-medium text-gray-900\">\n {formatAmount(p.amount, p.currency)}\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap text-gray-600\">\n {formatAmount(p.balance, p.currency)}\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n <StatusCell payment={p} onUpdateStatus={onUpdateStatus} />\n </td>\n <td className=\"px-4 py-3\">\n <TagCell\n payment={p}\n onAddTag={onAddTag}\n onRemoveTag={onRemoveTag}\n existingTags={existingTags}\n />\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n <div className=\"flex items-center gap-1.5\">\n {p.status === 'UNPROCESSED' && (\n <>\n <button\n onClick={() => onSend(p.id)}\n className=\"inline-flex items-center gap-1 px-2.5 py-1 text-xs font-medium text-white bg-indigo-600 rounded-md hover:bg-indigo-700 transition-colors\"\n >\n <Send className=\"w-3 h-3\" />\n Send\n </button>\n <button\n onClick={() => onSkip(p.id)}\n className=\"inline-flex items-center gap-1 px-2.5 py-1 text-xs font-medium text-gray-600 bg-white border border-gray-300 rounded-md hover:bg-gray-50 transition-colors\"\n >\n <XCircle className=\"w-3 h-3\" />\n Skip\n </button>\n </>\n )}\n <button\n onClick={() => { if (window.confirm('Delete this transaction?')) onDelete(p.id); }}\n className=\"inline-flex items-center gap-1 px-2 py-1 text-xs font-medium text-red-600 bg-white border border-red-200 rounded-md hover:bg-red-50 transition-colors\"\n title=\"Delete transaction\"\n >\n <Trash2 className=\"w-3 h-3\" />\n </button>\n </div>\n </td>\n </tr>\n {isExpanded && <ExpandedRow payment={p} />}\n </React.Fragment>\n );\n })}\n </tbody>\n </table>\n </div>\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"UploadPanel.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"UploadPanel.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"192 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState, useRef } from 'react';\nimport { Upload, FileText, CheckCircle, AlertCircle, X, ArrowLeft } from 'lucide-react';\n\nexport default function UploadPanel({ onUploadSuccess }) {\n const [files, setFiles] = useState([]);\n const [loading, setLoading] = useState(false);\n const [result, setResult] = useState(null);\n const [error, setError] = useState(null);\n const [dragging, setDragging] = useState(false);\n const fileInputRef = useRef();\n\n const addFiles = (incoming) => {\n const csvFiles = Array.from(incoming).filter(f =>\n f.name.toLowerCase().endsWith('.csv')\n );\n setFiles(prev => {\n const existingNames = new Set(prev.map(f => f.name));\n return [...prev, ...csvFiles.filter(f => !existingNames.has(f.name))];\n });\n };\n\n const handleDrop = (e) => {\n e.preventDefault();\n setDragging(false);\n addFiles(e.dataTransfer.files);\n };\n\n const handleFileSelect = (e) => {\n addFiles(e.target.files);\n e.target.value = '';\n };\n\n const removeFile = (idx) => setFiles(prev => prev.filter((_, i) => i !== idx));\n\n const handleUpload = async () => {\n if (!files.length) return;\n setLoading(true);\n setError(null);\n setResult(null);\n\n const formData = new FormData();\n files.forEach(f => formData.append('files', f));\n\n try {\n const res = await fetch('/api/upload/csv', { method: 'POST', body: formData });\n const data = await res.json();\n if (!res.ok) throw new Error(data.error || 'Upload failed');\n setResult(data);\n setFiles([]);\n } catch (err) {\n setError(err.message);\n } finally {\n setLoading(false);\n }\n };\n\n return (\n <div className=\"max-w-2xl mx-auto\">\n <div className=\"mb-6\">\n <h2 className=\"text-lg font-semibold text-gray-900\">Upload DSK Bank CSV</h2>\n <p className=\"text-sm text-gray-500 mt-1\">\n Import transactions from DSK Bank CSV exports. Multiple files are merged automatically.\n Internal transfers are skipped. Tags are auto-assigned based on payee and description.\n </p>\n </div>\n\n {/* Drop zone */}\n <div\n onDrop={handleDrop}\n onDragOver={(e) => { e.preventDefault(); setDragging(true); }}\n onDragLeave={() => setDragging(false)}\n onClick={() => fileInputRef.current.click()}\n className={`border-2 border-dashed rounded-xl p-12 text-center cursor-pointer transition-colors ${\n dragging\n ? 'border-emerald-400 bg-emerald-50'\n : 'border-gray-300 hover:border-emerald-400 hover:bg-emerald-50'\n }`}\n >\n <Upload className={`w-10 h-10 mx-auto mb-3 ${dragging ? 'text-emerald-500' : 'text-gray-400'}`} />\n <p className=\"text-sm font-medium text-gray-700\">Drop DSK Bank CSV files here</p>\n <p className=\"text-xs text-gray-500 mt-1\">or click to select files — multiple files supported</p>\n <input\n ref={fileInputRef}\n type=\"file\"\n multiple\n accept=\".csv\"\n className=\"hidden\"\n onChange={handleFileSelect}\n />\n </div>\n\n {/* File list */}\n {files.length > 0 && (\n <div className=\"mt-4 space-y-2\">\n {files.map((f, i) => (\n <div key={i} className=\"flex items-center gap-2 bg-white rounded-lg border border-gray-200 px-3 py-2\">\n <FileText className=\"w-4 h-4 text-gray-400 flex-shrink-0\" />\n <span className=\"text-sm text-gray-700 flex-1 truncate\">{f.name}</span>\n <span className=\"text-xs text-gray-400 flex-shrink-0\">{(f.size / 1024).toFixed(1)} KB</span>\n <button\n onClick={(e) => { e.stopPropagation(); removeFile(i); }}\n className=\"text-gray-400 hover:text-gray-600 flex-shrink-0\"\n >\n <X className=\"w-4 h-4\" />\n </button>\n </div>\n ))}\n\n <button\n onClick={handleUpload}\n disabled={loading}\n className=\"w-full py-2.5 text-sm font-medium text-white bg-emerald-600 rounded-lg hover:bg-emerald-700 disabled:opacity-50 disabled:cursor-not-allowed transition-colors mt-2\"\n >\n {loading\n ? 'Importing…'\n : `Import ${files.length} file${files.length !== 1 ? 's' : ''}`\n }\n </button>\n </div>\n )}\n\n {/* Success result */}\n {result && (\n <div className=\"mt-6 bg-green-50 border border-green-200 rounded-xl p-5\">\n <div className=\"flex items-center gap-2 mb-3\">\n <CheckCircle className=\"w-5 h-5 text-green-600 flex-shrink-0\" />\n <span className=\"font-medium text-green-800\">Import complete</span>\n </div>\n <div className=\"grid grid-cols-3 gap-3 text-center mb-3\">\n <div className=\"bg-white rounded-lg border border-green-100 py-2 px-3\">\n <p className=\"text-2xl font-bold text-green-700\">{result.imported}</p>\n <p className=\"text-xs text-gray-500\">Imported</p>\n </div>\n <div className=\"bg-white rounded-lg border border-green-100 py-2 px-3\">\n <p className=\"text-2xl font-bold text-gray-500\">{result.skipped}</p>\n <p className=\"text-xs text-gray-500\">Skipped</p>\n </div>\n <div className=\"bg-white rounded-lg border border-green-100 py-2 px-3\">\n <p className=\"text-2xl font-bold text-amber-600\">{result.errors?.length ?? 0}</p>\n <p className=\"text-xs text-gray-500\">Warnings</p>\n </div>\n </div>\n <p className=\"text-xs text-gray-500 mb-3\">\n Skipped rows are internal bank transfers (ТРАНСФЕР СОБСТВЕНИ СМЕТКИ).\n </p>\n {result.errors?.length > 0 && (\n <details className=\"mb-3\">\n <summary className=\"text-xs text-amber-700 cursor-pointer hover:text-amber-800\">\n Show {result.errors.length} warning{result.errors.length !== 1 ? 's' : ''}\n </summary>\n <ul className=\"mt-2 text-xs text-amber-600 space-y-0.5 max-h-32 overflow-y-auto\">\n {result.errors.map((e, i) => <li key={i} className=\"font-mono\">{e}</li>)}\n </ul>\n </details>\n )}\n <button\n onClick={onUploadSuccess}\n className=\"flex items-center gap-1.5 text-sm font-medium text-green-700 hover:text-green-800\"\n >\n <ArrowLeft className=\"w-4 h-4\" />\n View imported transactions\n </button>\n </div>\n )}\n\n {/* Error */}\n {error && (\n <div className=\"mt-4 bg-red-50 border border-red-200 rounded-xl p-4 flex items-start gap-3\">\n <AlertCircle className=\"w-5 h-5 text-red-500 flex-shrink-0 mt-0.5\" />\n <div>\n <p className=\"text-sm font-medium text-red-800\">Upload failed</p>\n <p className=\"text-sm text-red-700 mt-0.5\">{error}</p>\n </div>\n </div>\n )}\n\n {/* Info box */}\n {!result && !error && (\n <div className=\"mt-6 bg-blue-50 border border-blue-100 rounded-xl p-4\">\n <p className=\"text-xs font-medium text-blue-800 mb-1\">Expected CSV format (DSK Bank export)</p>\n <p className=\"text-xs text-blue-700 font-mono\">\n Дата, Вид на трансакцията, Основание, Дебит BGN, Кредит BGN, Наредител/Получател, Номер сметка...\n </p>\n <p className=\"text-xs text-blue-600 mt-2\">\n Both UTF-8 and Windows-1251 encodings are supported. Tags are auto-applied based on payee and description keywords.\n </p>\n </div>\n )}\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentCard.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentCard.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"186 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState } from 'react';\nimport {\n Send, XCircle, CheckCircle, MinusCircle, Clock,\n CreditCard, Tag, Plus, X,\n} from 'lucide-react';\n\nconst STATUS_CONFIG = {\n UNPROCESSED: { label: 'Unprocessed', icon: Clock, color: 'bg-amber-100 text-amber-700 border-amber-200' },\n SENT: { label: 'Sent', icon: CheckCircle, color: 'bg-green-100 text-green-700 border-green-200' },\n SKIPPED: { label: 'Skipped', icon: MinusCircle, color: 'bg-gray-100 text-gray-500 border-gray-200' },\n};\n\nconst TAG_COLORS = [\n '#ef4444', '#f97316', '#eab308', '#22c55e', '#06b6d4',\n '#3b82f6', '#8b5cf6', '#ec4899', '#6b7280',\n];\n\nexport default function PaymentCard({ payment, onSend, onSkip, onAddTag, onRemoveTag, existingTags }) {\n const [showTagInput, setShowTagInput] = useState(false);\n const [newTagName, setNewTagName] = useState('');\n const [newTagColor, setNewTagColor] = useState('#3b82f6');\n\n const statusCfg = STATUS_CONFIG[payment.status] || STATUS_CONFIG.UNPROCESSED;\n const StatusIcon = statusCfg.icon;\n\n const handleAddTag = (e) => {\n e.preventDefault();\n if (newTagName.trim()) {\n onAddTag(payment.id, newTagName.trim(), newTagColor);\n setNewTagName('');\n setShowTagInput(false);\n }\n };\n\n const paymentTags = payment.tags || [];\n const availableTags = existingTags.filter(t => !paymentTags.some(pt => pt.id === t.id));\n\n const formattedDate = payment.date\n ? new Date(payment.date).toLocaleDateString('en-GB', {\n day: '2-digit', month: 'short', year: 'numeric', hour: '2-digit', minute: '2-digit',\n })\n : 'N/A';\n\n const currency = payment.currency || 'EUR';\n\n return (\n <div className=\"bg-white rounded-xl border border-gray-200 shadow-sm hover:shadow-md transition-shadow p-4\">\n <div className=\"flex items-start justify-between gap-3 mb-3\">\n <div className=\"flex-1 min-w-0\">\n <div className=\"flex items-center gap-2 mb-1\">\n <span className={`inline-flex items-center gap-1 px-2 py-0.5 text-xs font-medium rounded-full border ${statusCfg.color}`}>\n <StatusIcon className=\"w-3 h-3\" />\n {statusCfg.label}\n </span>\n {payment.source === 'UPLOAD' ? (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-emerald-50 text-emerald-700\">CSV</span>\n ) : (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-indigo-50 text-indigo-700\">SMS</span>\n )}\n </div>\n <p className=\"text-sm text-gray-600 break-words leading-relaxed\">{payment.rawMessage}</p>\n </div>\n </div>\n\n <div className=\"grid grid-cols-2 sm:grid-cols-4 gap-3 mb-3 text-sm\">\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Amount</span>\n <p className=\"font-semibold text-gray-900\">\n {payment.amount != null ? `${payment.amount.toFixed(2)} ${currency}` : 'N/A'}\n </p>\n </div>\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Date</span>\n <p className=\"text-gray-700\">{formattedDate}</p>\n </div>\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Card</span>\n <p className=\"text-gray-700 flex items-center gap-1\">\n <CreditCard className=\"w-3 h-3 text-gray-400\" />\n {payment.card || 'N/A'}\n </p>\n </div>\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Balance</span>\n <p className=\"text-gray-700\">\n {payment.balance != null ? `${payment.balance.toFixed(2)} ${currency}` : 'N/A'}\n </p>\n </div>\n </div>\n\n {/* Tags */}\n <div className=\"flex flex-wrap items-center gap-1.5 mb-3\">\n <Tag className=\"w-3 h-3 text-gray-400\" />\n {paymentTags.map(tag => (\n <span\n key={tag.id}\n className=\"inline-flex items-center gap-1 px-2 py-0.5 text-xs font-medium rounded-full text-white\"\n style={{ backgroundColor: tag.color }}\n >\n {tag.name}\n <button onClick={() => onRemoveTag(payment.id, tag.id)} className=\"hover:opacity-75\">\n <X className=\"w-3 h-3\" />\n </button>\n </span>\n ))}\n {!showTagInput ? (\n <button\n onClick={() => setShowTagInput(true)}\n className=\"inline-flex items-center gap-0.5 px-2 py-0.5 text-xs text-gray-500 border border-dashed border-gray-300 rounded-full hover:border-gray-400 hover:text-gray-600\"\n >\n <Plus className=\"w-3 h-3\" />\n Tag\n </button>\n ) : (\n <form onSubmit={handleAddTag} className=\"inline-flex items-center gap-1\">\n <input\n type=\"text\"\n value={newTagName}\n onChange={(e) => setNewTagName(e.target.value)}\n placeholder=\"Tag name\"\n autoFocus\n className=\"w-24 px-2 py-0.5 text-xs border border-gray-300 rounded-md focus:ring-1 focus:ring-indigo-500 outline-none\"\n />\n <div className=\"flex gap-0.5\">\n {TAG_COLORS.map(c => (\n <button\n key={c}\n type=\"button\"\n onClick={() => setNewTagColor(c)}\n className={`w-4 h-4 rounded-full border-2 ${newTagColor === c ? 'border-gray-800' : 'border-transparent'}`}\n style={{ backgroundColor: c }}\n />\n ))}\n </div>\n <button type=\"submit\" className=\"text-xs text-indigo-600 font-medium hover:text-indigo-700\">Add</button>\n <button type=\"button\" onClick={() => setShowTagInput(false)} className=\"text-xs text-gray-400 hover:text-gray-600\">\n <X className=\"w-3 h-3\" />\n </button>\n </form>\n )}\n {showTagInput && availableTags.length > 0 && (\n <div className=\"flex flex-wrap gap-1 ml-1\">\n {availableTags.slice(0, 5).map(tag => (\n <button\n key={tag.id}\n onClick={() => { onAddTag(payment.id, tag.name, tag.color); setShowTagInput(false); }}\n className=\"px-2 py-0.5 text-xs rounded-full border border-gray-200 text-gray-600 hover:bg-gray-100\"\n >\n {tag.name}\n </button>\n ))}\n </div>\n )}\n </div>\n\n {payment.status === 'UNPROCESSED' && (\n <div className=\"flex items-center gap-2 pt-3 border-t border-gray-100\">\n <button\n onClick={() => onSend(payment.id)}\n className=\"flex items-center gap-1.5 px-4 py-2 text-sm font-medium text-white bg-indigo-600 rounded-lg hover:bg-indigo-700 transition-colors\"\n >\n <Send className=\"w-4 h-4\" />\n Send\n </button>\n <button\n onClick={() => onSkip(payment.id)}\n className=\"flex items-center gap-1.5 px-4 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 transition-colors\"\n >\n <XCircle className=\"w-4 h-4\" />\n Do Not Send\n </button>\n </div>\n )}\n\n {payment.status === 'SENT' && payment.notifiedAt && (\n <div className=\"pt-3 border-t border-gray-100\">\n <p className=\"text-xs text-green-600\">\n Notified on {new Date(payment.notifiedAt).toLocaleString('en-GB')}\n {payment.notifyPhone && ` to ${payment.notifyPhone}`}\n </p>\n </div>\n )}\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentList.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentList.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"40 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React from 'react';\nimport { Inbox } from 'lucide-react';\nimport PaymentCard from './PaymentCard';\n\nexport default function PaymentList({ payments, loading, onSend, onSkip, onAddTag, onRemoveTag, existingTags }) {\n if (loading) {\n return (\n <div className=\"flex items-center justify-center py-20\">\n <div className=\"animate-spin rounded-full h-8 w-8 border-b-2 border-indigo-600\"></div>\n </div>\n );\n }\n\n if (!payments || payments.length === 0) {\n return (\n <div className=\"flex flex-col items-center justify-center py-20 text-gray-400\">\n <Inbox className=\"w-12 h-12 mb-3\" />\n <p className=\"text-lg font-medium\">No transactions found</p>\n <p className=\"text-sm\">Try adjusting your filters, ingest a payment SMS, or upload a CSV.</p>\n </div>\n );\n }\n\n return (\n <div className=\"space-y-4\">\n {payments.map(payment => (\n <PaymentCard\n key={payment.id}\n payment={payment}\n onSend={onSend}\n onSkip={onSkip}\n onAddTag={onAddTag}\n onRemoveTag={onRemoveTag}\n existingTags={existingTags}\n />\n ))}\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"}]...
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6809041617504496635
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Explorer (⇧⌘E)
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2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
report(1).csv, Editor Group 1
report(2).csv, Editor Group 1
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
Design new payment-logge…, Editor Group 2
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Ln 9, Col 45
Info: Setting up SSH Host nas: Setting up SSH tunnel
Design new payment-logger and dsk-uploader hybrid app
Session history
New session
Message actions
payments.js
payments.js
ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.
Thinking
Thinking
I'll explore all three reference projects in parallel to understand their structure before planning.
Agent:
Explore payment-logger app structure and functionality
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How data flows (ingest, storage, retrieval)
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.
Agent:
Explore dsk-uploader app structure and functionality
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How file uploads work - what files, what format, how parsed
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.
Agent:
Explore auth folder and authentik integration
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. What auth system is being used (Authentik)
2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?
3. Middleware - how is auth enforced on routes?
4. Any frontend auth flow - login redirect, token handling, protected routes
5. Environment variables related to auth
6. Docker/deployment setup for the auth service itself
7. Any example of how other apps integrate with this auth
Report with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.
Message actions
payments.js
payments.js
continue
Thinking
Thinking
Launching parallel exploration of all three reference projects.
Agent:
Explore payment-logger app structure
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How data is ingested (look at /ingest route especially)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore dsk-uploader app structure
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How file uploads work (what format, what processing happens)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore auth project structure
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. What authentication system is used (authentik integration details)
3. How OAuth/OIDC flow works
4. Any middleware or helper functions for protecting routes
5. Session management approach
6. How frontend handles auth state
7. Any example of how other apps integrate with this auth system
8. Docker setup and environment variables
Please read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.
Thinking
Thinking
Now I have a complete picture of all three. Let me design the plan.
Agent:
Design combined app architecture
IN
Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:
---
## App 1: payments-logger (Node.js)
- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI
- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS
- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage
- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)
- **Schema** (PostgreSQL via Prisma):
- `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at
- `tags` table: id, name, color — M2M with payments via `_PaymentToTag`
- `users` table: id, username, hashed_password (this will be REMOVED)
- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system
- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance
## App 2: dsk-uploader (Python/Flask)
- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database
- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5
- **Auth**: None (open)
- **CSV format** (DSK Bank Bulgarian format, columns):
- `Дата` (date, DD.MM.YYYY)
- `Вид на трансакцията` (transaction type, Bulgarian)
- `Основание` (reason/description — contains card number regex: `^\d{6}x{6}\d{4}$`)
- `Дебит BGN` (debit amount, may be empty)
- `Кредит BGN` (credit amount, may be empty)
- `Наредител/Получател` (orderer/recipient name)
- `Номер сметка на наредителя / получателя` (account number)
- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers
- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)
## App 3: auth (Authentik)
- **Mode**: Proxy mode via NPM (forward auth)
- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:
- `X-authentik-username`
- `X-authentik-email`
- `X-authentik-groups`
- **No code integration needed** in the app itself — just trust these headers from NPM
- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`
---
## What the New Combined App Must Do
1. **Single PostgreSQL database** for all transactions
2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST
3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema
4. **Unified UI** — show all payments in one table regardless of source
5. **Source indicator** in UI — badge showing "INGEST", "UPLOAD", or "BOTH" (if duplicate detection added)
6. **Source filter** in FilterBar — filter by All/Ingest/Upload
7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM
8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination
9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL
---
## Technical Constraints
- Keep Node.js backend (not Python) — extend payments-logger's stack
- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)
- File upload: use `multer` npm middleware
- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)
- Add `source` enum field (INGEST/UPLOAD) to payments schema
- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is
- Remove `users` table from schema
---
## Please Design
1. Complete folder structure for the new app (suggest name: "finance-hub" or similar — note this is a placeholder, user will confirm)
2. Prisma schema with new fields (`source`, `currency`)
3. All backend API routes
4. CSV parser design in Node.js (port of the Python logic)
5. Authentik auth middleware
6. Frontend component structure (React) — what's reused from payments-logger, what's new
7. Docker Compose setup
8. Environment variables needed
9. Step-by-step implementation order
10. Verification checklist
Be specific about file paths and code structure. This will be used to write actual implementation code.
Thinking
Thinking
Good plan. Let me ask the one thing I need before writing the final plan.
AskUserQuestion
OUT
User has answered your questions: "What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding."="finance-hub". You can now continue with the user's answers in mind.
Thinking
Thinking
Writing the final plan now.
Thinking
Thinking
Write
ets-create-a-new-generic-sun.md
ets-create-a-new-generic-sun.md
326 lines
# finance-hub — Implementation Plan
## Context
Two separate finance apps exist as references and will be retired:
- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.
- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.
The new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).
---
## Tech Stack
| Layer | Choice | Rationale |
|-------|--------|-----------|
| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |
| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |
| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |
| Database | PostgreSQL 16 | Same as payments-logger |
| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |
| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |
| Container | Docker Compose | Same pattern as both reference apps |
**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage.
**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references.
**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.
---
## Folder Structure
```
/volume2/docker/finance/finance-hub/
├── docker-compose.yml
├── .env
├── .env.example
├── .gitignore
├── backend/
│ ├── Dockerfile
│ ├── package.json
│ ├── prisma/
│ │ ├── schema.prisma
│ │ └── migrations/
│ │ ├── migration_lock.toml
│ │ └── 20260508_init/
│ │ └── migration.sql
│ └── src/
│ ├── index.js ← entry point (Authentik middleware wired here)
│ ├── auth.js ← Authentik header middleware (replaces JWT auth)
│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)
│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)
│ └── routes/
│ ├── payments.js ← existing routes + source/currency additions
│ └── upload.js ← NEW: POST /api/upload/csv
└── frontend/
├── Dockerfile
├── package.json
├── vite.config.js
├── tailwind.config.js
├── postcss.config.js
├── index.html
└── src/
├── main.jsx ← remove AuthProvider wrapper
├── index.css
├── App.jsx ← remove auth state, add Upload tab toggle
└── components/
├── FilterBar.jsx ← add source filter select
├── PaymentTable.jsx ← add Source badge column + currency display
├── PaymentCard.jsx ← minor source badge addition
├── PaymentList.jsx ← unchanged
└── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI
```
---
## Database Schema (Prisma)
File: `backend/prisma/schema.prisma`
```prisma
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
}
model Payment {
id Int @id @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
auth.js
auth.js
27 lines
const PUBLIC_PATHS = new Set([
'/api/health',
'/api/payments/ingest',
]);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) {
return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });
}
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '')
.split(',')
.map(g => g.trim())
.filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
Write
parser.js
parser.js
104 lines
/**
* Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)
*
* Supported formats:
*
* POS / INTERNET / ECOM / P2P payment:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM withdrawal:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM utility payment (amount may include fee as AMOUNT/FEE):
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.
*/
const LOCAL_TZ = process.env.TZ || 'Europe/Sofia';
/**
* Convert a local-timezone date/time to a UTC Date object.
* Uses Intl to resolve the actual UTC offset (DST-aware).
*/
function localToUtc(year, month, day, hour, minute) {
const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));
const formatter = new Intl.DateTimeFormat('en-US', {
timeZone: LOCAL_TZ,
year: 'numeric', month: '2-digit', day: '2-digit',
hour: '2-digit', minute: '2-digit', second: '2-digit',
hour12: false,
});
const parts = {};
formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });
const localAtNaive = new Date(Date.UTC(
parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),
parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),
));
const offsetMs = localAtNaive.getTime() - naive.getTime();
return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);
}
function parsePaymentSms(message) {
const result = {
rawMessage: message,
date: null,
type: null,
card: null,
recipient: null,
amount: null,
balance: null,
};
// Date and time: "Na DD/MM/YYYY v HH:MM"
const dateMatch = message.match(/Na (\d{2})\/(\d{2})\/(\d{4}) v (\d{2}):(\d{2})/i);
if (dateMatch) {
const [, day, month, year, hour, minute] = dateMatch;
result.date = localToUtc(
parseInt(year), parseInt(month), parseInt(day),
parseInt(hour), parseInt(minute),
);
}
// Card mask: "s karta 400915***4447" or "s karta 483890***7162"
const cardMatch = message.match(/s karta\s+([\d*]+)/i);
if (cardMatch) {
result.card = cardMatch[1];
}
// Transaction type: supports both prepositions
// "na POS" / "na ATM" / "na INTERNET" etc. (payment)
// "ot ATM" (withdrawal)
const typeMatch = message.match(/(?:na|ot)\s+(POS|ATM|INTERNET|ECOM|P2P)\b/i);
if (typeMatch) {
result.type = typeMatch[1].toUpperCase();
}
// Recipient address: "s adres: MERCHANT" or "s adres:MERCHANT" (no space variant)
const recipientMatch = message.match(/s adres:\s*([^.]+)\./i);
if (recipientMatch) {
result.recipient = recipientMatch[1].trim();
}
// Amount: handles both verbs and the AMOUNT/FEE suffix format
// "sa plateni 7.78 EUR"
// "sa iztegleni 400.00 EUR"
// "sa plateni 0.50 EUR/0.50 EUR" → captures 0.50 (the charged amount, ignoring fee)
const amountMatch = message.match(/sa (?:plateni|iztegleni)\s+([\d.,]+)\s+[A-Z]{3}/i);
if (amountMatch) {
result.amount = parseFloat(amountMatch[1].replace(',', '.'));
}
// Balance: "Nalichni: 2583.07 EUR."
const balanceMatch = message.match(/Nalichni:\s*([\d.,]+)\s+[A-Z]{3}/i);
if (balanceMatch) {
result.balance = parseFloat(balanceMatch[1].replace(',', '.'));
}
return result;
}
module.exports = { parsePaymentSms };
Write
csvParser.js
csvParser.js
175 lines
/**
* DSK Bank CSV parser — Node.js port of dskuploader.py
*
* DSK Bank exports use Windows-1251 (cp1251) encoding.
* Each row maps to a Payment record with source=UPLOAD, currency=BGN.
*/
const { parse } = require('csv-parse');
const iconv = require('iconv-lite');
const SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';
const CARD_REGEX = /^\d{6}x{6}\d{4}$/;
const POS_REGEX = /^\s*ПЛАЩАНЕ\s+НА\s+ПОС\s+\d{2}\.\d{2}\.\d{4}\s+\d{2}:\d{2}/;
const COL = {
DATE: 'Дата',
TYPE: 'Вид на трансакцията',
REASON: 'Основание',
DEBIT: 'Дебит BGN',
CREDIT: 'Кредит BGN',
PAYEE: 'Наредител/Получател',
ACCT: 'Номер сметка на наредителя / получателя',
};
const TAG_RULES = [
['reason', 'ЗАПЛАТА', 'Salary'],
['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],
['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],
['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],
['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],
['payee', 'VIVACOM', 'Subscriptions'],
['payee', 'Google', 'Subscriptions'],
['payee', 'SkyShowtime', 'Subscriptions'],
['payee', 'NETFLIX', 'Subscriptions'],
['payee', 'LUKOIL', 'Bills'],
['payee', 'CityGate', 'Bills'],
['payee', 'CBA', 'Groceries'],
['payee', 'FANTASTICO', 'Groceries'],
['payee', 'LIDL', 'Groceries'],
];
function parseNum(val) {
if (val == null || val === '') return null;
if (typeof val === 'number') return isNaN(val) ? null : val;
const s = String(val).trim().replace(/\xa0/g, '').replace(/ /g, '').replace(',', '.');
const n = parseFloat(s);
return isNaN(n) ? null : n;
}
function parseDate(val) {
if (!val) return null;
const s = String(val).trim();
const m = s.match(/^(\d{2})\.(\d{2})\.(\d{4})$/);
if (m) {
return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));
}
return null;
}
function processReasonAndCard(reason) {
if (!reason || typeof reason !== 'string') return { reason: '', card: null };
const parts = reason.trim().split(' ');
let card = null;
let cleanReason = reason.trim();
if (parts[0] && CARD_REGEX.test(parts[0])) {
card = parts[0];
cleanReason = parts.slice(1).join(' ').trim();
}
if (POS_REGEX.test(cleanReason)) {
const posParts = cleanReason.split('<br/>');
try {
const dateTime = posParts[0].split('ПОС ')[1];
cleanReason = `POS PAYMENT ${dateTime}`;
} catch (_) { /* keep original */ }
}
return { reason: cleanReason.replace(/\s+/g, ' ').trim(), card };
}
function generateTags(fields) {
const tags = new Set();
for (const [field, keyword, tagName] of TAG_RULES) {
if ((fields[field] || '').includes(keyword)) {
tags.add(tagName);
}
}
return Array.from(tags);
}
function processRow(row) {
const transactionType = (row[COL.TYPE] || '').trim();
if (transactionType === SKIP_TYPE) return null;
const { reason, card } = processReasonAndCard(row[COL.REASON]);
const payee = (row[COL.PAYEE] || ...
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G)
Run and Debug (⇧⌘D)
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Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
report(1).csv, Editor Group 1
report(2).csv, Editor Group 1
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
Design new payment-logge…, Editor Group 2
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remote SSH: nas
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Ln 9, Col 45
Info: Setting up SSH Host nas: Setting up SSH tunnel
Design new payment-logger and dsk-uploader hybrid app
Session history
New session
Message actions
payments.js
payments.js
ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.
Thinking
Thinking
I'll explore all three reference projects in parallel to understand their structure before planning.
Agent:
Explore payment-logger app structure and functionality
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How data flows (ingest, storage, retrieval)
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.
Agent:
Explore dsk-uploader app structure and functionality
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How file uploads work - what files, what format, how parsed
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.
Agent:
Explore auth folder and authentik integration
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. What auth system is being used (Authentik)
2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?
3. Middleware - how is auth enforced on routes?
4. Any frontend auth flow - login redirect, token handling, protected routes
5. Environment variables related to auth
6. Docker/deployment setup for the auth service itself
7. Any example of how other apps integrate with this auth
Report with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.
Message actions
payments.js
payments.js
continue
Thinking
Thinking
Launching parallel exploration of all three reference projects.
Agent:
Explore payment-logger app structure
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How data is ingested (look at /ingest route especially)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore dsk-uploader app structure
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How file uploads work (what format, what processing happens)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore auth project structure
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. What authentication system is used (authentik integration details)
3. How OAuth/OIDC flow works
4. Any middleware or helper functions for protecting routes
5. Session management approach
6. How frontend handles auth state
7. Any example of how other apps integrate with this auth system
8. Docker setup and environment variables
Please read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.
Thinking
Thinking
Now I have a complete picture of all three. Let me design the plan.
Agent:
Design combined app architecture
IN
Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:
---
## App 1: payments-logger (Node.js)
- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI
- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS
- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage
- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)
- **Schema** (PostgreSQL via Prisma):
- `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at
- `tags` table: id, name, color — M2M with payments via `_PaymentToTag`
- `users` table: id, username, hashed_password (this will be REMOVED)
- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system
- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance
## App 2: dsk-uploader (Python/Flask)
- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database
- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5
- **Auth**: None (open)
- **CSV format** (DSK Bank Bulgarian format, columns):
- `Дата` (date, DD.MM.YYYY)
- `Вид на трансакцията` (transaction type, Bulgarian)
- `Основание` (reason/description — contains card number regex: `^\d{6}x{6}\d{4}$`)
- `Дебит BGN` (debit amount, may be empty)
- `Кредит BGN` (credit amount, may be empty)
- `Наредител/Получател` (orderer/recipient name)
- `Номер сметка на наредителя / получателя` (account number)
- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers
- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)
## App 3: auth (Authentik)
- **Mode**: Proxy mode via NPM (forward auth)
- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:
- `X-authentik-username`
- `X-authentik-email`
- `X-authentik-groups`
- **No code integration needed** in the app itself — just trust these headers from NPM
- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`
---
## What the New Combined App Must Do
1. **Single PostgreSQL database** for all transactions
2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST
3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema
4. **Unified UI** — show all payments in one table regardless of source
5. **Source indicator** in UI — badge showing "INGEST", "UPLOAD", or "BOTH" (if duplicate detection added)
6. **Source filter** in FilterBar — filter by All/Ingest/Upload
7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM
8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination
9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL
---
## Technical Constraints
- Keep Node.js backend (not Python) — extend payments-logger's stack
- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)
- File upload: use `multer` npm middleware
- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)
- Add `source` enum field (INGEST/UPLOAD) to payments schema
- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is
- Remove `users` table from schema
---
## Please Design
1. Complete folder structure for the new app (suggest name: "finance-hub" or similar — note this is a placeholder, user will confirm)
2. Prisma schema with new fields (`source`, `currency`)
3. All backend API routes
4. CSV parser design in Node.js (port of the Python logic)
5. Authentik auth middleware
6. Frontend component structure (React) — what's reused from payments-logger, what's new
7. Docker Compose setup
8. Environment variables needed
9. Step-by-step implementation order
10. Verification checklist
Be specific about file paths and code structure. This will be used to write actual implementation code.
Thinking
Thinking
Good plan. Let me ask the one thing I need before writing the final plan.
AskUserQuestion
OUT
User has answered your questions: "What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding."="finance-hub". You can now continue with the user's answers in mind.
Thinking
Thinking
Writing the final plan now.
Thinking
Thinking
Write
ets-create-a-new-generic-sun.md
ets-create-a-new-generic-sun.md
326 lines
# finance-hub — Implementation Plan
## Context
Two separate finance apps exist as references and will be retired:
- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.
- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.
The new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).
---
## Tech Stack
| Layer | Choice | Rationale |
|-------|--------|-----------|
| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |
| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |
| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |
| Database | PostgreSQL 16 | Same as payments-logger |
| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |
| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |
| Container | Docker Compose | Same pattern as both reference apps |
**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage.
**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references.
**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.
---
## Folder Structure
```
/volume2/docker/finance/finance-hub/
├── docker-compose.yml
├── .env
├── .env.example
├── .gitignore
├── backend/
│ ├── Dockerfile
│ ├── package.json
│ ├── prisma/
│ │ ├── schema.prisma
│ │ └── migrations/
│ │ ├── migration_lock.toml
│ │ └── 20260508_init/
│ │ └── migration.sql
│ └── src/
│ ├── index.js ← entry point (Authentik middleware wired here)
│ ├── auth.js ← Authentik header middleware (replaces JWT auth)
│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)
│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)
│ └── routes/
│ ├── payments.js ← existing routes + source/currency additions
│ └── upload.js ← NEW: POST /api/upload/csv
└── frontend/
├── Dockerfile
├── package.json
├── vite.config.js
├── tailwind.config.js
├── postcss.config.js
├── index.html
└── src/
├── main.jsx ← remove AuthProvider wrapper
├── index.css
├── App.jsx ← remove auth state, add Upload tab toggle
└── components/
├── FilterBar.jsx ← add source filter select
├── PaymentTable.jsx ← add Source badge column + currency display
├── PaymentCard.jsx ← minor source badge addition
├── PaymentList.jsx ← unchanged
└── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI
```
---
## Database Schema (Prisma)
File: `backend/prisma/schema.prisma`
```prisma
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
}
model Payment {
id Int @id @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
auth.js
auth.js
27 lines
const PUBLIC_PATHS = new Set([
'/api/health',
'/api/payments/ingest',
]);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) {
return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });
}
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '')
.split(',')
.map(g => g.trim())
.filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
Write
parser.js
parser.js
104 lines
/**
* Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)
*
* Supported formats:
*
* POS / INTERNET / ECOM / P2P payment:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM withdrawal:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM utility payment (amount may include fee as AMOUNT/FEE):
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.
*/
const LOCAL_TZ = process.env.TZ || 'Europe/Sofia';
/**
* Convert a local-timezone date/time to a UTC Date object.
* Uses Intl to resolve the actual UTC offset (DST-aware).
*/
function localToUtc(year, month, day, hour, minute) {
const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));
const formatter = new Intl.DateTimeFormat('en-US', {
timeZone: LOCAL_TZ,
year: 'numeric', month: '2-digit', day: '2-digit',
hour: '2-digit', minute: '2-digit', second: '2-digit',
hour12: false,
});
const parts = {};
formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });
const localAtNaive = new Date(Date.UTC(
parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),
parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),
));
const offsetMs = localAtNaive.getTime() - naive.getTime();
return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);
}
function parsePaymentSms(message) {
const result = {
rawMessage: message,
date: null,
type: null,
card: null,
recipient: null,
amount: null,
balance: null,
};
// Date and time: "Na DD/MM/YYYY v HH:MM"
const dateMatch = message.match(/Na (\d{2})\/(\d{2})\/(\d{4}) v (\d{2}):(\d{2})/i);
if (dateMatch) {
const [, day, month, year, hour, minute] = dateMatch;
result.date = localToUtc(
parseInt(year), parseInt(month), parseInt(day),
parseInt(hour), parseInt(minute),
);
}
// Card mask: "s karta 400915***4447" or "s karta 483890***7162"
const cardMatch = message.match(/s karta\s+([\d*]+)/i);
if (cardMatch) {
result.card = cardMatch[1];
}
// Transaction type: supports both prepositions
// "na POS" / "na ATM" / "na INTERNET" etc. (payment)
// "ot ATM" (withdrawal)
const typeMatch = message.match(/(?:na|ot)\s+(POS|ATM|INTERNET|ECOM|P2P)\b/i);
if (typeMatch) {
result.type = typeMatch[1].toUpperCase();
}
// Recipient address: "s adres: MERCHANT" or "s adres:MERCHANT" (no space variant)
const recipientMatch = message.match(/s adres:\s*([^.]+)\./i);
if (recipientMatch) {
result.recipient = recipientMatch[1].trim();
}
// Amount: handles both verbs and the AMOUNT/FEE suffix format
// "sa plateni 7.78 EUR"
// "sa iztegleni 400.00 EUR"
// "sa plateni 0.50 EUR/0.50 EUR" → captures 0.50 (the charged amount, ignoring fee)
const amountMatch = message.match(/sa (?:plateni|iztegleni)\s+([\d.,]+)\s+[A-Z]{3}/i);
if (amountMatch) {
result.amount = parseFloat(amountMatch[1].replace(',', '.'));
}
// Balance: "Nalichni: 2583.07 EUR."
const balanceMatch = message.match(/Nalichni:\s*([\d.,]+)\s+[A-Z]{3}/i);
if (balanceMatch) {
result.balance = parseFloat(balanceMatch[1].replace(',', '.'));
}
return result;
}
module.exports = { parsePaymentSms };
Write
csvParser.js
csvParser.js
175 lines
/**
* DSK Bank CSV parser — Node.js port of dskuploader.py
*
* DSK Bank exports use Windows-1251 (cp1251) encoding.
* Each row maps to a Payment record with source=UPLOAD, currency=BGN.
*/
const { parse } = require('csv-parse');
const iconv = require('iconv-lite');
const SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';
const CARD_REGEX = /^\d{6}x{6}\d{4}$/;
const POS_REGEX = /^\s*ПЛАЩАНЕ\s+НА\s+ПОС\s+\d{2}\.\d{2}\.\d{4}\s+\d{2}:\d{2}/;
const COL = {
DATE: 'Дата',
TYPE: 'Вид на трансакцията',
REASON: 'Основание',
DEBIT: 'Дебит BGN',
CREDIT: 'Кредит BGN',
PAYEE: 'Наредител/Получател',
ACCT: 'Номер сметка на наредителя / получателя',
};
const TAG_RULES = [
['reason', 'ЗАПЛАТА', 'Salary'],
['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],
['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],
['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],
['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],
['payee', 'VIVACOM', 'Subscriptions'],
['payee', 'Google', 'Subscriptions'],
['payee', 'SkyShowtime', 'Subscriptions'],
['payee', 'NETFLIX', 'Subscriptions'],
['payee', 'LUKOIL', 'Bills'],
['payee', 'CityGate', 'Bills'],
['payee', 'CBA', 'Groceries'],
['payee', 'FANTASTICO', 'Groceries'],
['payee', 'LIDL', 'Groceries'],
];
function parseNum(val) {
if (val == null || val === '') return null;
if (typeof val === 'number') return isNaN(val) ? null : val;
const s = String(val).trim().replace(/\xa0/g, '').replace(/ /g, '').replace(',', '.');
const n = parseFloat(s);
return isNaN(n) ? null : n;
}
function parseDate(val) {
if (!val) return null;
const s = String(val).trim();
const m = s.match(/^(\d{2})\.(\d{2})\.(\d{4})$/);
if (m) {
return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));
}
return null;
}
function processReasonAndCard(reason) {
if (!reason || typeof reason !== 'string') return { reason: '', card: null };
const parts = reason.trim().split(' ');
let card = null;
let cleanReason = reason.trim();
if (parts[0] && CARD_REGEX.test(parts[0])) {
card = parts[0];
cleanReason = parts.slice(1).join(' ').trim();
}
if (POS_REGEX.test(cleanReason)) {
const posParts = cleanReason.split('<br/>');
try {
const dateTime = posParts[0].split('ПОС ')[1];
cleanReason = `POS PAYMENT ${dateTime}`;
} catch (_) { /* keep original */ }
}
return { reason: cleanReason.replace(/\s+/g, ' ').trim(), card };
}
function generateTags(fields) {
const tags = new Set();
for (const [field, keyword, tagName] of TAG_RULES) {
if ((fields[field] || '').includes(keyword)) {
tags.add(tagName);
}
}
return Array.from(tags);
}
function processRow(row) {
const transactionType = (row[COL.TYPE] || '').trim();
if (transactionType === SKIP_TYPE) return null;
const { reason, card } = processReasonAndCard(row[COL.REASON]);
const payee = (row[COL.PAYEE] || ...
|
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(⌃⇧G)","depth":19,"bounds":{"left":0.0,"top":0.1245012,"width":0.015957447,"height":0.03830806},"on_screen":true,"role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"","depth":22,"bounds":{"left":0.0039893617,"top":0.13407822,"width":0.007978723,"height":0.01915403},"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Run and Debug (⇧⌘D)","depth":19,"bounds":{"left":0.0,"top":0.16280925,"width":0.015957447,"height":0.03830806},"on_screen":true,"role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"","depth":22,"bounds":{"left":0.0039893617,"top":0.17238627,"width":0.007978723,"height":0.01915403},"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Remote Explorer","depth":19,"bounds":{"left":0.0,"top":0.20111732,"width":0.015957447,"height":0.03830806},"on_screen":true,"role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"","depth":22,"bounds":{"left":0.0039893617,"top":0.21069433,"width":0.007978723,"height":0.01915403},"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Extensions (⇧⌘X) - 2 require 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actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"payments.js","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"I'll explore all three reference projects in parallel to understand their structure before planning.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How data flows (ingest, storage, retrieval)\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How file uploads work - what files, what format, how parsed\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth folder and authentik integration","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. What auth system is being used (Authentik)\n2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?\n3. Middleware - how is auth enforced on routes?\n4. Any frontend auth flow - login redirect, token handling, protected routes\n5. Environment variables related to auth\n6. Docker/deployment setup for the auth service itself\n7. Any example of how other apps integrate with this auth\n\nReport with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"payments.js","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"continue","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Launching parallel exploration of all three reference projects.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How data is ingested (look at /ingest route especially)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How file uploads work (what format, what processing happens)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth project structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. What authentication system is used (authentik integration details)\n3. How OAuth/OIDC flow works\n4. Any middleware or helper functions for protecting routes\n5. Session management approach\n6. How frontend handles auth state\n7. Any example of how other apps integrate with this auth system\n8. Docker setup and environment variables\n\nPlease read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now I have a complete picture of all three. Let me design the plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design combined app architecture","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:\n\n---\n\n## App 1: payments-logger (Node.js)\n- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI\n- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS\n- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage\n- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)\n- **Schema** (PostgreSQL via Prisma):\n - `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at\n - `tags` table: id, name, color — M2M with payments via `_PaymentToTag`\n - `users` table: id, username, hashed_password (this will be REMOVED)\n- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system\n- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance\n\n## App 2: dsk-uploader (Python/Flask)\n- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database\n- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5\n- **Auth**: None (open)\n- **CSV format** (DSK Bank Bulgarian format, columns):\n - `Дата` (date, DD.MM.YYYY)\n - `Вид на трансакцията` (transaction type, Bulgarian)\n - `Основание` (reason/description — contains card number regex: `^\\d{6}x{6}\\d{4}$`)\n - `Дебит BGN` (debit amount, may be empty)\n - `Кредит BGN` (credit amount, may be empty)\n - `Наредител/Получател` (orderer/recipient name)\n - `Номер сметка на наредителя / получателя` (account number)\n- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers\n- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)\n\n## App 3: auth (Authentik)\n- **Mode**: Proxy mode via NPM (forward auth)\n- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:\n - `X-authentik-username` \n - `X-authentik-email`\n - `X-authentik-groups`\n- **No code integration needed** in the app itself — just trust these headers from NPM\n- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`\n\n---\n\n## What the New Combined App Must Do\n\n1. **Single PostgreSQL database** for all transactions\n2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST\n3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema\n4. **Unified UI** — show all payments in one table regardless of source\n5. **Source indicator** in UI — badge showing \"INGEST\", \"UPLOAD\", or \"BOTH\" (if duplicate detection added)\n6. **Source filter** in FilterBar — filter by All/Ingest/Upload\n7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM\n8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination\n9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL\n\n---\n\n## Technical Constraints\n\n- Keep Node.js backend (not Python) — extend payments-logger's stack\n- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)\n- File upload: use `multer` npm middleware\n- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)\n- Add `source` enum field (INGEST/UPLOAD) to payments schema\n- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is\n- Remove `users` table from schema\n\n---\n\n## Please Design\n\n1. Complete folder structure for the new app (suggest name: \"finance-hub\" or similar — note this is a placeholder, user will confirm)\n2. Prisma schema with new fields (`source`, `currency`)\n3. All backend API routes\n4. CSV parser design in Node.js (port of the Python logic)\n5. Authentik auth middleware\n6. Frontend component structure (React) — what's reused from payments-logger, what's new\n7. Docker Compose setup\n8. Environment variables needed\n9. Step-by-step implementation order\n10. Verification checklist\n\nBe specific about file paths and code structure. This will be used to write actual implementation code.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good plan. Let me ask the one thing I need before writing the final plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"AskUserQuestion","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"OUT","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"User has answered your questions: \"What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding.\"=\"finance-hub\". You can now continue with the user's answers in mind.","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Writing the final plan now.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"326 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# finance-hub — Implementation Plan\n\n## Context\n\nTwo separate finance apps exist as references and will be retired:\n- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.\n- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.\n\nThe new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).\n\n---\n\n## Tech Stack\n\n| Layer | Choice | Rationale |\n|-------|--------|-----------|\n| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |\n| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |\n| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |\n| Database | PostgreSQL 16 | Same as payments-logger |\n| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |\n| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |\n| Container | Docker Compose | Same pattern as both reference apps |\n\n**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage. \n**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references. \n**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.\n\n---\n\n## Folder Structure\n\n```\n/volume2/docker/finance/finance-hub/\n├── docker-compose.yml\n├── .env\n├── .env.example\n├── .gitignore\n├── backend/\n│ ├── Dockerfile\n│ ├── package.json\n│ ├── prisma/\n│ │ ├── schema.prisma\n│ │ └── migrations/\n│ │ ├── migration_lock.toml\n│ │ └── 20260508_init/\n│ │ └── migration.sql\n│ └── src/\n│ ├── index.js ← entry point (Authentik middleware wired here)\n│ ├── auth.js ← Authentik header middleware (replaces JWT auth)\n│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)\n│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)\n│ └── routes/\n│ ├── payments.js ← existing routes + source/currency additions\n│ └── upload.js ← NEW: POST /api/upload/csv\n└── frontend/\n ├── Dockerfile\n ├── package.json\n ├── vite.config.js\n ├── tailwind.config.js\n ├── postcss.config.js\n ├── index.html\n └── src/\n ├── main.jsx ← remove AuthProvider wrapper\n ├── index.css\n ├── App.jsx ← remove auth state, add Upload tab toggle\n └── components/\n ├── FilterBar.jsx ← add source filter select\n ├── PaymentTable.jsx ← add Source badge column + currency display\n ├── PaymentCard.jsx ← minor source badge addition\n ├── PaymentList.jsx ← unchanged\n └── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI\n```\n\n---\n\n## Database Schema (Prisma)\n\nFile: `backend/prisma/schema.prisma`\n\n```prisma\ngenerator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status { UNPROCESSED SENT SKIPPED }\nenum Source { INGEST UPLOAD }\n```\n\n**Key decisions:**\n- No `User` model — Authentik owns identity.\n- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.\n- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.\n- `balance` is always null for CSV rows (DSK export does not include running balance).\n- Fresh consolidated migration — no data migration from reference apps required.\n\n---\n\n## API Routes\n\n| Method | Path | Auth | Description |\n|--------|------|------|-------------|\n| GET | /api/health | public | Health check |\n| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |\n| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |\n| GET | /api/payments/meta/tags | required | All tags |\n| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |\n| GET | /api/payments/:id | required | Single payment |\n| PATCH | /api/payments/:id | required | Update status |\n| DELETE | /api/payments/:id | required | Delete |\n| POST | /api/payments/:id/send | required | Send notification |\n| POST | /api/payments/:id/skip | required | Skip |\n| POST | /api/payments/:id/tags | required | Add/upsert tag |\n| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |\n| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |\n\n---\n\n## Key Implementation Details\n\n### auth.js (replaces entire old auth module)\n```js\nconst PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n const username = req.headers['x-authentik-username'];\n if (!username) return res.status(401).json({ error: 'Unauthorized' });\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),\n };\n next();\n}\nmodule.exports = { authentikMiddleware };\n```\n\n### csvParser.js (port of dskuploader.py)\n- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8\n- `csv-parse` parses the decoded text with `columns: true`\n- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`\n- Card extraction: regex `/^\\d{6}x{6}\\d{4}$/` on first token of `Основание`\n- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`\n- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`\n- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`\n\n### payments.js changes from payments-logger\n1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call\n2. Add `source` to the `GET /` where clause filter\n3. Add `sources` to `meta/filters` response\n4. Currency-aware amount formatting in notification message\n5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)\n\n### upload.js (new)\n- `multer` memory storage, max 10 files × 10 MB\n- Calls `parseDskCsv(buffer)` per file\n- Upserts tags via `prisma.tag.upsert` then connects\n- Returns `{ imported, skipped, errors, payments[] }`\n\n### Frontend changes\n- **Delete**: `auth.js`, `AuthProvider.jsx`\n- **main.jsx**: Remove `<AuthProvider>` wrapper\n- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add \"Payments\" / \"Upload CSV\" tab toggle\n- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols\n- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell\n- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`\n\n---\n\n## Docker Compose\n\n```yaml\nservices:\n db:\n image: postgres:16-alpine\n environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: ${DB_PASSWORD}, POSTGRES_DB: finance_hub }\n volumes: [pgdata:/var/lib/postgresql/data]\n healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }\n\n backend:\n build: ./backend\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports: [\"${BACKEND_PORT:-3001}:3001\"]\n depends_on: { db: { condition: service_healthy } }\n\n frontend:\n build: ./frontend\n ports: [\"${FRONTEND_PORT:-5175}:5173\"]\n depends_on: [backend]\n\nvolumes: { pgdata: }\n```\n\n**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.\n\n---\n\n## Environment Variables (.env)\n\n```bash\nDB_PASSWORD=change_me\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\nTZ=Europe/Sofia\nBACKEND_PORT=3001\nFRONTEND_PORT=5175\n```\n\nRemoved vs payments-logger: `JWT_SECRET`, `JWT_EXPIRE_MINUTES`.\n\n---\n\n## Implementation Order\n\n1. Create folder structure and write `docker-compose.yml`, `.env.example`, `.gitignore`\n2. Write `backend/prisma/schema.prisma` and migration SQL\n3. Write `backend/package.json` (add `csv-parse`, `iconv-lite`, `multer`; remove `bcryptjs`, `jose`)\n4. Write `backend/Dockerfile`\n5. Write `backend/src/auth.js` (Authentik middleware)\n6. Copy `backend/src/parser.js` verbatim from payments-logger\n7. Write `backend/src/csvParser.js` (Python port)\n8. Write `backend/src/routes/upload.js`\n9. Write `backend/src/routes/payments.js` (from payments-logger + 5 changes listed above)\n10. Write `backend/src/index.js`\n11. Copy frontend base from payments-logger; delete `auth.js` + `AuthProvider.jsx`\n12. Update `main.jsx`, `App.jsx`, `FilterBar.jsx`, `PaymentTable.jsx`\n13. Write `frontend/src/components/UploadPanel.jsx`\n14. Update `frontend/vite.config.js`\n15. `docker compose build && docker compose up -d`\n16. Run verification checklist\n\n---\n\n## Verification\n\n**Schema**\n- `payments` table has `source`, `currency`, `debit_bgn`, `credit_bgn`, `transaction_type`, `payer_account`\n- No `users` table; `Source` enum exists\n\n**Auth**\n- `GET /api/payments` → 401 without `x-authentik-username` header\n- `POST /api/payments/ingest` → 201 without any header\n- `curl -H \"x-authentik-username: test\" localhost:3001/api/payments` → 200\n\n**SMS Ingest**\n- DSK POS SMS → `source=INGEST`, `currency=EUR`, correct amount/card/recipient\n- Apple Wallet structured body → `type=WALLET`, `source=INGEST`\n- Rate limiter → 429 after 200 req/min\n\n**CSV Upload**\n- Single DSK CSV → rows with `source=UPLOAD`, `currency=BGN`\n- Multiple CSVs in one request → all merged\n- `ТРАНСФЕР СОБСТВЕНИ СМЕТКИ` rows counted in `skipped`, not imported\n- Card regex match from `Основание` column\n- Auto-tags applied (ЗАПЛАТА→Salary, LIDL→Groceries)\n- cp1251 file imports correctly\n\n**UI**\n- Source badge visible in payment table (SMS indigo, CSV emerald)\n- Source dropdown in FilterBar filters correctly\n- Amount shows correct currency per row\n- Upload Panel: drag-and-drop works, result summary shows counts\n- Logout redirects to Authentik sign_out\n- No login form shown (Authentik handles it at NPM level)\n- Tags, send, skip, delete all still work\n\n## Reference Files\n\n- `/volume2/docker/finance/payments-logger/backend/src/routes/payments.js`\n- `/volume2/docker/finance/payments-logger/backend/src/parser.js`\n- `/volume2/docker/finance/payments-logger/backend/src/index.js`\n- `/volume2/docker/finance/payments-logger/backend/src/auth.js`\n- `/volume2/docker/finance/payments-logger/backend/prisma/schema.prisma`\n- `/volume2/docker/finance/payments-logger/frontend/src/App.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/PaymentTable.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/FilterBar.jsx`\n- `/volume2/docker/finance/dsk-uploader/dskuploader.py`\n- `/volume2/docker/finance/auth/docker-compose.yml`","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Claude’s Plan","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Stayed in plan mode","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good question. Here's the full breakdown:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Backend Tech Stack — Options","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Backend Tech Stack — Options","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Why:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"payments-logger is already Node.js/Express/Prisma. The new app is 80% payments-logger with CSV upload added on top. Keeping the same stack means:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"verbatim, zero rewrite","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy the entire","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"routes/payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with minimal edits","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Same Prisma schema workflow, same migrations, same Docker image","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The CSV parsing logic (the only Python-specific thing) ports cleanly to","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"csv-parse","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— it's just regex + string manipulation, nothing pandas-specific","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Trade-off:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Have to port the Python CSV parsing to JS. It's ~150 lines and mostly string manipulation — straightforward.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option B: Python + FastAPI + SQLAlchemy","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option B: Python + FastAPI + SQLAlchemy","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rewrite everything in Python. dsk-uploader is Python, so CSV parsing is already done.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep the dsk-uploader CSV logic as-is (no porting). Python has better data science libraries if you later add analytics.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Lose the entire payments-logger backend (routes, parser, Prisma schema) — full rewrite. FastAPI + SQLAlchemy is a different mental model than Express + Prisma. Frontend stays React anyway, so the stack split doesn't simplify anything.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"More work overall, gains almost nothing.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep Node.js as the main API, add a separate Python FastAPI service just for CSV parsing. They share the DB.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Zero porting — Python CSV code used as-is.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two backend services to maintain, deploy, and keep in sync. Inter-service HTTP calls. Two Dockerfiles. For ~150 lines of CSV logic, this is massively over-engineered.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Not worth it.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Extend dsk-uploader into a full payments app.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pandas for CSV, no porting.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Jinja2 templates instead of React (or add React separately). Would need to reimplement the entire payments-logger (SMS parser, notification system, tag management, pagination/filtering). Flask's Jinja templating is far less capable than the existing React UI. The React frontend is the stronger UI foundation.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Worst of all options — rebuild the harder parts (UI, SMS parser, notification) for no gain.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Summary","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Summary","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"CSV porting effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"App rewrite effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Result 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Everything else in the plan reuses payments-logger code directly. That's why Node.js is the clear winner here.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Want to adjust the stack, or shall I proceed with Option A?","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ok sounds good. Implement all you suggested","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Starting implementation. Let me first read all the reference files I'll need to copy from.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"payments.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"App.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"App.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"FilterBar.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"FilterBar.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentTable.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentTable.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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payments-logger.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.css","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.css","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"vite.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"vite.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"tailwind.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"tailwind.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"postcss.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"postcss.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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components.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentCard.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentCard.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentList.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentList.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"schema.prisma","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"schema.prisma","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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Let me set up the todo list and start building.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create finance-hub directory structure","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"mkdir -p /volume2/docker/finance/finance-hub/backend/src/routes \\\n /volume2/docker/finance/finance-hub/backend/prisma/migrations/20260508_init \\\n /volume2/docker/finance/finance-hub/frontend/src/components && echo \"done\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":24,"on_screen":false,"help_text":"Copy code","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"OUT","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"done","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"docker-compose.yml","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"docker-compose.yml","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"45 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"version: '3.8'\n\nservices:\n db:\n image: postgres:16-alpine\n restart: unless-stopped\n environment:\n POSTGRES_USER: finance\n POSTGRES_PASSWORD: ${DB_PASSWORD}\n POSTGRES_DB: finance_hub\n volumes:\n - pgdata:/var/lib/postgresql/data\n healthcheck:\n test: [\"CMD-SHELL\", \"pg_isready -U finance -d finance_hub\"]\n interval: 5s\n timeout: 5s\n retries: 5\n\n backend:\n build: ./backend\n restart: unless-stopped\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports:\n - \"${BACKEND_PORT:-3001}:3001\"\n depends_on:\n db:\n condition: service_healthy\n\n frontend:\n build: ./frontend\n restart: unless-stopped\n ports:\n - \"${FRONTEND_PORT:-5175}:5173\"\n depends_on:\n - backend\n\nvolumes:\n pgdata:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".env.example","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".env.example","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"15 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Database\nDB_PASSWORD=change_me_strong_password\n\n# Notifier service (for SMS payment notifications)\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\n\n# Timezone (used by SMS parser for Bulgarian bank timestamps)\nTZ=Europe/Sofia\n\n# Ports (optional — defaults shown)\nBACKEND_PORT=3001\nFRONTEND_PORT=5175","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".gitignore","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".gitignore","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"5 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env\nnode_modules/\ndist/\n*.log","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"schema.prisma","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"schema.prisma","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"54 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"generator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status {\n UNPROCESSED\n SENT\n SKIPPED\n}\n\nenum Source {\n INGEST\n UPLOAD\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration.sql","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration.sql","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"55 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- CreateEnum\nCREATE TYPE \"Status\" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');\nCREATE TYPE \"Source\" AS ENUM ('INGEST', 'UPLOAD');\n\n-- CreateTable\nCREATE TABLE \"payments\" (\n \"id\" SERIAL PRIMARY KEY,\n \"raw_message\" TEXT NOT NULL,\n \"date\" TIMESTAMP(3),\n \"type\" TEXT,\n \"card\" TEXT,\n \"recipient\" TEXT,\n \"amount\" DOUBLE PRECISION,\n \"currency\" TEXT DEFAULT 'EUR',\n \"balance\" DOUBLE PRECISION,\n \"source\" \"Source\" NOT NULL DEFAULT 'INGEST',\n \"status\" \"Status\" NOT NULL DEFAULT 'UNPROCESSED',\n \"notified_at\" TIMESTAMP(3),\n \"notify_phone\" TEXT,\n \"debit_bgn\" DOUBLE PRECISION,\n \"credit_bgn\" DOUBLE PRECISION,\n \"transaction_type\" TEXT,\n \"payer_account\" TEXT,\n \"created_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,\n \"updated_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP\n);\n\n-- CreateTable\nCREATE TABLE \"tags\" (\n \"id\" SERIAL PRIMARY KEY,\n \"name\" TEXT NOT NULL,\n \"color\" TEXT NOT NULL DEFAULT '#6b7280'\n);\n\n-- CreateUniqueIndex\nCREATE UNIQUE INDEX \"tags_name_key\" ON \"tags\"(\"name\");\n\n-- CreateTable (M2M join)\nCREATE TABLE \"_PaymentToTag\" (\n \"A\" INTEGER NOT NULL,\n \"B\" INTEGER NOT NULL,\n CONSTRAINT \"_PaymentToTag_AB_pkey\" PRIMARY KEY (\"A\", \"B\")\n);\n\nCREATE INDEX \"_PaymentToTag_B_index\" ON \"_PaymentToTag\"(\"B\");\n\n-- AddForeignKey\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_A_fkey\"\n FOREIGN KEY (\"A\") REFERENCES \"payments\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;\n\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_B_fkey\"\n FOREIGN KEY (\"B\") REFERENCES \"tags\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration_lock.toml","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration_lock.toml","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"4 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Please do not edit this file manually\n# It should be added in your version-control system (e.g., Git)\nprovider = \"postgresql\"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"26 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"{\n \"name\": \"finance-hub-backend\",\n \"version\": \"1.0.0\",\n \"main\": \"src/index.js\",\n \"scripts\": {\n \"start\": \"node src/index.js\",\n \"dev\": \"nodemon src/index.js\",\n \"prisma:generate\": \"prisma generate\",\n \"prisma:migrate\": \"prisma migrate deploy\"\n },\n \"dependencies\": {\n \"@prisma/client\": \"^5.22.0\",\n \"cors\": \"^2.8.5\",\n \"csv-parse\": \"^5.5.6\",\n \"express\": \"^4.21.1\",\n \"express-rate-limit\": \"^7.4.0\",\n \"iconv-lite\": \"^0.6.3\",\n \"morgan\": \"^1.10.0\",\n \"multer\": \"^1.4.5-lts.1\"\n },\n \"devDependencies\": {\n \"nodemon\": \"^3.1.7\",\n \"prisma\": \"^5.22.0\"\n }\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"18 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"FROM node:20-alpine\n\nRUN apk add --no-cache openssl\n\nWORKDIR /app\n\nCOPY package.json package-lock.json* ./\nRUN npm install\n\nCOPY prisma ./prisma\nRUN npx prisma generate\n\nCOPY src ./src\n\nEXPOSE 3001\n\nCMD [\"sh\", \"-c\", \"npx prisma migrate deploy && node src/index.js\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"auth.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"auth.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"27 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const PUBLIC_PATHS = new Set([\n '/api/health',\n '/api/payments/ingest',\n]);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n\n const username = req.headers['x-authentik-username'];\n if (!username) {\n return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });\n }\n\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '')\n .split(',')\n .map(g => g.trim())\n .filter(Boolean),\n };\n\n next();\n}\n\nmodule.exports = { authentikMiddleware };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"104 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/**\n * Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)\n *\n * Supported formats:\n *\n * POS / INTERNET / ECOM / P2P payment:\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.\n *\n * ATM withdrawal:\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.\n *\n * ATM utility payment (amount may include fee as AMOUNT/FEE):\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.\n */\n\nconst LOCAL_TZ = process.env.TZ || 'Europe/Sofia';\n\n/**\n * Convert a local-timezone date/time to a UTC Date object.\n * Uses Intl to resolve the actual UTC offset (DST-aware).\n */\nfunction localToUtc(year, month, day, hour, minute) {\n const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));\n\n const formatter = new Intl.DateTimeFormat('en-US', {\n timeZone: LOCAL_TZ,\n year: 'numeric', month: '2-digit', day: '2-digit',\n hour: '2-digit', minute: '2-digit', second: '2-digit',\n hour12: false,\n });\n\n const parts = {};\n formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });\n\n const localAtNaive = new Date(Date.UTC(\n parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),\n parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),\n ));\n\n const offsetMs = localAtNaive.getTime() - naive.getTime();\n return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);\n}\n\nfunction parsePaymentSms(message) {\n const result = {\n rawMessage: message,\n date: null,\n type: null,\n card: null,\n recipient: null,\n amount: null,\n balance: null,\n };\n\n // Date and time: \"Na DD/MM/YYYY v HH:MM\"\n const dateMatch = message.match(/Na (\\d{2})\\/(\\d{2})\\/(\\d{4}) v (\\d{2}):(\\d{2})/i);\n if (dateMatch) {\n const [, day, month, year, hour, minute] = dateMatch;\n result.date = localToUtc(\n parseInt(year), parseInt(month), parseInt(day),\n parseInt(hour), parseInt(minute),\n );\n }\n\n // Card mask: \"s karta 400915***4447\" or \"s karta 483890***7162\"\n const cardMatch = message.match(/s karta\\s+([\\d*]+)/i);\n if (cardMatch) {\n result.card = cardMatch[1];\n }\n\n // Transaction type: supports both prepositions\n // \"na POS\" / \"na ATM\" / \"na INTERNET\" etc. (payment)\n // \"ot ATM\" (withdrawal)\n const typeMatch = message.match(/(?:na|ot)\\s+(POS|ATM|INTERNET|ECOM|P2P)\\b/i);\n if (typeMatch) {\n result.type = typeMatch[1].toUpperCase();\n }\n\n // Recipient address: \"s adres: MERCHANT\" or \"s adres:MERCHANT\" (no space variant)\n const recipientMatch = message.match(/s adres:\\s*([^.]+)\\./i);\n if (recipientMatch) {\n result.recipient = recipientMatch[1].trim();\n }\n\n // Amount: handles both verbs and the AMOUNT/FEE suffix format\n // \"sa plateni 7.78 EUR\"\n // \"sa iztegleni 400.00 EUR\"\n // \"sa plateni 0.50 EUR/0.50 EUR\" → captures 0.50 (the charged amount, ignoring fee)\n const amountMatch = message.match(/sa (?:plateni|iztegleni)\\s+([\\d.,]+)\\s+[A-Z]{3}/i);\n if (amountMatch) {\n result.amount = parseFloat(amountMatch[1].replace(',', '.'));\n }\n\n // Balance: \"Nalichni: 2583.07 EUR.\"\n const balanceMatch = message.match(/Nalichni:\\s*([\\d.,]+)\\s+[A-Z]{3}/i);\n if (balanceMatch) {\n result.balance = parseFloat(balanceMatch[1].replace(',', '.'));\n }\n\n return result;\n}\n\nmodule.exports = { parsePaymentSms };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"csvParser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"csvParser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"175 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/**\n * DSK Bank CSV parser — Node.js port of dskuploader.py\n *\n * DSK Bank exports use Windows-1251 (cp1251) encoding.\n * Each row maps to a Payment record with source=UPLOAD, currency=BGN.\n */\n\nconst { parse } = require('csv-parse');\nconst iconv = require('iconv-lite');\n\nconst SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';\nconst CARD_REGEX = /^\\d{6}x{6}\\d{4}$/;\nconst POS_REGEX = /^\\s*ПЛАЩАНЕ\\s+НА\\s+ПОС\\s+\\d{2}\\.\\d{2}\\.\\d{4}\\s+\\d{2}:\\d{2}/;\n\nconst COL = {\n DATE: 'Дата',\n TYPE: 'Вид на трансакцията',\n REASON: 'Основание',\n DEBIT: 'Дебит BGN',\n CREDIT: 'Кредит BGN',\n PAYEE: 'Наредител/Получател',\n ACCT: 'Номер сметка на наредителя / получателя',\n};\n\nconst TAG_RULES = [\n ['reason', 'ЗАПЛАТА', 'Salary'],\n ['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],\n ['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],\n ['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],\n ['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],\n ['payee', 'VIVACOM', 'Subscriptions'],\n ['payee', 'Google', 'Subscriptions'],\n ['payee', 'SkyShowtime', 'Subscriptions'],\n ['payee', 'NETFLIX', 'Subscriptions'],\n ['payee', 'LUKOIL', 'Bills'],\n ['payee', 'CityGate', 'Bills'],\n ['payee', 'CBA', 'Groceries'],\n ['payee', 'FANTASTICO', 'Groceries'],\n ['payee', 'LIDL', 'Groceries'],\n];\n\nfunction parseNum(val) {\n if (val == null || val === '') return null;\n if (typeof val === 'number') return isNaN(val) ? null : val;\n const s = String(val).trim().replace(/\\xa0/g, '').replace(/ /g, '').replace(',', '.');\n const n = parseFloat(s);\n return isNaN(n) ? null : n;\n}\n\nfunction parseDate(val) {\n if (!val) return null;\n const s = String(val).trim();\n const m = s.match(/^(\\d{2})\\.(\\d{2})\\.(\\d{4})$/);\n if (m) {\n return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));\n }\n return null;\n}\n\nfunction processReasonAndCard(reason) {\n if (!reason || typeof reason !== 'string') return { reason: '', card: null };\n\n const parts = reason.trim().split(' ');\n let card = null;\n let cleanReason = reason.trim();\n\n if (parts[0] && CARD_REGEX.test(parts[0])) {\n card = parts[0];\n cleanReason = parts.slice(1).join(' ').trim();\n }\n\n if (POS_REGEX.test(cleanReason)) {\n const posParts = cleanReason.split('<br/>');\n try {\n const dateTime = posParts[0].split('ПОС ')[1];\n cleanReason = `POS PAYMENT ${dateTime}`;\n } catch (_) { /* keep original */ }\n }\n\n return { reason: cleanReason.replace(/\\s+/g, ' ').trim(), card };\n}\n\nfunction generateTags(fields) {\n const tags = new Set();\n for (const [field, keyword, tagName] of TAG_RULES) {\n if ((fields[field] || '').includes(keyword)) {\n tags.add(tagName);\n }\n }\n return Array.from(tags);\n}\n\nfunction processRow(row) {\n const transactionType = (row[COL.TYPE] || '').trim();\n if (transactionType === SKIP_TYPE) return null;\n\n const { reason, card } = processReasonAndCard(row[COL.REASON]);\n const payee = (row[COL.PAYEE] || '').trim();\n const payerAccount = (row[COL.ACCT] || '').trim();\n const debitBgn = parseNum(row[COL.DEBIT]);\n const creditBgn = parseNum(row[COL.CREDIT]);\n const date = parseDate(row[COL.DATE]);\n\n const autoTags = generateTags({ reason, transactionType, payee, debitBgn, creditBgn });\n\n const amount = debitBgn ?? creditBgn ?? null;\n\n const rawMessage = [\n row[COL.DATE] && `Date: ${row[COL.DATE]}`,\n transactionType && `Type: ${transactionType}`,\n payee && `Payee: ${payee}`,\n debitBgn != null && `Debit: ${debitBgn} BGN`,\n creditBgn != null && `Credit: ${creditBgn} BGN`,\n ].filter(Boolean).join(' | ');\n\n return {\n rawMessage,\n date,\n type: null,\n card,\n recipient: payee || null,\n amount,\n currency: 'BGN',\n balance: null,\n source: 'UPLOAD',\n debitBgn,\n creditBgn,\n transactionType: transactionType || null,\n payerAccount: payerAccount || null,\n autoTags,\n };\n}\n\n/**\n * Parse a Buffer containing a DSK Bank CSV (cp1251 or UTF-8).\n * Returns { rows, skipped, errors }.\n */\nasync function parseDskCsv(buffer) {\n // Try cp1251 first (DSK Bank export encoding), fall back to UTF-8\n let text = iconv.decode(buffer, 'cp1251');\n if (!text.includes(COL.DATE)) {\n text = buffer.toString('utf-8');\n }\n\n return new Promise((resolve, reject) => {\n const rows = [];\n const errors = [];\n let skipped = 0;\n\n const parser = parse(text, {\n columns: true,\n skip_empty_lines: true,\n trim: true,\n relax_column_count: true,\n });\n\n parser.on('readable', () => {\n let record;\n while ((record = parser.read()) !== null) {\n try {\n const row = processRow(record);\n if (row === null) { skipped++; } else { rows.push(row); }\n } catch (err) {\n errors.push(err.message);\n }\n }\n });\n\n parser.on('error', reject);\n parser.on('end', () => resolve({ rows, skipped, errors }));\n });\n}\n\nmodule.exports = { parseDskCsv };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"39 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst cors = require('cors');\nconst morgan = require('morgan');\nconst rateLimit = require('express-rate-limit');\nconst { authentikMiddleware } = require('./auth');\nconst paymentsRouter = require('./routes/payments');\nconst uploadRouter = require('./routes/upload');\n\nconst app = express();\nconst PORT = process.env.PORT || 3001;\n\napp.use(cors());\napp.use(express.json({ limit: '16kb' }));\napp.use(morgan('combined'));\n\n// Rate-limit the public ingest endpoint before auth middleware\nconst ingestLimiter = rateLimit({\n windowMs: 60 * 1000,\n max: 200,\n standardHeaders: true,\n legacyHeaders: false,\n message: { error: 'Too many requests, slow down' },\n});\napp.use('/api/payments/ingest', ingestLimiter);\n\n// Authentik header auth (skips /api/health and /api/payments/ingest)\napp.use(authentikMiddleware);\n\napp.get('/api/health', (_req, res) => {\n res.json({ status: 'ok', timestamp: new Date().toISOString() });\n});\n\napp.use('/api/payments', paymentsRouter);\napp.use('/api/upload', uploadRouter);\n\napp.listen(PORT, '0.0.0.0', () => {\n console.log(`Finance Hub API running on port ${PORT}`);\n});","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"payments.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"399 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst { PrismaClient } = require('@prisma/client');\nconst { parsePaymentSms } = require('../parser');\n\nconst router = express.Router();\nconst prisma = new PrismaClient();\n\nconst NOTIFIER_URL = process.env.NOTIFIER_URL;\nconst NOTIFIER_CHANNEL = process.env.NOTIFIER_CHANNEL || 'viber';\nconst DEFAULT_PHONE = process.env.NOTIFY_DEFAULT_PHONE;\n\n// ── Helpers ───────────────────────────────────────────────────────────────────\n\nfunction parseId(raw) {\n const id = parseInt(raw, 10);\n return Number.isFinite(id) ? id : null;\n}\n\nfunction formatNotifyMessage(payment) {\n const currency = payment.currency || 'EUR';\n const parts = [];\n if (payment.amount != null) parts.push(`Amount: ${payment.amount.toFixed(2)} ${currency}`);\n if (payment.recipient) parts.push(`At: ${payment.recipient}`);\n if (payment.balance != null) parts.push(`Balance: ${payment.balance.toFixed(2)} ${currency}`);\n if (payment.date) parts.push(`Date: ${new Date(payment.date).toLocaleString('en-GB')}`);\n return parts.join('\\n');\n}\n\nasync function sendNotification(payment) {\n if (!NOTIFIER_URL) {\n console.warn('[NOTIFY] NOTIFIER_URL not set — skipping notification');\n return;\n }\n\n const phone = payment.notifyPhone || DEFAULT_PHONE;\n if (!phone) {\n console.warn('[NOTIFY] No phone number for payment #' + payment.id + ' and NOTIFY_DEFAULT_PHONE not set');\n return;\n }\n\n const body = {\n phone,\n notification: NOTIFIER_CHANNEL,\n message: formatNotifyMessage(payment),\n };\n\n const res = await fetch(NOTIFIER_URL, {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify(body),\n });\n\n if (!res.ok) {\n const text = await res.text().catch(() => '');\n throw new Error(`Notifier responded ${res.status}: ${text}`);\n }\n}\n\n// ── Ingest a payment (public — no auth) ──────────────────────────────────────\n//\n// Two modes:\n//\n// SMS mode (default):\n// { \"message\": \"<raw SMS text>\", \"notifyPhone\": \"...\" }\n//\n// Structured mode (Apple Wallet / manual):\n// { \"ingestMode\": \"apple_wallet\", \"amount\": 7.78, \"recipient\": \"Apple Store\",\n// \"type\": \"WALLET\", \"card\": \"••••4447\", \"date\": \"2026-02-22T10:30:00Z\" }\n//\nrouter.post('/ingest', async (req, res) => {\n try {\n const { message, notifyPhone, ingestMode } = req.body;\n\n let data;\n\n if (ingestMode === 'apple_wallet' || (!message && req.body.amount != null)) {\n // ── Structured / Apple Wallet mode ──────────────────────────────────────\n const { amount, recipient, type, card, date, balance } = req.body;\n if (amount == null || !recipient) {\n return res.status(400).json({ error: 'amount and recipient are required for structured ingest' });\n }\n\n const rawMessage = [\n `Source: ${ingestMode || 'structured'}`,\n `Amount: ${amount}`,\n recipient && `Recipient: ${recipient}`,\n type && `Type: ${type}`,\n card && `Card: ${card}`,\n ].filter(Boolean).join(' | ');\n\n data = {\n rawMessage,\n date: date ? new Date(date) : new Date(),\n type: type || 'WALLET',\n card: card || null,\n recipient,\n amount: parseFloat(amount),\n currency: 'EUR',\n balance: balance != null ? parseFloat(balance) : null,\n source: 'INGEST',\n notifyPhone: notifyPhone || null,\n };\n\n } else {\n // ── SMS mode ─────────────────────────────────────────────────────────────\n if (!message) {\n return res.status(400).json({ error: 'message is required' });\n }\n if (typeof message !== 'string' || message.length > 2000) {\n return res.status(400).json({ error: 'message must be a string under 2000 characters' });\n }\n\n const parsed = parsePaymentSms(message);\n data = {\n rawMessage: parsed.rawMessage,\n date: parsed.date,\n type: parsed.type,\n card: parsed.card,\n recipient: parsed.recipient,\n amount: parsed.amount,\n currency: 'EUR',\n balance: parsed.balance,\n source: 'INGEST',\n notifyPhone: notifyPhone || null,\n };\n }\n\n const payment = await prisma.payment.create({\n data,\n include: { tags: true },\n });\n\n res.status(201).json(payment);\n } catch (err) {\n console.error('Ingest error:', err);\n res.status(500).json({ error: 'Failed to ingest payment' });\n }\n});\n\n// ── List payments with filtering ──────────────────────────────────────────────\nrouter.get('/', async (req, res) => {\n try {\n const {\n status,\n type,\n tag,\n source,\n recipient,\n dateFrom,\n dateTo,\n search,\n sortBy = 'createdAt',\n sortDir = 'desc',\n page = 1,\n } = req.query;\n\n const limit = Math.min(parseInt(req.query.limit, 10) || 50, 200);\n\n const where = {};\n\n if (status) where.status = status;\n if (type) where.type = type;\n if (source) where.source = source;\n if (recipient) where.recipient = { contains: recipient, mode: 'insensitive' };\n if (tag) where.tags = { some: { name: tag } };\n if (search) {\n where.OR = [\n { rawMessage: { contains: search, mode: 'insensitive' } },\n { recipient: { contains: search, mode: 'insensitive' } },\n ];\n }\n if (dateFrom || dateTo) {\n where.date = {};\n if (dateFrom) where.date.gte = new Date(dateFrom);\n if (dateTo) where.date.lte = new Date(dateTo);\n }\n\n const allowedSortFields = ['date', 'amount', 'balance', 'recipient', 'type', 'source', 'createdAt', 'status'];\n const orderField = allowedSortFields.includes(sortBy) ? sortBy : 'createdAt';\n const orderDir = sortDir === 'asc' ? 'asc' : 'desc';\n\n const skip = (parseInt(page, 10) - 1) * limit;\n\n const [payments, total] = await Promise.all([\n prisma.payment.findMany({\n where,\n include: { tags: true },\n orderBy: { [orderField]: orderDir },\n skip,\n take: limit,\n }),\n prisma.payment.count({ where }),\n ]);\n\n res.json({ payments, total, page: parseInt(page, 10), limit });\n } catch (err) {\n console.error('List error:', err);\n res.status(500).json({ error: 'Failed to list payments' });\n }\n});\n\n// ── Get filter options ────────────────────────────────────────────────────────\nrouter.get('/meta/filters', async (_req, res) => {\n try {\n const [types, recipients, tags, sources] = await Promise.all([\n prisma.payment.findMany({ distinct: ['type'], select: { type: true }, where: { type: { not: null } } }),\n prisma.payment.findMany({ distinct: ['recipient'], select: { recipient: true }, where: { recipient: { not: null } } }),\n prisma.tag.findMany({ orderBy: { name: 'asc' } }),\n prisma.payment.findMany({ distinct: ['source'], select: { source: true } }),\n ]);\n\n res.json({\n types: types.map(t => t.type),\n recipients: recipients.map(r => r.recipient),\n tags,\n sources: sources.map(s => s.source),\n });\n } catch (err) {\n res.status(500).json({ error: 'Failed to get filters' });\n }\n});\n\n// ── Get all tags ──────────────────────────────────────────────────────────────\nrouter.get('/meta/tags', async (_req, res) => {\n try {\n const tags = await prisma.tag.findMany({ orderBy: { name: 'asc' } });\n res.json(tags);\n } catch (err) {\n res.status(500).json({ error: 'Failed to list tags' });\n }\n});\n\n// ── Get single payment ────────────────────────────────────────────────────────\nrouter.get('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({\n where: { id },\n include: { tags: true },\n });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n res.json(payment);\n } catch (err) {\n console.error('Get error:', err);\n res.status(500).json({ error: 'Failed to get payment' });\n }\n});\n\n// ── Update payment metadata (status) ─────────────────────────────────────────\nrouter.patch('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const { status } = req.body;\n const data = {};\n\n if (status) {\n const validStatuses = ['UNPROCESSED', 'SENT', 'SKIPPED'];\n if (!validStatuses.includes(status)) {\n return res.status(400).json({ error: `Invalid status. Must be one of: ${validStatuses.join(', ')}` });\n }\n data.status = status;\n }\n\n if (Object.keys(data).length === 0) {\n return res.status(400).json({ error: 'No valid fields to update' });\n }\n\n const updated = await prisma.payment.update({\n where: { id },\n data,\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n if (err.code === 'P2025') return res.status(404).json({ error: 'Not found' });\n console.error('Update error:', err);\n res.status(500).json({ error: 'Failed to update payment' });\n }\n});\n\n// ── Delete payment ───────────────────────────────────────────────────────────\nrouter.delete('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n await prisma.payment.delete({ where: { id } });\n res.json({ success: true });\n } catch (err) {\n if (err.code === 'P2025') return res.status(404).json({ error: 'Not found' });\n console.error('Delete error:', err);\n res.status(500).json({ error: 'Failed to delete payment' });\n }\n});\n\n// ── Send notification (mark as SENT + call notifier service) ─────────────────\nrouter.post('/:id/send', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({ where: { id } });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n if (payment.status !== 'UNPROCESSED') {\n return res.status(409).json({ error: `Payment is already ${payment.status.toLowerCase()}` });\n }\n\n await sendNotification(payment);\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { status: 'SENT', notifiedAt: new Date() },\n include: { tags: true },\n });\n\n res.json(updated);\n } catch (err) {\n console.error('Send error:', err);\n res.status(500).json({ error: 'Failed to send notification' });\n }\n});\n\n// ── Skip notification (mark as SKIPPED) ──────────────────────────────────────\nrouter.post('/:id/skip', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({ where: { id } });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n if (payment.status !== 'UNPROCESSED') {\n return res.status(409).json({ error: `Payment is already ${payment.status.toLowerCase()}` });\n }\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { status: 'SKIPPED' },\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n console.error('Skip error:', err);\n res.status(500).json({ error: 'Failed to skip payment' });\n }\n});\n\n// ── Add tag to payment ────────────────────────────────────────────────────────\nrouter.post('/:id/tags', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const { name, color } = req.body;\n if (!name) return res.status(400).json({ error: 'tag name is required' });\n\n const tag = await prisma.tag.upsert({\n where: { name },\n update: {},\n create: { name, color: color || '#6b7280' },\n });\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { tags: { connect: { id: tag.id } } },\n include: { tags: true },\n });\n\n res.json(updated);\n } catch (err) {\n console.error('Tag error:', err);\n res.status(500).json({ error: 'Failed to add tag' });\n }\n});\n\n// ── Remove tag from payment ───────────────────────────────────────────────────\nrouter.delete('/:id/tags/:tagId', async (req, res) => {\n const id = parseId(req.params.id);\n const tagId = parseId(req.params.tagId);\n if (id === null || tagId === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const updated = await prisma.payment.update({\n where: { id },\n data: { tags: { disconnect: { id: tagId } } },\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n console.error('Remove tag error:', err);\n res.status(500).json({ error: 'Failed to remove tag' });\n }\n});\n\nmodule.exports = router;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"upload.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"upload.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"89 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst multer = require('multer');\nconst { PrismaClient } = require('@prisma/client');\nconst { parseDskCsv } = require('../csvParser');\n\nconst router = express.Router();\nconst prisma = new PrismaClient();\n\nconst upload = multer({\n storage: multer.memoryStorage(),\n limits: { fileSize: 10 * 1024 * 1024, files: 10 },\n fileFilter: (_req, file, cb) => {\n if (file.mimetype === 'text/csv' || file.originalname.toLowerCase().endsWith('.csv')) {\n cb(null, true);\n } else {\n cb(new Error('Only CSV files are accepted'));\n }\n },\n});\n\n// POST /api/upload/csv\n// Accepts 1-10 CSV files, parses them, stores to DB with source=UPLOAD.\n// Returns { imported, skipped, errors, payments[] }\nrouter.post('/csv', upload.array('files', 10), async (req, res) => {\n if (!req.files || req.files.length === 0) {\n return res.status(400).json({ error: 'No files uploaded' });\n }\n\n const allRows = [];\n const allErrors = [];\n let totalSkipped = 0;\n\n for (const file of req.files) {\n try {\n const { rows, skipped, errors } = await parseDskCsv(file.buffer);\n allRows.push(...rows);\n totalSkipped += skipped;\n allErrors.push(...errors.map(e => `${file.originalname}: ${e}`));\n } catch (err) {\n allErrors.push(`${file.originalname}: ${err.message}`);\n }\n }\n\n if (allRows.length === 0) {\n return res.status(422).json({\n error: 'No importable rows found',\n skipped: totalSkipped,\n errors: allErrors,\n });\n }\n\n const created = [];\n\n for (const row of allRows) {\n const { autoTags, ...paymentData } = row;\n try {\n const tagConnects = [];\n for (const tagName of autoTags) {\n const tag = await prisma.tag.upsert({\n where: { name: tagName },\n update: {},\n create: { name: tagName, color: '#6b7280' },\n });\n tagConnects.push({ id: tag.id });\n }\n\n const payment = await prisma.payment.create({\n data: {\n ...paymentData,\n ...(tagConnects.length ? { tags: { connect: tagConnects } } : {}),\n },\n include: { tags: true },\n });\n created.push(payment);\n } catch (err) {\n allErrors.push(`Row insert failed: ${err.message}`);\n }\n }\n\n res.status(201).json({\n imported: created.length,\n skipped: totalSkipped,\n errors: allErrors,\n payments: created,\n });\n});\n\nmodule.exports = router;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now writing all frontend config files:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"24 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"{\n \"name\": \"finance-hub-frontend\",\n \"version\": \"1.0.0\",\n \"type\": \"module\",\n \"scripts\": {\n \"dev\": \"vite\",\n \"build\": \"vite build\",\n \"preview\": \"vite preview\"\n },\n \"dependencies\": {\n \"lucide-react\": \"^0.460.0\",\n \"react\": \"^18.3.1\",\n \"react-dom\": \"^18.3.1\"\n },\n \"devDependencies\": {\n \"@types/react\": \"^18.3.12\",\n \"@vitejs/plugin-react\": \"^4.3.4\",\n \"autoprefixer\": \"^10.4.20\",\n \"postcss\": \"^8.4.49\",\n \"tailwindcss\": \"^3.4.15\",\n \"vite\": \"^6.0.1\"\n }\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"FROM node:20-alpine\n\nWORKDIR /app\n\nCOPY package.json package-lock.json* ./\nRUN npm install\n\nCOPY . .\n\nEXPOSE 5173\n\nCMD [\"npm\", \"run\", \"dev\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"}]...
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Claude Code
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EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
report(1).csv, Editor Group 1
report(2).csv, Editor Group 1
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
Design new payment-logge…, Editor Group 2
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Ln 9, Col 45
Info: Setting up SSH Host nas: Setting up SSH tunnel
Design new payment-logger and dsk-uploader hybrid app
Session history
New session
Message actions
payments.js
payments.js
ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.
Thinking
Thinking
I'll explore all three reference projects in parallel to understand their structure before planning.
Agent:
Explore payment-logger app structure and functionality
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How data flows (ingest, storage, retrieval)
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.
Agent:
Explore dsk-uploader app structure and functionality
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How file uploads work - what files, what format, how parsed
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.
Agent:
Explore auth folder and authentik integration
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. What auth system is being used (Authentik)
2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?
3. Middleware - how is auth enforced on routes?
4. Any frontend auth flow - login redirect, token handling, protected routes
5. Environment variables related to auth
6. Docker/deployment setup for the auth service itself
7. Any example of how other apps integrate with this auth
Report with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.
Message actions
payments.js
payments.js
continue
Thinking
Thinking
Launching parallel exploration of all three reference projects.
Agent:
Explore payment-logger app structure
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How data is ingested (look at /ingest route especially)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore dsk-uploader app structure
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How file uploads work (what format, what processing happens)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore auth project structure
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. What authentication system is used (authentik integration details)
3. How OAuth/OIDC flow works
4. Any middleware or helper functions for protecting routes
5. Session management approach
6. How frontend handles auth state
7. Any example of how other apps integrate with this auth system
8. Docker setup and environment variables
Please read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.
Thinking
Thinking
Now I have a complete picture of all three. Let me design the plan.
Agent:
Design combined app architecture
IN
Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:
---
## App 1: payments-logger (Node.js)
- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI
- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS
- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage
- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)
- **Schema** (PostgreSQL via Prisma):
- `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at
- `tags` table: id, name, color — M2M with payments via `_PaymentToTag`
- `users` table: id, username, hashed_password (this will be REMOVED)
- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system
- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance
## App 2: dsk-uploader (Python/Flask)
- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database
- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5
- **Auth**: None (open)
- **CSV format** (DSK Bank Bulgarian format, columns):
- `Дата` (date, DD.MM.YYYY)
- `Вид на трансакцията` (transaction type, Bulgarian)
- `Основание` (reason/description — contains card number regex: `^\d{6}x{6}\d{4}$`)
- `Дебит BGN` (debit amount, may be empty)
- `Кредит BGN` (credit amount, may be empty)
- `Наредител/Получател` (orderer/recipient name)
- `Номер сметка на наредителя / получателя` (account number)
- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers
- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)
## App 3: auth (Authentik)
- **Mode**: Proxy mode via NPM (forward auth)
- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:
- `X-authentik-username`
- `X-authentik-email`
- `X-authentik-groups`
- **No code integration needed** in the app itself — just trust these headers from NPM
- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`
---
## What the New Combined App Must Do
1. **Single PostgreSQL database** for all transactions
2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST
3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema
4. **Unified UI** — show all payments in one table regardless of source
5. **Source indicator** in UI — badge showing "INGEST", "UPLOAD", or "BOTH" (if duplicate detection added)
6. **Source filter** in FilterBar — filter by All/Ingest/Upload
7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM
8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination
9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL
---
## Technical Constraints
- Keep Node.js backend (not Python) — extend payments-logger's stack
- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)
- File upload: use `multer` npm middleware
- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)
- Add `source` enum field (INGEST/UPLOAD) to payments schema
- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is
- Remove `users` table from schema
---
## Please Design
1. Complete folder structure for the new app (suggest name: "finance-hub" or similar — note this is a placeholder, user will confirm)
2. Prisma schema with new fields (`source`, `currency`)
3. All backend API routes
4. CSV parser design in Node.js (port of the Python logic)
5. Authentik auth middleware
6. Frontend component structure (React) — what's reused from payments-logger, what's new
7. Docker Compose setup
8. Environment variables needed
9. Step-by-step implementation order
10. Verification checklist
Be specific about file paths and code structure. This will be used to write actual implementation code.
Thinking
Thinking
Good plan. Let me ask the one thing I need before writing the final plan.
AskUserQuestion
OUT
User has answered your questions: "What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding."="finance-hub". You can now continue with the user's answers in mind.
Thinking
Thinking
Writing the final plan now.
Thinking
Thinking
Write
ets-create-a-new-generic-sun.md
ets-create-a-new-generic-sun.md
326 lines
# finance-hub — Implementation Plan
## Context
Two separate finance apps exist as references and will be retired:
- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.
- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.
The new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).
---
## Tech Stack
| Layer | Choice | Rationale |
|-------|--------|-----------|
| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |
| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |
| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |
| Database | PostgreSQL 16 | Same as payments-logger |
| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |
| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |
| Container | Docker Compose | Same pattern as both reference apps |
**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage.
**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references.
**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.
---
## Folder Structure
```
/volume2/docker/finance/finance-hub/
├── docker-compose.yml
├── .env
├── .env.example
├── .gitignore
├── backend/
│ ├── Dockerfile
│ ├── package.json
│ ├── prisma/
│ │ ├── schema.prisma
│ │ └── migrations/
│ │ ├── migration_lock.toml
│ │ └── 20260508_init/
│ │ └── migration.sql
│ └── src/
│ ├── index.js ← entry point (Authentik middleware wired here)
│ ├── auth.js ← Authentik header middleware (replaces JWT auth)
│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)
│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)
│ └── routes/
│ ├── payments.js ← existing routes + source/currency additions
│ └── upload.js ← NEW: POST /api/upload/csv
└── frontend/
├── Dockerfile
├── package.json
├── vite.config.js
├── tailwind.config.js
├── postcss.config.js
├── index.html
└── src/
├── main.jsx ← remove AuthProvider wrapper
├── index.css
├── App.jsx ← remove auth state, add Upload tab toggle
└── components/
├── FilterBar.jsx ← add source filter select
├── PaymentTable.jsx ← add Source badge column + currency display
├── PaymentCard.jsx ← minor source badge addition
├── PaymentList.jsx ← unchanged
└── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI
```
---
## Database Schema (Prisma)
File: `backend/prisma/schema.prisma`
```prisma
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
}
model Payment {
id Int @id @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
auth.js
auth.js
27 lines
const PUBLIC_PATHS = new Set([
'/api/health',
'/api/payments/ingest',
]);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) {
return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });
}
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '')
.split(',')
.map(g => g.trim())
.filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
Write
parser.js
parser.js
104 lines
/**
* Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)
*
* Supported formats:
*
* POS / INTERNET / ECOM / P2P payment:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM withdrawal:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM utility payment (amount may include fee as AMOUNT/FEE):
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.
*/
const LOCAL_TZ = process.env.TZ || 'Europe/Sofia';
/**
* Convert a local-timezone date/time to a UTC Date object.
* Uses Intl to resolve the actual UTC offset (DST-aware).
*/
function localToUtc(year, month, day, hour, minute) {
const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));
const formatter = new Intl.DateTimeFormat('en-US', {
timeZone: LOCAL_TZ,
year: 'numeric', month: '2-digit', day: '2-digit',
hour: '2-digit', minute: '2-digit', second: '2-digit',
hour12: false,
});
const parts = {};
formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });
const localAtNaive = new Date(Date.UTC(
parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),
parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),
));
const offsetMs = localAtNaive.getTime() - naive.getTime();
return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);
}
function parsePaymentSms(message) {
const result = {
rawMessage: message,
date: null,
type: null,
card: null,
recipient: null,
amount: null,
balance: null,
};
// Date and time: "Na DD/MM/YYYY v HH:MM"
const dateMatch = message.match(/Na (\d{2})\/(\d{2})\/(\d{4}) v (\d{2}):(\d{2})/i);
if (dateMatch) {
const [, day, month, year, hour, minute] = dateMatch;
result.date = localToUtc(
parseInt(year), parseInt(month), parseInt(day),
parseInt(hour), parseInt(minute),
);
}
// Card mask: "s karta 400915***4447" or "s karta 483890***7162"
const cardMatch = message.match(/s karta\s+([\d*]+)/i);
if (cardMatch) {
result.card = cardMatch[1];
}
// Transaction type: supports both prepositions
// "na POS" / "na ATM" / "na INTERNET" etc. (payment)
// "ot ATM" (withdrawal)
const typeMatch = message.match(/(?:na|ot)\s+(POS|ATM|INTERNET|ECOM|P2P)\b/i);
if (typeMatch) {
result.type = typeMatch[1].toUpperCase();
}
// Recipient address: "s adres: MERCHANT" or "s adres:MERCHANT" (no space variant)
const recipientMatch = message.match(/s adres:\s*([^.]+)\./i);
if (recipientMatch) {
result.recipient = recipientMatch[1].trim();
}
// Amount: handles both verbs and the AMOUNT/FEE suffix format
// "sa plateni 7.78 EUR"
// "sa iztegleni 400.00 EUR"
// "sa plateni 0.50 EUR/0.50 EUR" → captures 0.50 (the charged amount, ignoring fee)
const amountMatch = message.match(/sa (?:plateni|iztegleni)\s+([\d.,]+)\s+[A-Z]{3}/i);
if (amountMatch) {
result.amount = parseFloat(amountMatch[1].replace(',', '.'));
}
// Balance: "Nalichni: 2583.07 EUR."
const balanceMatch = message.match(/Nalichni:\s*([\d.,]+)\s+[A-Z]{3}/i);
if (balanceMatch) {
result.balance = parseFloat(balanceMatch[1].replace(',', '.'));
}
return result;
}
module.exports = { parsePaymentSms };
Write
csvParser.js
csvParser.js
175 lines
/**
* DSK Bank CSV parser — Node.js port of dskuploader.py
*
* DSK Bank exports use Windows-1251 (cp1251) encoding.
* Each row maps to a Payment record with source=UPLOAD, currency=BGN.
*/
const { parse } = require('csv-parse');
const iconv = require('iconv-lite');
const SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';
const CARD_REGEX = /^\d{6}x{6}\d{4}$/;
const POS_REGEX = /^\s*ПЛАЩАНЕ\s+НА\s+ПОС\s+\d{2}\.\d{2}\.\d{4}\s+\d{2}:\d{2}/;
const COL = {
DATE: 'Дата',
TYPE: 'Вид на трансакцията',
REASON: 'Основание',
DEBIT: 'Дебит BGN',
CREDIT: 'Кредит BGN',
PAYEE: 'Наредител/Получател',
ACCT: 'Номер сметка на наредителя / получателя',
};
const TAG_RULES = [
['reason', 'ЗАПЛАТА', 'Salary'],
['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],
['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],
['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],
['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],
['payee', 'VIVACOM', 'Subscriptions'],
['payee', 'Google', 'Subscriptions'],
['payee', 'SkyShowtime', 'Subscriptions'],
['payee', 'NETFLIX', 'Subscriptions'],
['payee', 'LUKOIL', 'Bills'],
['payee', 'CityGate', 'Bills'],
['payee', 'CBA', 'Groceries'],
['payee', 'FANTASTICO', 'Groceries'],
['payee', 'LIDL', 'Groceries'],
];
function parseNum(val) {
if (val == null || val === '') return null;
if (typeof val === 'number') return isNaN(val) ? null : val;
const s = String(val).trim().replace(/\xa0/g, '').replace(/ /g, '').replace(',', '.');
const n = parseFloat(s);
return isNaN(n) ? null : n;
}
function parseDate(val) {
if (!val) return null;
const s = String(val).trim();
const m = s.match(/^(\d{2})\.(\d{2})\.(\d{4})$/);
if (m) {
return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));
}
return null;
}
function processReasonAndCard(reason) {
if (!reason || typeof reason !== 'string') return { reason: '', card: null };
const parts = reason.trim().split(' ');
let card = null;
let cleanReason = reason.trim();
if (parts[0] && CARD_REGEX.test(parts[0])) {
card = parts[0];
cleanReason = parts.slice(1).join(' ').trim();
}
if (POS_REGEX.test(cleanReason)) {
const posParts = cleanReason.split('<br/>');
try {
const dateTime = posParts[0].split('ПОС ')[1];
cleanReason = `POS PAYMENT ${dateTime}`;
} catch (_) { /* keep original */ }
}
return { reason: cleanReason.replace(/\s+/g, ' ').trim(), card };
}
function generateTags(fields) {
const tags = new Set();
for (const [field, keyword, tagName] of TAG_RULES) {
if ((fields[field] || '').includes(keyword)) {
tags.add(tagName);
}
}
return Array.from(tags);
}
function processRow(row) {
const transactionType = (row[COL.TYPE] || '').trim();
if (transactionType === SKIP_TYPE) return null;
const { reason, card } = processReasonAndCard(row[COL.REASON]);
const payee = (row[COL.PAYEE] || ...
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/Users/lukas/Downloads/report(2).csv
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|
report(2).csv — finance [SSH: nas]
|
True
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monitor_1
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NULL
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NULL
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G)
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
report(1).csv, Editor Group 1
report(2).csv, Editor Group 1
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
Design new payment-logge…, Editor Group 2
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Info: Setting up SSH Host nas: Setting up SSH tunnel
Design new payment-logger and dsk-uploader hybrid app
Session history
New session
Message actions
payments.js
payments.js
ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.
Thinking
Thinking
I'll explore all three reference projects in parallel to understand their structure before planning.
Agent:
Explore payment-logger app structure and functionality
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How data flows (ingest, storage, retrieval)
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.
Agent:
Explore dsk-uploader app structure and functionality
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How file uploads work - what files, what format, how parsed
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.
Agent:
Explore auth folder and authentik integration
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. What auth system is being used (Authentik)
2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?
3. Middleware - how is auth enforced on routes?
4. Any frontend auth flow - login redirect, token handling, protected routes
5. Environment variables related to auth
6. Docker/deployment setup for the auth service itself
7. Any example of how other apps integrate with this auth
Report with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.
Message actions
payments.js
payments.js
continue
Thinking
Thinking
Launching parallel exploration of all three reference projects.
Agent:
Explore payment-logger app structure
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How data is ingested (look at /ingest route especially)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore dsk-uploader app structure
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How file uploads work (what format, what processing happens)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore auth project structure
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. What authentication system is used (authentik integration details)
3. How OAuth/OIDC flow works
4. Any middleware or helper functions for protecting routes
5. Session management approach
6. How frontend handles auth state
7. Any example of how other apps integrate with this auth system
8. Docker setup and environment variables
Please read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.
Thinking
Thinking
Now I have a complete picture of all three. Let me design the plan.
Agent:
Design combined app architecture
IN
Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:
---
## App 1: payments-logger (Node.js)
- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI
- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS
- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage
- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)
- **Schema** (PostgreSQL via Prisma):
- `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at
- `tags` table: id, name, color — M2M with payments via `_PaymentToTag`
- `users` table: id, username, hashed_password (this will be REMOVED)
- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system
- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance
## App 2: dsk-uploader (Python/Flask)
- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database
- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5
- **Auth**: None (open)
- **CSV format** (DSK Bank Bulgarian format, columns):
- `Дата` (date, DD.MM.YYYY)
- `Вид на трансакцията` (transaction type, Bulgarian)
- `Основание` (reason/description — contains card number regex: `^\d{6}x{6}\d{4}$`)
- `Дебит BGN` (debit amount, may be empty)
- `Кредит BGN` (credit amount, may be empty)
- `Наредител/Получател` (orderer/recipient name)
- `Номер сметка на наредителя / получателя` (account number)
- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers
- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)
## App 3: auth (Authentik)
- **Mode**: Proxy mode via NPM (forward auth)
- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:
- `X-authentik-username`
- `X-authentik-email`
- `X-authentik-groups`
- **No code integration needed** in the app itself — just trust these headers from NPM
- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`
---
## What the New Combined App Must Do
1. **Single PostgreSQL database** for all transactions
2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST
3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema
4. **Unified UI** — show all payments in one table regardless of source
5. **Source indicator** in UI — badge showing "INGEST", "UPLOAD", or "BOTH" (if duplicate detection added)
6. **Source filter** in FilterBar — filter by All/Ingest/Upload
7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM
8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination
9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL
---
## Technical Constraints
- Keep Node.js backend (not Python) — extend payments-logger's stack
- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)
- File upload: use `multer` npm middleware
- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)
- Add `source` enum field (INGEST/UPLOAD) to payments schema
- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is
- Remove `users` table from schema
---
## Please Design
1. Complete folder structure for the new app (suggest name: "finance-hub" or similar — note this is a placeholder, user will confirm)
2. Prisma schema with new fields (`source`, `currency`)
3. All backend API routes
4. CSV parser design in Node.js (port of the Python logic)
5. Authentik auth middleware
6. Frontend component structure (React) — what's reused from payments-logger, what's new
7. Docker Compose setup
8. Environment variables needed
9. Step-by-step implementation order
10. Verification checklist
Be specific about file paths and code structure. This will be used to write actual implementation code.
Thinking
Thinking
Good plan. Let me ask the one thing I need before writing the final plan.
AskUserQuestion
OUT
User has answered your questions: "What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding."="finance-hub". You can now continue with the user's answers in mind.
Thinking
Thinking
Writing the final plan now.
Thinking
Thinking
Write
ets-create-a-new-generic-sun.md
ets-create-a-new-generic-sun.md
326 lines
# finance-hub — Implementation Plan
## Context
Two separate finance apps exist as references and will be retired:
- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.
- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.
The new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).
---
## Tech Stack
| Layer | Choice | Rationale |
|-------|--------|-----------|
| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |
| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |
| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |
| Database | PostgreSQL 16 | Same as payments-logger |
| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |
| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |
| Container | Docker Compose | Same pattern as both reference apps |
**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage.
**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references.
**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.
---
## Folder Structure
```
/volume2/docker/finance/finance-hub/
├── docker-compose.yml
├── .env
├── .env.example
├── .gitignore
├── backend/
│ ├── Dockerfile
│ ├── package.json
│ ├── prisma/
│ │ ├── schema.prisma
│ │ └── migrations/
│ │ ├── migration_lock.toml
│ │ └── 20260508_init/
│ │ └── migration.sql
│ └── src/
│ ├── index.js ← entry point (Authentik middleware wired here)
│ ├── auth.js ← Authentik header middleware (replaces JWT auth)
│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)
│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)
│ └── routes/
│ ├── payments.js ← existing routes + source/currency additions
│ └── upload.js ← NEW: POST /api/upload/csv
└── frontend/
├── Dockerfile
├── package.json
├── vite.config.js
├── tailwind.config.js
├── postcss.config.js
├── index.html
└── src/
├── main.jsx ← remove AuthProvider wrapper
├── index.css
├── App.jsx ← remove auth state, add Upload tab toggle
└── components/
├── FilterBar.jsx ← add source filter select
├── PaymentTable.jsx ← add Source badge column + currency display
├── PaymentCard.jsx ← minor source badge addition
├── PaymentList.jsx ← unchanged
└── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI
```
---
## Database Schema (Prisma)
File: `backend/prisma/schema.prisma`
```prisma
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
}
model Payment {
id Int @id @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
auth.js
auth.js
27 lines
const PUBLIC_PATHS = new Set([
'/api/health',
'/api/payments/ingest',
]);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) {
return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });
}
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '')
.split(',')
.map(g => g.trim())
.filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
Write
parser.js
parser.js
104 lines
/**
* Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)
*
* Supported formats:
*
* POS / INTERNET / ECOM / P2P payment:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM withdrawal:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM utility payment (amount may include fee as AMOUNT/FEE):
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.
*/
const LOCAL_TZ = process.env.TZ || 'Europe/Sofia';
/**
* Convert a local-timezone date/time to a UTC Date object.
* Uses Intl to resolve the actual UTC offset (DST-aware).
*/
function localToUtc(year, month, day, hour, minute) {
const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));
const formatter = new Intl.DateTimeFormat('en-US', {
timeZone: LOCAL_TZ,
year: 'numeric', month: '2-digit', day: '2-digit',
hour: '2-digit', minute: '2-digit', second: '2-digit',
hour12: false,
});
const parts = {};
formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });
const localAtNaive = new Date(Date.UTC(
parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),
parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),
));
const offsetMs = localAtNaive.getTime() - naive.getTime();
return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);
}
function parsePaymentSms(message) {
const result = {
rawMessage: message,
date: null,
type: null,
card: null,
recipient: null,
amount: null,
balance: null,
};
// Date and time: "Na DD/MM/YYYY v HH:MM"
const dateMatch = message.match(/Na (\d{2})\/(\d{2})\/(\d{4}) v (\d{2}):(\d{2})/i);
if (dateMatch) {
const [, day, month, year, hour, minute] = dateMatch;
result.date = localToUtc(
parseInt(year), parseInt(month), parseInt(day),
parseInt(hour), parseInt(minute),
);
}
// Card mask: "s karta 400915***4447" or "s karta 483890***7162"
const cardMatch = message.match(/s karta\s+([\d*]+)/i);
if (cardMatch) {
result.card = cardMatch[1];
}
// Transaction type: supports both prepositions
// "na POS" / "na ATM" / "na INTERNET" etc. (payment)
// "ot ATM" (withdrawal)
const typeMatch = message.match(/(?:na|ot)\s+(POS|ATM|INTERNET|ECOM|P2P)\b/i);
if (typeMatch) {
result.type = typeMatch[1].toUpperCase();
}
// Recipient address: "s adres: MERCHANT" or "s adres:MERCHANT" (no space variant)
const recipientMatch = message.match(/s adres:\s*([^.]+)\./i);
if (recipientMatch) {
result.recipient = recipientMatch[1].trim();
}
// Amount: handles both verbs and the AMOUNT/FEE suffix format
// "sa plateni 7.78 EUR"
// "sa iztegleni 400.00 EUR"
// "sa plateni 0.50 EUR/0.50 EUR" → captures 0.50 (the charged amount, ignoring fee)
const amountMatch = message.match(/sa (?:plateni|iztegleni)\s+([\d.,]+)\s+[A-Z]{3}/i);
if (amountMatch) {
result.amount = parseFloat(amountMatch[1].replace(',', '.'));
}
// Balance: "Nalichni: 2583.07 EUR."
const balanceMatch = message.match(/Nalichni:\s*([\d.,]+)\s+[A-Z]{3}/i);
if (balanceMatch) {
result.balance = parseFloat(balanceMatch[1].replace(',', '.'));
}
return result;
}
module.exports = { parsePaymentSms };
Write
csvParser.js
csvParser.js
175 lines
/**
* DSK Bank CSV parser — Node.js port of dskuploader.py
*
* DSK Bank exports use Windows-1251 (cp1251) encoding.
* Each row maps to a Payment record with source=UPLOAD, currency=BGN.
*/
const { parse } = require('csv-parse');
const iconv = require('iconv-lite');
const SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';
const CARD_REGEX = /^\d{6}x{6}\d{4}$/;
const POS_REGEX = /^\s*ПЛАЩАНЕ\s+НА\s+ПОС\s+\d{2}\.\d{2}\.\d{4}\s+\d{2}:\d{2}/;
const COL = {
DATE: 'Дата',
TYPE: 'Вид на трансакцията',
REASON: 'Основание',
DEBIT: 'Дебит BGN',
CREDIT: 'Кредит BGN',
PAYEE: 'Наредител/Получател',
ACCT: 'Номер сметка на наредителя / получателя',
};
const TAG_RULES = [
['reason', 'ЗАПЛАТА', 'Salary'],
['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],
['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],
['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],
['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],
['payee', 'VIVACOM', 'Subscriptions'],
['payee', 'Google', 'Subscriptions'],
['payee', 'SkyShowtime', 'Subscriptions'],
['payee', 'NETFLIX', 'Subscriptions'],
['payee', 'LUKOIL', 'Bills'],
['payee', 'CityGate', 'Bills'],
['payee', 'CBA', 'Groceries'],
['payee', 'FANTASTICO', 'Groceries'],
['payee', 'LIDL', 'Groceries'],
];
function parseNum(val) {
if (val == null || val === '') return null;
if (typeof val === 'number') return isNaN(val) ? null : val;
const s = String(val).trim().replace(/\xa0/g, '').replace(/ /g, '').replace(',', '.');
const n = parseFloat(s);
return isNaN(n) ? null : n;
}
function parseDate(val) {
if (!val) return null;
const s = String(val).trim();
const m = s.match(/^(\d{2})\.(\d{2})\.(\d{4})$/);
if (m) {
return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));
}
return null;
}
function processReasonAndCard(reason) {
if (!reason || typeof reason !== 'string') return { reason: '', card: null };
const parts = reason.trim().split(' ');
let card = null;
let cleanReason = reason.trim();
if (parts[0] && CARD_REGEX.test(parts[0])) {
card = parts[0];
cleanReason = parts.slice(1).join(' ').trim();
}
if (POS_REGEX.test(cleanReason)) {
const posParts = cleanReason.split('<br/>');
try {
const dateTime = posParts[0].split('ПОС ')[1];
cleanReason = `POS PAYMENT ${dateTime}`;
} catch (_) { /* keep original */ }
}
return { reason: cleanReason.replace(/\s+/g, ' ').trim(), card };
}
function generateTags(fields) {
const tags = new Set();
for (const [field, keyword, tagName] of TAG_RULES) {
if ((fields[field] || '').includes(keyword)) {
tags.add(tagName);
}
}
return Array.from(tags);
}
function processRow(row) {
const transactionType = (row[COL.TYPE] || '').trim();
if (transactionType === SKIP_TYPE) return null;
const { reason, card } = processReasonAndCard(row[COL.REASON]);
const payee = (row[COL.PAYEE] || ...
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45","depth":16,"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Info: Setting up SSH Host nas: Setting up SSH tunnel","depth":12,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Design new payment-logger and dsk-uploader hybrid app","depth":19,"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Session history","depth":19,"on_screen":true,"help_text":"Session history","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"New session","depth":19,"on_screen":true,"help_text":"New session","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"payments.js","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"I'll explore all three reference projects in parallel to understand their structure before planning.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How data flows (ingest, storage, retrieval)\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How file uploads work - what files, what format, how parsed\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth folder and authentik integration","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. What auth system is being used (Authentik)\n2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?\n3. Middleware - how is auth enforced on routes?\n4. Any frontend auth flow - login redirect, token handling, protected routes\n5. Environment variables related to auth\n6. Docker/deployment setup for the auth service itself\n7. Any example of how other apps integrate with this auth\n\nReport with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"payments.js","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"continue","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Launching parallel exploration of all three reference projects.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How data is ingested (look at /ingest route especially)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How file uploads work (what format, what processing happens)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth project structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. What authentication system is used (authentik integration details)\n3. How OAuth/OIDC flow works\n4. Any middleware or helper functions for protecting routes\n5. Session management approach\n6. How frontend handles auth state\n7. Any example of how other apps integrate with this auth system\n8. Docker setup and environment variables\n\nPlease read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now I have a complete picture of all three. Let me design the plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design combined app architecture","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:\n\n---\n\n## App 1: payments-logger (Node.js)\n- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI\n- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS\n- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage\n- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)\n- **Schema** (PostgreSQL via Prisma):\n - `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at\n - `tags` table: id, name, color — M2M with payments via `_PaymentToTag`\n - `users` table: id, username, hashed_password (this will be REMOVED)\n- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system\n- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance\n\n## App 2: dsk-uploader (Python/Flask)\n- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database\n- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5\n- **Auth**: None (open)\n- **CSV format** (DSK Bank Bulgarian format, columns):\n - `Дата` (date, DD.MM.YYYY)\n - `Вид на трансакцията` (transaction type, Bulgarian)\n - `Основание` (reason/description — contains card number regex: `^\\d{6}x{6}\\d{4}$`)\n - `Дебит BGN` (debit amount, may be empty)\n - `Кредит BGN` (credit amount, may be empty)\n - `Наредител/Получател` (orderer/recipient name)\n - `Номер сметка на наредителя / получателя` (account number)\n- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers\n- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)\n\n## App 3: auth (Authentik)\n- **Mode**: Proxy mode via NPM (forward auth)\n- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:\n - `X-authentik-username` \n - `X-authentik-email`\n - `X-authentik-groups`\n- **No code integration needed** in the app itself — just trust these headers from NPM\n- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`\n\n---\n\n## What the New Combined App Must Do\n\n1. **Single PostgreSQL database** for all transactions\n2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST\n3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema\n4. **Unified UI** — show all payments in one table regardless of source\n5. **Source indicator** in UI — badge showing \"INGEST\", \"UPLOAD\", or \"BOTH\" (if duplicate detection added)\n6. **Source filter** in FilterBar — filter by All/Ingest/Upload\n7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM\n8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination\n9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL\n\n---\n\n## Technical Constraints\n\n- Keep Node.js backend (not Python) — extend payments-logger's stack\n- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)\n- File upload: use `multer` npm middleware\n- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)\n- Add `source` enum field (INGEST/UPLOAD) to payments schema\n- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is\n- Remove `users` table from schema\n\n---\n\n## Please Design\n\n1. Complete folder structure for the new app (suggest name: \"finance-hub\" or similar — note this is a placeholder, user will confirm)\n2. Prisma schema with new fields (`source`, `currency`)\n3. All backend API routes\n4. CSV parser design in Node.js (port of the Python logic)\n5. Authentik auth middleware\n6. Frontend component structure (React) — what's reused from payments-logger, what's new\n7. Docker Compose setup\n8. Environment variables needed\n9. Step-by-step implementation order\n10. Verification checklist\n\nBe specific about file paths and code structure. This will be used to write actual implementation code.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good plan. Let me ask the one thing I need before writing the final plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"AskUserQuestion","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"OUT","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"User has answered your questions: \"What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding.\"=\"finance-hub\". You can now continue with the user's answers in mind.","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Writing the final plan now.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"326 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# finance-hub — Implementation Plan\n\n## Context\n\nTwo separate finance apps exist as references and will be retired:\n- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.\n- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.\n\nThe new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).\n\n---\n\n## Tech Stack\n\n| Layer | Choice | Rationale |\n|-------|--------|-----------|\n| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |\n| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |\n| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |\n| Database | PostgreSQL 16 | Same as payments-logger |\n| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |\n| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |\n| Container | Docker Compose | Same pattern as both reference apps |\n\n**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage. \n**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references. \n**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.\n\n---\n\n## Folder Structure\n\n```\n/volume2/docker/finance/finance-hub/\n├── docker-compose.yml\n├── .env\n├── .env.example\n├── .gitignore\n├── backend/\n│ ├── Dockerfile\n│ ├── package.json\n│ ├── prisma/\n│ │ ├── schema.prisma\n│ │ └── migrations/\n│ │ ├── migration_lock.toml\n│ │ └── 20260508_init/\n│ │ └── migration.sql\n│ └── src/\n│ ├── index.js ← entry point (Authentik middleware wired here)\n│ ├── auth.js ← Authentik header middleware (replaces JWT auth)\n│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)\n│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)\n│ └── routes/\n│ ├── payments.js ← existing routes + source/currency additions\n│ └── upload.js ← NEW: POST /api/upload/csv\n└── frontend/\n ├── Dockerfile\n ├── package.json\n ├── vite.config.js\n ├── tailwind.config.js\n ├── postcss.config.js\n ├── index.html\n └── src/\n ├── main.jsx ← remove AuthProvider wrapper\n ├── index.css\n ├── App.jsx ← remove auth state, add Upload tab toggle\n └── components/\n ├── FilterBar.jsx ← add source filter select\n ├── PaymentTable.jsx ← add Source badge column + currency display\n ├── PaymentCard.jsx ← minor source badge addition\n ├── PaymentList.jsx ← unchanged\n └── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI\n```\n\n---\n\n## Database Schema (Prisma)\n\nFile: `backend/prisma/schema.prisma`\n\n```prisma\ngenerator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status { UNPROCESSED SENT SKIPPED }\nenum Source { INGEST UPLOAD }\n```\n\n**Key decisions:**\n- No `User` model — Authentik owns identity.\n- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.\n- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.\n- `balance` is always null for CSV rows (DSK export does not include running balance).\n- Fresh consolidated migration — no data migration from reference apps required.\n\n---\n\n## API Routes\n\n| Method | Path | Auth | Description |\n|--------|------|------|-------------|\n| GET | /api/health | public | Health check |\n| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |\n| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |\n| GET | /api/payments/meta/tags | required | All tags |\n| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |\n| GET | /api/payments/:id | required | Single payment |\n| PATCH | /api/payments/:id | required | Update status |\n| DELETE | /api/payments/:id | required | Delete |\n| POST | /api/payments/:id/send | required | Send notification |\n| POST | /api/payments/:id/skip | required | Skip |\n| POST | /api/payments/:id/tags | required | Add/upsert tag |\n| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |\n| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |\n\n---\n\n## Key Implementation Details\n\n### auth.js (replaces entire old auth module)\n```js\nconst PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n const username = req.headers['x-authentik-username'];\n if (!username) return res.status(401).json({ error: 'Unauthorized' });\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),\n };\n next();\n}\nmodule.exports = { authentikMiddleware };\n```\n\n### csvParser.js (port of dskuploader.py)\n- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8\n- `csv-parse` parses the decoded text with `columns: true`\n- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`\n- Card extraction: regex `/^\\d{6}x{6}\\d{4}$/` on first token of `Основание`\n- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`\n- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`\n- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`\n\n### payments.js changes from payments-logger\n1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call\n2. Add `source` to the `GET /` where clause filter\n3. Add `sources` to `meta/filters` response\n4. Currency-aware amount formatting in notification message\n5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)\n\n### upload.js (new)\n- `multer` memory storage, max 10 files × 10 MB\n- Calls `parseDskCsv(buffer)` per file\n- Upserts tags via `prisma.tag.upsert` then connects\n- Returns `{ imported, skipped, errors, payments[] }`\n\n### Frontend changes\n- **Delete**: `auth.js`, `AuthProvider.jsx`\n- **main.jsx**: Remove `<AuthProvider>` wrapper\n- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add \"Payments\" / \"Upload CSV\" tab toggle\n- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols\n- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell\n- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`\n\n---\n\n## Docker Compose\n\n```yaml\nservices:\n db:\n image: postgres:16-alpine\n environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: ${DB_PASSWORD}, POSTGRES_DB: finance_hub }\n volumes: [pgdata:/var/lib/postgresql/data]\n healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }\n\n backend:\n build: ./backend\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports: [\"${BACKEND_PORT:-3001}:3001\"]\n depends_on: { db: { condition: service_healthy } }\n\n frontend:\n build: ./frontend\n ports: [\"${FRONTEND_PORT:-5175}:5173\"]\n depends_on: [backend]\n\nvolumes: { pgdata: }\n```\n\n**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.\n\n---\n\n## Environment Variables (.env)\n\n```bash\nDB_PASSWORD=change_me\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\nTZ=Europe/Sofia\nBACKEND_PORT=3001\nFRONTEND_PORT=5175\n```\n\nRemoved vs payments-logger: `JWT_SECRET`, `JWT_EXPIRE_MINUTES`.\n\n---\n\n## Implementation Order\n\n1. Create folder structure and write `docker-compose.yml`, `.env.example`, `.gitignore`\n2. Write `backend/prisma/schema.prisma` and migration SQL\n3. Write `backend/package.json` (add `csv-parse`, `iconv-lite`, `multer`; remove `bcryptjs`, `jose`)\n4. Write `backend/Dockerfile`\n5. Write `backend/src/auth.js` (Authentik middleware)\n6. Copy `backend/src/parser.js` verbatim from payments-logger\n7. Write `backend/src/csvParser.js` (Python port)\n8. Write `backend/src/routes/upload.js`\n9. Write `backend/src/routes/payments.js` (from payments-logger + 5 changes listed above)\n10. Write `backend/src/index.js`\n11. Copy frontend base from payments-logger; delete `auth.js` + `AuthProvider.jsx`\n12. Update `main.jsx`, `App.jsx`, `FilterBar.jsx`, `PaymentTable.jsx`\n13. Write `frontend/src/components/UploadPanel.jsx`\n14. Update `frontend/vite.config.js`\n15. `docker compose build && docker compose up -d`\n16. Run verification checklist\n\n---\n\n## Verification\n\n**Schema**\n- `payments` table has `source`, `currency`, `debit_bgn`, `credit_bgn`, `transaction_type`, `payer_account`\n- No `users` table; `Source` enum exists\n\n**Auth**\n- `GET /api/payments` → 401 without `x-authentik-username` header\n- `POST /api/payments/ingest` → 201 without any header\n- `curl -H \"x-authentik-username: test\" localhost:3001/api/payments` → 200\n\n**SMS Ingest**\n- DSK POS SMS → `source=INGEST`, `currency=EUR`, correct amount/card/recipient\n- Apple Wallet structured body → `type=WALLET`, `source=INGEST`\n- Rate limiter → 429 after 200 req/min\n\n**CSV Upload**\n- Single DSK CSV → rows with `source=UPLOAD`, `currency=BGN`\n- Multiple CSVs in one request → all merged\n- `ТРАНСФЕР СОБСТВЕНИ СМЕТКИ` rows counted in `skipped`, not imported\n- Card regex match from `Основание` column\n- Auto-tags applied (ЗАПЛАТА→Salary, LIDL→Groceries)\n- cp1251 file imports correctly\n\n**UI**\n- Source badge visible in payment table (SMS indigo, CSV emerald)\n- Source dropdown in FilterBar filters correctly\n- Amount shows correct currency per row\n- Upload Panel: drag-and-drop works, result summary shows counts\n- Logout redirects to Authentik sign_out\n- No login form shown (Authentik handles it at NPM level)\n- Tags, send, skip, delete all still work\n\n## Reference Files\n\n- `/volume2/docker/finance/payments-logger/backend/src/routes/payments.js`\n- `/volume2/docker/finance/payments-logger/backend/src/parser.js`\n- `/volume2/docker/finance/payments-logger/backend/src/index.js`\n- `/volume2/docker/finance/payments-logger/backend/src/auth.js`\n- `/volume2/docker/finance/payments-logger/backend/prisma/schema.prisma`\n- `/volume2/docker/finance/payments-logger/frontend/src/App.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/PaymentTable.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/FilterBar.jsx`\n- `/volume2/docker/finance/dsk-uploader/dskuploader.py`\n- `/volume2/docker/finance/auth/docker-compose.yml`","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Claude’s Plan","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Stayed in plan mode","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good question. Here's the full breakdown:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Backend Tech Stack — Options","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Backend Tech Stack — Options","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Why:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"payments-logger is already Node.js/Express/Prisma. The new app is 80% payments-logger with CSV upload added on top. Keeping the same stack means:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"verbatim, zero rewrite","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy the entire","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"routes/payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with minimal edits","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Same Prisma schema workflow, same migrations, same Docker image","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The CSV parsing logic (the only Python-specific thing) ports cleanly to","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"csv-parse","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— it's just regex + string manipulation, nothing pandas-specific","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Trade-off:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Have to port the Python CSV parsing to JS. It's ~150 lines and mostly string manipulation — straightforward.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option B: Python + FastAPI + SQLAlchemy","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option B: Python + FastAPI + SQLAlchemy","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rewrite everything in Python. dsk-uploader is Python, so CSV parsing is already done.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep the dsk-uploader CSV logic as-is (no porting). Python has better data science libraries if you later add analytics.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Lose the entire payments-logger backend (routes, parser, Prisma schema) — full rewrite. FastAPI + SQLAlchemy is a different mental model than Express + Prisma. Frontend stays React anyway, so the stack split doesn't simplify anything.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"More work overall, gains almost nothing.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep Node.js as the main API, add a separate Python FastAPI service just for CSV parsing. They share the DB.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Zero porting — Python CSV code used as-is.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two backend services to maintain, deploy, and keep in sync. Inter-service HTTP calls. Two Dockerfiles. For ~150 lines of CSV logic, this is massively over-engineered.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Not worth it.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Extend dsk-uploader into a full payments app.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pandas for CSV, no porting.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Jinja2 templates instead of React (or add React separately). Would need to reimplement the entire payments-logger (SMS parser, notification system, tag management, pagination/filtering). Flask's Jinja templating is far less capable than the existing React UI. The React frontend is the stronger UI foundation.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Worst of all options — rebuild the harder parts (UI, SMS parser, notification) for no gain.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Summary","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Summary","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"CSV porting effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"App rewrite effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Result 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(Hybrid)","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"None","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Low + infra overhead","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Overkill","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"D (Python Flask)","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"None","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Very high","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Worst","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"A (Node.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"B (Python 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Everything else in the plan reuses payments-logger code directly. That's why Node.js is the clear winner here.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Want to adjust the stack, or shall I proceed with Option A?","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ok sounds good. Implement all you suggested","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Starting implementation. Let me first read all the reference files I'll need to copy from.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"payments.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"App.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"App.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"FilterBar.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"FilterBar.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentTable.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentTable.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now let me read the remaining frontend files and the Dockerfile from payments-logger.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.css","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.css","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"vite.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"vite.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"tailwind.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"tailwind.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"postcss.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"postcss.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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components.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentCard.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentCard.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentList.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentList.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"schema.prisma","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"schema.prisma","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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Let me set up the todo list and start building.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, 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/volume2/docker/finance/finance-hub/backend/prisma/migrations/20260508_init \\\n /volume2/docker/finance/finance-hub/frontend/src/components && echo \"done\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":24,"on_screen":false,"help_text":"Copy 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POSTGRES_USER: finance\n POSTGRES_PASSWORD: ${DB_PASSWORD}\n POSTGRES_DB: finance_hub\n volumes:\n - pgdata:/var/lib/postgresql/data\n healthcheck:\n test: [\"CMD-SHELL\", \"pg_isready -U finance -d finance_hub\"]\n interval: 5s\n timeout: 5s\n retries: 5\n\n backend:\n build: ./backend\n restart: unless-stopped\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports:\n - \"${BACKEND_PORT:-3001}:3001\"\n depends_on:\n db:\n condition: service_healthy\n\n frontend:\n build: ./frontend\n restart: unless-stopped\n ports:\n - \"${FRONTEND_PORT:-5175}:5173\"\n depends_on:\n - backend\n\nvolumes:\n pgdata:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".env.example","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".env.example","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"15 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Database\nDB_PASSWORD=change_me_strong_password\n\n# Notifier service (for SMS payment notifications)\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\n\n# Timezone (used by SMS parser for Bulgarian bank timestamps)\nTZ=Europe/Sofia\n\n# Ports (optional — defaults shown)\nBACKEND_PORT=3001\nFRONTEND_PORT=5175","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".gitignore","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".gitignore","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"5 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env\nnode_modules/\ndist/\n*.log","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config 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compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"schema.prisma","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"schema.prisma","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"54 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"generator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status {\n UNPROCESSED\n SENT\n SKIPPED\n}\n\nenum Source {\n INGEST\n UPLOAD\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration.sql","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration.sql","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"55 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- CreateEnum\nCREATE TYPE \"Status\" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');\nCREATE TYPE \"Source\" AS ENUM ('INGEST', 'UPLOAD');\n\n-- CreateTable\nCREATE TABLE \"payments\" (\n \"id\" SERIAL PRIMARY KEY,\n \"raw_message\" TEXT NOT NULL,\n \"date\" TIMESTAMP(3),\n \"type\" TEXT,\n \"card\" TEXT,\n \"recipient\" TEXT,\n \"amount\" DOUBLE PRECISION,\n \"currency\" TEXT DEFAULT 'EUR',\n \"balance\" DOUBLE PRECISION,\n \"source\" \"Source\" NOT NULL DEFAULT 'INGEST',\n \"status\" \"Status\" NOT NULL DEFAULT 'UNPROCESSED',\n \"notified_at\" TIMESTAMP(3),\n \"notify_phone\" TEXT,\n \"debit_bgn\" DOUBLE PRECISION,\n \"credit_bgn\" DOUBLE PRECISION,\n \"transaction_type\" TEXT,\n \"payer_account\" TEXT,\n \"created_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,\n \"updated_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP\n);\n\n-- CreateTable\nCREATE TABLE \"tags\" (\n \"id\" SERIAL PRIMARY KEY,\n \"name\" TEXT NOT NULL,\n \"color\" TEXT NOT NULL DEFAULT '#6b7280'\n);\n\n-- CreateUniqueIndex\nCREATE UNIQUE INDEX \"tags_name_key\" ON \"tags\"(\"name\");\n\n-- CreateTable (M2M join)\nCREATE TABLE \"_PaymentToTag\" (\n \"A\" INTEGER NOT NULL,\n \"B\" INTEGER NOT NULL,\n CONSTRAINT \"_PaymentToTag_AB_pkey\" PRIMARY KEY (\"A\", \"B\")\n);\n\nCREATE INDEX \"_PaymentToTag_B_index\" ON \"_PaymentToTag\"(\"B\");\n\n-- AddForeignKey\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_A_fkey\"\n FOREIGN KEY (\"A\") REFERENCES \"payments\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;\n\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_B_fkey\"\n FOREIGN KEY (\"B\") REFERENCES \"tags\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration_lock.toml","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration_lock.toml","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"4 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Please do not edit this file manually\n# It should be added in your version-control system (e.g., Git)\nprovider = \"postgresql\"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"26 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"{\n \"name\": \"finance-hub-backend\",\n \"version\": \"1.0.0\",\n \"main\": \"src/index.js\",\n \"scripts\": {\n \"start\": \"node src/index.js\",\n \"dev\": \"nodemon src/index.js\",\n \"prisma:generate\": \"prisma generate\",\n \"prisma:migrate\": \"prisma migrate deploy\"\n },\n \"dependencies\": {\n \"@prisma/client\": \"^5.22.0\",\n \"cors\": \"^2.8.5\",\n \"csv-parse\": \"^5.5.6\",\n \"express\": \"^4.21.1\",\n \"express-rate-limit\": \"^7.4.0\",\n \"iconv-lite\": \"^0.6.3\",\n \"morgan\": \"^1.10.0\",\n \"multer\": \"^1.4.5-lts.1\"\n },\n \"devDependencies\": {\n \"nodemon\": \"^3.1.7\",\n \"prisma\": \"^5.22.0\"\n }\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"18 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"FROM node:20-alpine\n\nRUN apk add --no-cache openssl\n\nWORKDIR /app\n\nCOPY package.json package-lock.json* ./\nRUN npm install\n\nCOPY prisma ./prisma\nRUN npx prisma generate\n\nCOPY src ./src\n\nEXPOSE 3001\n\nCMD [\"sh\", \"-c\", \"npx prisma migrate deploy && node src/index.js\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"auth.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"auth.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"27 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const PUBLIC_PATHS = new Set([\n '/api/health',\n '/api/payments/ingest',\n]);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n\n const username = req.headers['x-authentik-username'];\n if (!username) {\n return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });\n }\n\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '')\n .split(',')\n .map(g => g.trim())\n .filter(Boolean),\n };\n\n next();\n}\n\nmodule.exports = { authentikMiddleware };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"104 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/**\n * Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)\n *\n * Supported formats:\n *\n * POS / INTERNET / ECOM / P2P payment:\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.\n *\n * ATM withdrawal:\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.\n *\n * ATM utility payment (amount may include fee as AMOUNT/FEE):\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.\n */\n\nconst LOCAL_TZ = process.env.TZ || 'Europe/Sofia';\n\n/**\n * Convert a local-timezone date/time to a UTC Date object.\n * Uses Intl to resolve the actual UTC offset (DST-aware).\n */\nfunction localToUtc(year, month, day, hour, minute) {\n const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));\n\n const formatter = new Intl.DateTimeFormat('en-US', {\n timeZone: LOCAL_TZ,\n year: 'numeric', month: '2-digit', day: '2-digit',\n hour: '2-digit', minute: '2-digit', second: '2-digit',\n hour12: false,\n });\n\n const parts = {};\n formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });\n\n const localAtNaive = new Date(Date.UTC(\n parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),\n parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),\n ));\n\n const offsetMs = localAtNaive.getTime() - naive.getTime();\n return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);\n}\n\nfunction parsePaymentSms(message) {\n const result = {\n rawMessage: message,\n date: null,\n type: null,\n card: null,\n recipient: null,\n amount: null,\n balance: null,\n };\n\n // Date and time: \"Na DD/MM/YYYY v HH:MM\"\n const dateMatch = message.match(/Na (\\d{2})\\/(\\d{2})\\/(\\d{4}) v (\\d{2}):(\\d{2})/i);\n if (dateMatch) {\n const [, day, month, year, hour, minute] = dateMatch;\n result.date = localToUtc(\n parseInt(year), parseInt(month), parseInt(day),\n parseInt(hour), parseInt(minute),\n );\n }\n\n // Card mask: \"s karta 400915***4447\" or \"s karta 483890***7162\"\n const cardMatch = message.match(/s karta\\s+([\\d*]+)/i);\n if (cardMatch) {\n result.card = cardMatch[1];\n }\n\n // Transaction type: supports both prepositions\n // \"na POS\" / \"na ATM\" / \"na INTERNET\" etc. (payment)\n // \"ot ATM\" (withdrawal)\n const typeMatch = message.match(/(?:na|ot)\\s+(POS|ATM|INTERNET|ECOM|P2P)\\b/i);\n if (typeMatch) {\n result.type = typeMatch[1].toUpperCase();\n }\n\n // Recipient address: \"s adres: MERCHANT\" or \"s adres:MERCHANT\" (no space variant)\n const recipientMatch = message.match(/s adres:\\s*([^.]+)\\./i);\n if (recipientMatch) {\n result.recipient = recipientMatch[1].trim();\n }\n\n // Amount: handles both verbs and the AMOUNT/FEE suffix format\n // \"sa plateni 7.78 EUR\"\n // \"sa iztegleni 400.00 EUR\"\n // \"sa plateni 0.50 EUR/0.50 EUR\" → captures 0.50 (the charged amount, ignoring fee)\n const amountMatch = message.match(/sa (?:plateni|iztegleni)\\s+([\\d.,]+)\\s+[A-Z]{3}/i);\n if (amountMatch) {\n result.amount = parseFloat(amountMatch[1].replace(',', '.'));\n }\n\n // Balance: \"Nalichni: 2583.07 EUR.\"\n const balanceMatch = message.match(/Nalichni:\\s*([\\d.,]+)\\s+[A-Z]{3}/i);\n if (balanceMatch) {\n result.balance = parseFloat(balanceMatch[1].replace(',', '.'));\n }\n\n return result;\n}\n\nmodule.exports = { parsePaymentSms };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"csvParser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"csvParser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"175 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/**\n * DSK Bank CSV parser — Node.js port of dskuploader.py\n *\n * DSK Bank exports use Windows-1251 (cp1251) encoding.\n * Each row maps to a Payment record with source=UPLOAD, currency=BGN.\n */\n\nconst { parse } = require('csv-parse');\nconst iconv = require('iconv-lite');\n\nconst SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';\nconst CARD_REGEX = /^\\d{6}x{6}\\d{4}$/;\nconst POS_REGEX = /^\\s*ПЛАЩАНЕ\\s+НА\\s+ПОС\\s+\\d{2}\\.\\d{2}\\.\\d{4}\\s+\\d{2}:\\d{2}/;\n\nconst COL = {\n DATE: 'Дата',\n TYPE: 'Вид на трансакцията',\n REASON: 'Основание',\n DEBIT: 'Дебит BGN',\n CREDIT: 'Кредит BGN',\n PAYEE: 'Наредител/Получател',\n ACCT: 'Номер сметка на наредителя / получателя',\n};\n\nconst TAG_RULES = [\n ['reason', 'ЗАПЛАТА', 'Salary'],\n ['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],\n ['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],\n ['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],\n ['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],\n ['payee', 'VIVACOM', 'Subscriptions'],\n ['payee', 'Google', 'Subscriptions'],\n ['payee', 'SkyShowtime', 'Subscriptions'],\n ['payee', 'NETFLIX', 'Subscriptions'],\n ['payee', 'LUKOIL', 'Bills'],\n ['payee', 'CityGate', 'Bills'],\n ['payee', 'CBA', 'Groceries'],\n ['payee', 'FANTASTICO', 'Groceries'],\n ['payee', 'LIDL', 'Groceries'],\n];\n\nfunction parseNum(val) {\n if (val == null || val === '') return null;\n if (typeof val === 'number') return isNaN(val) ? null : val;\n const s = String(val).trim().replace(/\\xa0/g, '').replace(/ /g, '').replace(',', '.');\n const n = parseFloat(s);\n return isNaN(n) ? null : n;\n}\n\nfunction parseDate(val) {\n if (!val) return null;\n const s = String(val).trim();\n const m = s.match(/^(\\d{2})\\.(\\d{2})\\.(\\d{4})$/);\n if (m) {\n return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));\n }\n return null;\n}\n\nfunction processReasonAndCard(reason) {\n if (!reason || typeof reason !== 'string') return { reason: '', card: null };\n\n const parts = reason.trim().split(' ');\n let card = null;\n let cleanReason = reason.trim();\n\n if (parts[0] && CARD_REGEX.test(parts[0])) {\n card = parts[0];\n cleanReason = parts.slice(1).join(' ').trim();\n }\n\n if (POS_REGEX.test(cleanReason)) {\n const posParts = cleanReason.split('<br/>');\n try {\n const dateTime = posParts[0].split('ПОС ')[1];\n cleanReason = `POS PAYMENT ${dateTime}`;\n } catch (_) { /* keep original */ }\n }\n\n return { reason: cleanReason.replace(/\\s+/g, ' ').trim(), card };\n}\n\nfunction generateTags(fields) {\n const tags = new Set();\n for (const [field, keyword, tagName] of TAG_RULES) {\n if ((fields[field] || '').includes(keyword)) {\n tags.add(tagName);\n }\n }\n return Array.from(tags);\n}\n\nfunction processRow(row) {\n const transactionType = (row[COL.TYPE] || '').trim();\n if (transactionType === SKIP_TYPE) return null;\n\n const { reason, card } = processReasonAndCard(row[COL.REASON]);\n const payee = (row[COL.PAYEE] || '').trim();\n const payerAccount = (row[COL.ACCT] || '').trim();\n const debitBgn = parseNum(row[COL.DEBIT]);\n const creditBgn = parseNum(row[COL.CREDIT]);\n const date = parseDate(row[COL.DATE]);\n\n const autoTags = generateTags({ reason, transactionType, payee, debitBgn, creditBgn });\n\n const amount = debitBgn ?? creditBgn ?? null;\n\n const rawMessage = [\n row[COL.DATE] && `Date: ${row[COL.DATE]}`,\n transactionType && `Type: ${transactionType}`,\n payee && `Payee: ${payee}`,\n debitBgn != null && `Debit: ${debitBgn} BGN`,\n creditBgn != null && `Credit: ${creditBgn} BGN`,\n ].filter(Boolean).join(' | ');\n\n return {\n rawMessage,\n date,\n type: null,\n card,\n recipient: payee || null,\n amount,\n currency: 'BGN',\n balance: null,\n source: 'UPLOAD',\n debitBgn,\n creditBgn,\n transactionType: transactionType || null,\n payerAccount: payerAccount || null,\n autoTags,\n };\n}\n\n/**\n * Parse a Buffer containing a DSK Bank CSV (cp1251 or UTF-8).\n * Returns { rows, skipped, errors }.\n */\nasync function parseDskCsv(buffer) {\n // Try cp1251 first (DSK Bank export encoding), fall back to UTF-8\n let text = iconv.decode(buffer, 'cp1251');\n if (!text.includes(COL.DATE)) {\n text = buffer.toString('utf-8');\n }\n\n return new Promise((resolve, reject) => {\n const rows = [];\n const errors = [];\n let skipped = 0;\n\n const parser = parse(text, {\n columns: true,\n skip_empty_lines: true,\n trim: true,\n relax_column_count: true,\n });\n\n parser.on('readable', () => {\n let record;\n while ((record = parser.read()) !== null) {\n try {\n const row = processRow(record);\n if (row === null) { skipped++; } else { rows.push(row); }\n } catch (err) {\n errors.push(err.message);\n }\n }\n });\n\n parser.on('error', reject);\n parser.on('end', () => resolve({ rows, skipped, errors }));\n });\n}\n\nmodule.exports = { parseDskCsv };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"39 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst cors = require('cors');\nconst morgan = require('morgan');\nconst rateLimit = require('express-rate-limit');\nconst { authentikMiddleware } = require('./auth');\nconst paymentsRouter = require('./routes/payments');\nconst uploadRouter = require('./routes/upload');\n\nconst app = express();\nconst PORT = process.env.PORT || 3001;\n\napp.use(cors());\napp.use(express.json({ limit: '16kb' }));\napp.use(morgan('combined'));\n\n// Rate-limit the public ingest endpoint before auth middleware\nconst ingestLimiter = rateLimit({\n windowMs: 60 * 1000,\n max: 200,\n standardHeaders: true,\n legacyHeaders: false,\n message: { error: 'Too many requests, slow down' },\n});\napp.use('/api/payments/ingest', ingestLimiter);\n\n// Authentik header auth (skips /api/health and /api/payments/ingest)\napp.use(authentikMiddleware);\n\napp.get('/api/health', (_req, res) => {\n res.json({ status: 'ok', timestamp: new Date().toISOString() });\n});\n\napp.use('/api/payments', paymentsRouter);\napp.use('/api/upload', uploadRouter);\n\napp.listen(PORT, '0.0.0.0', () => {\n console.log(`Finance Hub API running on port ${PORT}`);\n});","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"payments.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"399 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst { PrismaClient } = require('@prisma/client');\nconst { parsePaymentSms } = require('../parser');\n\nconst router = express.Router();\nconst prisma = new PrismaClient();\n\nconst NOTIFIER_URL = process.env.NOTIFIER_URL;\nconst NOTIFIER_CHANNEL = process.env.NOTIFIER_CHANNEL || 'viber';\nconst DEFAULT_PHONE = process.env.NOTIFY_DEFAULT_PHONE;\n\n// ── Helpers ───────────────────────────────────────────────────────────────────\n\nfunction parseId(raw) {\n const id = parseInt(raw, 10);\n return Number.isFinite(id) ? id : null;\n}\n\nfunction formatNotifyMessage(payment) {\n const currency = payment.currency || 'EUR';\n const parts = [];\n if (payment.amount != null) parts.push(`Amount: ${payment.amount.toFixed(2)} ${currency}`);\n if (payment.recipient) parts.push(`At: ${payment.recipient}`);\n if (payment.balance != null) parts.push(`Balance: ${payment.balance.toFixed(2)} ${currency}`);\n if (payment.date) parts.push(`Date: ${new Date(payment.date).toLocaleString('en-GB')}`);\n return parts.join('\\n');\n}\n\nasync function sendNotification(payment) {\n if (!NOTIFIER_URL) {\n console.warn('[NOTIFY] NOTIFIER_URL not set — skipping notification');\n return;\n }\n\n const phone = payment.notifyPhone || DEFAULT_PHONE;\n if (!phone) {\n console.warn('[NOTIFY] No phone number for payment #' + payment.id + ' and NOTIFY_DEFAULT_PHONE not set');\n return;\n }\n\n const body = {\n phone,\n notification: NOTIFIER_CHANNEL,\n message: formatNotifyMessage(payment),\n };\n\n const res = await fetch(NOTIFIER_URL, {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify(body),\n });\n\n if (!res.ok) {\n const text = await res.text().catch(() => '');\n throw new Error(`Notifier responded ${res.status}: ${text}`);\n }\n}\n\n// ── Ingest a payment (public — no auth) ──────────────────────────────────────\n//\n// Two modes:\n//\n// SMS mode (default):\n// { \"message\": \"<raw SMS text>\", \"notifyPhone\": \"...\" }\n//\n// Structured mode (Apple Wallet / manual):\n// { \"ingestMode\": \"apple_wallet\", \"amount\": 7.78, \"recipient\": \"Apple Store\",\n// \"type\": \"WALLET\", \"card\": \"••••4447\", \"date\": \"2026-02-22T10:30:00Z\" }\n//\nrouter.post('/ingest', async (req, res) => {\n try {\n const { message, notifyPhone, ingestMode } = req.body;\n\n let data;\n\n if (ingestMode === 'apple_wallet' || (!message && req.body.amount != null)) {\n // ── Structured / Apple Wallet mode ──────────────────────────────────────\n const { amount, recipient, type, card, date, balance } = req.body;\n if (amount == null || !recipient) {\n return res.status(400).json({ error: 'amount and recipient are required for structured ingest' });\n }\n\n const rawMessage = [\n `Source: ${ingestMode || 'structured'}`,\n `Amount: ${amount}`,\n recipient && `Recipient: ${recipient}`,\n type && `Type: ${type}`,\n card && `Card: ${card}`,\n ].filter(Boolean).join(' | ');\n\n data = {\n rawMessage,\n date: date ? new Date(date) : new Date(),\n type: type || 'WALLET',\n card: card || null,\n recipient,\n amount: parseFloat(amount),\n currency: 'EUR',\n balance: balance != null ? parseFloat(balance) : null,\n source: 'INGEST',\n notifyPhone: notifyPhone || null,\n };\n\n } else {\n // ── SMS mode ─────────────────────────────────────────────────────────────\n if (!message) {\n return res.status(400).json({ error: 'message is required' });\n }\n if (typeof message !== 'string' || message.length > 2000) {\n return res.status(400).json({ error: 'message must be a string under 2000 characters' });\n }\n\n const parsed = parsePaymentSms(message);\n data = {\n rawMessage: parsed.rawMessage,\n date: parsed.date,\n type: parsed.type,\n card: parsed.card,\n recipient: parsed.recipient,\n amount: parsed.amount,\n currency: 'EUR',\n balance: parsed.balance,\n source: 'INGEST',\n notifyPhone: notifyPhone || null,\n };\n }\n\n const payment = await prisma.payment.create({\n data,\n include: { tags: true },\n });\n\n res.status(201).json(payment);\n } catch (err) {\n console.error('Ingest error:', err);\n res.status(500).json({ error: 'Failed to ingest payment' });\n }\n});\n\n// ── List payments with filtering ──────────────────────────────────────────────\nrouter.get('/', async (req, res) => {\n try {\n const {\n status,\n type,\n tag,\n source,\n recipient,\n dateFrom,\n dateTo,\n search,\n sortBy = 'createdAt',\n sortDir = 'desc',\n page = 1,\n } = req.query;\n\n const limit = Math.min(parseInt(req.query.limit, 10) || 50, 200);\n\n const where = {};\n\n if (status) where.status = status;\n if (type) where.type = type;\n if (source) where.source = source;\n if (recipient) where.recipient = { contains: recipient, mode: 'insensitive' };\n if (tag) where.tags = { some: { name: tag } };\n if (search) {\n where.OR = [\n { rawMessage: { contains: search, mode: 'insensitive' } },\n { recipient: { contains: search, mode: 'insensitive' } },\n ];\n }\n if (dateFrom || dateTo) {\n where.date = {};\n if (dateFrom) where.date.gte = new Date(dateFrom);\n if (dateTo) where.date.lte = new Date(dateTo);\n }\n\n const allowedSortFields = ['date', 'amount', 'balance', 'recipient', 'type', 'source', 'createdAt', 'status'];\n const orderField = allowedSortFields.includes(sortBy) ? sortBy : 'createdAt';\n const orderDir = sortDir === 'asc' ? 'asc' : 'desc';\n\n const skip = (parseInt(page, 10) - 1) * limit;\n\n const [payments, total] = await Promise.all([\n prisma.payment.findMany({\n where,\n include: { tags: true },\n orderBy: { [orderField]: orderDir },\n skip,\n take: limit,\n }),\n prisma.payment.count({ where }),\n ]);\n\n res.json({ payments, total, page: parseInt(page, 10), limit });\n } catch (err) {\n console.error('List error:', err);\n res.status(500).json({ error: 'Failed to list payments' });\n }\n});\n\n// ── Get filter options ────────────────────────────────────────────────────────\nrouter.get('/meta/filters', async (_req, res) => {\n try {\n const [types, recipients, tags, sources] = await Promise.all([\n prisma.payment.findMany({ distinct: ['type'], select: { type: true }, where: { type: { not: null } } }),\n prisma.payment.findMany({ distinct: ['recipient'], select: { recipient: true }, where: { recipient: { not: null } } }),\n prisma.tag.findMany({ orderBy: { name: 'asc' } }),\n prisma.payment.findMany({ distinct: ['source'], select: { source: true } }),\n ]);\n\n res.json({\n types: types.map(t => t.type),\n recipients: recipients.map(r => r.recipient),\n tags,\n sources: sources.map(s => s.source),\n });\n } catch (err) {\n res.status(500).json({ error: 'Failed to get filters' });\n }\n});\n\n// ── Get all tags ──────────────────────────────────────────────────────────────\nrouter.get('/meta/tags', async (_req, res) => {\n try {\n const tags = await prisma.tag.findMany({ orderBy: { name: 'asc' } });\n res.json(tags);\n } catch (err) {\n res.status(500).json({ error: 'Failed to list tags' });\n }\n});\n\n// ── Get single payment ────────────────────────────────────────────────────────\nrouter.get('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({\n where: { id },\n include: { tags: true },\n });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n res.json(payment);\n } catch (err) {\n console.error('Get error:', err);\n res.status(500).json({ error: 'Failed to get payment' });\n }\n});\n\n// ── Update payment metadata (status) ─────────────────────────────────────────\nrouter.patch('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const { status } = req.body;\n const data = {};\n\n if (status) {\n const validStatuses = ['UNPROCESSED', 'SENT', 'SKIPPED'];\n if (!validStatuses.includes(status)) {\n return res.status(400).json({ error: `Invalid status. Must be one of: ${validStatuses.join(', ')}` });\n }\n data.status = status;\n }\n\n if (Object.keys(data).length === 0) {\n return res.status(400).json({ error: 'No valid fields to update' });\n }\n\n const updated = await prisma.payment.update({\n where: { id },\n data,\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n if (err.code === 'P2025') return res.status(404).json({ error: 'Not found' });\n console.error('Update error:', err);\n res.status(500).json({ error: 'Failed to update payment' });\n }\n});\n\n// ── Delete payment ───────────────────────────────────────────────────────────\nrouter.delete('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n await prisma.payment.delete({ where: { id } });\n res.json({ success: true });\n } catch (err) {\n if (err.code === 'P2025') return res.status(404).json({ error: 'Not found' });\n console.error('Delete error:', err);\n res.status(500).json({ error: 'Failed to delete payment' });\n }\n});\n\n// ── Send notification (mark as SENT + call notifier service) ─────────────────\nrouter.post('/:id/send', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({ where: { id } });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n if (payment.status !== 'UNPROCESSED') {\n return res.status(409).json({ error: `Payment is already ${payment.status.toLowerCase()}` });\n }\n\n await sendNotification(payment);\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { status: 'SENT', notifiedAt: new Date() },\n include: { tags: true },\n });\n\n res.json(updated);\n } catch (err) {\n console.error('Send error:', err);\n res.status(500).json({ error: 'Failed to send notification' });\n }\n});\n\n// ── Skip notification (mark as SKIPPED) ──────────────────────────────────────\nrouter.post('/:id/skip', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({ where: { id } });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n if (payment.status !== 'UNPROCESSED') {\n return res.status(409).json({ error: `Payment is already ${payment.status.toLowerCase()}` });\n }\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { status: 'SKIPPED' },\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n console.error('Skip error:', err);\n res.status(500).json({ error: 'Failed to skip payment' });\n }\n});\n\n// ── Add tag to payment ────────────────────────────────────────────────────────\nrouter.post('/:id/tags', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const { name, color } = req.body;\n if (!name) return res.status(400).json({ error: 'tag name is required' });\n\n const tag = await prisma.tag.upsert({\n where: { name },\n update: {},\n create: { name, color: color || '#6b7280' },\n });\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { tags: { connect: { id: tag.id } } },\n include: { tags: true },\n });\n\n res.json(updated);\n } catch (err) {\n console.error('Tag error:', err);\n res.status(500).json({ error: 'Failed to add tag' });\n }\n});\n\n// ── Remove tag from payment ───────────────────────────────────────────────────\nrouter.delete('/:id/tags/:tagId', async (req, res) => {\n const id = parseId(req.params.id);\n const tagId = parseId(req.params.tagId);\n if (id === null || tagId === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const updated = await prisma.payment.update({\n where: { id },\n data: { tags: { disconnect: { id: tagId } } },\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n console.error('Remove tag error:', err);\n res.status(500).json({ error: 'Failed to remove tag' });\n }\n});\n\nmodule.exports = router;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"upload.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"upload.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"89 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst multer = require('multer');\nconst { PrismaClient } = require('@prisma/client');\nconst { parseDskCsv } = require('../csvParser');\n\nconst router = express.Router();\nconst prisma = new PrismaClient();\n\nconst upload = multer({\n storage: multer.memoryStorage(),\n limits: { fileSize: 10 * 1024 * 1024, files: 10 },\n fileFilter: (_req, file, cb) => {\n if (file.mimetype === 'text/csv' || file.originalname.toLowerCase().endsWith('.csv')) {\n cb(null, true);\n } else {\n cb(new Error('Only CSV files are accepted'));\n }\n },\n});\n\n// POST /api/upload/csv\n// Accepts 1-10 CSV files, parses them, stores to DB with source=UPLOAD.\n// Returns { imported, skipped, errors, payments[] }\nrouter.post('/csv', upload.array('files', 10), async (req, res) => {\n if (!req.files || req.files.length === 0) {\n return res.status(400).json({ error: 'No files uploaded' });\n }\n\n const allRows = [];\n const allErrors = [];\n let totalSkipped = 0;\n\n for (const file of req.files) {\n try {\n const { rows, skipped, errors } = await parseDskCsv(file.buffer);\n allRows.push(...rows);\n totalSkipped += skipped;\n allErrors.push(...errors.map(e => `${file.originalname}: ${e}`));\n } catch (err) {\n allErrors.push(`${file.originalname}: ${err.message}`);\n }\n }\n\n if (allRows.length === 0) {\n return res.status(422).json({\n error: 'No importable rows found',\n skipped: totalSkipped,\n errors: allErrors,\n });\n }\n\n const created = [];\n\n for (const row of allRows) {\n const { autoTags, ...paymentData } = row;\n try {\n const tagConnects = [];\n for (const tagName of autoTags) {\n const tag = await prisma.tag.upsert({\n where: { name: tagName },\n update: {},\n create: { name: tagName, color: '#6b7280' },\n });\n tagConnects.push({ id: tag.id });\n }\n\n const payment = await prisma.payment.create({\n data: {\n ...paymentData,\n ...(tagConnects.length ? { tags: { connect: tagConnects } } : {}),\n },\n include: { tags: true },\n });\n created.push(payment);\n } catch (err) {\n allErrors.push(`Row insert failed: ${err.message}`);\n }\n }\n\n res.status(201).json({\n imported: created.length,\n skipped: totalSkipped,\n errors: allErrors,\n payments: created,\n });\n});\n\nmodule.exports = router;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now writing all frontend config files:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"24 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"{\n \"name\": \"finance-hub-frontend\",\n \"version\": \"1.0.0\",\n \"type\": \"module\",\n \"scripts\": {\n \"dev\": \"vite\",\n \"build\": \"vite build\",\n \"preview\": \"vite preview\"\n },\n \"dependencies\": {\n \"lucide-react\": \"^0.460.0\",\n \"react\": \"^18.3.1\",\n \"react-dom\": \"^18.3.1\"\n },\n \"devDependencies\": {\n \"@types/react\": \"^18.3.12\",\n \"@vitejs/plugin-react\": \"^4.3.4\",\n \"autoprefixer\": \"^10.4.20\",\n \"postcss\": \"^8.4.49\",\n \"tailwindcss\": \"^3.4.15\",\n \"vite\": \"^6.0.1\"\n }\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"FROM node:20-alpine\n\nWORKDIR /app\n\nCOPY package.json package-lock.json* ./\nRUN npm install\n\nCOPY . .\n\nEXPOSE 5173\n\nCMD [\"npm\", \"run\", \"dev\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"vite.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"vite.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"18 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import { defineConfig } from 'vite';\nimport react from '@vitejs/plugin-react';\n\nexport default defineConfig({\n plugins: [react()],\n server: {\n host: '0.0.0.0',\n port: 5173,\n allowedHosts: ['finance-hub.lakylak.xyz'],\n proxy: {\n '/api': {\n target: 'http://backend:3001',\n changeOrigin: true,\n },\n },\n },\n});","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"tailwind.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"tailwind.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"12 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/** @type {import('tailwindcss').Config} */\nexport default {\n content: [\n \"./index.html\",\n \"./src/**/*.{js,ts,jsx,tsx}\",\n ],\n theme: {\n extend: {},\n },\n plugins: [],\n};","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"postcss.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"postcss.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"7 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"export default {\n plugins: {\n tailwindcss: {},\n autoprefixer: {},\n },\n};","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.html","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.html","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"14 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"<!DOCTYPE html>\n<html lang=\"en\">\n <head>\n <meta charset=\"UTF-8\" />\n <meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\" />\n <title>Finance Hub</title>\n <link rel=\"icon\" type=\"image/svg+xml\" href=\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 100 100'><text y='.9em' font-size='90'>💰</text></svg>\" />\n </head>\n <body class=\"bg-gray-50 min-h-screen\">\n <div id=\"root\"></div>\n <script type=\"module\" src=\"/src/main.jsx\"></script>\n </body>\n</html>","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.css","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.css","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"4 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"@tailwind base;\n@tailwind components;\n@tailwind utilities;","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now writing all React components:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"}]...
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Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
report(1).csv, Editor Group 1
report(2).csv, Editor Group 1
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
Design new payment-logge…, Editor Group 2
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Ln 9, Col 45
Info: Setting up SSH Host nas: Setting up SSH tunnel
Design new payment-logger and dsk-uploader hybrid app
Session history
New session
Message actions
payments.js
payments.js
ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.
Thinking
Thinking
I'll explore all three reference projects in parallel to understand their structure before planning.
Agent:
Explore payment-logger app structure and functionality
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How data flows (ingest, storage, retrieval)
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.
Agent:
Explore dsk-uploader app structure and functionality
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How file uploads work - what files, what format, how parsed
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.
Agent:
Explore auth folder and authentik integration
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. What auth system is being used (Authentik)
2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?
3. Middleware - how is auth enforced on routes?
4. Any frontend auth flow - login redirect, token handling, protected routes
5. Environment variables related to auth
6. Docker/deployment setup for the auth service itself
7. Any example of how other apps integrate with this auth
Report with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.
Message actions
payments.js
payments.js
continue
Thinking
Thinking
Launching parallel exploration of all three reference projects.
Agent:
Explore payment-logger app structure
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How data is ingested (look at /ingest route especially)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore dsk-uploader app structure
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How file uploads work (what format, what processing happens)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore auth project structure
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. What authentication system is used (authentik integration details)
3. How OAuth/OIDC flow works
4. Any middleware or helper functions for protecting routes
5. Session management approach
6. How frontend handles auth state
7. Any example of how other apps integrate with this auth system
8. Docker setup and environment variables
Please read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.
Thinking
Thinking
Now I have a complete picture of all three. Let me design the plan.
Agent:
Design combined app architecture
IN
Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:
---
## App 1: payments-logger (Node.js)
- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI
- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS
- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage
- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)
- **Schema** (PostgreSQL via Prisma):
- `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at
- `tags` table: id, name, color — M2M with payments via `_PaymentToTag`
- `users` table: id, username, hashed_password (this will be REMOVED)
- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system
- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance
## App 2: dsk-uploader (Python/Flask)
- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database
- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5
- **Auth**: None (open)
- **CSV format** (DSK Bank Bulgarian format, columns):
- `Дата` (date, DD.MM.YYYY)
- `Вид на трансакцията` (transaction type, Bulgarian)
- `Основание` (reason/description — contains card number regex: `^\d{6}x{6}\d{4}$`)
- `Дебит BGN` (debit amount, may be empty)
- `Кредит BGN` (credit amount, may be empty)
- `Наредител/Получател` (orderer/recipient name)
- `Номер сметка на наредителя / получателя` (account number)
- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers
- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)
## App 3: auth (Authentik)
- **Mode**: Proxy mode via NPM (forward auth)
- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:
- `X-authentik-username`
- `X-authentik-email`
- `X-authentik-groups`
- **No code integration needed** in the app itself — just trust these headers from NPM
- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`
---
## What the New Combined App Must Do
1. **Single PostgreSQL database** for all transactions
2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST
3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema
4. **Unified UI** — show all payments in one table regardless of source
5. **Source indicator** in UI — badge showing "INGEST", "UPLOAD", or "BOTH" (if duplicate detection added)
6. **Source filter** in FilterBar — filter by All/Ingest/Upload
7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM
8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination
9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL
---
## Technical Constraints
- Keep Node.js backend (not Python) — extend payments-logger's stack
- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)
- File upload: use `multer` npm middleware
- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)
- Add `source` enum field (INGEST/UPLOAD) to payments schema
- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is
- Remove `users` table from schema
---
## Please Design
1. Complete folder structure for the new app (suggest name: "finance-hub" or similar — note this is a placeholder, user will confirm)
2. Prisma schema with new fields (`source`, `currency`)
3. All backend API routes
4. CSV parser design in Node.js (port of the Python logic)
5. Authentik auth middleware
6. Frontend component structure (React) — what's reused from payments-logger, what's new
7. Docker Compose setup
8. Environment variables needed
9. Step-by-step implementation order
10. Verification checklist
Be specific about file paths and code structure. This will be used to write actual implementation code.
Thinking
Thinking
Good plan. Let me ask the one thing I need before writing the final plan.
AskUserQuestion
OUT
User has answered your questions: "What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding."="finance-hub". You can now continue with the user's answers in mind.
Thinking
Thinking
Writing the final plan now.
Thinking
Thinking
Write
ets-create-a-new-generic-sun.md
ets-create-a-new-generic-sun.md
326 lines
# finance-hub — Implementation Plan
## Context
Two separate finance apps exist as references and will be retired:
- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.
- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.
The new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).
---
## Tech Stack
| Layer | Choice | Rationale |
|-------|--------|-----------|
| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |
| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |
| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |
| Database | PostgreSQL 16 | Same as payments-logger |
| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |
| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |
| Container | Docker Compose | Same pattern as both reference apps |
**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage.
**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references.
**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.
---
## Folder Structure
```
/volume2/docker/finance/finance-hub/
├── docker-compose.yml
├── .env
├── .env.example
├── .gitignore
├── backend/
│ ├── Dockerfile
│ ├── package.json
│ ├── prisma/
│ │ ├── schema.prisma
│ │ └── migrations/
│ │ ├── migration_lock.toml
│ │ └── 20260508_init/
│ │ └── migration.sql
│ └── src/
│ ├── index.js ← entry point (Authentik middleware wired here)
│ ├── auth.js ← Authentik header middleware (replaces JWT auth)
│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)
│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)
│ └── routes/
│ ├── payments.js ← existing routes + source/currency additions
│ └── upload.js ← NEW: POST /api/upload/csv
└── frontend/
├── Dockerfile
├── package.json
├── vite.config.js
├── tailwind.config.js
├── postcss.config.js
├── index.html
└── src/
├── main.jsx ← remove AuthProvider wrapper
├── index.css
├── App.jsx ← remove auth state, add Upload tab toggle
└── components/
├── FilterBar.jsx ← add source filter select
├── PaymentTable.jsx ← add Source badge column + currency display
├── PaymentCard.jsx ← minor source badge addition
├── PaymentList.jsx ← unchanged
└── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI
```
---
## Database Schema (Prisma)
File: `backend/prisma/schema.prisma`
```prisma
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
}
model Payment {
id Int @id @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
auth.js
auth.js
27 lines
const PUBLIC_PATHS = new Set([
'/api/health',
'/api/payments/ingest',
]);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) {
return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });
}
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '')
.split(',')
.map(g => g.trim())
.filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
Write
parser.js
parser.js
104 lines
/**
* Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)
*
* Supported formats:
*
* POS / INTERNET / ECOM / P2P payment:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM withdrawal:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM utility payment (amount may include fee as AMOUNT/FEE):
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.
*/
const LOCAL_TZ = process.env.TZ || 'Europe/Sofia';
/**
* Convert a local-timezone date/time to a UTC Date object.
* Uses Intl to resolve the actual UTC offset (DST-aware).
*/
function localToUtc(year, month, day, hour, minute) {
const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));
const formatter = new Intl.DateTimeFormat('en-US', {
timeZone: LOCAL_TZ,
year: 'numeric', month: '2-digit', day: '2-digit',
hour: '2-digit', minute: '2-digit', second: '2-digit',
hour12: false,
});
const parts = {};
formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });
const localAtNaive = new Date(Date.UTC(
parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),
parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),
));
const offsetMs = localAtNaive.getTime() - naive.getTime();
return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);
}
function parsePaymentSms(message) {
const result = {
rawMessage: message,
date: null,
type: null,
card: null,
recipient: null,
amount: null,
balance: null,
};
// Date and time: "Na DD/MM/YYYY v HH:MM"
const dateMatch = message.match(/Na (\d{2})\/(\d{2})\/(\d{4}) v (\d{2}):(\d{2})/i);
if (dateMatch) {
const [, day, month, year, hour, minute] = dateMatch;
result.date = localToUtc(
parseInt(year), parseInt(month), parseInt(day),
parseInt(hour), parseInt(minute),
);
}
// Card mask: "s karta 400915***4447" or "s karta 483890***7162"
const cardMatch = message.match(/s karta\s+([\d*]+)/i);
if (cardMatch) {
result.card = cardMatch[1];
}
// Transaction type: supports both prepositions
// "na POS" / "na ATM" / "na INTERNET" etc. (payment)
// "ot ATM" (withdrawal)
const typeMatch = message.match(/(?:na|ot)\s+(POS|ATM|INTERNET|ECOM|P2P)\b/i);
if (typeMatch) {
result.type = typeMatch[1].toUpperCase();
}
// Recipient address: "s adres: MERCHANT" or "s adres:MERCHANT" (no space variant)
const recipientMatch = message.match(/s adres:\s*([^.]+)\./i);
if (recipientMatch) {
result.recipient = recipientMatch[1].trim();
}
// Amount: handles both verbs and the AMOUNT/FEE suffix format
// "sa plateni 7.78 EUR"
// "sa iztegleni 400.00 EUR"
// "sa plateni 0.50 EUR/0.50 EUR" → captures 0.50 (the charged amount, ignoring fee)
const amountMatch = message.match(/sa (?:plateni|iztegleni)\s+([\d.,]+)\s+[A-Z]{3}/i);
if (amountMatch) {
result.amount = parseFloat(amountMatch[1].replace(',', '.'));
}
// Balance: "Nalichni: 2583.07 EUR."
const balanceMatch = message.match(/Nalichni:\s*([\d.,]+)\s+[A-Z]{3}/i);
if (balanceMatch) {
result.balance = parseFloat(balanceMatch[1].replace(',', '.'));
}
return result;
}
module.exports = { parsePaymentSms };
Write
csvParser.js
csvParser.js
175 lines
/**
* DSK Bank CSV parser — Node.js port of dskuploader.py
*
* DSK Bank exports use Windows-1251 (cp1251) encoding.
* Each row maps to a Payment record with source=UPLOAD, currency=BGN.
*/
const { parse } = require('csv-parse');
const iconv = require('iconv-lite');
const SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';
const CARD_REGEX = /^\d{6}x{6}\d{4}$/;
const POS_REGEX = /^\s*ПЛАЩАНЕ\s+НА\s+ПОС\s+\d{2}\.\d{2}\.\d{4}\s+\d{2}:\d{2}/;
const COL = {
DATE: 'Дата',
TYPE: 'Вид на трансакцията',
REASON: 'Основание',
DEBIT: 'Дебит BGN',
CREDIT: 'Кредит BGN',
PAYEE: 'Наредител/Получател',
ACCT: 'Номер сметка на наредителя / получателя',
};
const TAG_RULES = [
['reason', 'ЗАПЛАТА', 'Salary'],
['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],
['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],
['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],
['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],
['payee', 'VIVACOM', 'Subscriptions'],
['payee', 'Google', 'Subscriptions'],
['payee', 'SkyShowtime', 'Subscriptions'],
['payee', 'NETFLIX', 'Subscriptions'],
['payee', 'LUKOIL', 'Bills'],
['payee', 'CityGate', 'Bills'],
['payee', 'CBA', 'Groceries'],
['payee', 'FANTASTICO', 'Groceries'],
['payee', 'LIDL', 'Groceries'],
];
function parseNum(val) {
if (val == null || val === '') return null;
if (typeof val === 'number') return isNaN(val) ? null : val;
const s = String(val).trim().replace(/\xa0/g, '').replace(/ /g, '').replace(',', '.');
const n = parseFloat(s);
return isNaN(n) ? null : n;
}
function parseDate(val) {
if (!val) return null;
const s = String(val).trim();
const m = s.match(/^(\d{2})\.(\d{2})\.(\d{4})$/);
if (m) {
return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));
}
return null;
}
function processReasonAndCard(reason) {
if (!reason || typeof reason !== 'string') return { reason: '', card: null };
const parts = reason.trim().split(' ');
let card = null;
let cleanReason = reason.trim();
if (parts[0] && CARD_REGEX.test(parts[0])) {
card = parts[0];
cleanReason = parts.slice(1).join(' ').trim();
}
if (POS_REGEX.test(cleanReason)) {
const posParts = cleanReason.split('<br/>');
try {
const dateTime = posParts[0].split('ПОС ')[1];
cleanReason = `POS PAYMENT ${dateTime}`;
} catch (_) { /* keep original */ }
}
return { reason: cleanReason.replace(/\s+/g, ' ').trim(), card };
}
function generateTags(fields) {
const tags = new Set();
for (const [field, keyword, tagName] of TAG_RULES) {
if ((fields[field] || '').includes(keyword)) {
tags.add(tagName);
}
}
return Array.from(tags);
}
function processRow(row) {
const transactionType = (row[COL.TYPE] || '').trim();
if (transactionType === SKIP_TYPE) return null;
const { reason, card } = processReasonAndCard(row[COL.REASON]);
const payee = (row[COL.PAYEE] || ...
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report(2).csv — finance [SSH: nas]
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G)
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
report(1).csv, Editor Group 1
report(2).csv, Editor Group 1
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
Design new payment-logge…, Editor Group 2
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Design new payment-logger and dsk-uploader hybrid app
Session history
New session
Message actions
payments.js
payments.js
ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.
Thinking
Thinking
I'll explore all three reference projects in parallel to understand their structure before planning.
Agent:
Explore payment-logger app structure and functionality
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How data flows (ingest, storage, retrieval)
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.
Agent:
Explore dsk-uploader app structure and functionality
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How file uploads work - what files, what format, how parsed
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.
Agent:
Explore auth folder and authentik integration
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. What auth system is being used (Authentik)
2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?
3. Middleware - how is auth enforced on routes?
4. Any frontend auth flow - login redirect, token handling, protected routes
5. Environment variables related to auth
6. Docker/deployment setup for the auth service itself
7. Any example of how other apps integrate with this auth
Report with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.
Message actions
payments.js
payments.js
continue
Thinking
Thinking
Launching parallel exploration of all three reference projects.
Agent:
Explore payment-logger app structure
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How data is ingested (look at /ingest route especially)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore dsk-uploader app structure
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How file uploads work (what format, what processing happens)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore auth project structure
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. What authentication system is used (authentik integration details)
3. How OAuth/OIDC flow works
4. Any middleware or helper functions for protecting routes
5. Session management approach
6. How frontend handles auth state
7. Any example of how other apps integrate with this auth system
8. Docker setup and environment variables
Please read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.
Thinking
Thinking
Now I have a complete picture of all three. Let me design the plan.
Agent:
Design combined app architecture
IN
Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:
---
## App 1: payments-logger (Node.js)
- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI
- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS
- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage
- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)
- **Schema** (PostgreSQL via Prisma):
- `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at
- `tags` table: id, name, color — M2M with payments via `_PaymentToTag`
- `users` table: id, username, hashed_password (this will be REMOVED)
- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system
- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance
## App 2: dsk-uploader (Python/Flask)
- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database
- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5
- **Auth**: None (open)
- **CSV format** (DSK Bank Bulgarian format, columns):
- `Дата` (date, DD.MM.YYYY)
- `Вид на трансакцията` (transaction type, Bulgarian)
- `Основание` (reason/description — contains card number regex: `^\d{6}x{6}\d{4}$`)
- `Дебит BGN` (debit amount, may be empty)
- `Кредит BGN` (credit amount, may be empty)
- `Наредител/Получател` (orderer/recipient name)
- `Номер сметка на наредителя / получателя` (account number)
- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers
- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)
## App 3: auth (Authentik)
- **Mode**: Proxy mode via NPM (forward auth)
- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:
- `X-authentik-username`
- `X-authentik-email`
- `X-authentik-groups`
- **No code integration needed** in the app itself — just trust these headers from NPM
- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`
---
## What the New Combined App Must Do
1. **Single PostgreSQL database** for all transactions
2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST
3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema
4. **Unified UI** — show all payments in one table regardless of source
5. **Source indicator** in UI — badge showing "INGEST", "UPLOAD", or "BOTH" (if duplicate detection added)
6. **Source filter** in FilterBar — filter by All/Ingest/Upload
7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM
8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination
9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL
---
## Technical Constraints
- Keep Node.js backend (not Python) — extend payments-logger's stack
- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)
- File upload: use `multer` npm middleware
- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)
- Add `source` enum field (INGEST/UPLOAD) to payments schema
- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is
- Remove `users` table from schema
---
## Please Design
1. Complete folder structure for the new app (suggest name: "finance-hub" or similar — note this is a placeholder, user will confirm)
2. Prisma schema with new fields (`source`, `currency`)
3. All backend API routes
4. CSV parser design in Node.js (port of the Python logic)
5. Authentik auth middleware
6. Frontend component structure (React) — what's reused from payments-logger, what's new
7. Docker Compose setup
8. Environment variables needed
9. Step-by-step implementation order
10. Verification checklist
Be specific about file paths and code structure. This will be used to write actual implementation code.
Thinking
Thinking
Good plan. Let me ask the one thing I need before writing the final plan.
AskUserQuestion
OUT
User has answered your questions: "What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding."="finance-hub". You can now continue with the user's answers in mind.
Thinking
Thinking
Writing the final plan now.
Thinking
Thinking
Write
ets-create-a-new-generic-sun.md
ets-create-a-new-generic-sun.md
326 lines
# finance-hub — Implementation Plan
## Context
Two separate finance apps exist as references and will be retired:
- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.
- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.
The new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).
---
## Tech Stack
| Layer | Choice | Rationale |
|-------|--------|-----------|
| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |
| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |
| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |
| Database | PostgreSQL 16 | Same as payments-logger |
| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |
| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |
| Container | Docker Compose | Same pattern as both reference apps |
**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage.
**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references.
**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.
---
## Folder Structure
```
/volume2/docker/finance/finance-hub/
├── docker-compose.yml
├── .env
├── .env.example
├── .gitignore
├── backend/
│ ├── Dockerfile
│ ├── package.json
│ ├── prisma/
│ │ ├── schema.prisma
│ │ └── migrations/
│ │ ├── migration_lock.toml
│ │ └── 20260508_init/
│ │ └── migration.sql
│ └── src/
│ ├── index.js ← entry point (Authentik middleware wired here)
│ ├── auth.js ← Authentik header middleware (replaces JWT auth)
│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)
│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)
│ └── routes/
│ ├── payments.js ← existing routes + source/currency additions
│ └── upload.js ← NEW: POST /api/upload/csv
└── frontend/
├── Dockerfile
├── package.json
├── vite.config.js
├── tailwind.config.js
├── postcss.config.js
├── index.html
└── src/
├── main.jsx ← remove AuthProvider wrapper
├── index.css
├── App.jsx ← remove auth state, add Upload tab toggle
└── components/
├── FilterBar.jsx ← add source filter select
├── PaymentTable.jsx ← add Source badge column + currency display
├── PaymentCard.jsx ← minor source badge addition
├── PaymentList.jsx ← unchanged
└── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI
```
---
## Database Schema (Prisma)
File: `backend/prisma/schema.prisma`
```prisma
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
}
model Payment {
id Int @id @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
auth.js
auth.js
27 lines
const PUBLIC_PATHS = new Set([
'/api/health',
'/api/payments/ingest',
]);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) {
return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });
}
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '')
.split(',')
.map(g => g.trim())
.filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
Write
parser.js
parser.js
104 lines
/**
* Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)
*
* Supported formats:
*
* POS / INTERNET / ECOM / P2P payment:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM withdrawal:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM utility payment (amount may include fee as AMOUNT/FEE):
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.
*/
const LOCAL_TZ = process.env.TZ || 'Europe/Sofia';
/**
* Convert a local-timezone date/time to a UTC Date object.
* Uses Intl to resolve the actual UTC offset (DST-aware).
*/
function localToUtc(year, month, day, hour, minute) {
const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));
const formatter = new Intl.DateTimeFormat('en-US', {
timeZone: LOCAL_TZ,
year: 'numeric', month: '2-digit', day: '2-digit',
hour: '2-digit', minute: '2-digit', second: '2-digit',
hour12: false,
});
const parts = {};
formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });
const localAtNaive = new Date(Date.UTC(
parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),
parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),
));
const offsetMs = localAtNaive.getTime() - naive.getTime();
return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);
}
function parsePaymentSms(message) {
const result = {
rawMessage: message,
date: null,
type: null,
card: null,
recipient: null,
amount: null,
balance: null,
};
// Date and time: "Na DD/MM/YYYY v HH:MM"
const dateMatch = message.match(/Na (\d{2})\/(\d{2})\/(\d{4}) v (\d{2}):(\d{2})/i);
if (dateMatch) {
const [, day, month, year, hour, minute] = dateMatch;
result.date = localToUtc(
parseInt(year), parseInt(month), parseInt(day),
parseInt(hour), parseInt(minute),
);
}
// Card mask: "s karta 400915***4447" or "s karta 483890***7162"
const cardMatch = message.match(/s karta\s+([\d*]+)/i);
if (cardMatch) {
result.card = cardMatch[1];
}
// Transaction type: supports both prepositions
// "na POS" / "na ATM" / "na INTERNET" etc. (payment)
// "ot ATM" (withdrawal)
const typeMatch = message.match(/(?:na|ot)\s+(POS|ATM|INTERNET|ECOM|P2P)\b/i);
if (typeMatch) {
result.type = typeMatch[1].toUpperCase();
}
// Recipient address: "s adres: MERCHANT" or "s adres:MERCHANT" (no space variant)
const recipientMatch = message.match(/s adres:\s*([^.]+)\./i);
if (recipientMatch) {
result.recipient = recipientMatch[1].trim();
}
// Amount: handles both verbs and the AMOUNT/FEE suffix format
// "sa plateni 7.78 EUR"
// "sa iztegleni 400.00 EUR"
// "sa plateni 0.50 EUR/0.50 EUR" → captures 0.50 (the charged amount, ignoring fee)
const amountMatch = message.match(/sa (?:plateni|iztegleni)\s+([\d.,]+)\s+[A-Z]{3}/i);
if (amountMatch) {
result.amount = parseFloat(amountMatch[1].replace(',', '.'));
}
// Balance: "Nalichni: 2583.07 EUR."
const balanceMatch = message.match(/Nalichni:\s*([\d.,]+)\s+[A-Z]{3}/i);
if (balanceMatch) {
result.balance = parseFloat(balanceMatch[1].replace(',', '.'));
}
return result;
}
module.exports = { parsePaymentSms };
Write
csvParser.js
csvParser.js
175 lines
/**
* DSK Bank CSV parser — Node.js port of dskuploader.py
*
* DSK Bank exports use Windows-1251 (cp1251) encoding.
* Each row maps to a Payment record with source=UPLOAD, currency=BGN.
*/
const { parse } = require('csv-parse');
const iconv = require('iconv-lite');
const SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';
const CARD_REGEX = /^\d{6}x{6}\d{4}$/;
const POS_REGEX = /^\s*ПЛАЩАНЕ\s+НА\s+ПОС\s+\d{2}\.\d{2}\.\d{4}\s+\d{2}:\d{2}/;
const COL = {
DATE: 'Дата',
TYPE: 'Вид на трансакцията',
REASON: 'Основание',
DEBIT: 'Дебит BGN',
CREDIT: 'Кредит BGN',
PAYEE: 'Наредител/Получател',
ACCT: 'Номер сметка на наредителя / получателя',
};
const TAG_RULES = [
['reason', 'ЗАПЛАТА', 'Salary'],
['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],
['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],
['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],
['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],
['payee', 'VIVACOM', 'Subscriptions'],
['payee', 'Google', 'Subscriptions'],
['payee', 'SkyShowtime', 'Subscriptions'],
['payee', 'NETFLIX', 'Subscriptions'],
['payee', 'LUKOIL', 'Bills'],
['payee', 'CityGate', 'Bills'],
['payee', 'CBA', 'Groceries'],
['payee', 'FANTASTICO', 'Groceries'],
['payee', 'LIDL', 'Groceries'],
];
function parseNum(val) {
if (val == null || val === '') return null;
if (typeof val === 'number') return isNaN(val) ? null : val;
const s = String(val).trim().replace(/\xa0/g, '').replace(/ /g, '').replace(',', '.');
const n = parseFloat(s);
return isNaN(n) ? null : n;
}
function parseDate(val) {
if (!val) return null;
const s = String(val).trim();
const m = s.match(/^(\d{2})\.(\d{2})\.(\d{4})$/);
if (m) {
return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));
}
return null;
}
function processReasonAndCard(reason) {
if (!reason || typeof reason !== 'string') return { reason: '', card: null };
const parts = reason.trim().split(' ');
let card = null;
let cleanReason = reason.trim();
if (parts[0] && CARD_REGEX.test(parts[0])) {
card = parts[0];
cleanReason = parts.slice(1).join(' ').trim();
}
if (POS_REGEX.test(cleanReason)) {
const posParts = cleanReason.split('<br/>');
try {
const dateTime = posParts[0].split('ПОС ')[1];
cleanReason = `POS PAYMENT ${dateTime}`;
} catch (_) { /* keep original */ }
}
return { reason: cleanReason.replace(/\s+/g, ' ').trim(), card };
}
function generateTags(fields) {
const tags = new Set();
for (const [field, keyword, tagName] of TAG_RULES) {
if ((fields[field] || '').includes(keyword)) {
tags.add(tagName);
}
}
return Array.from(tags);
}
function processRow(row) {
const transactionType = (row[COL.TYPE] || '').trim();
if (transactionType === SKIP_TYPE) return null;
const { reason, card } = processReasonAndCard(row[COL.REASON]);
const payee = (row[COL.PAYEE] || ...
|
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4","depth":16,"bounds":{"left":0.85837764,"top":0.98244214,"width":0.022273935,"height":0.01755786},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Ln 9, Col 45","depth":16,"bounds":{"left":0.83011967,"top":0.98244214,"width":0.026595745,"height":0.01755786},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Info: Setting up SSH Host nas: Setting up SSH tunnel","depth":12,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Design new payment-logger and dsk-uploader hybrid app","depth":19,"bounds":{"left":0.56017286,"top":0.08060654,"width":0.099734046,"height":0.022346368},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Session 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actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"payments.js","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"I'll explore all three reference projects in parallel to understand their structure before planning.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How data flows (ingest, storage, retrieval)\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How file uploads work - what files, what format, how parsed\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth folder and authentik integration","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. What auth system is being used (Authentik)\n2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?\n3. Middleware - how is auth enforced on routes?\n4. Any frontend auth flow - login redirect, token handling, protected routes\n5. Environment variables related to auth\n6. Docker/deployment setup for the auth service itself\n7. Any example of how other apps integrate with this auth\n\nReport with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"payments.js","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"continue","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Launching parallel exploration of all three reference projects.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How data is ingested (look at /ingest route especially)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How file uploads work (what format, what processing happens)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth project structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. What authentication system is used (authentik integration details)\n3. How OAuth/OIDC flow works\n4. Any middleware or helper functions for protecting routes\n5. Session management approach\n6. How frontend handles auth state\n7. Any example of how other apps integrate with this auth system\n8. Docker setup and environment variables\n\nPlease read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now I have a complete picture of all three. Let me design the plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design combined app architecture","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:\n\n---\n\n## App 1: payments-logger (Node.js)\n- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI\n- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS\n- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage\n- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)\n- **Schema** (PostgreSQL via Prisma):\n - `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at\n - `tags` table: id, name, color — M2M with payments via `_PaymentToTag`\n - `users` table: id, username, hashed_password (this will be REMOVED)\n- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system\n- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance\n\n## App 2: dsk-uploader (Python/Flask)\n- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database\n- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5\n- **Auth**: None (open)\n- **CSV format** (DSK Bank Bulgarian format, columns):\n - `Дата` (date, DD.MM.YYYY)\n - `Вид на трансакцията` (transaction type, Bulgarian)\n - `Основание` (reason/description — contains card number regex: `^\\d{6}x{6}\\d{4}$`)\n - `Дебит BGN` (debit amount, may be empty)\n - `Кредит BGN` (credit amount, may be empty)\n - `Наредител/Получател` (orderer/recipient name)\n - `Номер сметка на наредителя / получателя` (account number)\n- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers\n- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)\n\n## App 3: auth (Authentik)\n- **Mode**: Proxy mode via NPM (forward auth)\n- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:\n - `X-authentik-username` \n - `X-authentik-email`\n - `X-authentik-groups`\n- **No code integration needed** in the app itself — just trust these headers from NPM\n- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`\n\n---\n\n## What the New Combined App Must Do\n\n1. **Single PostgreSQL database** for all transactions\n2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST\n3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema\n4. **Unified UI** — show all payments in one table regardless of source\n5. **Source indicator** in UI — badge showing \"INGEST\", \"UPLOAD\", or \"BOTH\" (if duplicate detection added)\n6. **Source filter** in FilterBar — filter by All/Ingest/Upload\n7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM\n8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination\n9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL\n\n---\n\n## Technical Constraints\n\n- Keep Node.js backend (not Python) — extend payments-logger's stack\n- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)\n- File upload: use `multer` npm middleware\n- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)\n- Add `source` enum field (INGEST/UPLOAD) to payments schema\n- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is\n- Remove `users` table from schema\n\n---\n\n## Please Design\n\n1. Complete folder structure for the new app (suggest name: \"finance-hub\" or similar — note this is a placeholder, user will confirm)\n2. Prisma schema with new fields (`source`, `currency`)\n3. All backend API routes\n4. CSV parser design in Node.js (port of the Python logic)\n5. Authentik auth middleware\n6. Frontend component structure (React) — what's reused from payments-logger, what's new\n7. Docker Compose setup\n8. Environment variables needed\n9. Step-by-step implementation order\n10. Verification checklist\n\nBe specific about file paths and code structure. This will be used to write actual implementation code.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good plan. Let me ask the one thing I need before writing the final plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"AskUserQuestion","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"OUT","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"User has answered your questions: \"What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding.\"=\"finance-hub\". You can now continue with the user's answers in mind.","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Writing the final plan now.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"326 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# finance-hub — Implementation Plan\n\n## Context\n\nTwo separate finance apps exist as references and will be retired:\n- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.\n- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.\n\nThe new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).\n\n---\n\n## Tech Stack\n\n| Layer | Choice | Rationale |\n|-------|--------|-----------|\n| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |\n| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |\n| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |\n| Database | PostgreSQL 16 | Same as payments-logger |\n| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |\n| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |\n| Container | Docker Compose | Same pattern as both reference apps |\n\n**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage. \n**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references. \n**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.\n\n---\n\n## Folder Structure\n\n```\n/volume2/docker/finance/finance-hub/\n├── docker-compose.yml\n├── .env\n├── .env.example\n├── .gitignore\n├── backend/\n│ ├── Dockerfile\n│ ├── package.json\n│ ├── prisma/\n│ │ ├── schema.prisma\n│ │ └── migrations/\n│ │ ├── migration_lock.toml\n│ │ └── 20260508_init/\n│ │ └── migration.sql\n│ └── src/\n│ ├── index.js ← entry point (Authentik middleware wired here)\n│ ├── auth.js ← Authentik header middleware (replaces JWT auth)\n│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)\n│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)\n│ └── routes/\n│ ├── payments.js ← existing routes + source/currency additions\n│ └── upload.js ← NEW: POST /api/upload/csv\n└── frontend/\n ├── Dockerfile\n ├── package.json\n ├── vite.config.js\n ├── tailwind.config.js\n ├── postcss.config.js\n ├── index.html\n └── src/\n ├── main.jsx ← remove AuthProvider wrapper\n ├── index.css\n ├── App.jsx ← remove auth state, add Upload tab toggle\n └── components/\n ├── FilterBar.jsx ← add source filter select\n ├── PaymentTable.jsx ← add Source badge column + currency display\n ├── PaymentCard.jsx ← minor source badge addition\n ├── PaymentList.jsx ← unchanged\n └── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI\n```\n\n---\n\n## Database Schema (Prisma)\n\nFile: `backend/prisma/schema.prisma`\n\n```prisma\ngenerator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status { UNPROCESSED SENT SKIPPED }\nenum Source { INGEST UPLOAD }\n```\n\n**Key decisions:**\n- No `User` model — Authentik owns identity.\n- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.\n- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.\n- `balance` is always null for CSV rows (DSK export does not include running balance).\n- Fresh consolidated migration — no data migration from reference apps required.\n\n---\n\n## API Routes\n\n| Method | Path | Auth | Description |\n|--------|------|------|-------------|\n| GET | /api/health | public | Health check |\n| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |\n| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |\n| GET | /api/payments/meta/tags | required | All tags |\n| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |\n| GET | /api/payments/:id | required | Single payment |\n| PATCH | /api/payments/:id | required | Update status |\n| DELETE | /api/payments/:id | required | Delete |\n| POST | /api/payments/:id/send | required | Send notification |\n| POST | /api/payments/:id/skip | required | Skip |\n| POST | /api/payments/:id/tags | required | Add/upsert tag |\n| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |\n| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |\n\n---\n\n## Key Implementation Details\n\n### auth.js (replaces entire old auth module)\n```js\nconst PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n const username = req.headers['x-authentik-username'];\n if (!username) return res.status(401).json({ error: 'Unauthorized' });\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),\n };\n next();\n}\nmodule.exports = { authentikMiddleware };\n```\n\n### csvParser.js (port of dskuploader.py)\n- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8\n- `csv-parse` parses the decoded text with `columns: true`\n- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`\n- Card extraction: regex `/^\\d{6}x{6}\\d{4}$/` on first token of `Основание`\n- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`\n- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`\n- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`\n\n### payments.js changes from payments-logger\n1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call\n2. Add `source` to the `GET /` where clause filter\n3. Add `sources` to `meta/filters` response\n4. Currency-aware amount formatting in notification message\n5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)\n\n### upload.js (new)\n- `multer` memory storage, max 10 files × 10 MB\n- Calls `parseDskCsv(buffer)` per file\n- Upserts tags via `prisma.tag.upsert` then connects\n- Returns `{ imported, skipped, errors, payments[] }`\n\n### Frontend changes\n- **Delete**: `auth.js`, `AuthProvider.jsx`\n- **main.jsx**: Remove `<AuthProvider>` wrapper\n- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add \"Payments\" / \"Upload CSV\" tab toggle\n- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols\n- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell\n- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`\n\n---\n\n## Docker Compose\n\n```yaml\nservices:\n db:\n image: postgres:16-alpine\n environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: ${DB_PASSWORD}, POSTGRES_DB: finance_hub }\n volumes: [pgdata:/var/lib/postgresql/data]\n healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }\n\n backend:\n build: ./backend\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports: [\"${BACKEND_PORT:-3001}:3001\"]\n depends_on: { db: { condition: service_healthy } }\n\n frontend:\n build: ./frontend\n ports: [\"${FRONTEND_PORT:-5175}:5173\"]\n depends_on: [backend]\n\nvolumes: { pgdata: }\n```\n\n**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.\n\n---\n\n## Environment Variables (.env)\n\n```bash\nDB_PASSWORD=change_me\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\nTZ=Europe/Sofia\nBACKEND_PORT=3001\nFRONTEND_PORT=5175\n```\n\nRemoved vs payments-logger: `JWT_SECRET`, `JWT_EXPIRE_MINUTES`.\n\n---\n\n## Implementation Order\n\n1. Create folder structure and write `docker-compose.yml`, `.env.example`, `.gitignore`\n2. Write `backend/prisma/schema.prisma` and migration SQL\n3. Write `backend/package.json` (add `csv-parse`, `iconv-lite`, `multer`; remove `bcryptjs`, `jose`)\n4. Write `backend/Dockerfile`\n5. Write `backend/src/auth.js` (Authentik middleware)\n6. Copy `backend/src/parser.js` verbatim from payments-logger\n7. Write `backend/src/csvParser.js` (Python port)\n8. Write `backend/src/routes/upload.js`\n9. Write `backend/src/routes/payments.js` (from payments-logger + 5 changes listed above)\n10. Write `backend/src/index.js`\n11. Copy frontend base from payments-logger; delete `auth.js` + `AuthProvider.jsx`\n12. Update `main.jsx`, `App.jsx`, `FilterBar.jsx`, `PaymentTable.jsx`\n13. Write `frontend/src/components/UploadPanel.jsx`\n14. Update `frontend/vite.config.js`\n15. `docker compose build && docker compose up -d`\n16. Run verification checklist\n\n---\n\n## Verification\n\n**Schema**\n- `payments` table has `source`, `currency`, `debit_bgn`, `credit_bgn`, `transaction_type`, `payer_account`\n- No `users` table; `Source` enum exists\n\n**Auth**\n- `GET /api/payments` → 401 without `x-authentik-username` header\n- `POST /api/payments/ingest` → 201 without any header\n- `curl -H \"x-authentik-username: test\" localhost:3001/api/payments` → 200\n\n**SMS Ingest**\n- DSK POS SMS → `source=INGEST`, `currency=EUR`, correct amount/card/recipient\n- Apple Wallet structured body → `type=WALLET`, `source=INGEST`\n- Rate limiter → 429 after 200 req/min\n\n**CSV Upload**\n- Single DSK CSV → rows with `source=UPLOAD`, `currency=BGN`\n- Multiple CSVs in one request → all merged\n- `ТРАНСФЕР СОБСТВЕНИ СМЕТКИ` rows counted in `skipped`, not imported\n- Card regex match from `Основание` column\n- Auto-tags applied (ЗАПЛАТА→Salary, LIDL→Groceries)\n- cp1251 file imports correctly\n\n**UI**\n- Source badge visible in payment table (SMS indigo, CSV emerald)\n- Source dropdown in FilterBar filters correctly\n- Amount shows correct currency per row\n- Upload Panel: drag-and-drop works, result summary shows counts\n- Logout redirects to Authentik sign_out\n- No login form shown (Authentik handles it at NPM level)\n- Tags, send, skip, delete all still work\n\n## Reference Files\n\n- `/volume2/docker/finance/payments-logger/backend/src/routes/payments.js`\n- `/volume2/docker/finance/payments-logger/backend/src/parser.js`\n- `/volume2/docker/finance/payments-logger/backend/src/index.js`\n- `/volume2/docker/finance/payments-logger/backend/src/auth.js`\n- `/volume2/docker/finance/payments-logger/backend/prisma/schema.prisma`\n- `/volume2/docker/finance/payments-logger/frontend/src/App.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/PaymentTable.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/FilterBar.jsx`\n- `/volume2/docker/finance/dsk-uploader/dskuploader.py`\n- `/volume2/docker/finance/auth/docker-compose.yml`","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Claude’s Plan","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Stayed in plan mode","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good question. Here's the full breakdown:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Backend Tech Stack — Options","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Backend Tech Stack — Options","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Why:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"payments-logger is already Node.js/Express/Prisma. The new app is 80% payments-logger with CSV upload added on top. Keeping the same stack means:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"verbatim, zero rewrite","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy the entire","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"routes/payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with minimal edits","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Same Prisma schema workflow, same migrations, same Docker image","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The CSV parsing logic (the only Python-specific thing) ports cleanly to","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"csv-parse","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— it's just regex + string manipulation, nothing pandas-specific","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Trade-off:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Have to port the Python CSV parsing to JS. It's ~150 lines and mostly string manipulation — straightforward.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option B: Python + FastAPI + SQLAlchemy","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option B: Python + FastAPI + SQLAlchemy","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rewrite everything in Python. dsk-uploader is Python, so CSV parsing is already done.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep the dsk-uploader CSV logic as-is (no porting). Python has better data science libraries if you later add analytics.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Lose the entire payments-logger backend (routes, parser, Prisma schema) — full rewrite. FastAPI + SQLAlchemy is a different mental model than Express + Prisma. Frontend stays React anyway, so the stack split doesn't simplify anything.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"More work overall, gains almost nothing.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep Node.js as the main API, add a separate Python FastAPI service just for CSV parsing. 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For ~150 lines of CSV logic, this is massively over-engineered.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Not worth it.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Extend dsk-uploader into a full payments app.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pandas for CSV, no porting.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Jinja2 templates instead of React (or add React separately). Would need to reimplement the entire payments-logger (SMS parser, notification system, tag management, pagination/filtering). Flask's Jinja templating is far less capable than the existing React UI. The React frontend is the stronger UI foundation.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Worst of all options — rebuild the harder parts (UI, SMS parser, notification) for no gain.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Summary","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Summary","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"CSV porting effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"App rewrite effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Result 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Everything else in the plan reuses payments-logger code directly. That's why Node.js is the clear winner here.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Want to adjust the stack, or shall I proceed with Option A?","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ok sounds good. Implement all you suggested","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Starting implementation. Let me first read all the reference files I'll need to copy from.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"payments.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"App.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"App.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"FilterBar.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"FilterBar.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentTable.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentTable.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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payments-logger.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.css","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.css","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"vite.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"vite.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"tailwind.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"tailwind.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"postcss.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"postcss.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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Let me set up the todo list and start building.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, 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/volume2/docker/finance/finance-hub/backend/prisma/migrations/20260508_init \\\n /volume2/docker/finance/finance-hub/frontend/src/components && echo \"done\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":24,"on_screen":false,"help_text":"Copy 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POSTGRES_USER: finance\n POSTGRES_PASSWORD: ${DB_PASSWORD}\n POSTGRES_DB: finance_hub\n volumes:\n - pgdata:/var/lib/postgresql/data\n healthcheck:\n test: [\"CMD-SHELL\", \"pg_isready -U finance -d finance_hub\"]\n interval: 5s\n timeout: 5s\n retries: 5\n\n backend:\n build: ./backend\n restart: unless-stopped\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports:\n - \"${BACKEND_PORT:-3001}:3001\"\n depends_on:\n db:\n condition: service_healthy\n\n frontend:\n build: ./frontend\n restart: unless-stopped\n ports:\n - \"${FRONTEND_PORT:-5175}:5173\"\n depends_on:\n - backend\n\nvolumes:\n pgdata:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".env.example","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".env.example","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"15 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Database\nDB_PASSWORD=change_me_strong_password\n\n# Notifier service (for SMS payment notifications)\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\n\n# Timezone (used by SMS parser for Bulgarian bank timestamps)\nTZ=Europe/Sofia\n\n# Ports (optional — defaults shown)\nBACKEND_PORT=3001\nFRONTEND_PORT=5175","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".gitignore","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".gitignore","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"5 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env\nnode_modules/\ndist/\n*.log","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config 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compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"schema.prisma","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"schema.prisma","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"54 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"generator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status {\n UNPROCESSED\n SENT\n SKIPPED\n}\n\nenum Source {\n INGEST\n UPLOAD\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration.sql","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration.sql","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"55 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- CreateEnum\nCREATE TYPE \"Status\" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');\nCREATE TYPE \"Source\" AS ENUM ('INGEST', 'UPLOAD');\n\n-- CreateTable\nCREATE TABLE \"payments\" (\n \"id\" SERIAL PRIMARY KEY,\n \"raw_message\" TEXT NOT NULL,\n \"date\" TIMESTAMP(3),\n \"type\" TEXT,\n \"card\" TEXT,\n \"recipient\" TEXT,\n \"amount\" DOUBLE PRECISION,\n \"currency\" TEXT DEFAULT 'EUR',\n \"balance\" DOUBLE PRECISION,\n \"source\" \"Source\" NOT NULL DEFAULT 'INGEST',\n \"status\" \"Status\" NOT NULL DEFAULT 'UNPROCESSED',\n \"notified_at\" TIMESTAMP(3),\n \"notify_phone\" TEXT,\n \"debit_bgn\" DOUBLE PRECISION,\n \"credit_bgn\" DOUBLE PRECISION,\n \"transaction_type\" TEXT,\n \"payer_account\" TEXT,\n \"created_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,\n \"updated_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP\n);\n\n-- CreateTable\nCREATE TABLE \"tags\" (\n \"id\" SERIAL PRIMARY KEY,\n \"name\" TEXT NOT NULL,\n \"color\" TEXT NOT NULL DEFAULT '#6b7280'\n);\n\n-- CreateUniqueIndex\nCREATE UNIQUE INDEX \"tags_name_key\" ON \"tags\"(\"name\");\n\n-- CreateTable (M2M join)\nCREATE TABLE \"_PaymentToTag\" (\n \"A\" INTEGER NOT NULL,\n \"B\" INTEGER NOT NULL,\n CONSTRAINT \"_PaymentToTag_AB_pkey\" PRIMARY KEY (\"A\", \"B\")\n);\n\nCREATE INDEX \"_PaymentToTag_B_index\" ON \"_PaymentToTag\"(\"B\");\n\n-- AddForeignKey\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_A_fkey\"\n FOREIGN KEY (\"A\") REFERENCES \"payments\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;\n\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_B_fkey\"\n FOREIGN KEY (\"B\") REFERENCES \"tags\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration_lock.toml","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration_lock.toml","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"4 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Please do not edit this file manually\n# It should be added in your version-control system (e.g., Git)\nprovider = \"postgresql\"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"26 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"{\n \"name\": \"finance-hub-backend\",\n \"version\": \"1.0.0\",\n \"main\": \"src/index.js\",\n \"scripts\": {\n \"start\": \"node src/index.js\",\n \"dev\": \"nodemon src/index.js\",\n \"prisma:generate\": \"prisma generate\",\n \"prisma:migrate\": \"prisma migrate deploy\"\n },\n \"dependencies\": {\n \"@prisma/client\": \"^5.22.0\",\n \"cors\": \"^2.8.5\",\n \"csv-parse\": \"^5.5.6\",\n \"express\": \"^4.21.1\",\n \"express-rate-limit\": \"^7.4.0\",\n \"iconv-lite\": \"^0.6.3\",\n \"morgan\": \"^1.10.0\",\n \"multer\": \"^1.4.5-lts.1\"\n },\n \"devDependencies\": {\n \"nodemon\": \"^3.1.7\",\n \"prisma\": \"^5.22.0\"\n }\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"18 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"FROM node:20-alpine\n\nRUN apk add --no-cache openssl\n\nWORKDIR /app\n\nCOPY package.json package-lock.json* ./\nRUN npm install\n\nCOPY prisma ./prisma\nRUN npx prisma generate\n\nCOPY src ./src\n\nEXPOSE 3001\n\nCMD [\"sh\", \"-c\", \"npx prisma migrate deploy && node src/index.js\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"auth.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"auth.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"27 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const PUBLIC_PATHS = new Set([\n '/api/health',\n '/api/payments/ingest',\n]);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n\n const username = req.headers['x-authentik-username'];\n if (!username) {\n return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });\n }\n\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '')\n .split(',')\n .map(g => g.trim())\n .filter(Boolean),\n };\n\n next();\n}\n\nmodule.exports = { authentikMiddleware };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"104 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/**\n * Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)\n *\n * Supported formats:\n *\n * POS / INTERNET / ECOM / P2P payment:\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.\n *\n * ATM withdrawal:\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.\n *\n * ATM utility payment (amount may include fee as AMOUNT/FEE):\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.\n */\n\nconst LOCAL_TZ = process.env.TZ || 'Europe/Sofia';\n\n/**\n * Convert a local-timezone date/time to a UTC Date object.\n * Uses Intl to resolve the actual UTC offset (DST-aware).\n */\nfunction localToUtc(year, month, day, hour, minute) {\n const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));\n\n const formatter = new Intl.DateTimeFormat('en-US', {\n timeZone: LOCAL_TZ,\n year: 'numeric', month: '2-digit', day: '2-digit',\n hour: '2-digit', minute: '2-digit', second: '2-digit',\n hour12: false,\n });\n\n const parts = {};\n formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });\n\n const localAtNaive = new Date(Date.UTC(\n parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),\n parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),\n ));\n\n const offsetMs = localAtNaive.getTime() - naive.getTime();\n return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);\n}\n\nfunction parsePaymentSms(message) {\n const result = {\n rawMessage: message,\n date: null,\n type: null,\n card: null,\n recipient: null,\n amount: null,\n balance: null,\n };\n\n // Date and time: \"Na DD/MM/YYYY v HH:MM\"\n const dateMatch = message.match(/Na (\\d{2})\\/(\\d{2})\\/(\\d{4}) v (\\d{2}):(\\d{2})/i);\n if (dateMatch) {\n const [, day, month, year, hour, minute] = dateMatch;\n result.date = localToUtc(\n parseInt(year), parseInt(month), parseInt(day),\n parseInt(hour), parseInt(minute),\n );\n }\n\n // Card mask: \"s karta 400915***4447\" or \"s karta 483890***7162\"\n const cardMatch = message.match(/s karta\\s+([\\d*]+)/i);\n if (cardMatch) {\n result.card = cardMatch[1];\n }\n\n // Transaction type: supports both prepositions\n // \"na POS\" / \"na ATM\" / \"na INTERNET\" etc. (payment)\n // \"ot ATM\" (withdrawal)\n const typeMatch = message.match(/(?:na|ot)\\s+(POS|ATM|INTERNET|ECOM|P2P)\\b/i);\n if (typeMatch) {\n result.type = typeMatch[1].toUpperCase();\n }\n\n // Recipient address: \"s adres: MERCHANT\" or \"s adres:MERCHANT\" (no space variant)\n const recipientMatch = message.match(/s adres:\\s*([^.]+)\\./i);\n if (recipientMatch) {\n result.recipient = recipientMatch[1].trim();\n }\n\n // Amount: handles both verbs and the AMOUNT/FEE suffix format\n // \"sa plateni 7.78 EUR\"\n // \"sa iztegleni 400.00 EUR\"\n // \"sa plateni 0.50 EUR/0.50 EUR\" → captures 0.50 (the charged amount, ignoring fee)\n const amountMatch = message.match(/sa (?:plateni|iztegleni)\\s+([\\d.,]+)\\s+[A-Z]{3}/i);\n if (amountMatch) {\n result.amount = parseFloat(amountMatch[1].replace(',', '.'));\n }\n\n // Balance: \"Nalichni: 2583.07 EUR.\"\n const balanceMatch = message.match(/Nalichni:\\s*([\\d.,]+)\\s+[A-Z]{3}/i);\n if (balanceMatch) {\n result.balance = parseFloat(balanceMatch[1].replace(',', '.'));\n }\n\n return result;\n}\n\nmodule.exports = { parsePaymentSms };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"csvParser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"csvParser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"175 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/**\n * DSK Bank CSV parser — Node.js port of dskuploader.py\n *\n * DSK Bank exports use Windows-1251 (cp1251) encoding.\n * Each row maps to a Payment record with source=UPLOAD, currency=BGN.\n */\n\nconst { parse } = require('csv-parse');\nconst iconv = require('iconv-lite');\n\nconst SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';\nconst CARD_REGEX = /^\\d{6}x{6}\\d{4}$/;\nconst POS_REGEX = /^\\s*ПЛАЩАНЕ\\s+НА\\s+ПОС\\s+\\d{2}\\.\\d{2}\\.\\d{4}\\s+\\d{2}:\\d{2}/;\n\nconst COL = {\n DATE: 'Дата',\n TYPE: 'Вид на трансакцията',\n REASON: 'Основание',\n DEBIT: 'Дебит BGN',\n CREDIT: 'Кредит BGN',\n PAYEE: 'Наредител/Получател',\n ACCT: 'Номер сметка на наредителя / получателя',\n};\n\nconst TAG_RULES = [\n ['reason', 'ЗАПЛАТА', 'Salary'],\n ['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],\n ['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],\n ['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],\n ['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],\n ['payee', 'VIVACOM', 'Subscriptions'],\n ['payee', 'Google', 'Subscriptions'],\n ['payee', 'SkyShowtime', 'Subscriptions'],\n ['payee', 'NETFLIX', 'Subscriptions'],\n ['payee', 'LUKOIL', 'Bills'],\n ['payee', 'CityGate', 'Bills'],\n ['payee', 'CBA', 'Groceries'],\n ['payee', 'FANTASTICO', 'Groceries'],\n ['payee', 'LIDL', 'Groceries'],\n];\n\nfunction parseNum(val) {\n if (val == null || val === '') return null;\n if (typeof val === 'number') return isNaN(val) ? null : val;\n const s = String(val).trim().replace(/\\xa0/g, '').replace(/ /g, '').replace(',', '.');\n const n = parseFloat(s);\n return isNaN(n) ? null : n;\n}\n\nfunction parseDate(val) {\n if (!val) return null;\n const s = String(val).trim();\n const m = s.match(/^(\\d{2})\\.(\\d{2})\\.(\\d{4})$/);\n if (m) {\n return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));\n }\n return null;\n}\n\nfunction processReasonAndCard(reason) {\n if (!reason || typeof reason !== 'string') return { reason: '', card: null };\n\n const parts = reason.trim().split(' ');\n let card = null;\n let cleanReason = reason.trim();\n\n if (parts[0] && CARD_REGEX.test(parts[0])) {\n card = parts[0];\n cleanReason = parts.slice(1).join(' ').trim();\n }\n\n if (POS_REGEX.test(cleanReason)) {\n const posParts = cleanReason.split('<br/>');\n try {\n const dateTime = posParts[0].split('ПОС ')[1];\n cleanReason = `POS PAYMENT ${dateTime}`;\n } catch (_) { /* keep original */ }\n }\n\n return { reason: cleanReason.replace(/\\s+/g, ' ').trim(), card };\n}\n\nfunction generateTags(fields) {\n const tags = new Set();\n for (const [field, keyword, tagName] of TAG_RULES) {\n if ((fields[field] || '').includes(keyword)) {\n tags.add(tagName);\n }\n }\n return Array.from(tags);\n}\n\nfunction processRow(row) {\n const transactionType = (row[COL.TYPE] || '').trim();\n if (transactionType === SKIP_TYPE) return null;\n\n const { reason, card } = processReasonAndCard(row[COL.REASON]);\n const payee = (row[COL.PAYEE] || '').trim();\n const payerAccount = (row[COL.ACCT] || '').trim();\n const debitBgn = parseNum(row[COL.DEBIT]);\n const creditBgn = parseNum(row[COL.CREDIT]);\n const date = parseDate(row[COL.DATE]);\n\n const autoTags = generateTags({ reason, transactionType, payee, debitBgn, creditBgn });\n\n const amount = debitBgn ?? creditBgn ?? null;\n\n const rawMessage = [\n row[COL.DATE] && `Date: ${row[COL.DATE]}`,\n transactionType && `Type: ${transactionType}`,\n payee && `Payee: ${payee}`,\n debitBgn != null && `Debit: ${debitBgn} BGN`,\n creditBgn != null && `Credit: ${creditBgn} BGN`,\n ].filter(Boolean).join(' | ');\n\n return {\n rawMessage,\n date,\n type: null,\n card,\n recipient: payee || null,\n amount,\n currency: 'BGN',\n balance: null,\n source: 'UPLOAD',\n debitBgn,\n creditBgn,\n transactionType: transactionType || null,\n payerAccount: payerAccount || null,\n autoTags,\n };\n}\n\n/**\n * Parse a Buffer containing a DSK Bank CSV (cp1251 or UTF-8).\n * Returns { rows, skipped, errors }.\n */\nasync function parseDskCsv(buffer) {\n // Try cp1251 first (DSK Bank export encoding), fall back to UTF-8\n let text = iconv.decode(buffer, 'cp1251');\n if (!text.includes(COL.DATE)) {\n text = buffer.toString('utf-8');\n }\n\n return new Promise((resolve, reject) => {\n const rows = [];\n const errors = [];\n let skipped = 0;\n\n const parser = parse(text, {\n columns: true,\n skip_empty_lines: true,\n trim: true,\n relax_column_count: true,\n });\n\n parser.on('readable', () => {\n let record;\n while ((record = parser.read()) !== null) {\n try {\n const row = processRow(record);\n if (row === null) { skipped++; } else { rows.push(row); }\n } catch (err) {\n errors.push(err.message);\n }\n }\n });\n\n parser.on('error', reject);\n parser.on('end', () => resolve({ rows, skipped, errors }));\n });\n}\n\nmodule.exports = { parseDskCsv };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"39 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst cors = require('cors');\nconst morgan = require('morgan');\nconst rateLimit = require('express-rate-limit');\nconst { authentikMiddleware } = require('./auth');\nconst paymentsRouter = require('./routes/payments');\nconst uploadRouter = require('./routes/upload');\n\nconst app = express();\nconst PORT = process.env.PORT || 3001;\n\napp.use(cors());\napp.use(express.json({ limit: '16kb' }));\napp.use(morgan('combined'));\n\n// Rate-limit the public ingest endpoint before auth middleware\nconst ingestLimiter = rateLimit({\n windowMs: 60 * 1000,\n max: 200,\n standardHeaders: true,\n legacyHeaders: false,\n message: { error: 'Too many requests, slow down' },\n});\napp.use('/api/payments/ingest', ingestLimiter);\n\n// Authentik header auth (skips /api/health and /api/payments/ingest)\napp.use(authentikMiddleware);\n\napp.get('/api/health', (_req, res) => {\n res.json({ status: 'ok', timestamp: new Date().toISOString() });\n});\n\napp.use('/api/payments', paymentsRouter);\napp.use('/api/upload', uploadRouter);\n\napp.listen(PORT, '0.0.0.0', () => {\n console.log(`Finance Hub API running on port ${PORT}`);\n});","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"payments.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"399 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst { PrismaClient } = require('@prisma/client');\nconst { parsePaymentSms } = require('../parser');\n\nconst router = express.Router();\nconst prisma = new PrismaClient();\n\nconst NOTIFIER_URL = process.env.NOTIFIER_URL;\nconst NOTIFIER_CHANNEL = process.env.NOTIFIER_CHANNEL || 'viber';\nconst DEFAULT_PHONE = process.env.NOTIFY_DEFAULT_PHONE;\n\n// ── Helpers ───────────────────────────────────────────────────────────────────\n\nfunction parseId(raw) {\n const id = parseInt(raw, 10);\n return Number.isFinite(id) ? id : null;\n}\n\nfunction formatNotifyMessage(payment) {\n const currency = payment.currency || 'EUR';\n const parts = [];\n if (payment.amount != null) parts.push(`Amount: ${payment.amount.toFixed(2)} ${currency}`);\n if (payment.recipient) parts.push(`At: ${payment.recipient}`);\n if (payment.balance != null) parts.push(`Balance: ${payment.balance.toFixed(2)} ${currency}`);\n if (payment.date) parts.push(`Date: ${new Date(payment.date).toLocaleString('en-GB')}`);\n return parts.join('\\n');\n}\n\nasync function sendNotification(payment) {\n if (!NOTIFIER_URL) {\n console.warn('[NOTIFY] NOTIFIER_URL not set — skipping notification');\n return;\n }\n\n const phone = payment.notifyPhone || DEFAULT_PHONE;\n if (!phone) {\n console.warn('[NOTIFY] No phone number for payment #' + payment.id + ' and NOTIFY_DEFAULT_PHONE not set');\n return;\n }\n\n const body = {\n phone,\n notification: NOTIFIER_CHANNEL,\n message: formatNotifyMessage(payment),\n };\n\n const res = await fetch(NOTIFIER_URL, {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify(body),\n });\n\n if (!res.ok) {\n const text = await res.text().catch(() => '');\n throw new Error(`Notifier responded ${res.status}: ${text}`);\n }\n}\n\n// ── Ingest a payment (public — no auth) ──────────────────────────────────────\n//\n// Two modes:\n//\n// SMS mode (default):\n// { \"message\": \"<raw SMS text>\", \"notifyPhone\": \"...\" }\n//\n// Structured mode (Apple Wallet / manual):\n// { \"ingestMode\": \"apple_wallet\", \"amount\": 7.78, \"recipient\": \"Apple Store\",\n// \"type\": \"WALLET\", \"card\": \"••••4447\", \"date\": \"2026-02-22T10:30:00Z\" }\n//\nrouter.post('/ingest', async (req, res) => {\n try {\n const { message, notifyPhone, ingestMode } = req.body;\n\n let data;\n\n if (ingestMode === 'apple_wallet' || (!message && req.body.amount != null)) {\n // ── Structured / Apple Wallet mode ──────────────────────────────────────\n const { amount, recipient, type, card, date, balance } = req.body;\n if (amount == null || !recipient) {\n return res.status(400).json({ error: 'amount and recipient are required for structured ingest' });\n }\n\n const rawMessage = [\n `Source: ${ingestMode || 'structured'}`,\n `Amount: ${amount}`,\n recipient && `Recipient: ${recipient}`,\n type && `Type: ${type}`,\n card && `Card: ${card}`,\n ].filter(Boolean).join(' | ');\n\n data = {\n rawMessage,\n date: date ? new Date(date) : new Date(),\n type: type || 'WALLET',\n card: card || null,\n recipient,\n amount: parseFloat(amount),\n currency: 'EUR',\n balance: balance != null ? parseFloat(balance) : null,\n source: 'INGEST',\n notifyPhone: notifyPhone || null,\n };\n\n } else {\n // ── SMS mode ─────────────────────────────────────────────────────────────\n if (!message) {\n return res.status(400).json({ error: 'message is required' });\n }\n if (typeof message !== 'string' || message.length > 2000) {\n return res.status(400).json({ error: 'message must be a string under 2000 characters' });\n }\n\n const parsed = parsePaymentSms(message);\n data = {\n rawMessage: parsed.rawMessage,\n date: parsed.date,\n type: parsed.type,\n card: parsed.card,\n recipient: parsed.recipient,\n amount: parsed.amount,\n currency: 'EUR',\n balance: parsed.balance,\n source: 'INGEST',\n notifyPhone: notifyPhone || null,\n };\n }\n\n const payment = await prisma.payment.create({\n data,\n include: { tags: true },\n });\n\n res.status(201).json(payment);\n } catch (err) {\n console.error('Ingest error:', err);\n res.status(500).json({ error: 'Failed to ingest payment' });\n }\n});\n\n// ── List payments with filtering ──────────────────────────────────────────────\nrouter.get('/', async (req, res) => {\n try {\n const {\n status,\n type,\n tag,\n source,\n recipient,\n dateFrom,\n dateTo,\n search,\n sortBy = 'createdAt',\n sortDir = 'desc',\n page = 1,\n } = req.query;\n\n const limit = Math.min(parseInt(req.query.limit, 10) || 50, 200);\n\n const where = {};\n\n if (status) where.status = status;\n if (type) where.type = type;\n if (source) where.source = source;\n if (recipient) where.recipient = { contains: recipient, mode: 'insensitive' };\n if (tag) where.tags = { some: { name: tag } };\n if (search) {\n where.OR = [\n { rawMessage: { contains: search, mode: 'insensitive' } },\n { recipient: { contains: search, mode: 'insensitive' } },\n ];\n }\n if (dateFrom || dateTo) {\n where.date = {};\n if (dateFrom) where.date.gte = new Date(dateFrom);\n if (dateTo) where.date.lte = new Date(dateTo);\n }\n\n const allowedSortFields = ['date', 'amount', 'balance', 'recipient', 'type', 'source', 'createdAt', 'status'];\n const orderField = allowedSortFields.includes(sortBy) ? sortBy : 'createdAt';\n const orderDir = sortDir === 'asc' ? 'asc' : 'desc';\n\n const skip = (parseInt(page, 10) - 1) * limit;\n\n const [payments, total] = await Promise.all([\n prisma.payment.findMany({\n where,\n include: { tags: true },\n orderBy: { [orderField]: orderDir },\n skip,\n take: limit,\n }),\n prisma.payment.count({ where }),\n ]);\n\n res.json({ payments, total, page: parseInt(page, 10), limit });\n } catch (err) {\n console.error('List error:', err);\n res.status(500).json({ error: 'Failed to list payments' });\n }\n});\n\n// ── Get filter options ────────────────────────────────────────────────────────\nrouter.get('/meta/filters', async (_req, res) => {\n try {\n const [types, recipients, tags, sources] = await Promise.all([\n prisma.payment.findMany({ distinct: ['type'], select: { type: true }, where: { type: { not: null } } }),\n prisma.payment.findMany({ distinct: ['recipient'], select: { recipient: true }, where: { recipient: { not: null } } }),\n prisma.tag.findMany({ orderBy: { name: 'asc' } }),\n prisma.payment.findMany({ distinct: ['source'], select: { source: true } }),\n ]);\n\n res.json({\n types: types.map(t => t.type),\n recipients: recipients.map(r => r.recipient),\n tags,\n sources: sources.map(s => s.source),\n });\n } catch (err) {\n res.status(500).json({ error: 'Failed to get filters' });\n }\n});\n\n// ── Get all tags ──────────────────────────────────────────────────────────────\nrouter.get('/meta/tags', async (_req, res) => {\n try {\n const tags = await prisma.tag.findMany({ orderBy: { name: 'asc' } });\n res.json(tags);\n } catch (err) {\n res.status(500).json({ error: 'Failed to list tags' });\n }\n});\n\n// ── Get single payment ────────────────────────────────────────────────────────\nrouter.get('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({\n where: { id },\n include: { tags: true },\n });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n res.json(payment);\n } catch (err) {\n console.error('Get error:', err);\n res.status(500).json({ error: 'Failed to get payment' });\n }\n});\n\n// ── Update payment metadata (status) ─────────────────────────────────────────\nrouter.patch('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const { status } = req.body;\n const data = {};\n\n if (status) {\n const validStatuses = ['UNPROCESSED', 'SENT', 'SKIPPED'];\n if (!validStatuses.includes(status)) {\n return res.status(400).json({ error: `Invalid status. Must be one of: ${validStatuses.join(', ')}` });\n }\n data.status = status;\n }\n\n if (Object.keys(data).length === 0) {\n return res.status(400).json({ error: 'No valid fields to update' });\n }\n\n const updated = await prisma.payment.update({\n where: { id },\n data,\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n if (err.code === 'P2025') return res.status(404).json({ error: 'Not found' });\n console.error('Update error:', err);\n res.status(500).json({ error: 'Failed to update payment' });\n }\n});\n\n// ── Delete payment ───────────────────────────────────────────────────────────\nrouter.delete('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n await prisma.payment.delete({ where: { id } });\n res.json({ success: true });\n } catch (err) {\n if (err.code === 'P2025') return res.status(404).json({ error: 'Not found' });\n console.error('Delete error:', err);\n res.status(500).json({ error: 'Failed to delete payment' });\n }\n});\n\n// ── Send notification (mark as SENT + call notifier service) ─────────────────\nrouter.post('/:id/send', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({ where: { id } });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n if (payment.status !== 'UNPROCESSED') {\n return res.status(409).json({ error: `Payment is already ${payment.status.toLowerCase()}` });\n }\n\n await sendNotification(payment);\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { status: 'SENT', notifiedAt: new Date() },\n include: { tags: true },\n });\n\n res.json(updated);\n } catch (err) {\n console.error('Send error:', err);\n res.status(500).json({ error: 'Failed to send notification' });\n }\n});\n\n// ── Skip notification (mark as SKIPPED) ──────────────────────────────────────\nrouter.post('/:id/skip', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({ where: { id } });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n if (payment.status !== 'UNPROCESSED') {\n return res.status(409).json({ error: `Payment is already ${payment.status.toLowerCase()}` });\n }\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { status: 'SKIPPED' },\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n console.error('Skip error:', err);\n res.status(500).json({ error: 'Failed to skip payment' });\n }\n});\n\n// ── Add tag to payment ────────────────────────────────────────────────────────\nrouter.post('/:id/tags', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const { name, color } = req.body;\n if (!name) return res.status(400).json({ error: 'tag name is required' });\n\n const tag = await prisma.tag.upsert({\n where: { name },\n update: {},\n create: { name, color: color || '#6b7280' },\n });\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { tags: { connect: { id: tag.id } } },\n include: { tags: true },\n });\n\n res.json(updated);\n } catch (err) {\n console.error('Tag error:', err);\n res.status(500).json({ error: 'Failed to add tag' });\n }\n});\n\n// ── Remove tag from payment ───────────────────────────────────────────────────\nrouter.delete('/:id/tags/:tagId', async (req, res) => {\n const id = parseId(req.params.id);\n const tagId = parseId(req.params.tagId);\n if (id === null || tagId === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const updated = await prisma.payment.update({\n where: { id },\n data: { tags: { disconnect: { id: tagId } } },\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n console.error('Remove tag error:', err);\n res.status(500).json({ error: 'Failed to remove tag' });\n }\n});\n\nmodule.exports = router;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"upload.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"upload.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"89 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst multer = require('multer');\nconst { PrismaClient } = require('@prisma/client');\nconst { parseDskCsv } = require('../csvParser');\n\nconst router = express.Router();\nconst prisma = new PrismaClient();\n\nconst upload = multer({\n storage: multer.memoryStorage(),\n limits: { fileSize: 10 * 1024 * 1024, files: 10 },\n fileFilter: (_req, file, cb) => {\n if (file.mimetype === 'text/csv' || file.originalname.toLowerCase().endsWith('.csv')) {\n cb(null, true);\n } else {\n cb(new Error('Only CSV files are accepted'));\n }\n },\n});\n\n// POST /api/upload/csv\n// Accepts 1-10 CSV files, parses them, stores to DB with source=UPLOAD.\n// Returns { imported, skipped, errors, payments[] }\nrouter.post('/csv', upload.array('files', 10), async (req, res) => {\n if (!req.files || req.files.length === 0) {\n return res.status(400).json({ error: 'No files uploaded' });\n }\n\n const allRows = [];\n const allErrors = [];\n let totalSkipped = 0;\n\n for (const file of req.files) {\n try {\n const { rows, skipped, errors } = await parseDskCsv(file.buffer);\n allRows.push(...rows);\n totalSkipped += skipped;\n allErrors.push(...errors.map(e => `${file.originalname}: ${e}`));\n } catch (err) {\n allErrors.push(`${file.originalname}: ${err.message}`);\n }\n }\n\n if (allRows.length === 0) {\n return res.status(422).json({\n error: 'No importable rows found',\n skipped: totalSkipped,\n errors: allErrors,\n });\n }\n\n const created = [];\n\n for (const row of allRows) {\n const { autoTags, ...paymentData } = row;\n try {\n const tagConnects = [];\n for (const tagName of autoTags) {\n const tag = await prisma.tag.upsert({\n where: { name: tagName },\n update: {},\n create: { name: tagName, color: '#6b7280' },\n });\n tagConnects.push({ id: tag.id });\n }\n\n const payment = await prisma.payment.create({\n data: {\n ...paymentData,\n ...(tagConnects.length ? { tags: { connect: tagConnects } } : {}),\n },\n include: { tags: true },\n });\n created.push(payment);\n } catch (err) {\n allErrors.push(`Row insert failed: ${err.message}`);\n }\n }\n\n res.status(201).json({\n imported: created.length,\n skipped: totalSkipped,\n errors: allErrors,\n payments: created,\n });\n});\n\nmodule.exports = router;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now writing all frontend config files:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"24 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"{\n \"name\": \"finance-hub-frontend\",\n \"version\": \"1.0.0\",\n \"type\": \"module\",\n \"scripts\": {\n \"dev\": \"vite\",\n \"build\": \"vite build\",\n \"preview\": \"vite preview\"\n },\n \"dependencies\": {\n \"lucide-react\": \"^0.460.0\",\n \"react\": \"^18.3.1\",\n \"react-dom\": \"^18.3.1\"\n },\n \"devDependencies\": {\n \"@types/react\": \"^18.3.12\",\n \"@vitejs/plugin-react\": \"^4.3.4\",\n \"autoprefixer\": \"^10.4.20\",\n \"postcss\": \"^8.4.49\",\n \"tailwindcss\": \"^3.4.15\",\n \"vite\": \"^6.0.1\"\n }\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"FROM node:20-alpine\n\nWORKDIR /app\n\nCOPY package.json package-lock.json* ./\nRUN npm install\n\nCOPY . .\n\nEXPOSE 5173\n\nCMD [\"npm\", \"run\", \"dev\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"vite.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"vite.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"18 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import { defineConfig } from 'vite';\nimport react from '@vitejs/plugin-react';\n\nexport default defineConfig({\n plugins: [react()],\n server: {\n host: '0.0.0.0',\n port: 5173,\n allowedHosts: ['finance-hub.lakylak.xyz'],\n proxy: {\n '/api': {\n target: 'http://backend:3001',\n changeOrigin: true,\n },\n },\n },\n});","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"tailwind.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"tailwind.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"12 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/** @type {import('tailwindcss').Config} */\nexport default {\n content: [\n \"./index.html\",\n \"./src/**/*.{js,ts,jsx,tsx}\",\n ],\n theme: {\n extend: {},\n },\n plugins: [],\n};","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"postcss.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"postcss.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"7 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"export default {\n plugins: {\n tailwindcss: {},\n autoprefixer: {},\n },\n};","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.html","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.html","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"14 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"<!DOCTYPE html>\n<html lang=\"en\">\n <head>\n <meta charset=\"UTF-8\" />\n <meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\" />\n <title>Finance Hub</title>\n <link rel=\"icon\" type=\"image/svg+xml\" href=\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 100 100'><text y='.9em' font-size='90'>💰</text></svg>\" />\n </head>\n <body class=\"bg-gray-50 min-h-screen\">\n <div id=\"root\"></div>\n <script type=\"module\" src=\"/src/main.jsx\"></script>\n </body>\n</html>","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.css","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.css","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"4 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"@tailwind base;\n@tailwind components;\n@tailwind utilities;","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now writing all React components:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"11 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React from 'react';\nimport ReactDOM from 'react-dom/client';\nimport App from './App';\nimport './index.css';\n\nReactDOM.createRoot(document.getElementById('root')).render(\n <React.StrictMode>\n <App />\n </React.StrictMode>\n);","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"App.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"App.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"257 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState, useEffect, useCallback } from 'react';\nimport { LayoutDashboard, Upload, RefreshCw, LogOut } from 'lucide-react';\nimport FilterBar from './components/FilterBar';\nimport PaymentTable from './components/PaymentTable';\nimport UploadPanel from './components/UploadPanel';\n\nconst API_BASE = '/api/payments';\n\nexport default function App() {\n const [activeTab, setActiveTab] = useState('payments');\n const [payments, setPayments] = useState([]);\n const [total, setTotal] = useState(0);\n const [page, setPage] = useState(1);\n const [filters, setFilters] = useState({});\n const [sortBy, setSortBy] = useState('createdAt');\n const [sortDir, setSortDir] = useState('desc');\n const [filterOptions, setFilterOptions] = useState({ types: [], recipients: [], tags: [], sources: [] });\n const [loading, setLoading] = useState(false);\n\n const fetchPayments = useCallback(async () => {\n setLoading(true);\n try {\n const params = new URLSearchParams();\n params.set('page', page);\n params.set('limit', 50);\n params.set('sortBy', sortBy);\n params.set('sortDir', sortDir);\n Object.entries(filters).forEach(([key, val]) => {\n if (val) params.set(key, val);\n });\n const res = await fetch(`${API_BASE}?${params}`);\n const data = await res.json();\n setPayments(data.payments || []);\n setTotal(data.total || 0);\n } catch (err) {\n console.error('Failed to fetch payments:', err);\n } finally {\n setLoading(false);\n }\n }, [page, filters, sortBy, sortDir]);\n\n const fetchFilterOptions = useCallback(async () => {\n try {\n const res = await fetch(`${API_BASE}/meta/filters`);\n const data = await res.json();\n setFilterOptions(data);\n } catch (err) {\n console.error('Failed to fetch filter options:', err);\n }\n }, []);\n\n useEffect(() => {\n fetchPayments();\n }, [fetchPayments]);\n\n useEffect(() => {\n fetchFilterOptions();\n }, [fetchFilterOptions]);\n\n // Refresh payments list after a successful CSV upload\n const handleUploadSuccess = () => {\n fetchPayments();\n fetchFilterOptions();\n setActiveTab('payments');\n };\n\n const handleAction = async (id, action) => {\n try {\n await fetch(`${API_BASE}/${id}/${action}`, { method: 'POST' });\n fetchPayments();\n fetchFilterOptions();\n } catch (err) {\n console.error(`Failed to ${action} payment:`, err);\n }\n };\n\n const handleAddTag = async (id, tagName, tagColor) => {\n try {\n await fetch(`${API_BASE}/${id}/tags`, {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify({ name: tagName, color: tagColor }),\n });\n fetchPayments();\n fetchFilterOptions();\n } catch (err) {\n console.error('Failed to add tag:', err);\n }\n };\n\n const handleRemoveTag = async (paymentId, tagId) => {\n try {\n await fetch(`${API_BASE}/${paymentId}/tags/${tagId}`, { method: 'DELETE' });\n fetchPayments();\n } catch (err) {\n console.error('Failed to remove tag:', err);\n }\n };\n\n const handleDelete = async (id) => {\n try {\n await fetch(`${API_BASE}/${id}`, { method: 'DELETE' });\n fetchPayments();\n fetchFilterOptions();\n } catch (err) {\n console.error('Failed to delete payment:', err);\n }\n };\n\n const handleUpdateStatus = async (id, status) => {\n try {\n await fetch(`${API_BASE}/${id}`, {\n method: 'PATCH',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify({ status }),\n });\n fetchPayments();\n } catch (err) {\n console.error('Failed to update status:', err);\n }\n };\n\n const handleFilterChange = (newFilters) => {\n setFilters(newFilters);\n setPage(1);\n };\n\n const handleSort = (field) => {\n if (sortBy === field) {\n setSortDir(d => d === 'asc' ? 'desc' : 'asc');\n } else {\n setSortBy(field);\n setSortDir('desc');\n }\n setPage(1);\n };\n\n const totalPages = Math.ceil(total / 50);\n\n return (\n <div className=\"min-h-screen bg-gray-50\">\n <header className=\"bg-white border-b border-gray-200 shadow-sm\">\n <div className=\"max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-4\">\n <div className=\"flex items-center justify-between\">\n <div className=\"flex items-center gap-3\">\n <div className=\"bg-indigo-600 p-2 rounded-lg\">\n <LayoutDashboard className=\"w-6 h-6 text-white\" />\n </div>\n <div>\n <h1 className=\"text-xl font-bold text-gray-900\">Finance Hub</h1>\n <p className=\"text-sm text-gray-500\">{total} transaction{total !== 1 ? 's' : ''} total</p>\n </div>\n </div>\n\n <div className=\"flex items-center gap-2\">\n {/* Tab switcher */}\n <div className=\"flex items-center rounded-lg border border-gray-200 bg-gray-50 p-1 gap-1\">\n <button\n onClick={() => setActiveTab('payments')}\n className={`flex items-center gap-1.5 px-3 py-1.5 text-sm font-medium rounded-md transition-colors ${\n activeTab === 'payments'\n ? 'bg-white text-indigo-700 shadow-sm'\n : 'text-gray-600 hover:text-gray-900'\n }`}\n >\n <LayoutDashboard className=\"w-4 h-4\" />\n Payments\n </button>\n <button\n onClick={() => setActiveTab('upload')}\n className={`flex items-center gap-1.5 px-3 py-1.5 text-sm font-medium rounded-md transition-colors ${\n activeTab === 'upload'\n ? 'bg-white text-emerald-700 shadow-sm'\n : 'text-gray-600 hover:text-gray-900'\n }`}\n >\n <Upload className=\"w-4 h-4\" />\n Upload CSV\n </button>\n </div>\n\n {activeTab === 'payments' && (\n <button\n onClick={() => { fetchPayments(); fetchFilterOptions(); }}\n className=\"flex items-center gap-2 px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 transition-colors\"\n >\n <RefreshCw className={`w-4 h-4 ${loading ? 'animate-spin' : ''}`} />\n Refresh\n </button>\n )}\n\n <button\n onClick={() => { window.location.href = '/outpost.goauthentik.io/sign_out'; }}\n className=\"flex items-center gap-2 px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 transition-colors\"\n title=\"Sign out\"\n >\n <LogOut className=\"w-4 h-4\" />\n </button>\n </div>\n </div>\n </div>\n </header>\n\n <main className=\"max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-6\">\n {activeTab === 'payments' ? (\n <>\n <FilterBar\n filters={filters}\n filterOptions={filterOptions}\n onFilterChange={handleFilterChange}\n />\n\n <PaymentTable\n payments={payments}\n loading={loading}\n sortBy={sortBy}\n sortDir={sortDir}\n onSort={handleSort}\n onSend={(id) => handleAction(id, 'send')}\n onSkip={(id) => handleAction(id, 'skip')}\n onAddTag={handleAddTag}\n onRemoveTag={handleRemoveTag}\n onDelete={handleDelete}\n onUpdateStatus={handleUpdateStatus}\n existingTags={filterOptions.tags}\n />\n\n {totalPages > 1 && (\n <div className=\"flex items-center justify-center gap-2 mt-6\">\n <button\n onClick={() => setPage(p => Math.max(1, p - 1))}\n disabled={page === 1}\n className=\"px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 disabled:opacity-50 disabled:cursor-not-allowed\"\n >\n Previous\n </button>\n <span className=\"text-sm text-gray-600\">\n Page {page} of {totalPages}\n </span>\n <button\n onClick={() => setPage(p => Math.min(totalPages, p + 1))}\n disabled={page === totalPages}\n className=\"px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 disabled:opacity-50 disabled:cursor-not-allowed\"\n >\n Next\n </button>\n </div>\n )}\n </>\n ) : (\n <UploadPanel onUploadSuccess={handleUploadSuccess} />\n )}\n </main>\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"FilterBar.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"FilterBar.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"167 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState, useEffect } from 'react';\nimport { Search, Filter, X, Calendar, ChevronDown, ChevronUp } from 'lucide-react';\n\nconst STATUS_OPTIONS = [\n { value: '', label: 'All Statuses' },\n { value: 'UNPROCESSED', label: 'Unprocessed' },\n { value: 'SENT', label: 'Sent' },\n { value: 'SKIPPED', label: 'Skipped' },\n];\n\nconst SOURCE_OPTIONS = [\n { value: '', label: 'All Sources' },\n { value: 'INGEST', label: 'SMS Ingest' },\n { value: 'UPLOAD', label: 'CSV Upload' },\n];\n\nexport default function FilterBar({ filters, filterOptions, onFilterChange }) {\n const [search, setSearch] = useState(filters.search || '');\n const [isOpen, setIsOpen] = useState(() => window.innerWidth >= 768);\n\n useEffect(() => {\n const mq = window.matchMedia('(min-width: 768px)');\n const handler = (e) => setIsOpen(e.matches);\n mq.addEventListener('change', handler);\n return () => mq.removeEventListener('change', handler);\n }, []);\n\n const handleSearchSubmit = (e) => {\n e.preventDefault();\n onFilterChange({ ...filters, search: search || undefined });\n };\n\n const handleSelectChange = (key, value) => {\n const newFilters = { ...filters };\n if (value) {\n newFilters[key] = value;\n } else {\n delete newFilters[key];\n }\n onFilterChange(newFilters);\n };\n\n const clearFilters = () => {\n setSearch('');\n onFilterChange({});\n };\n\n const activeFilterCount = Object.keys(filters).length;\n const hasActiveFilters = activeFilterCount > 0;\n\n return (\n <div className=\"bg-white rounded-xl border border-gray-200 shadow-sm p-4 mb-6\">\n <button\n onClick={() => setIsOpen(!isOpen)}\n className=\"w-full flex items-center gap-2\"\n >\n <Filter className=\"w-4 h-4 text-gray-500\" />\n <span className=\"text-sm font-medium text-gray-700\">Filters</span>\n {hasActiveFilters && (\n <span className=\"inline-flex items-center justify-center w-5 h-5 text-xs font-bold text-white bg-indigo-600 rounded-full\">\n {activeFilterCount}\n </span>\n )}\n {hasActiveFilters && (\n <span\n onClick={(e) => { e.stopPropagation(); clearFilters(); }}\n className=\"ml-1 flex items-center gap-1 text-xs text-red-600 hover:text-red-700\"\n >\n <X className=\"w-3 h-3\" />\n Clear\n </span>\n )}\n <span className=\"ml-auto\">\n {isOpen\n ? <ChevronUp className=\"w-4 h-4 text-gray-400\" />\n : <ChevronDown className=\"w-4 h-4 text-gray-400\" />\n }\n </span>\n </button>\n\n {isOpen && (\n <div className=\"space-y-3 mt-3 pt-3 border-t border-gray-100\">\n <div className=\"grid grid-cols-1 sm:grid-cols-2 lg:grid-cols-5 gap-3\">\n <form onSubmit={handleSearchSubmit} className=\"relative\">\n <Search className=\"absolute left-3 top-1/2 -translate-y-1/2 w-4 h-4 text-gray-400\" />\n <input\n type=\"text\"\n placeholder=\"Search...\"\n value={search}\n onChange={(e) => setSearch(e.target.value)}\n onBlur={() => onFilterChange({ ...filters, search: search || undefined })}\n className=\"w-full pl-9 pr-3 py-2 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none\"\n />\n </form>\n\n <select\n value={filters.source || ''}\n onChange={(e) => handleSelectChange('source', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n {SOURCE_OPTIONS.map(opt => (\n <option key={opt.value} value={opt.value}>{opt.label}</option>\n ))}\n </select>\n\n <select\n value={filters.status || ''}\n onChange={(e) => handleSelectChange('status', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n {STATUS_OPTIONS.map(opt => (\n <option key={opt.value} value={opt.value}>{opt.label}</option>\n ))}\n </select>\n\n <select\n value={filters.type || ''}\n onChange={(e) => handleSelectChange('type', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n <option value=\"\">All Types</option>\n {(filterOptions.types || []).map(t => (\n <option key={t} value={t}>{t}</option>\n ))}\n </select>\n\n <select\n value={filters.tag || ''}\n onChange={(e) => handleSelectChange('tag', e.target.value)}\n className=\"w-full py-2 px-3 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none bg-white\"\n >\n <option value=\"\">All Tags</option>\n {(filterOptions.tags || []).map(t => (\n <option key={t.id} value={t.name}>{t.name}</option>\n ))}\n </select>\n </div>\n\n <div className=\"grid grid-cols-1 sm:grid-cols-2 gap-3\">\n <div className=\"relative\">\n <Calendar className=\"absolute left-3 top-1/2 -translate-y-1/2 w-4 h-4 text-gray-400\" />\n <input\n type=\"date\"\n placeholder=\"From date\"\n value={filters.dateFrom || ''}\n onChange={(e) => handleSelectChange('dateFrom', e.target.value)}\n className=\"w-full pl-9 pr-3 py-2 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none\"\n />\n </div>\n\n <div className=\"relative\">\n <Calendar className=\"absolute left-3 top-1/2 -translate-y-1/2 w-4 h-4 text-gray-400\" />\n <input\n type=\"date\"\n placeholder=\"To date\"\n value={filters.dateTo || ''}\n onChange={(e) => handleSelectChange('dateTo', e.target.value)}\n className=\"w-full pl-9 pr-3 py-2 text-sm border border-gray-300 rounded-lg focus:ring-2 focus:ring-indigo-500 focus:border-indigo-500 outline-none\"\n />\n </div>\n </div>\n </div>\n )}\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentTable.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentTable.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"339 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState } from 'react';\nimport {\n ArrowUpDown, ArrowUp, ArrowDown,\n Send, XCircle, CheckCircle, MinusCircle, Clock,\n Inbox, Plus, X, ChevronDown, ChevronUp, Trash2,\n} from 'lucide-react';\n\nconst STATUS_CONFIG = {\n UNPROCESSED: { label: 'Unprocessed', icon: Clock, color: 'bg-amber-100 text-amber-700' },\n SENT: { label: 'Sent', icon: CheckCircle, color: 'bg-green-100 text-green-700' },\n SKIPPED: { label: 'Skipped', icon: MinusCircle, color: 'bg-gray-100 text-gray-500' },\n};\n\nconst TAG_COLORS = [\n '#ef4444', '#f97316', '#eab308', '#22c55e', '#06b6d4',\n '#3b82f6', '#8b5cf6', '#ec4899', '#6b7280',\n];\n\nconst COLUMNS = [\n { key: 'date', label: 'Date & Time', sortable: true },\n { key: 'source', label: 'Source', sortable: true },\n { key: 'type', label: 'Type', sortable: true },\n { key: 'recipient', label: 'Recipient', sortable: true },\n { key: 'amount', label: 'Amount', sortable: true },\n { key: 'balance', label: 'Balance', sortable: true },\n { key: 'status', label: 'Status', sortable: true },\n { key: 'tags', label: 'Tags', sortable: false },\n { key: 'actions', label: 'Actions', sortable: false },\n];\n\nfunction SortIcon({ column, sortBy, sortDir }) {\n if (sortBy !== column) return <ArrowUpDown className=\"w-3 h-3 text-gray-400\" />;\n return sortDir === 'asc'\n ? <ArrowUp className=\"w-3 h-3 text-indigo-600\" />\n : <ArrowDown className=\"w-3 h-3 text-indigo-600\" />;\n}\n\nfunction SourceBadge({ source }) {\n if (source === 'UPLOAD') {\n return (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-emerald-50 text-emerald-700\">\n CSV\n </span>\n );\n }\n return (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-indigo-50 text-indigo-700\">\n SMS\n </span>\n );\n}\n\nfunction TagCell({ payment, onAddTag, onRemoveTag, existingTags }) {\n const [open, setOpen] = useState(false);\n const [newTagName, setNewTagName] = useState('');\n const [newTagColor, setNewTagColor] = useState('#3b82f6');\n\n const paymentTags = payment.tags || [];\n const availableTags = existingTags.filter(t => !paymentTags.some(pt => pt.id === t.id));\n\n const handleAdd = (e) => {\n e.preventDefault();\n if (newTagName.trim()) {\n onAddTag(payment.id, newTagName.trim(), newTagColor);\n setNewTagName('');\n setOpen(false);\n }\n };\n\n return (\n <div className=\"flex flex-wrap items-center gap-1\">\n {paymentTags.map(tag => (\n <span\n key={tag.id}\n className=\"inline-flex items-center gap-0.5 px-1.5 py-0.5 text-xs font-medium rounded-full text-white\"\n style={{ backgroundColor: tag.color }}\n >\n {tag.name}\n <button onClick={() => onRemoveTag(payment.id, tag.id)} className=\"hover:opacity-75\">\n <X className=\"w-2.5 h-2.5\" />\n </button>\n </span>\n ))}\n <div className=\"relative\">\n <button\n onClick={() => setOpen(!open)}\n className=\"inline-flex items-center gap-0.5 px-1.5 py-0.5 text-xs text-gray-500 border border-dashed border-gray-300 rounded-full hover:border-gray-400\"\n >\n <Plus className=\"w-2.5 h-2.5\" />\n </button>\n {open && (\n <div className=\"absolute z-20 top-full left-0 mt-1 bg-white border border-gray-200 rounded-lg shadow-lg p-2 w-56\">\n <form onSubmit={handleAdd} className=\"flex items-center gap-1 mb-2\">\n <input\n type=\"text\"\n value={newTagName}\n onChange={(e) => setNewTagName(e.target.value)}\n placeholder=\"New tag\"\n autoFocus\n className=\"flex-1 px-2 py-1 text-xs border border-gray-300 rounded focus:ring-1 focus:ring-indigo-500 outline-none\"\n />\n <button type=\"submit\" className=\"text-xs text-indigo-600 font-medium hover:text-indigo-700 whitespace-nowrap\">Add</button>\n </form>\n <div className=\"flex gap-1 mb-2\">\n {TAG_COLORS.map(c => (\n <button\n key={c}\n type=\"button\"\n onClick={() => setNewTagColor(c)}\n className={`w-4 h-4 rounded-full border-2 ${newTagColor === c ? 'border-gray-800' : 'border-transparent'}`}\n style={{ backgroundColor: c }}\n />\n ))}\n </div>\n {availableTags.length > 0 && (\n <div className=\"border-t border-gray-100 pt-1 flex flex-wrap gap-1\">\n {availableTags.map(tag => (\n <button\n key={tag.id}\n onClick={() => { onAddTag(payment.id, tag.name, tag.color); setOpen(false); }}\n className=\"px-1.5 py-0.5 text-xs rounded-full border border-gray-200 text-gray-600 hover:bg-gray-100\"\n >\n {tag.name}\n </button>\n ))}\n </div>\n )}\n </div>\n )}\n </div>\n </div>\n );\n}\n\nfunction ExpandedRow({ payment }) {\n return (\n <tr className=\"bg-gray-50\">\n <td colSpan={COLUMNS.length} className=\"px-4 py-3\">\n <div className=\"text-xs text-gray-500 uppercase tracking-wide mb-1\">Original Message / Raw Data</div>\n <p className=\"text-sm text-gray-700 whitespace-pre-wrap break-words\">{payment.rawMessage}</p>\n {payment.debitBgn != null && (\n <p className=\"text-xs text-gray-500 mt-1\">Debit: {payment.debitBgn.toFixed(2)} BGN</p>\n )}\n {payment.creditBgn != null && (\n <p className=\"text-xs text-gray-500 mt-0.5\">Credit: {payment.creditBgn.toFixed(2)} BGN</p>\n )}\n {payment.transactionType && (\n <p className=\"text-xs text-gray-500 mt-0.5\">Transaction type: {payment.transactionType}</p>\n )}\n {payment.payerAccount && (\n <p className=\"text-xs text-gray-500 mt-0.5\">Account: {payment.payerAccount}</p>\n )}\n {payment.notifiedAt && (\n <p className=\"text-xs text-green-600 mt-2\">\n Notified on {new Date(payment.notifiedAt).toLocaleString('en-GB')}\n {payment.notifyPhone && ` to ${payment.notifyPhone}`}\n </p>\n )}\n </td>\n </tr>\n );\n}\n\nfunction StatusCell({ payment, onUpdateStatus }) {\n const [open, setOpen] = useState(false);\n const statusCfg = STATUS_CONFIG[payment.status] || STATUS_CONFIG.UNPROCESSED;\n const StatusIcon = statusCfg.icon;\n\n return (\n <div className=\"relative\">\n <button\n onClick={() => setOpen(!open)}\n className={`inline-flex items-center gap-1 px-2 py-0.5 text-xs font-medium rounded-full cursor-pointer ${statusCfg.color}`}\n >\n <StatusIcon className=\"w-3 h-3\" />\n {statusCfg.label}\n </button>\n {open && (\n <div className=\"absolute z-20 top-full left-0 mt-1 bg-white border border-gray-200 rounded-lg shadow-lg py-1 w-36\">\n {Object.entries(STATUS_CONFIG).map(([key, cfg]) => {\n const Icon = cfg.icon;\n return (\n <button\n key={key}\n onClick={() => { onUpdateStatus(payment.id, key); setOpen(false); }}\n className={`w-full flex items-center gap-2 px-3 py-1.5 text-xs hover:bg-gray-50 ${payment.status === key ? 'font-bold' : ''}`}\n >\n <Icon className=\"w-3 h-3\" />\n {cfg.label}\n </button>\n );\n })}\n </div>\n )}\n </div>\n );\n}\n\nexport default function PaymentTable({\n payments, loading, sortBy, sortDir, onSort,\n onSend, onSkip, onAddTag, onRemoveTag, onDelete, onUpdateStatus, existingTags,\n}) {\n const [expandedId, setExpandedId] = useState(null);\n\n if (loading) {\n return (\n <div className=\"flex items-center justify-center py-20\">\n <div className=\"animate-spin rounded-full h-8 w-8 border-b-2 border-indigo-600\"></div>\n </div>\n );\n }\n\n if (!payments || payments.length === 0) {\n return (\n <div className=\"flex flex-col items-center justify-center py-20 text-gray-400\">\n <Inbox className=\"w-12 h-12 mb-3\" />\n <p className=\"text-lg font-medium\">No transactions found</p>\n <p className=\"text-sm\">Try adjusting your filters, ingest a payment SMS, or upload a CSV.</p>\n </div>\n );\n }\n\n const formatDate = (d) => {\n if (!d) return '—';\n return new Date(d).toLocaleDateString('en-GB', {\n day: '2-digit', month: 'short', year: 'numeric', hour: '2-digit', minute: '2-digit',\n });\n };\n\n const formatAmount = (v, currency) =>\n v != null ? `${v.toFixed(2)} ${currency || 'EUR'}` : '—';\n\n return (\n <div className=\"bg-white rounded-xl border border-gray-200 shadow-sm overflow-hidden\">\n <div className=\"overflow-x-auto\">\n <table className=\"w-full text-sm\">\n <thead>\n <tr className=\"bg-gray-50 border-b border-gray-200\">\n {COLUMNS.map(col => (\n <th\n key={col.key}\n className={`px-4 py-3 text-left text-xs font-semibold text-gray-600 uppercase tracking-wider ${col.sortable ? 'cursor-pointer select-none hover:bg-gray-100' : ''}`}\n onClick={() => col.sortable && onSort(col.key)}\n >\n <span className=\"inline-flex items-center gap-1\">\n {col.label}\n {col.sortable && <SortIcon column={col.key} sortBy={sortBy} sortDir={sortDir} />}\n </span>\n </th>\n ))}\n </tr>\n </thead>\n <tbody className=\"divide-y divide-gray-100\">\n {payments.map(p => {\n const isExpanded = expandedId === p.id;\n return (\n <React.Fragment key={p.id}>\n <tr className=\"hover:bg-gray-50 transition-colors\">\n <td className=\"px-4 py-3 whitespace-nowrap text-gray-700\">{formatDate(p.date)}</td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n <SourceBadge source={p.source} />\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n {p.type ? (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-blue-50 text-blue-700\">{p.type}</span>\n ) : (p.transactionType ? (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-gray-100 text-gray-600 max-w-24 truncate block\" title={p.transactionType}>{p.transactionType}</span>\n ) : '—')}\n </td>\n <td className=\"px-4 py-3 text-gray-700 max-w-xs truncate\" title={p.recipient || ''}>\n <div className=\"flex items-center gap-1\">\n <span className=\"truncate\">{p.recipient || '—'}</span>\n <button\n onClick={() => setExpandedId(isExpanded ? null : p.id)}\n className=\"flex-shrink-0 text-gray-400 hover:text-gray-600\"\n title=\"Show raw data\"\n >\n {isExpanded ? <ChevronUp className=\"w-3.5 h-3.5\" /> : <ChevronDown className=\"w-3.5 h-3.5\" />}\n </button>\n </div>\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap font-medium text-gray-900\">\n {formatAmount(p.amount, p.currency)}\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap text-gray-600\">\n {formatAmount(p.balance, p.currency)}\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n <StatusCell payment={p} onUpdateStatus={onUpdateStatus} />\n </td>\n <td className=\"px-4 py-3\">\n <TagCell\n payment={p}\n onAddTag={onAddTag}\n onRemoveTag={onRemoveTag}\n existingTags={existingTags}\n />\n </td>\n <td className=\"px-4 py-3 whitespace-nowrap\">\n <div className=\"flex items-center gap-1.5\">\n {p.status === 'UNPROCESSED' && (\n <>\n <button\n onClick={() => onSend(p.id)}\n className=\"inline-flex items-center gap-1 px-2.5 py-1 text-xs font-medium text-white bg-indigo-600 rounded-md hover:bg-indigo-700 transition-colors\"\n >\n <Send className=\"w-3 h-3\" />\n Send\n </button>\n <button\n onClick={() => onSkip(p.id)}\n className=\"inline-flex items-center gap-1 px-2.5 py-1 text-xs font-medium text-gray-600 bg-white border border-gray-300 rounded-md hover:bg-gray-50 transition-colors\"\n >\n <XCircle className=\"w-3 h-3\" />\n Skip\n </button>\n </>\n )}\n <button\n onClick={() => { if (window.confirm('Delete this transaction?')) onDelete(p.id); }}\n className=\"inline-flex items-center gap-1 px-2 py-1 text-xs font-medium text-red-600 bg-white border border-red-200 rounded-md hover:bg-red-50 transition-colors\"\n title=\"Delete transaction\"\n >\n <Trash2 className=\"w-3 h-3\" />\n </button>\n </div>\n </td>\n </tr>\n {isExpanded && <ExpandedRow payment={p} />}\n </React.Fragment>\n );\n })}\n </tbody>\n </table>\n </div>\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"UploadPanel.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"UploadPanel.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"192 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState, useRef } from 'react';\nimport { Upload, FileText, CheckCircle, AlertCircle, X, ArrowLeft } from 'lucide-react';\n\nexport default function UploadPanel({ onUploadSuccess }) {\n const [files, setFiles] = useState([]);\n const [loading, setLoading] = useState(false);\n const [result, setResult] = useState(null);\n const [error, setError] = useState(null);\n const [dragging, setDragging] = useState(false);\n const fileInputRef = useRef();\n\n const addFiles = (incoming) => {\n const csvFiles = Array.from(incoming).filter(f =>\n f.name.toLowerCase().endsWith('.csv')\n );\n setFiles(prev => {\n const existingNames = new Set(prev.map(f => f.name));\n return [...prev, ...csvFiles.filter(f => !existingNames.has(f.name))];\n });\n };\n\n const handleDrop = (e) => {\n e.preventDefault();\n setDragging(false);\n addFiles(e.dataTransfer.files);\n };\n\n const handleFileSelect = (e) => {\n addFiles(e.target.files);\n e.target.value = '';\n };\n\n const removeFile = (idx) => setFiles(prev => prev.filter((_, i) => i !== idx));\n\n const handleUpload = async () => {\n if (!files.length) return;\n setLoading(true);\n setError(null);\n setResult(null);\n\n const formData = new FormData();\n files.forEach(f => formData.append('files', f));\n\n try {\n const res = await fetch('/api/upload/csv', { method: 'POST', body: formData });\n const data = await res.json();\n if (!res.ok) throw new Error(data.error || 'Upload failed');\n setResult(data);\n setFiles([]);\n } catch (err) {\n setError(err.message);\n } finally {\n setLoading(false);\n }\n };\n\n return (\n <div className=\"max-w-2xl mx-auto\">\n <div className=\"mb-6\">\n <h2 className=\"text-lg font-semibold text-gray-900\">Upload DSK Bank CSV</h2>\n <p className=\"text-sm text-gray-500 mt-1\">\n Import transactions from DSK Bank CSV exports. Multiple files are merged automatically.\n Internal transfers are skipped. Tags are auto-assigned based on payee and description.\n </p>\n </div>\n\n {/* Drop zone */}\n <div\n onDrop={handleDrop}\n onDragOver={(e) => { e.preventDefault(); setDragging(true); }}\n onDragLeave={() => setDragging(false)}\n onClick={() => fileInputRef.current.click()}\n className={`border-2 border-dashed rounded-xl p-12 text-center cursor-pointer transition-colors ${\n dragging\n ? 'border-emerald-400 bg-emerald-50'\n : 'border-gray-300 hover:border-emerald-400 hover:bg-emerald-50'\n }`}\n >\n <Upload className={`w-10 h-10 mx-auto mb-3 ${dragging ? 'text-emerald-500' : 'text-gray-400'}`} />\n <p className=\"text-sm font-medium text-gray-700\">Drop DSK Bank CSV files here</p>\n <p className=\"text-xs text-gray-500 mt-1\">or click to select files — multiple files supported</p>\n <input\n ref={fileInputRef}\n type=\"file\"\n multiple\n accept=\".csv\"\n className=\"hidden\"\n onChange={handleFileSelect}\n />\n </div>\n\n {/* File list */}\n {files.length > 0 && (\n <div className=\"mt-4 space-y-2\">\n {files.map((f, i) => (\n <div key={i} className=\"flex items-center gap-2 bg-white rounded-lg border border-gray-200 px-3 py-2\">\n <FileText className=\"w-4 h-4 text-gray-400 flex-shrink-0\" />\n <span className=\"text-sm text-gray-700 flex-1 truncate\">{f.name}</span>\n <span className=\"text-xs text-gray-400 flex-shrink-0\">{(f.size / 1024).toFixed(1)} KB</span>\n <button\n onClick={(e) => { e.stopPropagation(); removeFile(i); }}\n className=\"text-gray-400 hover:text-gray-600 flex-shrink-0\"\n >\n <X className=\"w-4 h-4\" />\n </button>\n </div>\n ))}\n\n <button\n onClick={handleUpload}\n disabled={loading}\n className=\"w-full py-2.5 text-sm font-medium text-white bg-emerald-600 rounded-lg hover:bg-emerald-700 disabled:opacity-50 disabled:cursor-not-allowed transition-colors mt-2\"\n >\n {loading\n ? 'Importing…'\n : `Import ${files.length} file${files.length !== 1 ? 's' : ''}`\n }\n </button>\n </div>\n )}\n\n {/* Success result */}\n {result && (\n <div className=\"mt-6 bg-green-50 border border-green-200 rounded-xl p-5\">\n <div className=\"flex items-center gap-2 mb-3\">\n <CheckCircle className=\"w-5 h-5 text-green-600 flex-shrink-0\" />\n <span className=\"font-medium text-green-800\">Import complete</span>\n </div>\n <div className=\"grid grid-cols-3 gap-3 text-center mb-3\">\n <div className=\"bg-white rounded-lg border border-green-100 py-2 px-3\">\n <p className=\"text-2xl font-bold text-green-700\">{result.imported}</p>\n <p className=\"text-xs text-gray-500\">Imported</p>\n </div>\n <div className=\"bg-white rounded-lg border border-green-100 py-2 px-3\">\n <p className=\"text-2xl font-bold text-gray-500\">{result.skipped}</p>\n <p className=\"text-xs text-gray-500\">Skipped</p>\n </div>\n <div className=\"bg-white rounded-lg border border-green-100 py-2 px-3\">\n <p className=\"text-2xl font-bold text-amber-600\">{result.errors?.length ?? 0}</p>\n <p className=\"text-xs text-gray-500\">Warnings</p>\n </div>\n </div>\n <p className=\"text-xs text-gray-500 mb-3\">\n Skipped rows are internal bank transfers (ТРАНСФЕР СОБСТВЕНИ СМЕТКИ).\n </p>\n {result.errors?.length > 0 && (\n <details className=\"mb-3\">\n <summary className=\"text-xs text-amber-700 cursor-pointer hover:text-amber-800\">\n Show {result.errors.length} warning{result.errors.length !== 1 ? 's' : ''}\n </summary>\n <ul className=\"mt-2 text-xs text-amber-600 space-y-0.5 max-h-32 overflow-y-auto\">\n {result.errors.map((e, i) => <li key={i} className=\"font-mono\">{e}</li>)}\n </ul>\n </details>\n )}\n <button\n onClick={onUploadSuccess}\n className=\"flex items-center gap-1.5 text-sm font-medium text-green-700 hover:text-green-800\"\n >\n <ArrowLeft className=\"w-4 h-4\" />\n View imported transactions\n </button>\n </div>\n )}\n\n {/* Error */}\n {error && (\n <div className=\"mt-4 bg-red-50 border border-red-200 rounded-xl p-4 flex items-start gap-3\">\n <AlertCircle className=\"w-5 h-5 text-red-500 flex-shrink-0 mt-0.5\" />\n <div>\n <p className=\"text-sm font-medium text-red-800\">Upload failed</p>\n <p className=\"text-sm text-red-700 mt-0.5\">{error}</p>\n </div>\n </div>\n )}\n\n {/* Info box */}\n {!result && !error && (\n <div className=\"mt-6 bg-blue-50 border border-blue-100 rounded-xl p-4\">\n <p className=\"text-xs font-medium text-blue-800 mb-1\">Expected CSV format (DSK Bank export)</p>\n <p className=\"text-xs text-blue-700 font-mono\">\n Дата, Вид на трансакцията, Основание, Дебит BGN, Кредит BGN, Наредител/Получател, Номер сметка...\n </p>\n <p className=\"text-xs text-blue-600 mt-2\">\n Both UTF-8 and Windows-1251 encodings are supported. Tags are auto-applied based on payee and description keywords.\n </p>\n </div>\n )}\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentCard.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentCard.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"186 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState } from 'react';\nimport {\n Send, XCircle, CheckCircle, MinusCircle, Clock,\n CreditCard, Tag, Plus, X,\n} from 'lucide-react';\n\nconst STATUS_CONFIG = {\n UNPROCESSED: { label: 'Unprocessed', icon: Clock, color: 'bg-amber-100 text-amber-700 border-amber-200' },\n SENT: { label: 'Sent', icon: CheckCircle, color: 'bg-green-100 text-green-700 border-green-200' },\n SKIPPED: { label: 'Skipped', icon: MinusCircle, color: 'bg-gray-100 text-gray-500 border-gray-200' },\n};\n\nconst TAG_COLORS = [\n '#ef4444', '#f97316', '#eab308', '#22c55e', '#06b6d4',\n '#3b82f6', '#8b5cf6', '#ec4899', '#6b7280',\n];\n\nexport default function PaymentCard({ payment, onSend, onSkip, onAddTag, onRemoveTag, existingTags }) {\n const [showTagInput, setShowTagInput] = useState(false);\n const [newTagName, setNewTagName] = useState('');\n const [newTagColor, setNewTagColor] = useState('#3b82f6');\n\n const statusCfg = STATUS_CONFIG[payment.status] || STATUS_CONFIG.UNPROCESSED;\n const StatusIcon = statusCfg.icon;\n\n const handleAddTag = (e) => {\n e.preventDefault();\n if (newTagName.trim()) {\n onAddTag(payment.id, newTagName.trim(), newTagColor);\n setNewTagName('');\n setShowTagInput(false);\n }\n };\n\n const paymentTags = payment.tags || [];\n const availableTags = existingTags.filter(t => !paymentTags.some(pt => pt.id === t.id));\n\n const formattedDate = payment.date\n ? new Date(payment.date).toLocaleDateString('en-GB', {\n day: '2-digit', month: 'short', year: 'numeric', hour: '2-digit', minute: '2-digit',\n })\n : 'N/A';\n\n const currency = payment.currency || 'EUR';\n\n return (\n <div className=\"bg-white rounded-xl border border-gray-200 shadow-sm hover:shadow-md transition-shadow p-4\">\n <div className=\"flex items-start justify-between gap-3 mb-3\">\n <div className=\"flex-1 min-w-0\">\n <div className=\"flex items-center gap-2 mb-1\">\n <span className={`inline-flex items-center gap-1 px-2 py-0.5 text-xs font-medium rounded-full border ${statusCfg.color}`}>\n <StatusIcon className=\"w-3 h-3\" />\n {statusCfg.label}\n </span>\n {payment.source === 'UPLOAD' ? (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-emerald-50 text-emerald-700\">CSV</span>\n ) : (\n <span className=\"px-2 py-0.5 text-xs font-medium rounded bg-indigo-50 text-indigo-700\">SMS</span>\n )}\n </div>\n <p className=\"text-sm text-gray-600 break-words leading-relaxed\">{payment.rawMessage}</p>\n </div>\n </div>\n\n <div className=\"grid grid-cols-2 sm:grid-cols-4 gap-3 mb-3 text-sm\">\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Amount</span>\n <p className=\"font-semibold text-gray-900\">\n {payment.amount != null ? `${payment.amount.toFixed(2)} ${currency}` : 'N/A'}\n </p>\n </div>\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Date</span>\n <p className=\"text-gray-700\">{formattedDate}</p>\n </div>\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Card</span>\n <p className=\"text-gray-700 flex items-center gap-1\">\n <CreditCard className=\"w-3 h-3 text-gray-400\" />\n {payment.card || 'N/A'}\n </p>\n </div>\n <div>\n <span className=\"text-xs text-gray-400 uppercase tracking-wide\">Balance</span>\n <p className=\"text-gray-700\">\n {payment.balance != null ? `${payment.balance.toFixed(2)} ${currency}` : 'N/A'}\n </p>\n </div>\n </div>\n\n {/* Tags */}\n <div className=\"flex flex-wrap items-center gap-1.5 mb-3\">\n <Tag className=\"w-3 h-3 text-gray-400\" />\n {paymentTags.map(tag => (\n <span\n key={tag.id}\n className=\"inline-flex items-center gap-1 px-2 py-0.5 text-xs font-medium rounded-full text-white\"\n style={{ backgroundColor: tag.color }}\n >\n {tag.name}\n <button onClick={() => onRemoveTag(payment.id, tag.id)} className=\"hover:opacity-75\">\n <X className=\"w-3 h-3\" />\n </button>\n </span>\n ))}\n {!showTagInput ? (\n <button\n onClick={() => setShowTagInput(true)}\n className=\"inline-flex items-center gap-0.5 px-2 py-0.5 text-xs text-gray-500 border border-dashed border-gray-300 rounded-full hover:border-gray-400 hover:text-gray-600\"\n >\n <Plus className=\"w-3 h-3\" />\n Tag\n </button>\n ) : (\n <form onSubmit={handleAddTag} className=\"inline-flex items-center gap-1\">\n <input\n type=\"text\"\n value={newTagName}\n onChange={(e) => setNewTagName(e.target.value)}\n placeholder=\"Tag name\"\n autoFocus\n className=\"w-24 px-2 py-0.5 text-xs border border-gray-300 rounded-md focus:ring-1 focus:ring-indigo-500 outline-none\"\n />\n <div className=\"flex gap-0.5\">\n {TAG_COLORS.map(c => (\n <button\n key={c}\n type=\"button\"\n onClick={() => setNewTagColor(c)}\n className={`w-4 h-4 rounded-full border-2 ${newTagColor === c ? 'border-gray-800' : 'border-transparent'}`}\n style={{ backgroundColor: c }}\n />\n ))}\n </div>\n <button type=\"submit\" className=\"text-xs text-indigo-600 font-medium hover:text-indigo-700\">Add</button>\n <button type=\"button\" onClick={() => setShowTagInput(false)} className=\"text-xs text-gray-400 hover:text-gray-600\">\n <X className=\"w-3 h-3\" />\n </button>\n </form>\n )}\n {showTagInput && availableTags.length > 0 && (\n <div className=\"flex flex-wrap gap-1 ml-1\">\n {availableTags.slice(0, 5).map(tag => (\n <button\n key={tag.id}\n onClick={() => { onAddTag(payment.id, tag.name, tag.color); setShowTagInput(false); }}\n className=\"px-2 py-0.5 text-xs rounded-full border border-gray-200 text-gray-600 hover:bg-gray-100\"\n >\n {tag.name}\n </button>\n ))}\n </div>\n )}\n </div>\n\n {payment.status === 'UNPROCESSED' && (\n <div className=\"flex items-center gap-2 pt-3 border-t border-gray-100\">\n <button\n onClick={() => onSend(payment.id)}\n className=\"flex items-center gap-1.5 px-4 py-2 text-sm font-medium text-white bg-indigo-600 rounded-lg hover:bg-indigo-700 transition-colors\"\n >\n <Send className=\"w-4 h-4\" />\n Send\n </button>\n <button\n onClick={() => onSkip(payment.id)}\n className=\"flex items-center gap-1.5 px-4 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 transition-colors\"\n >\n <XCircle className=\"w-4 h-4\" />\n Do Not Send\n </button>\n </div>\n )}\n\n {payment.status === 'SENT' && payment.notifiedAt && (\n <div className=\"pt-3 border-t border-gray-100\">\n <p className=\"text-xs text-green-600\">\n Notified on {new Date(payment.notifiedAt).toLocaleString('en-GB')}\n {payment.notifyPhone && ` to ${payment.notifyPhone}`}\n </p>\n </div>\n )}\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentList.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentList.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"40 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React from 'react';\nimport { Inbox } from 'lucide-react';\nimport PaymentCard from './PaymentCard';\n\nexport default function PaymentList({ payments, loading, onSend, onSkip, onAddTag, onRemoveTag, existingTags }) {\n if (loading) {\n return (\n <div className=\"flex items-center justify-center py-20\">\n <div className=\"animate-spin rounded-full h-8 w-8 border-b-2 border-indigo-600\"></div>\n </div>\n );\n }\n\n if (!payments || payments.length === 0) {\n return (\n <div className=\"flex flex-col items-center justify-center py-20 text-gray-400\">\n <Inbox className=\"w-12 h-12 mb-3\" />\n <p className=\"text-lg font-medium\">No transactions found</p>\n <p className=\"text-sm\">Try adjusting your filters, ingest a payment SMS, or upload a CSV.</p>\n </div>\n );\n }\n\n return (\n <div className=\"space-y-4\">\n {payments.map(payment => (\n <PaymentCard\n key={payment.id}\n payment={payment}\n onSend={onSend}\n onSkip={onSkip}\n onAddTag={onAddTag}\n onRemoveTag={onRemoveTag}\n existingTags={existingTags}\n />\n ))}\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"}]...
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Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
report(1).csv, Editor Group 1
report(2).csv, Editor Group 1
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
"Дата","Основание","Наредител/Получател","Номер сметка на наредителя / получателя","Вид на трансакцията","Свързваща референция","Валутен курс","Сума във валутата на превода","Дебит EUR","Кредит EUR"
"04.05.2026","04.05.2026 ПРОФЕСИОНАЛЕН ДОМОУАБ.N. 14044121 НАШИЯТ ВХОД ООД","КОМУНАЛНИ РАЗХОДИ ЕЛ. КАНАЛИ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","17,93",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","8,44",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","47,63",""
"04.05.2026","04.05.2026 ЕЛ ЕНЕРГИЯ АБ.N. 310264962737 ЕЛЕКТРОХОЛД ПРОДАЖБИ АД","ЕЛЕКТPОХОЛДПPОДАЖБИ/ДСКДИРЕКТ/ЕЛ.ЕНЕРГИЯ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","0,09",""
"04.05.2026","04.05.2026 СТУДЕНА ВОДА АБ.N. 1005400804 СОФИЙСКА ВОДА АД","С0ФИЙСКА ВОДА ДСК ДИРЕКТ","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","29,54",""
"04.05.2026","04.05.2026 ПРИРОДЕН ГАЗ АБ.N. 1000083763 OVERGAS","ОВЕГАЗ МРЕЖИ АД-ЕЛЕКТРОННИ КАНАЛИ И КАСА","[IBAN]","КОМУНАЛНИ УСЛУГИ","","","","14,27",""
"04.05.2026","ДАНИЕЛ КОВАЛИК МАЙ","ЧЦДГ МИЛА","[IBAN]","ПРЕВОД SEPA","","","","460,00",""
"30.04.2026","ТАКСА ПАКЕТНО ОБСЛУЖВАНЕ","","[CREDIT_CARD]","","","","","10,22",""
"30.04.2026","ЗАПЛАТА ЗА МЕСЕЦ 04.2026 OPNAT 0","ВЕДА ПЕЙРОЛ ООД","[IBAN]","ВХОДЯЩ ПАРИЧЕН ПРЕВОД","","","","","4325,26"
"22.04.2026","ЗАХРАНВАНЕ СМЕТКА ISI2204260011502","МАРТИНА СВЕТОСЛАВОВА КОВАЛИК","[IBAN]","НЕЗАБАВЕН КРЕДИТЕН ПРЕВОД","","","","","1000,00"
Design new payment-logge…, Editor Group 2
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Ln 9, Col 45
Info: Setting up SSH Host nas: Setting up SSH tunnel
Design new payment-logger and dsk-uploader hybrid app
Session history
New session
Message actions
payments.js
payments.js
ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.
Thinking
Thinking
I'll explore all three reference projects in parallel to understand their structure before planning.
Agent:
Explore payment-logger app structure and functionality
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How data flows (ingest, storage, retrieval)
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.
Agent:
Explore dsk-uploader app structure and functionality
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Tech stack (frontend framework, backend framework, database)
2. What the app does - its core purpose and features
3. Database schema - all tables, relationships
4. API routes - all endpoints, their purpose and request/response shapes
5. How file uploads work - what files, what format, how parsed
6. Any auth/middleware setup
7. Docker/deployment setup
8. Key files and their roles
Report with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.
Agent:
Explore auth folder and authentik integration
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. What auth system is being used (Authentik)
2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?
3. Middleware - how is auth enforced on routes?
4. Any frontend auth flow - login redirect, token handling, protected routes
5. Environment variables related to auth
6. Docker/deployment setup for the auth service itself
7. Any example of how other apps integrate with this auth
Report with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.
Message actions
payments.js
payments.js
continue
Thinking
Thinking
Launching parallel exploration of all three reference projects.
Agent:
Explore payment-logger app structure
IN
Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How data is ingested (look at /ingest route especially)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore dsk-uploader app structure
IN
Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. Tech stack (frontend framework, backend framework, database, etc.)
3. What the app does - its core functionality
4. How file uploads work (what format, what processing happens)
5. Database schema (what tables/collections exist)
6. API routes and their purposes
7. Frontend pages and components
8. Docker setup
9. Any auth/session handling
Please read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.
Agent:
Explore auth project structure
IN
Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:
1. Full directory structure (tree)
2. What authentication system is used (authentik integration details)
3. How OAuth/OIDC flow works
4. Any middleware or helper functions for protecting routes
5. Session management approach
6. How frontend handles auth state
7. Any example of how other apps integrate with this auth system
8. Docker setup and environment variables
Please read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.
Thinking
Thinking
Now I have a complete picture of all three. Let me design the plan.
Agent:
Design combined app architecture
IN
Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:
---
## App 1: payments-logger (Node.js)
- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI
- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS
- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage
- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)
- **Schema** (PostgreSQL via Prisma):
- `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at
- `tags` table: id, name, color — M2M with payments via `_PaymentToTag`
- `users` table: id, username, hashed_password (this will be REMOVED)
- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system
- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance
## App 2: dsk-uploader (Python/Flask)
- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database
- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5
- **Auth**: None (open)
- **CSV format** (DSK Bank Bulgarian format, columns):
- `Дата` (date, DD.MM.YYYY)
- `Вид на трансакцията` (transaction type, Bulgarian)
- `Основание` (reason/description — contains card number regex: `^\d{6}x{6}\d{4}$`)
- `Дебит BGN` (debit amount, may be empty)
- `Кредит BGN` (credit amount, may be empty)
- `Наредител/Получател` (orderer/recipient name)
- `Номер сметка на наредителя / получателя` (account number)
- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers
- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)
## App 3: auth (Authentik)
- **Mode**: Proxy mode via NPM (forward auth)
- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:
- `X-authentik-username`
- `X-authentik-email`
- `X-authentik-groups`
- **No code integration needed** in the app itself — just trust these headers from NPM
- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`
---
## What the New Combined App Must Do
1. **Single PostgreSQL database** for all transactions
2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST
3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema
4. **Unified UI** — show all payments in one table regardless of source
5. **Source indicator** in UI — badge showing "INGEST", "UPLOAD", or "BOTH" (if duplicate detection added)
6. **Source filter** in FilterBar — filter by All/Ingest/Upload
7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM
8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination
9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL
---
## Technical Constraints
- Keep Node.js backend (not Python) — extend payments-logger's stack
- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)
- File upload: use `multer` npm middleware
- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)
- Add `source` enum field (INGEST/UPLOAD) to payments schema
- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is
- Remove `users` table from schema
---
## Please Design
1. Complete folder structure for the new app (suggest name: "finance-hub" or similar — note this is a placeholder, user will confirm)
2. Prisma schema with new fields (`source`, `currency`)
3. All backend API routes
4. CSV parser design in Node.js (port of the Python logic)
5. Authentik auth middleware
6. Frontend component structure (React) — what's reused from payments-logger, what's new
7. Docker Compose setup
8. Environment variables needed
9. Step-by-step implementation order
10. Verification checklist
Be specific about file paths and code structure. This will be used to write actual implementation code.
Thinking
Thinking
Good plan. Let me ask the one thing I need before writing the final plan.
AskUserQuestion
OUT
User has answered your questions: "What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding."="finance-hub". You can now continue with the user's answers in mind.
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ets-create-a-new-generic-sun.md
ets-create-a-new-generic-sun.md
326 lines
# finance-hub — Implementation Plan
## Context
Two separate finance apps exist as references and will be retired:
- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.
- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.
The new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).
---
## Tech Stack
| Layer | Choice | Rationale |
|-------|--------|-----------|
| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |
| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |
| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |
| Database | PostgreSQL 16 | Same as payments-logger |
| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |
| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |
| Container | Docker Compose | Same pattern as both reference apps |
**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage.
**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references.
**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.
---
## Folder Structure
```
/volume2/docker/finance/finance-hub/
├── docker-compose.yml
├── .env
├── .env.example
├── .gitignore
├── backend/
│ ├── Dockerfile
│ ├── package.json
│ ├── prisma/
│ │ ├── schema.prisma
│ │ └── migrations/
│ │ ├── migration_lock.toml
│ │ └── 20260508_init/
│ │ └── migration.sql
│ └── src/
│ ├── index.js ← entry point (Authentik middleware wired here)
│ ├── auth.js ← Authentik header middleware (replaces JWT auth)
│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)
│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)
│ └── routes/
│ ├── payments.js ← existing routes + source/currency additions
│ └── upload.js ← NEW: POST /api/upload/csv
└── frontend/
├── Dockerfile
├── package.json
├── vite.config.js
├── tailwind.config.js
├── postcss.config.js
├── index.html
└── src/
├── main.jsx ← remove AuthProvider wrapper
├── index.css
├── App.jsx ← remove auth state, add Upload tab toggle
└── components/
├── FilterBar.jsx ← add source filter select
├── PaymentTable.jsx ← add Source badge column + currency display
├── PaymentCard.jsx ← minor source badge addition
├── PaymentList.jsx ← unchanged
└── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI
```
---
## Database Schema (Prisma)
File: `backend/prisma/schema.prisma`
```prisma
generator client {
provider = "prisma-client-js"
}
datasource db {
provider = "postgresql"
url = env("DATABASE_URL")
}
model Payment {
id Int @id @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
auth.js
auth.js
27 lines
const PUBLIC_PATHS = new Set([
'/api/health',
'/api/payments/ingest',
]);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) {
return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });
}
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '')
.split(',')
.map(g => g.trim())
.filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
Write
parser.js
parser.js
104 lines
/**
* Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)
*
* Supported formats:
*
* POS / INTERNET / ECOM / P2P payment:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM withdrawal:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM utility payment (amount may include fee as AMOUNT/FEE):
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.
*/
const LOCAL_TZ = process.env.TZ || 'Europe/Sofia';
/**
* Convert a local-timezone date/time to a UTC Date object.
* Uses Intl to resolve the actual UTC offset (DST-aware).
*/
function localToUtc(year, month, day, hour, minute) {
const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));
const formatter = new Intl.DateTimeFormat('en-US', {
timeZone: LOCAL_TZ,
year: 'numeric', month: '2-digit', day: '2-digit',
hour: '2-digit', minute: '2-digit', second: '2-digit',
hour12: false,
});
const parts = {};
formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });
const localAtNaive = new Date(Date.UTC(
parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),
parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),
));
const offsetMs = localAtNaive.getTime() - naive.getTime();
return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);
}
function parsePaymentSms(message) {
const result = {
rawMessage: message,
date: null,
type: null,
card: null,
recipient: null,
amount: null,
balance: null,
};
// Date and time: "Na DD/MM/YYYY v HH:MM"
const dateMatch = message.match(/Na (\d{2})\/(\d{2})\/(\d{4}) v (\d{2}):(\d{2})/i);
if (dateMatch) {
const [, day, month, year, hour, minute] = dateMatch;
result.date = localToUtc(
parseInt(year), parseInt(month), parseInt(day),
parseInt(hour), parseInt(minute),
);
}
// Card mask: "s karta 400915***4447" or "s karta 483890***7162"
const cardMatch = message.match(/s karta\s+([\d*]+)/i);
if (cardMatch) {
result.card = cardMatch[1];
}
// Transaction type: supports both prepositions
// "na POS" / "na ATM" / "na INTERNET" etc. (payment)
// "ot ATM" (withdrawal)
const typeMatch = message.match(/(?:na|ot)\s+(POS|ATM|INTERNET|ECOM|P2P)\b/i);
if (typeMatch) {
result.type = typeMatch[1].toUpperCase();
}
// Recipient address: "s adres: MERCHANT" or "s adres:MERCHANT" (no space variant)
const recipientMatch = message.match(/s adres:\s*([^.]+)\./i);
if (recipientMatch) {
result.recipient = recipientMatch[1].trim();
}
// Amount: handles both verbs and the AMOUNT/FEE suffix format
// "sa plateni 7.78 EUR"
// "sa iztegleni 400.00 EUR"
// "sa plateni 0.50 EUR/0.50 EUR" → captures 0.50 (the charged amount, ignoring fee)
const amountMatch = message.match(/sa (?:plateni|iztegleni)\s+([\d.,]+)\s+[A-Z]{3}/i);
if (amountMatch) {
result.amount = parseFloat(amountMatch[1].replace(',', '.'));
}
// Balance: "Nalichni: 2583.07 EUR."
const balanceMatch = message.match(/Nalichni:\s*([\d.,]+)\s+[A-Z]{3}/i);
if (balanceMatch) {
result.balance = parseFloat(balanceMatch[1].replace(',', '.'));
}
return result;
}
module.exports = { parsePaymentSms };
Write
csvParser.js
csvParser.js
175 lines
/**
* DSK Bank CSV parser — Node.js port of dskuploader.py
*
* DSK Bank exports use Windows-1251 (cp1251) encoding.
* Each row maps to a Payment record with source=UPLOAD, currency=BGN.
*/
const { parse } = require('csv-parse');
const iconv = require('iconv-lite');
const SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';
const CARD_REGEX = /^\d{6}x{6}\d{4}$/;
const POS_REGEX = /^\s*ПЛАЩАНЕ\s+НА\s+ПОС\s+\d{2}\.\d{2}\.\d{4}\s+\d{2}:\d{2}/;
const COL = {
DATE: 'Дата',
TYPE: 'Вид на трансакцията',
REASON: 'Основание',
DEBIT: 'Дебит BGN',
CREDIT: 'Кредит BGN',
PAYEE: 'Наредител/Получател',
ACCT: 'Номер сметка на наредителя / получателя',
};
const TAG_RULES = [
['reason', 'ЗАПЛАТА', 'Salary'],
['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],
['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],
['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],
['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],
['payee', 'VIVACOM', 'Subscriptions'],
['payee', 'Google', 'Subscriptions'],
['payee', 'SkyShowtime', 'Subscriptions'],
['payee', 'NETFLIX', 'Subscriptions'],
['payee', 'LUKOIL', 'Bills'],
['payee', 'CityGate', 'Bills'],
['payee', 'CBA', 'Groceries'],
['payee', 'FANTASTICO', 'Groceries'],
['payee', 'LIDL', 'Groceries'],
];
function parseNum(val) {
if (val == null || val === '') return null;
if (typeof val === 'number') return isNaN(val) ? null : val;
const s = String(val).trim().replace(/\xa0/g, '').replace(/ /g, '').replace(',', '.');
const n = parseFloat(s);
return isNaN(n) ? null : n;
}
function parseDate(val) {
if (!val) return null;
const s = String(val).trim();
const m = s.match(/^(\d{2})\.(\d{2})\.(\d{4})$/);
if (m) {
return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));
}
return null;
}
function processReasonAndCard(reason) {
if (!reason || typeof reason !== 'string') return { reason: '', card: null };
const parts = reason.trim().split(' ');
let card = null;
let cleanReason = reason.trim();
if (parts[0] && CARD_REGEX.test(parts[0])) {
card = parts[0];
cleanReason = parts.slice(1).join(' ').trim();
}
if (POS_REGEX.test(cleanReason)) {
const posParts = cleanReason.split('<br/>');
try {
const dateTime = posParts[0].split('ПОС ')[1];
cleanReason = `POS PAYMENT ${dateTime}`;
} catch (_) { /* keep original */ }
}
return { reason: cleanReason.replace(/\s+/g, ' ').trim(), card };
}
function generateTags(fields) {
const tags = new Set();
for (const [field, keyword, tagName] of TAG_RULES) {
if ((fields[field] || '').includes(keyword)) {
tags.add(tagName);
}
}
return Array.from(tags);
}
function processRow(row) {
const transactionType = (row[COL.TYPE] || '').trim();
if (transactionType === SKIP_TYPE) return null;
const { reason, card } = processReasonAndCard(row[COL.REASON]);
const payee = (row[COL.PAYEE] || ...
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G)
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
# ── Database ───────────────────────────────────────────────────────────────────
[ENV_SECRET]
# ── Notifier service ──────────────────────────────────────────────────────────
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
auth.js
auth.js
27 lines
const PUBLIC_PATHS = new Set([
'/api/health',
'/api/payments/ingest',
]);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) {
return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });
}
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '')
.split(',')
.map(g => g.trim())
.filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
Write
parser.js
parser.js
104 lines
/**
* Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)
*
* Supported formats:
*
* POS / INTERNET / ECOM / P2P payment:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM withdrawal:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM utility payment (amount may include fee as AMOUNT/FEE):
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.
*/
const LOCAL_TZ = process.env.TZ || 'Europe/Sofia';
/**
* Convert a local-timezone date/time to a UTC Date object.
* Uses Intl to resolve the actual UTC offset (DST-aware).
*/
function localToUtc(year, month, day, hour, minute) {
const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));
const formatter = new Intl.DateTimeFormat('en-US', {
timeZone: LOCAL_TZ,
year: 'numeric', month: '2-digit', day: '2-digit',
hour: '2-digit', minute: '2-digit', second: '2-digit',
hour12: false,
});
const parts = {};
formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });
const localAtNaive = new Date(Date.UTC(
parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),
parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),
));
const offsetMs = localAtNaive.getTime() - naive.getTime();
return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);
}
function parsePaymentSms(message) {
const result = {
rawMessage: message,
date: null,
type: null,
card: null,
recipient: null,
amount: null,
balance: null,
};
// Date and time: "Na DD/MM/YYYY v HH:MM"
const dateMatch = message.match(/Na (\d{2})\/(\d{2})\/(\d{4}) v (\d{2}):(\d{2})/i);
if (dateMatch) {
const [, day, month, year, hour, minute] = dateMatch;
result.date = localToUtc(
parseInt(year), parseInt(month), parseInt(day),
parseInt(hour), parseInt(minute),
);
}
// Card mask: "s karta 400915***4447" or "s karta 483890***7162"
const cardMatch = message.match(/s karta\s+([\d*]+)/i);
if (cardMatch) {
result.card = cardMatch[1];
}
// Transaction type: supports both prepositions
// "na POS" / "na ATM" / "na INTERNET" etc. (payment)
// "ot ATM" (withdrawal)
const typeMatch = message.match(/(?:na|ot)\s+(POS|ATM|INTERNET|ECOM|P2P)\b/i);
if (typeMatch) {
result.type = typeMatch[1].toUpperCase();
}
// Recipient address: "s adres: MERCHANT" or "s adres:MERCHANT" (no space variant)
const recipientMatch = message.match(/s adres:\s*([^.]+)\./i);
if (recipientMatch) {
result.recipient = recipientMatch[1].trim();
}
// Amount: handles both verbs and the AMOUNT/FEE suffix format
// "sa plateni 7.78 EUR"
// "sa iztegleni 400.00 EUR"
// "sa plateni 0.50 EUR/0.50 EUR" → captures 0.50 (the charged amount, ignoring fee)
const amountMatch = message.match(/sa (?:plateni|iztegleni)\s+([\d.,]+)\s+[A-Z]{3}/i);
if (amountMatch) {
result.amount = parseFloat(amountMatch[1].replace(',', '.'));
}
// Balance: "Nalichni: 2583.07 EUR."
const balanceMatch = message.match(/Nalichni:\s*([\d.,]+)\s+[A-Z]{3}/i);
if (balanceMatch) {
result.balance = parseFloat(balanceMatch[1].replace(',', '.'));
}
return result;
}
module.exports = { parsePaymentSms };
Write
csvParser.js
csvParser.js
175 lines
/**
* DSK Bank CSV parser — Node.js port of dskuploader.py
*
* DSK Bank exports use Windows-1251 (cp1251) encoding.
* Each row maps to a Payment record with source=UPLOAD, currency=BGN.
*/
const { parse } = require('csv-parse');
const iconv = require('iconv-lite');
const SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';
const CARD_REGEX = /^\d{6}x{6}\d{4}$/;
const POS_REGEX = /^\s*ПЛАЩАНЕ\s+НА\s+ПОС\s+\d{2}\.\d{2}\.\d{4}\s+\d{2}:\d{2}/;
const COL = {
DATE: 'Дата',
TYPE: 'Вид на трансакцията',
REASON: 'Основание',
DEBIT: 'Дебит BGN',
CREDIT: 'Кредит BGN',
PAYEE: 'Наредител/Получател',
ACCT: 'Номер сметка на наредителя / получателя',
};
const TAG_RULES = [
['reason', 'ЗАПЛАТА', 'Salary'],
['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],
['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],
['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],
['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],
['payee', 'VIVACOM', 'Subscriptions'],
['payee', 'Google', 'Subscriptions'],
['payee', 'SkyShowtime', 'Subscriptions'],
['payee', 'NETFLIX', 'Subscriptions'],
['payee', 'LUKOIL', 'Bills'],
['payee', 'CityGate', 'Bills'],
['payee', 'CBA', 'Groceries'],
['payee', 'FANTASTICO', 'Groceries'],
['payee', 'LIDL', 'Groceries'],
];
function parseNum(val) {
if (val == null || val === '') return null;
if (typeof val === 'number') return isNaN(val) ? null : val;
const s = String(val).trim().replace(/\xa0/g, '').replace(/ /g, '').replace(',', '.');
const n = parseFloat(s);
return isNaN(n) ? null : n;
}
function parseDate(val) {
if (!val) return null;
const s = String(val).trim();
const m = s.match(/^(\d{2})\.(\d{2})\.(\d{4})$/);
if (m) {
return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));
}
return null;
}
function processReasonAndCard(reason) {
if (!reason || typeof reason !== 'string') return { reason: '', card: null };
const parts = reason.trim().split(' ');
let card = null;
let cleanReason = reason.trim();
if (parts[0] && CARD_REGEX.test(parts[0])) {
card = parts[0];
cleanReason = parts.slice(1).join(' ').trim();
}
if (POS_REGEX.test(cleanReason)) {
const posParts = cleanReason.split('<br/>');
try {
const dateTime = posParts[0].split('ПОС ')[1];
cleanReason = `POS PAYMENT ${dateTime}`;
} catch (_) { /* keep original */ }
}
return { reason: cleanReason.replace(/\s+/g, ' ').trim(), card };
}
function generateTags(fields) {
const tags = new Set();
for (const [field, keyword, tagName] of TAG_RULES) {
if ((fields[field] || '').includes(keyword)) {
tags.add(tagName);
}
}
return Array.from(tags);
}
function processRow(row) {
const transactionType = (row[COL.TYPE] || '').trim();
if (transactionType === SKIP_TYPE) return null;
const { reason, card } = processReasonAndCard(row[COL.REASON]);
const payee = (row[COL.PAYEE] || '').trim();
const payerAccount = (row[COL.ACCT] || '').trim();
const debitBgn = parseNum(row[COL.DEBIT]);
const creditBgn = parseNum(row[COL.CREDIT]);
const date = parseDate(row[COL.DATE]);
const autoTags = generateTags({ reason, transactionType, payee, debitBgn, creditBgn });
const amount = debitBgn ?? creditBgn ?? null;
const rawMessage = [
row[COL.DATE] && `Date: ${row[COL.DATE]}`,
transactionType && `Type: ${transactionType}`,
payee && `Payee: ${payee}`,
debitBgn != null && `Debit: ${debitBgn} BGN`,
creditBgn != null && `Credit: ${creditBgn} BGN`,
].filter(Boolean).join(' | ');
return {
rawMessage,
date,
type: null,
card,
recipient: payee || null,
amount,
currency: 'BGN',
balance: null,
source: 'UPLOAD',
debitBgn,
creditBgn,
transactionType: transactionType || null,
payerAccount: payerAccount || null,
autoTags,
};
}
/**
* Parse a Buffer containing a DSK Bank CSV (cp1251 or UTF-8).
* Returns { rows, skipped, errors }.
*/
async function parseDskCsv(buffer) {
// Try cp1251 first (DSK Bank export encoding), fall back to UTF-8
let text = iconv.decode(buffer, 'cp1251');
if (!text.includes(COL.DATE)) {
text = buffer.toString('utf-8');
}
return new Promise((resolve, reject) => {
const rows = [];
const errors = [];
let skipped = 0;
const parser = parse(text, {
columns: true,
skip_empty_lines: true,
trim: true,
relax_column_count: true,
});
parser.on('readable', () => {
let record;
while ((record = parser.read()) !== null) {
try {
const row = processRow(record);
if (row === null) { skipped++; } else { rows.push(row); }
} catch (err) {
errors.push(err.message);
}
}
});
parser.on('error', reject);
parser.on('end', () => resolve({ rows, skipped, errors }));
});
}
module.exports = { parseDskCsv };
Write
index.js
index.js
39 lines
const express = require('express');
const cors = require('cors');
const morgan = require('morgan');
const rateLimit = require('express-rate-limit');
const { authentikMiddleware } = require('./auth');
const paymentsRouter = require('./routes/payments');
const uploadRouter = require('./routes/upload');
const app = express();
const PORT = process.env.PORT || 3001;
app.use(cors());
app.use(express.json({ limit: '16kb' }));
app.use(morgan('combined'));
// Rate-limit the public ingest endpoint before auth middleware
const ingestLimiter = rateLimit({
windowMs: 60 * 1000,
max: 200,
standardHeaders: true,
legacyHeaders: false,
message: { error: 'Too many requests, slow down' },
});
app.use('/api/payments/ingest', ingestLimiter);
// Authentik header auth (skips /api/health and /api/payments/ingest)
app.use(authentikMiddleware);
app.get('/api/health', (_req, res) => {
res.json({ status: 'ok', timestamp: new Date().toISOString() });
});
app.use('/api/payments', paymentsRouter);
app.use('/api/upload', uploadRouter);
app.listen(PORT, '[IP_ADDRESS]', () => {
console.log(`Finance Hub API running on port ${PORT}`);
});
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
payments.js
payments.js
3...
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It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"I'll explore all three reference projects in parallel to understand their structure before planning.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How data flows (ingest, storage, retrieval)\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How file uploads work - what files, what format, how parsed\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth folder and authentik integration","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. What auth system is being used (Authentik)\n2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?\n3. Middleware - how is auth enforced on routes?\n4. Any frontend auth flow - login redirect, token handling, protected routes\n5. Environment variables related to auth\n6. Docker/deployment setup for the auth service itself\n7. Any example of how other apps integrate with this auth\n\nReport with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"payments.js","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"continue","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Launching parallel exploration of all three reference projects.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How data is ingested (look at /ingest route especially)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How file uploads work (what format, what processing happens)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth project structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. What authentication system is used (authentik integration details)\n3. How OAuth/OIDC flow works\n4. Any middleware or helper functions for protecting routes\n5. Session management approach\n6. How frontend handles auth state\n7. Any example of how other apps integrate with this auth system\n8. Docker setup and environment variables\n\nPlease read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now I have a complete picture of all three. Let me design the plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design combined app architecture","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:\n\n---\n\n## App 1: payments-logger (Node.js)\n- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI\n- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS\n- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage\n- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)\n- **Schema** (PostgreSQL via Prisma):\n - `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at\n - `tags` table: id, name, color — M2M with payments via `_PaymentToTag`\n - `users` table: id, username, hashed_password (this will be REMOVED)\n- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system\n- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance\n\n## App 2: dsk-uploader (Python/Flask)\n- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database\n- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5\n- **Auth**: None (open)\n- **CSV format** (DSK Bank Bulgarian format, columns):\n - `Дата` (date, DD.MM.YYYY)\n - `Вид на трансакцията` (transaction type, Bulgarian)\n - `Основание` (reason/description — contains card number regex: `^\\d{6}x{6}\\d{4}$`)\n - `Дебит BGN` (debit amount, may be empty)\n - `Кредит BGN` (credit amount, may be empty)\n - `Наредител/Получател` (orderer/recipient name)\n - `Номер сметка на наредителя / получателя` (account number)\n- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers\n- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)\n\n## App 3: auth (Authentik)\n- **Mode**: Proxy mode via NPM (forward auth)\n- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:\n - `X-authentik-username` \n - `X-authentik-email`\n - `X-authentik-groups`\n- **No code integration needed** in the app itself — just trust these headers from NPM\n- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`\n\n---\n\n## What the New Combined App Must Do\n\n1. **Single PostgreSQL database** for all transactions\n2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST\n3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema\n4. **Unified UI** — show all payments in one table regardless of source\n5. **Source indicator** in UI — badge showing \"INGEST\", \"UPLOAD\", or \"BOTH\" (if duplicate detection added)\n6. **Source filter** in FilterBar — filter by All/Ingest/Upload\n7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM\n8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination\n9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL\n\n---\n\n## Technical Constraints\n\n- Keep Node.js backend (not Python) — extend payments-logger's stack\n- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)\n- File upload: use `multer` npm middleware\n- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)\n- Add `source` enum field (INGEST/UPLOAD) to payments schema\n- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is\n- Remove `users` table from schema\n\n---\n\n## Please Design\n\n1. Complete folder structure for the new app (suggest name: \"finance-hub\" or similar — note this is a placeholder, user will confirm)\n2. Prisma schema with new fields (`source`, `currency`)\n3. All backend API routes\n4. CSV parser design in Node.js (port of the Python logic)\n5. Authentik auth middleware\n6. Frontend component structure (React) — what's reused from payments-logger, what's new\n7. Docker Compose setup\n8. Environment variables needed\n9. Step-by-step implementation order\n10. Verification checklist\n\nBe specific about file paths and code structure. This will be used to write actual implementation code.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good plan. Let me ask the one thing I need before writing the final plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"AskUserQuestion","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"OUT","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"User has answered your questions: \"What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding.\"=\"finance-hub\". You can now continue with the user's answers in mind.","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Writing the final plan now.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"326 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# finance-hub — Implementation Plan\n\n## Context\n\nTwo separate finance apps exist as references and will be retired:\n- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.\n- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.\n\nThe new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).\n\n---\n\n## Tech Stack\n\n| Layer | Choice | Rationale |\n|-------|--------|-----------|\n| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |\n| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |\n| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |\n| Database | PostgreSQL 16 | Same as payments-logger |\n| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |\n| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |\n| Container | Docker Compose | Same pattern as both reference apps |\n\n**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage. \n**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references. \n**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.\n\n---\n\n## Folder Structure\n\n```\n/volume2/docker/finance/finance-hub/\n├── docker-compose.yml\n├── .env\n├── .env.example\n├── .gitignore\n├── backend/\n│ ├── Dockerfile\n│ ├── package.json\n│ ├── prisma/\n│ │ ├── schema.prisma\n│ │ └── migrations/\n│ │ ├── migration_lock.toml\n│ │ └── 20260508_init/\n│ │ └── migration.sql\n│ └── src/\n│ ├── index.js ← entry point (Authentik middleware wired here)\n│ ├── auth.js ← Authentik header middleware (replaces JWT auth)\n│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)\n│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)\n│ └── routes/\n│ ├── payments.js ← existing routes + source/currency additions\n│ └── upload.js ← NEW: POST /api/upload/csv\n└── frontend/\n ├── Dockerfile\n ├── package.json\n ├── vite.config.js\n ├── tailwind.config.js\n ├── postcss.config.js\n ├── index.html\n └── src/\n ├── main.jsx ← remove AuthProvider wrapper\n ├── index.css\n ├── App.jsx ← remove auth state, add Upload tab toggle\n └── components/\n ├── FilterBar.jsx ← add source filter select\n ├── PaymentTable.jsx ← add Source badge column + currency display\n ├── PaymentCard.jsx ← minor source badge addition\n ├── PaymentList.jsx ← unchanged\n └── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI\n```\n\n---\n\n## Database Schema (Prisma)\n\nFile: `backend/prisma/schema.prisma`\n\n```prisma\ngenerator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status { UNPROCESSED SENT SKIPPED }\nenum Source { INGEST UPLOAD }\n```\n\n**Key decisions:**\n- No `User` model — Authentik owns identity.\n- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.\n- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.\n- `balance` is always null for CSV rows (DSK export does not include running balance).\n- Fresh consolidated migration — no data migration from reference apps required.\n\n---\n\n## API Routes\n\n| Method | Path | Auth | Description |\n|--------|------|------|-------------|\n| GET | /api/health | public | Health check |\n| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |\n| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |\n| GET | /api/payments/meta/tags | required | All tags |\n| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |\n| GET | /api/payments/:id | required | Single payment |\n| PATCH | /api/payments/:id | required | Update status |\n| DELETE | /api/payments/:id | required | Delete |\n| POST | /api/payments/:id/send | required | Send notification |\n| POST | /api/payments/:id/skip | required | Skip |\n| POST | /api/payments/:id/tags | required | Add/upsert tag |\n| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |\n| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |\n\n---\n\n## Key Implementation Details\n\n### auth.js (replaces entire old auth module)\n```js\nconst PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n const username = req.headers['x-authentik-username'];\n if (!username) return res.status(401).json({ error: 'Unauthorized' });\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),\n };\n next();\n}\nmodule.exports = { authentikMiddleware };\n```\n\n### csvParser.js (port of dskuploader.py)\n- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8\n- `csv-parse` parses the decoded text with `columns: true`\n- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`\n- Card extraction: regex `/^\\d{6}x{6}\\d{4}$/` on first token of `Основание`\n- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`\n- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`\n- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`\n\n### payments.js changes from payments-logger\n1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call\n2. Add `source` to the `GET /` where clause filter\n3. Add `sources` to `meta/filters` response\n4. Currency-aware amount formatting in notification message\n5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)\n\n### upload.js (new)\n- `multer` memory storage, max 10 files × 10 MB\n- Calls `parseDskCsv(buffer)` per file\n- Upserts tags via `prisma.tag.upsert` then connects\n- Returns `{ imported, skipped, errors, payments[] }`\n\n### Frontend changes\n- **Delete**: `auth.js`, `AuthProvider.jsx`\n- **main.jsx**: Remove `<AuthProvider>` wrapper\n- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add \"Payments\" / \"Upload CSV\" tab toggle\n- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols\n- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell\n- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`\n\n---\n\n## Docker Compose\n\n```yaml\nservices:\n db:\n image: postgres:16-alpine\n environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: ${DB_PASSWORD}, POSTGRES_DB: finance_hub }\n volumes: [pgdata:/var/lib/postgresql/data]\n healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }\n\n backend:\n build: ./backend\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports: [\"${BACKEND_PORT:-3001}:3001\"]\n depends_on: { db: { condition: service_healthy } }\n\n frontend:\n build: ./frontend\n ports: [\"${FRONTEND_PORT:-5175}:5173\"]\n depends_on: [backend]\n\nvolumes: { pgdata: }\n```\n\n**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.\n\n---\n\n## Environment Variables (.env)\n\n```bash\nDB_PASSWORD=change_me\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\nTZ=Europe/Sofia\nBACKEND_PORT=3001\nFRONTEND_PORT=5175\n```\n\nRemoved vs payments-logger: `JWT_SECRET`, `JWT_EXPIRE_MINUTES`.\n\n---\n\n## Implementation Order\n\n1. Create folder structure and write `docker-compose.yml`, `.env.example`, `.gitignore`\n2. Write `backend/prisma/schema.prisma` and migration SQL\n3. Write `backend/package.json` (add `csv-parse`, `iconv-lite`, `multer`; remove `bcryptjs`, `jose`)\n4. Write `backend/Dockerfile`\n5. Write `backend/src/auth.js` (Authentik middleware)\n6. Copy `backend/src/parser.js` verbatim from payments-logger\n7. Write `backend/src/csvParser.js` (Python port)\n8. Write `backend/src/routes/upload.js`\n9. Write `backend/src/routes/payments.js` (from payments-logger + 5 changes listed above)\n10. Write `backend/src/index.js`\n11. Copy frontend base from payments-logger; delete `auth.js` + `AuthProvider.jsx`\n12. Update `main.jsx`, `App.jsx`, `FilterBar.jsx`, `PaymentTable.jsx`\n13. Write `frontend/src/components/UploadPanel.jsx`\n14. Update `frontend/vite.config.js`\n15. `docker compose build && docker compose up -d`\n16. Run verification checklist\n\n---\n\n## Verification\n\n**Schema**\n- `payments` table has `source`, `currency`, `debit_bgn`, `credit_bgn`, `transaction_type`, `payer_account`\n- No `users` table; `Source` enum exists\n\n**Auth**\n- `GET /api/payments` → 401 without `x-authentik-username` header\n- `POST /api/payments/ingest` → 201 without any header\n- `curl -H \"x-authentik-username: test\" localhost:3001/api/payments` → 200\n\n**SMS Ingest**\n- DSK POS SMS → `source=INGEST`, `currency=EUR`, correct amount/card/recipient\n- Apple Wallet structured body → `type=WALLET`, `source=INGEST`\n- Rate limiter → 429 after 200 req/min\n\n**CSV Upload**\n- Single DSK CSV → rows with `source=UPLOAD`, `currency=BGN`\n- Multiple CSVs in one request → all merged\n- `ТРАНСФЕР СОБСТВЕНИ СМЕТКИ` rows counted in `skipped`, not imported\n- Card regex match from `Основание` column\n- Auto-tags applied (ЗАПЛАТА→Salary, LIDL→Groceries)\n- cp1251 file imports correctly\n\n**UI**\n- Source badge visible in payment table (SMS indigo, CSV emerald)\n- Source dropdown in FilterBar filters correctly\n- Amount shows correct currency per row\n- Upload Panel: drag-and-drop works, result summary shows counts\n- Logout redirects to Authentik sign_out\n- No login form shown (Authentik handles it at NPM level)\n- Tags, send, skip, delete all still work\n\n## Reference Files\n\n- `/volume2/docker/finance/payments-logger/backend/src/routes/payments.js`\n- `/volume2/docker/finance/payments-logger/backend/src/parser.js`\n- `/volume2/docker/finance/payments-logger/backend/src/index.js`\n- `/volume2/docker/finance/payments-logger/backend/src/auth.js`\n- `/volume2/docker/finance/payments-logger/backend/prisma/schema.prisma`\n- `/volume2/docker/finance/payments-logger/frontend/src/App.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/PaymentTable.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/FilterBar.jsx`\n- `/volume2/docker/finance/dsk-uploader/dskuploader.py`\n- `/volume2/docker/finance/auth/docker-compose.yml`","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Claude’s Plan","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Stayed in plan mode","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good question. Here's the full breakdown:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Backend Tech Stack — Options","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Backend Tech Stack — Options","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Why:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"payments-logger is already Node.js/Express/Prisma. The new app is 80% payments-logger with CSV upload added on top. Keeping the same stack means:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"verbatim, zero rewrite","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy the entire","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"routes/payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with minimal edits","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Same Prisma schema workflow, same migrations, same Docker image","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The CSV parsing logic (the only Python-specific thing) ports cleanly to","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"csv-parse","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— it's just regex + string manipulation, nothing pandas-specific","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Trade-off:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Have to port the Python CSV parsing to JS. It's ~150 lines and mostly string manipulation — straightforward.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option B: Python + FastAPI + SQLAlchemy","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option B: Python + FastAPI + SQLAlchemy","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rewrite everything in Python. dsk-uploader is Python, so CSV parsing is already done.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep the dsk-uploader CSV logic as-is (no porting). Python has better data science libraries if you later add analytics.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Lose the entire payments-logger backend (routes, parser, Prisma schema) — full rewrite. FastAPI + SQLAlchemy is a different mental model than Express + Prisma. Frontend stays React anyway, so the stack split doesn't simplify anything.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"More work overall, gains almost nothing.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep Node.js as the main API, add a separate Python FastAPI service just for CSV parsing. They share the DB.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Zero porting — Python CSV code used as-is.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two backend services to maintain, deploy, and keep in sync. Inter-service HTTP calls. Two Dockerfiles. For ~150 lines of CSV logic, this is massively over-engineered.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Not worth it.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Extend dsk-uploader into a full payments app.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pandas for CSV, no porting.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Jinja2 templates instead of React (or add React separately). Would need to reimplement the entire payments-logger (SMS parser, notification system, tag management, pagination/filtering). Flask's Jinja templating is far less capable than the existing React UI. The React frontend is the stronger UI foundation.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Worst of all options — rebuild the harder parts (UI, SMS parser, notification) for no gain.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Summary","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Summary","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"CSV porting effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"App rewrite effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Result 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Everything else in the plan reuses payments-logger code directly. That's why Node.js is the clear winner here.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Want to adjust the stack, or shall I proceed with Option A?","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ok sounds good. Implement all you suggested","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Starting implementation. Let me first read all the reference files I'll need to copy from.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"payments.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"App.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"App.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"FilterBar.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"FilterBar.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentTable.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentTable.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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payments-logger.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.css","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.css","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"vite.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"vite.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"tailwind.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"tailwind.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"postcss.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"postcss.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Let me also grab the remaining frontend components.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentCard.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentCard.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentList.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentList.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"schema.prisma","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"schema.prisma","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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Let me set up the todo list and start building.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create finance-hub directory structure","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"mkdir -p /volume2/docker/finance/finance-hub/backend/src/routes \\\n /volume2/docker/finance/finance-hub/backend/prisma/migrations/20260508_init \\\n /volume2/docker/finance/finance-hub/frontend/src/components && echo \"done\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":24,"on_screen":false,"help_text":"Copy code","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"OUT","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"done","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"docker-compose.yml","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"docker-compose.yml","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"45 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"version: '3.8'\n\nservices:\n db:\n image: postgres:16-alpine\n restart: unless-stopped\n environment:\n POSTGRES_USER: finance\n POSTGRES_PASSWORD: ${DB_PASSWORD}\n POSTGRES_DB: finance_hub\n volumes:\n - pgdata:/var/lib/postgresql/data\n healthcheck:\n test: [\"CMD-SHELL\", \"pg_isready -U finance -d finance_hub\"]\n interval: 5s\n timeout: 5s\n retries: 5\n\n backend:\n build: ./backend\n restart: unless-stopped\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports:\n - \"${BACKEND_PORT:-3001}:3001\"\n depends_on:\n db:\n condition: service_healthy\n\n frontend:\n build: ./frontend\n restart: unless-stopped\n ports:\n - \"${FRONTEND_PORT:-5175}:5173\"\n depends_on:\n - backend\n\nvolumes:\n pgdata:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".env.example","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".env.example","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"15 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Database\nDB_PASSWORD=change_me_strong_password\n\n# Notifier service (for SMS payment notifications)\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\n\n# Timezone (used by SMS parser for Bulgarian bank timestamps)\nTZ=Europe/Sofia\n\n# Ports (optional — defaults shown)\nBACKEND_PORT=3001\nFRONTEND_PORT=5175","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".gitignore","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".gitignore","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"5 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env\nnode_modules/\ndist/\n*.log","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"schema.prisma","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"schema.prisma","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"54 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"generator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status {\n UNPROCESSED\n SENT\n SKIPPED\n}\n\nenum Source {\n INGEST\n UPLOAD\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration.sql","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration.sql","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"55 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- CreateEnum\nCREATE TYPE \"Status\" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');\nCREATE TYPE \"Source\" AS ENUM ('INGEST', 'UPLOAD');\n\n-- CreateTable\nCREATE TABLE \"payments\" (\n \"id\" SERIAL PRIMARY KEY,\n \"raw_message\" TEXT NOT NULL,\n \"date\" TIMESTAMP(3),\n \"type\" TEXT,\n \"card\" TEXT,\n \"recipient\" TEXT,\n \"amount\" DOUBLE PRECISION,\n \"currency\" TEXT DEFAULT 'EUR',\n \"balance\" DOUBLE PRECISION,\n \"source\" \"Source\" NOT NULL DEFAULT 'INGEST',\n \"status\" \"Status\" NOT NULL DEFAULT 'UNPROCESSED',\n \"notified_at\" TIMESTAMP(3),\n \"notify_phone\" TEXT,\n \"debit_bgn\" DOUBLE PRECISION,\n \"credit_bgn\" DOUBLE PRECISION,\n \"transaction_type\" TEXT,\n \"payer_account\" TEXT,\n \"created_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,\n \"updated_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP\n);\n\n-- CreateTable\nCREATE TABLE \"tags\" (\n \"id\" SERIAL PRIMARY KEY,\n \"name\" TEXT NOT NULL,\n \"color\" TEXT NOT NULL DEFAULT '#6b7280'\n);\n\n-- CreateUniqueIndex\nCREATE UNIQUE INDEX \"tags_name_key\" ON \"tags\"(\"name\");\n\n-- CreateTable (M2M join)\nCREATE TABLE \"_PaymentToTag\" (\n \"A\" INTEGER NOT NULL,\n \"B\" INTEGER NOT NULL,\n CONSTRAINT \"_PaymentToTag_AB_pkey\" PRIMARY KEY (\"A\", \"B\")\n);\n\nCREATE INDEX \"_PaymentToTag_B_index\" ON \"_PaymentToTag\"(\"B\");\n\n-- AddForeignKey\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_A_fkey\"\n FOREIGN KEY (\"A\") REFERENCES \"payments\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;\n\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_B_fkey\"\n FOREIGN KEY (\"B\") REFERENCES \"tags\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration_lock.toml","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration_lock.toml","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"4 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Please do not edit this file manually\n# It should be added in your version-control system (e.g., Git)\nprovider = \"postgresql\"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"26 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"{\n \"name\": \"finance-hub-backend\",\n \"version\": \"1.0.0\",\n \"main\": \"src/index.js\",\n \"scripts\": {\n \"start\": \"node src/index.js\",\n \"dev\": \"nodemon src/index.js\",\n \"prisma:generate\": \"prisma generate\",\n \"prisma:migrate\": \"prisma migrate deploy\"\n },\n \"dependencies\": {\n \"@prisma/client\": \"^5.22.0\",\n \"cors\": \"^2.8.5\",\n \"csv-parse\": \"^5.5.6\",\n \"express\": \"^4.21.1\",\n \"express-rate-limit\": \"^7.4.0\",\n \"iconv-lite\": \"^0.6.3\",\n \"morgan\": \"^1.10.0\",\n \"multer\": \"^1.4.5-lts.1\"\n },\n \"devDependencies\": {\n \"nodemon\": \"^3.1.7\",\n \"prisma\": \"^5.22.0\"\n }\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"18 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"FROM node:20-alpine\n\nRUN apk add --no-cache openssl\n\nWORKDIR /app\n\nCOPY package.json package-lock.json* ./\nRUN npm install\n\nCOPY prisma ./prisma\nRUN npx prisma generate\n\nCOPY src ./src\n\nEXPOSE 3001\n\nCMD [\"sh\", \"-c\", \"npx prisma migrate deploy && node src/index.js\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"auth.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"auth.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"27 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const PUBLIC_PATHS = new Set([\n '/api/health',\n '/api/payments/ingest',\n]);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n\n const username = req.headers['x-authentik-username'];\n if (!username) {\n return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });\n }\n\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '')\n .split(',')\n .map(g => g.trim())\n .filter(Boolean),\n };\n\n next();\n}\n\nmodule.exports = { authentikMiddleware };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"104 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/**\n * Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)\n *\n * Supported formats:\n *\n * POS / INTERNET / ECOM / P2P payment:\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.\n *\n * ATM withdrawal:\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.\n *\n * ATM utility payment (amount may include fee as AMOUNT/FEE):\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.\n */\n\nconst LOCAL_TZ = process.env.TZ || 'Europe/Sofia';\n\n/**\n * Convert a local-timezone date/time to a UTC Date object.\n * Uses Intl to resolve the actual UTC offset (DST-aware).\n */\nfunction localToUtc(year, month, day, hour, minute) {\n const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));\n\n const formatter = new Intl.DateTimeFormat('en-US', {\n timeZone: LOCAL_TZ,\n year: 'numeric', month: '2-digit', day: '2-digit',\n hour: '2-digit', minute: '2-digit', second: '2-digit',\n hour12: false,\n });\n\n const parts = {};\n formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });\n\n const localAtNaive = new Date(Date.UTC(\n parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),\n parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),\n ));\n\n const offsetMs = localAtNaive.getTime() - naive.getTime();\n return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);\n}\n\nfunction parsePaymentSms(message) {\n const result = {\n rawMessage: message,\n date: null,\n type: null,\n card: null,\n recipient: null,\n amount: null,\n balance: null,\n };\n\n // Date and time: \"Na DD/MM/YYYY v HH:MM\"\n const dateMatch = message.match(/Na (\\d{2})\\/(\\d{2})\\/(\\d{4}) v (\\d{2}):(\\d{2})/i);\n if (dateMatch) {\n const [, day, month, year, hour, minute] = dateMatch;\n result.date = localToUtc(\n parseInt(year), parseInt(month), parseInt(day),\n parseInt(hour), parseInt(minute),\n );\n }\n\n // Card mask: \"s karta 400915***4447\" or \"s karta 483890***7162\"\n const cardMatch = message.match(/s karta\\s+([\\d*]+)/i);\n if (cardMatch) {\n result.card = cardMatch[1];\n }\n\n // Transaction type: supports both prepositions\n // \"na POS\" / \"na ATM\" / \"na INTERNET\" etc. (payment)\n // \"ot ATM\" (withdrawal)\n const typeMatch = message.match(/(?:na|ot)\\s+(POS|ATM|INTERNET|ECOM|P2P)\\b/i);\n if (typeMatch) {\n result.type = typeMatch[1].toUpperCase();\n }\n\n // Recipient address: \"s adres: MERCHANT\" or \"s adres:MERCHANT\" (no space variant)\n const recipientMatch = message.match(/s adres:\\s*([^.]+)\\./i);\n if (recipientMatch) {\n result.recipient = recipientMatch[1].trim();\n }\n\n // Amount: handles both verbs and the AMOUNT/FEE suffix format\n // \"sa plateni 7.78 EUR\"\n // \"sa iztegleni 400.00 EUR\"\n // \"sa plateni 0.50 EUR/0.50 EUR\" → captures 0.50 (the charged amount, ignoring fee)\n const amountMatch = message.match(/sa (?:plateni|iztegleni)\\s+([\\d.,]+)\\s+[A-Z]{3}/i);\n if (amountMatch) {\n result.amount = parseFloat(amountMatch[1].replace(',', '.'));\n }\n\n // Balance: \"Nalichni: 2583.07 EUR.\"\n const balanceMatch = message.match(/Nalichni:\\s*([\\d.,]+)\\s+[A-Z]{3}/i);\n if (balanceMatch) {\n result.balance = parseFloat(balanceMatch[1].replace(',', '.'));\n }\n\n return result;\n}\n\nmodule.exports = { parsePaymentSms };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"csvParser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"csvParser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"175 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/**\n * DSK Bank CSV parser — Node.js port of dskuploader.py\n *\n * DSK Bank exports use Windows-1251 (cp1251) encoding.\n * Each row maps to a Payment record with source=UPLOAD, currency=BGN.\n */\n\nconst { parse } = require('csv-parse');\nconst iconv = require('iconv-lite');\n\nconst SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';\nconst CARD_REGEX = /^\\d{6}x{6}\\d{4}$/;\nconst POS_REGEX = /^\\s*ПЛАЩАНЕ\\s+НА\\s+ПОС\\s+\\d{2}\\.\\d{2}\\.\\d{4}\\s+\\d{2}:\\d{2}/;\n\nconst COL = {\n DATE: 'Дата',\n TYPE: 'Вид на трансакцията',\n REASON: 'Основание',\n DEBIT: 'Дебит BGN',\n CREDIT: 'Кредит BGN',\n PAYEE: 'Наредител/Получател',\n ACCT: 'Номер сметка на наредителя / получателя',\n};\n\nconst TAG_RULES = [\n ['reason', 'ЗАПЛАТА', 'Salary'],\n ['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],\n ['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],\n ['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],\n ['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],\n ['payee', 'VIVACOM', 'Subscriptions'],\n ['payee', 'Google', 'Subscriptions'],\n ['payee', 'SkyShowtime', 'Subscriptions'],\n ['payee', 'NETFLIX', 'Subscriptions'],\n ['payee', 'LUKOIL', 'Bills'],\n ['payee', 'CityGate', 'Bills'],\n ['payee', 'CBA', 'Groceries'],\n ['payee', 'FANTASTICO', 'Groceries'],\n ['payee', 'LIDL', 'Groceries'],\n];\n\nfunction parseNum(val) {\n if (val == null || val === '') return null;\n if (typeof val === 'number') return isNaN(val) ? null : val;\n const s = String(val).trim().replace(/\\xa0/g, '').replace(/ /g, '').replace(',', '.');\n const n = parseFloat(s);\n return isNaN(n) ? null : n;\n}\n\nfunction parseDate(val) {\n if (!val) return null;\n const s = String(val).trim();\n const m = s.match(/^(\\d{2})\\.(\\d{2})\\.(\\d{4})$/);\n if (m) {\n return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));\n }\n return null;\n}\n\nfunction processReasonAndCard(reason) {\n if (!reason || typeof reason !== 'string') return { reason: '', card: null };\n\n const parts = reason.trim().split(' ');\n let card = null;\n let cleanReason = reason.trim();\n\n if (parts[0] && CARD_REGEX.test(parts[0])) {\n card = parts[0];\n cleanReason = parts.slice(1).join(' ').trim();\n }\n\n if (POS_REGEX.test(cleanReason)) {\n const posParts = cleanReason.split('<br/>');\n try {\n const dateTime = posParts[0].split('ПОС ')[1];\n cleanReason = `POS PAYMENT ${dateTime}`;\n } catch (_) { /* keep original */ }\n }\n\n return { reason: cleanReason.replace(/\\s+/g, ' ').trim(), card };\n}\n\nfunction generateTags(fields) {\n const tags = new Set();\n for (const [field, keyword, tagName] of TAG_RULES) {\n if ((fields[field] || '').includes(keyword)) {\n tags.add(tagName);\n }\n }\n return Array.from(tags);\n}\n\nfunction processRow(row) {\n const transactionType = (row[COL.TYPE] || '').trim();\n if (transactionType === SKIP_TYPE) return null;\n\n const { reason, card } = processReasonAndCard(row[COL.REASON]);\n const payee = (row[COL.PAYEE] || '').trim();\n const payerAccount = (row[COL.ACCT] || '').trim();\n const debitBgn = parseNum(row[COL.DEBIT]);\n const creditBgn = parseNum(row[COL.CREDIT]);\n const date = parseDate(row[COL.DATE]);\n\n const autoTags = generateTags({ reason, transactionType, payee, debitBgn, creditBgn });\n\n const amount = debitBgn ?? creditBgn ?? null;\n\n const rawMessage = [\n row[COL.DATE] && `Date: ${row[COL.DATE]}`,\n transactionType && `Type: ${transactionType}`,\n payee && `Payee: ${payee}`,\n debitBgn != null && `Debit: ${debitBgn} BGN`,\n creditBgn != null && `Credit: ${creditBgn} BGN`,\n ].filter(Boolean).join(' | ');\n\n return {\n rawMessage,\n date,\n type: null,\n card,\n recipient: payee || null,\n amount,\n currency: 'BGN',\n balance: null,\n source: 'UPLOAD',\n debitBgn,\n creditBgn,\n transactionType: transactionType || null,\n payerAccount: payerAccount || null,\n autoTags,\n };\n}\n\n/**\n * Parse a Buffer containing a DSK Bank CSV (cp1251 or UTF-8).\n * Returns { rows, skipped, errors }.\n */\nasync function parseDskCsv(buffer) {\n // Try cp1251 first (DSK Bank export encoding), fall back to UTF-8\n let text = iconv.decode(buffer, 'cp1251');\n if (!text.includes(COL.DATE)) {\n text = buffer.toString('utf-8');\n }\n\n return new Promise((resolve, reject) => {\n const rows = [];\n const errors = [];\n let skipped = 0;\n\n const parser = parse(text, {\n columns: true,\n skip_empty_lines: true,\n trim: true,\n relax_column_count: true,\n });\n\n parser.on('readable', () => {\n let record;\n while ((record = parser.read()) !== null) {\n try {\n const row = processRow(record);\n if (row === null) { skipped++; } else { rows.push(row); }\n } catch (err) {\n errors.push(err.message);\n }\n }\n });\n\n parser.on('error', reject);\n parser.on('end', () => resolve({ rows, skipped, errors }));\n });\n}\n\nmodule.exports = { parseDskCsv };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"39 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst cors = require('cors');\nconst morgan = require('morgan');\nconst rateLimit = require('express-rate-limit');\nconst { authentikMiddleware } = require('./auth');\nconst paymentsRouter = require('./routes/payments');\nconst uploadRouter = require('./routes/upload');\n\nconst app = express();\nconst PORT = process.env.PORT || 3001;\n\napp.use(cors());\napp.use(express.json({ limit: '16kb' }));\napp.use(morgan('combined'));\n\n// Rate-limit the public ingest endpoint before auth middleware\nconst ingestLimiter = rateLimit({\n windowMs: 60 * 1000,\n max: 200,\n standardHeaders: true,\n legacyHeaders: false,\n message: { error: 'Too many requests, slow down' },\n});\napp.use('/api/payments/ingest', ingestLimiter);\n\n// Authentik header auth (skips /api/health and /api/payments/ingest)\napp.use(authentikMiddleware);\n\napp.get('/api/health', (_req, res) => {\n res.json({ status: 'ok', timestamp: new Date().toISOString() });\n});\n\napp.use('/api/payments', paymentsRouter);\napp.use('/api/upload', uploadRouter);\n\napp.listen(PORT, '0.0.0.0', () => {\n console.log(`Finance Hub API running on port ${PORT}`);\n});","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"payments.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"399 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst { PrismaClient } = require('@prisma/client');\nconst { parsePaymentSms } = require('../parser');\n\nconst router = express.Router();\nconst prisma = new PrismaClient();\n\nconst NOTIFIER_URL = process.env.NOTIFIER_URL;\nconst NOTIFIER_CHANNEL = process.env.NOTIFIER_CHANNEL || 'viber';\nconst DEFAULT_PHONE = process.env.NOTIFY_DEFAULT_PHONE;\n\n// ── Helpers ───────────────────────────────────────────────────────────────────\n\nfunction parseId(raw) {\n const id = parseInt(raw, 10);\n return Number.isFinite(id) ? id : null;\n}\n\nfunction formatNotifyMessage(payment) {\n const currency = payment.currency || 'EUR';\n const parts = [];\n if (payment.amount != null) parts.push(`Amount: ${payment.amount.toFixed(2)} ${currency}`);\n if (payment.recipient) parts.push(`At: ${payment.recipient}`);\n if (payment.balance != null) parts.push(`Balance: ${payment.balance.toFixed(2)} ${currency}`);\n if (payment.date) parts.push(`Date: ${new Date(payment.date).toLocaleString('en-GB')}`);\n return parts.join('\\n');\n}\n\nasync function sendNotification(payment) {\n if (!NOTIFIER_URL) {\n console.warn('[NOTIFY] NOTIFIER_URL not set — skipping notification');\n return;\n }\n\n const phone = payment.notifyPhone || DEFAULT_PHONE;\n if (!phone) {\n console.warn('[NOTIFY] No phone number for payment #' + payment.id + ' and NOTIFY_DEFAULT_PHONE not set');\n return;\n }\n\n const body = {\n phone,\n notification: NOTIFIER_CHANNEL,\n message: formatNotifyMessage(payment),\n };\n\n const res = await fetch(NOTIFIER_URL, {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify(body),\n });\n\n if (!res.ok) {\n const text = await res.text().catch(() => '');\n throw new Error(`Notifier responded ${res.status}: ${text}`);\n }\n}\n\n// ── Ingest a payment (public — no auth) ──────────────────────────────────────\n//\n// Two modes:\n//\n// SMS mode (default):\n// { \"message\": \"<raw SMS text>\", \"notifyPhone\": \"...\" }\n//\n// Structured mode (Apple Wallet / manual):\n// { \"ingestMode\": \"apple_wallet\", \"amount\": 7.78, \"recipient\": \"Apple Store\",\n// \"type\": \"WALLET\", \"card\": \"••••4447\", \"date\": \"2026-02-22T10:30:00Z\" }\n//\nrouter.post('/ingest', async (req, res) => {\n try {\n const { message, notifyPhone, ingestMode } = req.body;\n\n let data;\n\n if (ingestMode === 'apple_wallet' || (!message && req.body.amount != null)) {\n // ── Structured / Apple Wallet mode ──────────────────────────────────────\n const { amount, recipient, type, card, date, balance } = req.body;\n if (amount == null || !recipient) {\n return res.status(400).json({ error: 'amount and recipient are required for structured ingest' });\n }\n\n const rawMessage = [\n `Source: ${ingestMode || 'structured'}`,\n `Amount: ${amount}`,\n recipient && `Recipient: ${recipient}`,\n type && `Type: ${type}`,\n card && `Card: ${card}`,\n ].filter(Boolean).join(' | ');\n\n data = {\n rawMessage,\n date: date ? new Date(date) : new Date(),\n type: type || 'WALLET',\n card: card || null,\n recipient,\n amount: parseFloat(amount),\n currency: 'EUR',\n balance: balance != null ? parseFloat(balance) : null,\n source: 'INGEST',\n notifyPhone: notifyPhone || null,\n };\n\n } else {\n // ── SMS mode ─────────────────────────────────────────────────────────────\n if (!message) {\n return res.status(400).json({ error: 'message is required' });\n }\n if (typeof message !== 'string' || message.length > 2000) {\n return res.status(400).json({ error: 'message must be a string under 2000 characters' });\n }\n\n const parsed = parsePaymentSms(message);\n data = {\n rawMessage: parsed.rawMessage,\n date: parsed.date,\n type: parsed.type,\n card: parsed.card,\n recipient: parsed.recipient,\n amount: parsed.amount,\n currency: 'EUR',\n balance: parsed.balance,\n source: 'INGEST',\n notifyPhone: notifyPhone || null,\n };\n }\n\n const payment = await prisma.payment.create({\n data,\n include: { tags: true },\n });\n\n res.status(201).json(payment);\n } catch (err) {\n console.error('Ingest error:', err);\n res.status(500).json({ error: 'Failed to ingest payment' });\n }\n});\n\n// ── List payments with filtering ──────────────────────────────────────────────\nrouter.get('/', async (req, res) => {\n try {\n const {\n status,\n type,\n tag,\n source,\n recipient,\n dateFrom,\n dateTo,\n search,\n sortBy = 'createdAt',\n sortDir = 'desc',\n page = 1,\n } = req.query;\n\n const limit = Math.min(parseInt(req.query.limit, 10) || 50, 200);\n\n const where = {};\n\n if (status) where.status = status;\n if (type) where.type = type;\n if (source) where.source = source;\n if (recipient) where.recipient = { contains: recipient, mode: 'insensitive' };\n if (tag) where.tags = { some: { name: tag } };\n if (search) {\n where.OR = [\n { rawMessage: { contains: search, mode: 'insensitive' } },\n { recipient: { contains: search, mode: 'insensitive' } },\n ];\n }\n if (dateFrom || dateTo) {\n where.date = {};\n if (dateFrom) where.date.gte = new Date(dateFrom);\n if (dateTo) where.date.lte = new Date(dateTo);\n }\n\n const allowedSortFields = ['date', 'amount', 'balance', 'recipient', 'type', 'source', 'createdAt', 'status'];\n const orderField = allowedSortFields.includes(sortBy) ? sortBy : 'createdAt';\n const orderDir = sortDir === 'asc' ? 'asc' : 'desc';\n\n const skip = (parseInt(page, 10) - 1) * limit;\n\n const [payments, total] = await Promise.all([\n prisma.payment.findMany({\n where,\n include: { tags: true },\n orderBy: { [orderField]: orderDir },\n skip,\n take: limit,\n }),\n prisma.payment.count({ where }),\n ]);\n\n res.json({ payments, total, page: parseInt(page, 10), limit });\n } catch (err) {\n console.error('List error:', err);\n res.status(500).json({ error: 'Failed to list payments' });\n }\n});\n\n// ── Get filter options ────────────────────────────────────────────────────────\nrouter.get('/meta/filters', async (_req, res) => {\n try {\n const [types, recipients, tags, sources] = await Promise.all([\n prisma.payment.findMany({ distinct: ['type'], select: { type: true }, where: { type: { not: null } } }),\n prisma.payment.findMany({ distinct: ['recipient'], select: { recipient: true }, where: { recipient: { not: null } } }),\n prisma.tag.findMany({ orderBy: { name: 'asc' } }),\n prisma.payment.findMany({ distinct: ['source'], select: { source: true } }),\n ]);\n\n res.json({\n types: types.map(t => t.type),\n recipients: recipients.map(r => r.recipient),\n tags,\n sources: sources.map(s => s.source),\n });\n } catch (err) {\n res.status(500).json({ error: 'Failed to get filters' });\n }\n});\n\n// ── Get all tags ──────────────────────────────────────────────────────────────\nrouter.get('/meta/tags', async (_req, res) => {\n try {\n const tags = await prisma.tag.findMany({ orderBy: { name: 'asc' } });\n res.json(tags);\n } catch (err) {\n res.status(500).json({ error: 'Failed to list tags' });\n }\n});\n\n// ── Get single payment ────────────────────────────────────────────────────────\nrouter.get('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({\n where: { id },\n include: { tags: true },\n });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n res.json(payment);\n } catch (err) {\n console.error('Get error:', err);\n res.status(500).json({ error: 'Failed to get payment' });\n }\n});\n\n// ── Update payment metadata (status) ─────────────────────────────────────────\nrouter.patch('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const { status } = req.body;\n const data = {};\n\n if (status) {\n const validStatuses = ['UNPROCESSED', 'SENT', 'SKIPPED'];\n if (!validStatuses.includes(status)) {\n return res.status(400).json({ error: `Invalid status. Must be one of: ${validStatuses.join(', ')}` });\n }\n data.status = status;\n }\n\n if (Object.keys(data).length === 0) {\n return res.status(400).json({ error: 'No valid fields to update' });\n }\n\n const updated = await prisma.payment.update({\n where: { id },\n data,\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n if (err.code === 'P2025') return res.status(404).json({ error: 'Not found' });\n console.error('Update error:', err);\n res.status(500).json({ error: 'Failed to update payment' });\n }\n});\n\n// ── Delete payment ───────────────────────────────────────────────────────────\nrouter.delete('/:id', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n await prisma.payment.delete({ where: { id } });\n res.json({ success: true });\n } catch (err) {\n if (err.code === 'P2025') return res.status(404).json({ error: 'Not found' });\n console.error('Delete error:', err);\n res.status(500).json({ error: 'Failed to delete payment' });\n }\n});\n\n// ── Send notification (mark as SENT + call notifier service) ─────────────────\nrouter.post('/:id/send', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({ where: { id } });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n if (payment.status !== 'UNPROCESSED') {\n return res.status(409).json({ error: `Payment is already ${payment.status.toLowerCase()}` });\n }\n\n await sendNotification(payment);\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { status: 'SENT', notifiedAt: new Date() },\n include: { tags: true },\n });\n\n res.json(updated);\n } catch (err) {\n console.error('Send error:', err);\n res.status(500).json({ error: 'Failed to send notification' });\n }\n});\n\n// ── Skip notification (mark as SKIPPED) ──────────────────────────────────────\nrouter.post('/:id/skip', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const payment = await prisma.payment.findUnique({ where: { id } });\n if (!payment) return res.status(404).json({ error: 'Not found' });\n if (payment.status !== 'UNPROCESSED') {\n return res.status(409).json({ error: `Payment is already ${payment.status.toLowerCase()}` });\n }\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { status: 'SKIPPED' },\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n console.error('Skip error:', err);\n res.status(500).json({ error: 'Failed to skip payment' });\n }\n});\n\n// ── Add tag to payment ────────────────────────────────────────────────────────\nrouter.post('/:id/tags', async (req, res) => {\n const id = parseId(req.params.id);\n if (id === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const { name, color } = req.body;\n if (!name) return res.status(400).json({ error: 'tag name is required' });\n\n const tag = await prisma.tag.upsert({\n where: { name },\n update: {},\n create: { name, color: color || '#6b7280' },\n });\n\n const updated = await prisma.payment.update({\n where: { id },\n data: { tags: { connect: { id: tag.id } } },\n include: { tags: true },\n });\n\n res.json(updated);\n } catch (err) {\n console.error('Tag error:', err);\n res.status(500).json({ error: 'Failed to add tag' });\n }\n});\n\n// ── Remove tag from payment ───────────────────────────────────────────────────\nrouter.delete('/:id/tags/:tagId', async (req, res) => {\n const id = parseId(req.params.id);\n const tagId = parseId(req.params.tagId);\n if (id === null || tagId === null) return res.status(400).json({ error: 'Invalid id' });\n\n try {\n const updated = await prisma.payment.update({\n where: { id },\n data: { tags: { disconnect: { id: tagId } } },\n include: { tags: true },\n });\n res.json(updated);\n } catch (err) {\n console.error('Remove tag error:', err);\n res.status(500).json({ error: 'Failed to remove tag' });\n }\n});\n\nmodule.exports = router;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"upload.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"upload.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"89 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst multer = require('multer');\nconst { PrismaClient } = require('@prisma/client');\nconst { parseDskCsv } = require('../csvParser');\n\nconst router = express.Router();\nconst prisma = new PrismaClient();\n\nconst upload = multer({\n storage: multer.memoryStorage(),\n limits: { fileSize: 10 * 1024 * 1024, files: 10 },\n fileFilter: (_req, file, cb) => {\n if (file.mimetype === 'text/csv' || file.originalname.toLowerCase().endsWith('.csv')) {\n cb(null, true);\n } else {\n cb(new Error('Only CSV files are accepted'));\n }\n },\n});\n\n// POST /api/upload/csv\n// Accepts 1-10 CSV files, parses them, stores to DB with source=UPLOAD.\n// Returns { imported, skipped, errors, payments[] }\nrouter.post('/csv', upload.array('files', 10), async (req, res) => {\n if (!req.files || req.files.length === 0) {\n return res.status(400).json({ error: 'No files uploaded' });\n }\n\n const allRows = [];\n const allErrors = [];\n let totalSkipped = 0;\n\n for (const file of req.files) {\n try {\n const { rows, skipped, errors } = await parseDskCsv(file.buffer);\n allRows.push(...rows);\n totalSkipped += skipped;\n allErrors.push(...errors.map(e => `${file.originalname}: ${e}`));\n } catch (err) {\n allErrors.push(`${file.originalname}: ${err.message}`);\n }\n }\n\n if (allRows.length === 0) {\n return res.status(422).json({\n error: 'No importable rows found',\n skipped: totalSkipped,\n errors: allErrors,\n });\n }\n\n const created = [];\n\n for (const row of allRows) {\n const { autoTags, ...paymentData } = row;\n try {\n const tagConnects = [];\n for (const tagName of autoTags) {\n const tag = await prisma.tag.upsert({\n where: { name: tagName },\n update: {},\n create: { name: tagName, color: '#6b7280' },\n });\n tagConnects.push({ id: tag.id });\n }\n\n const payment = await prisma.payment.create({\n data: {\n ...paymentData,\n ...(tagConnects.length ? { tags: { connect: tagConnects } } : {}),\n },\n include: { tags: true },\n });\n created.push(payment);\n } catch (err) {\n allErrors.push(`Row insert failed: ${err.message}`);\n }\n }\n\n res.status(201).json({\n imported: created.length,\n skipped: totalSkipped,\n errors: allErrors,\n payments: created,\n });\n});\n\nmodule.exports = router;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now writing all frontend config files:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"24 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"{\n \"name\": \"finance-hub-frontend\",\n \"version\": \"1.0.0\",\n \"type\": \"module\",\n \"scripts\": {\n \"dev\": \"vite\",\n \"build\": \"vite build\",\n \"preview\": \"vite preview\"\n },\n \"dependencies\": {\n \"lucide-react\": \"^0.460.0\",\n \"react\": \"^18.3.1\",\n \"react-dom\": \"^18.3.1\"\n },\n \"devDependencies\": {\n \"@types/react\": \"^18.3.12\",\n \"@vitejs/plugin-react\": \"^4.3.4\",\n \"autoprefixer\": \"^10.4.20\",\n \"postcss\": \"^8.4.49\",\n \"tailwindcss\": \"^3.4.15\",\n \"vite\": \"^6.0.1\"\n }\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"13 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"FROM node:20-alpine\n\nWORKDIR /app\n\nCOPY package.json package-lock.json* ./\nRUN npm install\n\nCOPY . .\n\nEXPOSE 5173\n\nCMD [\"npm\", \"run\", \"dev\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"vite.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"vite.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"18 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import { defineConfig } from 'vite';\nimport react from '@vitejs/plugin-react';\n\nexport default defineConfig({\n plugins: [react()],\n server: {\n host: '0.0.0.0',\n port: 5173,\n allowedHosts: ['finance-hub.lakylak.xyz'],\n proxy: {\n '/api': {\n target: 'http://backend:3001',\n changeOrigin: true,\n },\n },\n },\n});","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"tailwind.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"tailwind.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"12 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/** @type {import('tailwindcss').Config} */\nexport default {\n content: [\n \"./index.html\",\n \"./src/**/*.{js,ts,jsx,tsx}\",\n ],\n theme: {\n extend: {},\n },\n plugins: [],\n};","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"postcss.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"postcss.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"7 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"export default {\n plugins: {\n tailwindcss: {},\n autoprefixer: {},\n },\n};","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.html","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.html","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"14 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"<!DOCTYPE html>\n<html lang=\"en\">\n <head>\n <meta charset=\"UTF-8\" />\n <meta name=\"viewport\" content=\"width=device-width, initial-scale=1.0\" />\n <title>Finance Hub</title>\n <link rel=\"icon\" type=\"image/svg+xml\" href=\"data:image/svg+xml,<svg xmlns='http://www.w3.org/2000/svg' viewBox='0 0 100 100'><text y='.9em' font-size='90'>💰</text></svg>\" />\n </head>\n <body class=\"bg-gray-50 min-h-screen\">\n <div id=\"root\"></div>\n <script type=\"module\" src=\"/src/main.jsx\"></script>\n </body>\n</html>","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.css","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.css","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"4 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"@tailwind base;\n@tailwind components;\n@tailwind utilities;","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now writing all React components:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"11 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React from 'react';\nimport ReactDOM from 'react-dom/client';\nimport App from './App';\nimport './index.css';\n\nReactDOM.createRoot(document.getElementById('root')).render(\n <React.StrictMode>\n <App />\n </React.StrictMode>\n);","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"App.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"App.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"257 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"import React, { useState, useEffect, useCallback } from 'react';\nimport { LayoutDashboard, Upload, RefreshCw, LogOut } from 'lucide-react';\nimport FilterBar from './components/FilterBar';\nimport PaymentTable from './components/PaymentTable';\nimport UploadPanel from './components/UploadPanel';\n\nconst API_BASE = '/api/payments';\n\nexport default function App() {\n const [activeTab, setActiveTab] = useState('payments');\n const [payments, setPayments] = useState([]);\n const [total, setTotal] = useState(0);\n const [page, setPage] = useState(1);\n const [filters, setFilters] = useState({});\n const [sortBy, setSortBy] = useState('createdAt');\n const [sortDir, setSortDir] = useState('desc');\n const [filterOptions, setFilterOptions] = useState({ types: [], recipients: [], tags: [], sources: [] });\n const [loading, setLoading] = useState(false);\n\n const fetchPayments = useCallback(async () => {\n setLoading(true);\n try {\n const params = new URLSearchParams();\n params.set('page', page);\n params.set('limit', 50);\n params.set('sortBy', sortBy);\n params.set('sortDir', sortDir);\n Object.entries(filters).forEach(([key, val]) => {\n if (val) params.set(key, val);\n });\n const res = await fetch(`${API_BASE}?${params}`);\n const data = await res.json();\n setPayments(data.payments || []);\n setTotal(data.total || 0);\n } catch (err) {\n console.error('Failed to fetch payments:', err);\n } finally {\n setLoading(false);\n }\n }, [page, filters, sortBy, sortDir]);\n\n const fetchFilterOptions = useCallback(async () => {\n try {\n const res = await fetch(`${API_BASE}/meta/filters`);\n const data = await res.json();\n setFilterOptions(data);\n } catch (err) {\n console.error('Failed to fetch filter options:', err);\n }\n }, []);\n\n useEffect(() => {\n fetchPayments();\n }, [fetchPayments]);\n\n useEffect(() => {\n fetchFilterOptions();\n }, [fetchFilterOptions]);\n\n // Refresh payments list after a successful CSV upload\n const handleUploadSuccess = () => {\n fetchPayments();\n fetchFilterOptions();\n setActiveTab('payments');\n };\n\n const handleAction = async (id, action) => {\n try {\n await fetch(`${API_BASE}/${id}/${action}`, { method: 'POST' });\n fetchPayments();\n fetchFilterOptions();\n } catch (err) {\n console.error(`Failed to ${action} payment:`, err);\n }\n };\n\n const handleAddTag = async (id, tagName, tagColor) => {\n try {\n await fetch(`${API_BASE}/${id}/tags`, {\n method: 'POST',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify({ name: tagName, color: tagColor }),\n });\n fetchPayments();\n fetchFilterOptions();\n } catch (err) {\n console.error('Failed to add tag:', err);\n }\n };\n\n const handleRemoveTag = async (paymentId, tagId) => {\n try {\n await fetch(`${API_BASE}/${paymentId}/tags/${tagId}`, { method: 'DELETE' });\n fetchPayments();\n } catch (err) {\n console.error('Failed to remove tag:', err);\n }\n };\n\n const handleDelete = async (id) => {\n try {\n await fetch(`${API_BASE}/${id}`, { method: 'DELETE' });\n fetchPayments();\n fetchFilterOptions();\n } catch (err) {\n console.error('Failed to delete payment:', err);\n }\n };\n\n const handleUpdateStatus = async (id, status) => {\n try {\n await fetch(`${API_BASE}/${id}`, {\n method: 'PATCH',\n headers: { 'Content-Type': 'application/json' },\n body: JSON.stringify({ status }),\n });\n fetchPayments();\n } catch (err) {\n console.error('Failed to update status:', err);\n }\n };\n\n const handleFilterChange = (newFilters) => {\n setFilters(newFilters);\n setPage(1);\n };\n\n const handleSort = (field) => {\n if (sortBy === field) {\n setSortDir(d => d === 'asc' ? 'desc' : 'asc');\n } else {\n setSortBy(field);\n setSortDir('desc');\n }\n setPage(1);\n };\n\n const totalPages = Math.ceil(total / 50);\n\n return (\n <div className=\"min-h-screen bg-gray-50\">\n <header className=\"bg-white border-b border-gray-200 shadow-sm\">\n <div className=\"max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-4\">\n <div className=\"flex items-center justify-between\">\n <div className=\"flex items-center gap-3\">\n <div className=\"bg-indigo-600 p-2 rounded-lg\">\n <LayoutDashboard className=\"w-6 h-6 text-white\" />\n </div>\n <div>\n <h1 className=\"text-xl font-bold text-gray-900\">Finance Hub</h1>\n <p className=\"text-sm text-gray-500\">{total} transaction{total !== 1 ? 's' : ''} total</p>\n </div>\n </div>\n\n <div className=\"flex items-center gap-2\">\n {/* Tab switcher */}\n <div className=\"flex items-center rounded-lg border border-gray-200 bg-gray-50 p-1 gap-1\">\n <button\n onClick={() => setActiveTab('payments')}\n className={`flex items-center gap-1.5 px-3 py-1.5 text-sm font-medium rounded-md transition-colors ${\n activeTab === 'payments'\n ? 'bg-white text-indigo-700 shadow-sm'\n : 'text-gray-600 hover:text-gray-900'\n }`}\n >\n <LayoutDashboard className=\"w-4 h-4\" />\n Payments\n </button>\n <button\n onClick={() => setActiveTab('upload')}\n className={`flex items-center gap-1.5 px-3 py-1.5 text-sm font-medium rounded-md transition-colors ${\n activeTab === 'upload'\n ? 'bg-white text-emerald-700 shadow-sm'\n : 'text-gray-600 hover:text-gray-900'\n }`}\n >\n <Upload className=\"w-4 h-4\" />\n Upload CSV\n </button>\n </div>\n\n {activeTab === 'payments' && (\n <button\n onClick={() => { fetchPayments(); fetchFilterOptions(); }}\n className=\"flex items-center gap-2 px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 transition-colors\"\n >\n <RefreshCw className={`w-4 h-4 ${loading ? 'animate-spin' : ''}`} />\n Refresh\n </button>\n )}\n\n <button\n onClick={() => { window.location.href = '/outpost.goauthentik.io/sign_out'; }}\n className=\"flex items-center gap-2 px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 transition-colors\"\n title=\"Sign out\"\n >\n <LogOut className=\"w-4 h-4\" />\n </button>\n </div>\n </div>\n </div>\n </header>\n\n <main className=\"max-w-7xl mx-auto px-4 sm:px-6 lg:px-8 py-6\">\n {activeTab === 'payments' ? (\n <>\n <FilterBar\n filters={filters}\n filterOptions={filterOptions}\n onFilterChange={handleFilterChange}\n />\n\n <PaymentTable\n payments={payments}\n loading={loading}\n sortBy={sortBy}\n sortDir={sortDir}\n onSort={handleSort}\n onSend={(id) => handleAction(id, 'send')}\n onSkip={(id) => handleAction(id, 'skip')}\n onAddTag={handleAddTag}\n onRemoveTag={handleRemoveTag}\n onDelete={handleDelete}\n onUpdateStatus={handleUpdateStatus}\n existingTags={filterOptions.tags}\n />\n\n {totalPages > 1 && (\n <div className=\"flex items-center justify-center gap-2 mt-6\">\n <button\n onClick={() => setPage(p => Math.max(1, p - 1))}\n disabled={page === 1}\n className=\"px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 disabled:opacity-50 disabled:cursor-not-allowed\"\n >\n Previous\n </button>\n <span className=\"text-sm text-gray-600\">\n Page {page} of {totalPages}\n </span>\n <button\n onClick={() => setPage(p => Math.min(totalPages, p + 1))}\n disabled={page === totalPages}\n className=\"px-3 py-2 text-sm font-medium text-gray-700 bg-white border border-gray-300 rounded-lg hover:bg-gray-50 disabled:opacity-50 disabled:cursor-not-allowed\"\n >\n Next\n </button>\n </div>\n )}\n </>\n ) : (\n <UploadPanel onUploadSuccess={handleUploadSuccess} />\n )}\n </main>\n </div>\n );\n}","depth":25,"on_screen":false,"role_description":"text"}]...
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G)
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
# ── Database ───────────────────────────────────────────────────────────────────
[ENV_SECRET]
# ── Notifier service ──────────────────────────────────────────────────────────
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
auth.js
auth.js
27 lines
const PUBLIC_PATHS = new Set([
'/api/health',
'/api/payments/ingest',
]);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) {
return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });
}
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '')
.split(',')
.map(g => g.trim())
.filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
Write
parser.js
parser.js
104 lines
/**
* Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)
*
* Supported formats:
*
* POS / INTERNET / ECOM / P2P payment:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM withdrawal:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM utility payment (amount may include fee as AMOUNT/FEE):
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.
*/
const LOCAL_TZ = process.env.TZ || 'Europe/Sofia';
/**
* Convert a local-timezone date/time to a UTC Date object.
* Uses Intl to resolve the actual UTC offset (DST-aware).
*/
function localToUtc(year, month, day, hour, minute) {
const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));
const formatter = new Intl.DateTimeFormat('en-US', {
timeZone: LOCAL_TZ,
year: 'numeric', month: '2-digit', day: '2-digit',
hour: '2-digit', minute: '2-digit', second: '2-digit',
hour12: false,
});
const parts = {};
formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });
const localAtNaive = new Date(Date.UTC(
parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),
parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),
));
const offsetMs = localAtNaive.getTime() - naive.getTime();
return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);
}
function parsePaymentSms(message) {
const result = {
rawMessage: message,
date: null,
type: null,
card: null,
recipient: null,
amount: null,
balance: null,
};
// Date and time: "Na DD/MM/YYYY v HH:MM"
const dateMatch = message.match(/Na (\d{2})\/(\d{2})\/(\d{4}) v (\d{2}):(\d{2})/i);
if (dateMatch) {
const [, day, month, year, hour, minute] = dateMatch;
result.date = localToUtc(
parseInt(year), parseInt(month), parseInt(day),
parseInt(hour), parseInt(minute),
);
}
// Card mask: "s karta 400915***4447" or "s karta 483890***7162"
const cardMatch = message.match(/s karta\s+([\d*]+)/i);
if (cardMatch) {
result.card = cardMatch[1];
}
// Transaction type: supports both prepositions
// "na POS" / "na ATM" / "na INTERNET" etc. (payment)
// "ot ATM" (withdrawal)
const typeMatch = message.match(/(?:na|ot)\s+(POS|ATM|INTERNET|ECOM|P2P)\b/i);
if (typeMatch) {
result.type = typeMatch[1].toUpperCase();
}
// Recipient address: "s adres: MERCHANT" or "s adres:MERCHANT" (no space variant)
const recipientMatch = message.match(/s adres:\s*([^.]+)\./i);
if (recipientMatch) {
result.recipient = recipientMatch[1].trim();
}
// Amount: handles both verbs and the AMOUNT/FEE suffix format
// "sa plateni 7.78 EUR"
// "sa iztegleni 400.00 EUR"
// "sa plateni 0.50 EUR/0.50 EUR" → captures 0.50 (the charged amount, ignoring fee)
const amountMatch = message.match(/sa (?:plateni|iztegleni)\s+([\d.,]+)\s+[A-Z]{3}/i);
if (amountMatch) {
result.amount = parseFloat(amountMatch[1].replace(',', '.'));
}
// Balance: "Nalichni: 2583.07 EUR."
const balanceMatch = message.match(/Nalichni:\s*([\d.,]+)\s+[A-Z]{3}/i);
if (balanceMatch) {
result.balance = parseFloat(balanceMatch[1].replace(',', '.'));
}
return result;
}
module.exports = { parsePaymentSms };
Write
csvParser.js
csvParser.js
175 lines
/**
* DSK Bank CSV parser — Node.js port of dskuploader.py
*
* DSK Bank exports use Windows-1251 (cp1251) encoding.
* Each row maps to a Payment record with source=UPLOAD, currency=BGN.
*/
const { parse } = require('csv-parse');
const iconv = require('iconv-lite');
const SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';
const CARD_REGEX = /^\d{6}x{6}\d{4}$/;
const POS_REGEX = /^\s*ПЛАЩАНЕ\s+НА\s+ПОС\s+\d{2}\.\d{2}\.\d{4}\s+\d{2}:\d{2}/;
const COL = {
DATE: 'Дата',
TYPE: 'Вид на трансакцията',
REASON: 'Основание',
DEBIT: 'Дебит BGN',
CREDIT: 'Кредит BGN',
PAYEE: 'Наредител/Получател',
ACCT: 'Номер сметка на наредителя / получателя',
};
const TAG_RULES = [
['reason', 'ЗАПЛАТА', 'Salary'],
['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],
['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],
['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],
['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],
['payee', 'VIVACOM', 'Subscriptions'],
['payee', 'Google', 'Subscriptions'],
['payee', 'SkyShowtime', 'Subscriptions'],
['payee', 'NETFLIX', 'Subscriptions'],
['payee', 'LUKOIL', 'Bills'],
['payee', 'CityGate', 'Bills'],
['payee', 'CBA', 'Groceries'],
['payee', 'FANTASTICO', 'Groceries'],
['payee', 'LIDL', 'Groceries'],
];
function parseNum(val) {
if (val == null || val === '') return null;
if (typeof val === 'number') return isNaN(val) ? null : val;
const s = String(val).trim().replace(/\xa0/g, '').replace(/ /g, '').replace(',', '.');
const n = parseFloat(s);
return isNaN(n) ? null : n;
}
function parseDate(val) {
if (!val) return null;
const s = String(val).trim();
const m = s.match(/^(\d{2})\.(\d{2})\.(\d{4})$/);
if (m) {
return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));
}
return null;
}
function processReasonAndCard(reason) {
if (!reason || typeof reason !== 'string') return { reason: '', card: null };
const parts = reason.trim().split(' ');
let card = null;
let cleanReason = reason.trim();
if (parts[0] && CARD_REGEX.test(parts[0])) {
card = parts[0];
cleanReason = parts.slice(1).join(' ').trim();
}
if (POS_REGEX.test(cleanReason)) {
const posParts = cleanReason.split('<br/>');
try {
const dateTime = posParts[0].split('ПОС ')[1];
cleanReason = `POS PAYMENT ${dateTime}`;
} catch (_) { /* keep original */ }
}
return { reason: cleanReason.replace(/\s+/g, ' ').trim(), card };
}
function generateTags(fields) {
const tags = new Set();
for (const [field, keyword, tagName] of TAG_RULES) {
if ((fields[field] || '').includes(keyword)) {
tags.add(tagName);
}
}
return Array.from(tags);
}
function processRow(row) {
const transactionType = (row[COL.TYPE] || '').trim();
if (transactionType === SKIP_TYPE) return null;
const { reason, card } = processReasonAndCard(row[COL.REASON]);
const payee = (row[COL.PAYEE] || '').trim();
const payerAccount = (row[COL.ACCT] || '').trim();
const debitBgn = parseNum(row[COL.DEBIT]);
const creditBgn = parseNum(row[COL.CREDIT]);
const date = parseDate(row[COL.DATE]);
const autoTags = generateTags({ reason, transactionType, payee, debitBgn, creditBgn });
const amount = debitBgn ?? creditBgn ?? null;
const rawMessage = [
row[COL.DATE] && `Date: ${row[COL.DATE]}`,
transactionType && `Type: ${transactionType}`,
payee && `Payee: ${payee}`,
debitBgn != null && `Debit: ${debitBgn} BGN`,
creditBgn != null && `Credit: ${creditBgn} BGN`,
].filter(Boolean).join(' | ');
return {
rawMessage,
date,
type: null,
card,
recipient: payee || null,
amount,
currency: 'BGN',
balance: null,
source: 'UPLOAD',
debitBgn,
creditBgn,
transactionType: transactionType || null,
payerAccount: payerAccount || null,
autoTags,
};
}
/**
* Parse a Buffer containing a DSK Bank CSV (cp1251 or UTF-8).
* Returns { rows, skipped, errors }.
*/
async function parseDskCsv(buffer) {
// Try cp1251 first (DSK Bank export encoding), fall back to UTF-8
let text = iconv.decode(buffer, 'cp1251');
if (!text.includes(COL.DATE)) {
text = buffer.toString('utf-8');
}
return new Promise((resolve, reject) => {
const rows = [];
const errors = [];
let skipped = 0;
const parser = parse(text, {
columns: true,
skip_empty_lines: true,
trim: true,
relax_column_count: true,
});
parser.on('readable', () => {
let record;
while ((record = parser.read()) !== null) {
try {
const row = processRow(record);
if (row === null) { skipped++; } else { rows.push(row); }
} catch (err) {
errors.push(err.message);
}
}
});
parser.on('error', reject);
parser.on('end', () => resolve({ rows, skipped, errors }));
});
}
module.exports = { parseDskCsv };
Write
index.js
index.js
39 lines
const express = require('express');
const cors = require('cors');
const morgan = require('morgan');
const rateLimit = require('express-rate-limit');
const { authentikMiddleware } = require('./auth');
const paymentsRouter = require('./routes/payments');
const uploadRouter = require('./routes/upload');
const app = express();
const PORT = process.env.PORT || 3001;
app.use(cors());
app.use(express.json({ limit: '16kb' }));
app.use(morgan('combined'));
// Rate-limit the public ingest endpoint before auth middleware
const ingestLimiter = rateLimit({
windowMs: 60 * 1000,
max: 200,
standardHeaders: true,
legacyHeaders: false,
message: { error: 'Too many requests, slow down' },
});
app.use('/api/payments/ingest', ingestLimiter);
// Authentik header auth (skips /api/health and /api/payments/ingest)
app.use(authentikMiddleware);
app.get('/api/health', (_req, res) => {
res.json({ status: 'ok', timestamp: new Date().toISOString() });
});
app.use('/api/payments', paymentsRouter);
app.use('/api/upload', uploadRouter);
app.listen(PORT, '[IP_ADDRESS]', () => {
console.log(`Finance Hub API running on port ${PORT}`);
});
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
payments.js
payments.js
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G)
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
# ── Database ───────────────────────────────────────────────────────────────────
[ENV_SECRET]
# ── Notifier service ──────────────────────────────────────────────────────────
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
auth.js
auth.js
27 lines
const PUBLIC_PATHS = new Set([
'/api/health',
'/api/payments/ingest',
]);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) {
return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });
}
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '')
.split(',')
.map(g => g.trim())
.filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
Write
parser.js
parser.js
104 lines
/**
* Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)
*
* Supported formats:
*
* POS / INTERNET / ECOM / P2P payment:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM withdrawal:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM utility payment (amount may include fee as AMOUNT/FEE):
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.
*/
const LOCAL_TZ = process.env.TZ || 'Europe/Sofia';
/**
* Convert a local-timezone date/time to a UTC Date object.
* Uses Intl to resolve the actual UTC offset (DST-aware).
*/
function localToUtc(year, month, day, hour, minute) {
const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));
const formatter = new Intl.DateTimeFormat('en-US', {
timeZone: LOCAL_TZ,
year: 'numeric', month: '2-digit', day: '2-digit',
hour: '2-digit', minute: '2-digit', second: '2-digit',
hour12: false,
});
const parts = {};
formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });
const localAtNaive = new Date(Date.UTC(
parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),
parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),
));
const offsetMs = localAtNaive.getTime() - naive.getTime();
return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);
}
function parsePaymentSms(message) {
const result = {
rawMessage: message,
date: null,
type: null,
card: null,
recipient: null,
amount: null,
balance: null,
};
// Date and time: "Na DD/MM/YYYY v HH:MM"
const dateMatch = message.match(/Na (\d{2})\/(\d{2})\/(\d{4}) v (\d{2}):(\d{2})/i);
if (dateMatch) {
const [, day, month, year, hour, minute] = dateMatch;
result.date = localToUtc(
parseInt(year), parseInt(month), parseInt(day),
parseInt(hour), parseInt(minute),
);
}
// Card mask: "s karta 400915***4447" or "s karta 483890***7162"
const cardMatch = message.match(/s karta\s+([\d*]+)/i);
if (cardMatch) {
result.card = cardMatch[1];
}
// Transaction type: supports both prepositions
// "na POS" / "na ATM" / "na INTERNET" etc. (payment)
// "ot ATM" (withdrawal)
const typeMatch = message.match(/(?:na|ot)\s+(POS|ATM|INTERNET|ECOM|P2P)\b/i);
if (typeMatch) {
result.type = typeMatch[1].toUpperCase();
}
// Recipient address: "s adres: MERCHANT" or "s adres:MERCHANT" (no space variant)
const recipientMatch = message.match(/s adres:\s*([^.]+)\./i);
if (recipientMatch) {
result.recipient = recipientMatch[1].trim();
}
// Amount: handles both verbs and the AMOUNT/FEE suffix format
// "sa plateni 7.78 EUR"
// "sa iztegleni 400.00 EUR"
// "sa plateni 0.50 EUR/0.50 EUR" → captures 0.50 (the charged amount, ignoring fee)
const amountMatch = message.match(/sa (?:plateni|iztegleni)\s+([\d.,]+)\s+[A-Z]{3}/i);
if (amountMatch) {
result.amount = parseFloat(amountMatch[1].replace(',', '.'));
}
// Balance: "Nalichni: 2583.07 EUR."
const balanceMatch = message.match(/Nalichni:\s*([\d.,]+)\s+[A-Z]{3}/i);
if (balanceMatch) {
result.balance = parseFloat(balanceMatch[1].replace(',', '.'));
}
return result;
}
module.exports = { parsePaymentSms };
Write
csvParser.js
csvParser.js
175 lines
/**
* DSK Bank CSV parser — Node.js port of dskuploader.py
*
* DSK Bank exports use Windows-1251 (cp1251) encoding.
* Each row maps to a Payment record with source=UPLOAD, currency=BGN.
*/
const { parse } = require('csv-parse');
const iconv = require('iconv-lite');
const SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';
const CARD_REGEX = /^\d{6}x{6}\d{4}$/;
const POS_REGEX = /^\s*ПЛАЩАНЕ\s+НА\s+ПОС\s+\d{2}\.\d{2}\.\d{4}\s+\d{2}:\d{2}/;
const COL = {
DATE: 'Дата',
TYPE: 'Вид на трансакцията',
REASON: 'Основание',
DEBIT: 'Дебит BGN',
CREDIT: 'Кредит BGN',
PAYEE: 'Наредител/Получател',
ACCT: 'Номер сметка на наредителя / получателя',
};
const TAG_RULES = [
['reason', 'ЗАПЛАТА', 'Salary'],
['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],
['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],
['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],
['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],
['payee', 'VIVACOM', 'Subscriptions'],
['payee', 'Google', 'Subscriptions'],
['payee', 'SkyShowtime', 'Subscriptions'],
['payee', 'NETFLIX', 'Subscriptions'],
['payee', 'LUKOIL', 'Bills'],
['payee', 'CityGate', 'Bills'],
['payee', 'CBA', 'Groceries'],
['payee', 'FANTASTICO', 'Groceries'],
['payee', 'LIDL', 'Groceries'],
];
function parseNum(val) {
if (val == null || val === '') return null;
if (typeof val === 'number') return isNaN(val) ? null : val;
const s = String(val).trim().replace(/\xa0/g, '').replace(/ /g, '').replace(',', '.');
const n = parseFloat(s);
return isNaN(n) ? null : n;
}
function parseDate(val) {
if (!val) return null;
const s = String(val).trim();
const m = s.match(/^(\d{2})\.(\d{2})\.(\d{4})$/);
if (m) {
return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));
}
return null;
}
function processReasonAndCard(reason) {
if (!reason || typeof reason !== 'string') return { reason: '', card: null };
const parts = reason.trim().split(' ');
let card = null;
let cleanReason = reason.trim();
if (parts[0] && CARD_REGEX.test(parts[0])) {
card = parts[0];
cleanReason = parts.slice(1).join(' ').trim();
}
if (POS_REGEX.test(cleanReason)) {
const posParts = cleanReason.split('<br/>');
try {
const dateTime = posParts[0].split('ПОС ')[1];
cleanReason = `POS PAYMENT ${dateTime}`;
} catch (_) { /* keep original */ }
}
return { reason: cleanReason.replace(/\s+/g, ' ').trim(), card };
}
function generateTags(fields) {
const tags = new Set();
for (const [field, keyword, tagName] of TAG_RULES) {
if ((fields[field] || '').includes(keyword)) {
tags.add(tagName);
}
}
return Array.from(tags);
}
function processRow(row) {
const transactionType = (row[COL.TYPE] || '').trim();
if (transactionType === SKIP_TYPE) return null;
const { reason, card } = processReasonAndCard(row[COL.REASON]);
const payee = (row[COL.PAYEE] || '').trim();
const payerAccount = (row[COL.ACCT] || '').trim();
const debitBgn = parseNum(row[COL.DEBIT]);
const creditBgn = parseNum(row[COL.CREDIT]);
const date = parseDate(row[COL.DATE]);
const autoTags = generateTags({ reason, transactionType, payee, debitBgn, creditBgn });
const amount = debitBgn ?? creditBgn ?? null;
const rawMessage = [
row[COL.DATE] && `Date: ${row[COL.DATE]}`,
transactionType && `Type: ${transactionType}`,
payee && `Payee: ${payee}`,
debitBgn != null && `Debit: ${debitBgn} BGN`,
creditBgn != null && `Credit: ${creditBgn} BGN`,
].filter(Boolean).join(' | ');
return {
rawMessage,
date,
type: null,
card,
recipient: payee || null,
amount,
currency: 'BGN',
balance: null,
source: 'UPLOAD',
debitBgn,
creditBgn,
transactionType: transactionType || null,
payerAccount: payerAccount || null,
autoTags,
};
}
/**
* Parse a Buffer containing a DSK Bank CSV (cp1251 or UTF-8).
* Returns { rows, skipped, errors }.
*/
async function parseDskCsv(buffer) {
// Try cp1251 first (DSK Bank export encoding), fall back to UTF-8
let text = iconv.decode(buffer, 'cp1251');
if (!text.includes(COL.DATE)) {
text = buffer.toString('utf-8');
}
return new Promise((resolve, reject) => {
const rows = [];
const errors = [];
let skipped = 0;
const parser = parse(text, {
columns: true,
skip_empty_lines: true,
trim: true,
relax_column_count: true,
});
parser.on('readable', () => {
let record;
while ((record = parser.read()) !== null) {
try {
const row = processRow(record);
if (row === null) { skipped++; } else { rows.push(row); }
} catch (err) {
errors.push(err.message);
}
}
});
parser.on('error', reject);
parser.on('end', () => resolve({ rows, skipped, errors }));
});
}
module.exports = { parseDskCsv };
Write
index.js
index.js
39 lines
const express = require('express');
const cors = require('cors');
const morgan = require('morgan');
const rateLimit = require('express-rate-limit');
const { authentikMiddleware } = require('./auth');
const paymentsRouter = require('./routes/payments');
const uploadRouter = require('./routes/upload');
const app = express();
const PORT = process.env.PORT || 3001;
app.use(cors());
app.use(express.json({ limit: '16kb' }));
app.use(morgan('combined'));
// Rate-limit the public ingest endpoint before auth middleware
const ingestLimiter = rateLimit({
windowMs: 60 * 1000,
max: 200,
standardHeaders: true,
legacyHeaders: false,
message: { error: 'Too many requests, slow down' },
});
app.use('/api/payments/ingest', ingestLimiter);
// Authentik header auth (skips /api/health and /api/payments/ingest)
app.use(authentikMiddleware);
app.get('/api/health', (_req, res) => {
res.json({ status: 'ok', timestamp: new Date().toISOString() });
});
app.use('/api/payments', paymentsRouter);
app.use('/api/upload', uploadRouter);
app.listen(PORT, '[IP_ADDRESS]', () => {
console.log(`Finance Hub API running on port ${PORT}`);
});
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)...
|
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───────────────────────\nDEV_BYPASS_AUTH=true","depth":28,"on_screen":true,"value":"# ── Database ───────────────────────────────────────────────────────────────────\nDB_PASSWORD=payments_secret\n\n# ── Notifier service ──────────────────────────────────────────────────────────\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\n\n# ── Timezone ─────────────────────────────────────────────────────────────────\nTZ=Europe/Sofia\n\n# ── Dev only — remove when NPM + Authentik is wired up ───────────────────────\nDEV_BYPASS_AUTH=true","role_description":"editor","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"# ── Database ───────────────────────────────────────────────────────────────────\nDB_PASSWORD=payments_secret\n\n# ── Notifier service ──────────────────────────────────────────────────────────\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\n\n# ── Timezone ─────────────────────────────────────────────────────────────────\nTZ=Europe/Sofia\n\n# ── Dev only — remove when NPM + Authentik is wired up ───────────────────────\nDEV_BYPASS_AUTH=true","depth":29,"on_screen":true,"role_description":"text"},{"role":"AXButton","text":"remote SSH: nas","depth":16,"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"","depth":17,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"SSH: nas","depth":17,"on_screen":true,"role_description":"text"},{"role":"AXButton","text":"No 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1","depth":16,"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Info: Do you want to install the recommended 'Rainbow CSV' extension from mechatroner for report(1).csv?","depth":12,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Design new payment-logger and dsk-uploader hybrid app","depth":19,"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Session history","depth":19,"on_screen":true,"help_text":"Session history","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"New session","depth":19,"on_screen":true,"help_text":"New session","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"payments.js","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ets create a new app that should be combination of payment-logger and dsk-uploader. It should have authorization via authentik (auth folder). All three folders (payment-logger, dsk-uploader and auth) are just refference these will be removed later. Auth project is separated it lives on its own. First reveiw them and see how these should be combined. It will be whole new app (also the folder name). Think very carefully of whatr these two apps do and how cold they be combined. THerer should be common db and uploader should store data the same way the /ingest does. It should be properly marked in UI if it is upload or ingest or both. FIrst think of tech stack and plan carefully.","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"I'll explore all three reference projects in parallel to understand their structure before planning.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How data flows (ingest, storage, retrieval)\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, and how data is ingested. Be thorough on the /ingest endpoint specifically.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure and functionality","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Tech stack (frontend framework, backend framework, database)\n2. What the app does - its core purpose and features\n3. Database schema - all tables, relationships\n4. API routes - all endpoints, their purpose and request/response shapes\n5. How file uploads work - what files, what format, how parsed\n6. Any auth/middleware setup\n7. Docker/deployment setup\n8. Key files and their roles\n\nReport with: directory structure, tech stack summary, database schema details, all API endpoints listed, UI features, how file upload parsing works, and what data is extracted from uploads. Be very thorough about the data model and what fields are stored.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth folder and authentik integration","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. What auth system is being used (Authentik)\n2. How authentication/authorization is implemented - OAuth2, OIDC, session tokens, JWT?\n3. Middleware - how is auth enforced on routes?\n4. Any frontend auth flow - login redirect, token handling, protected routes\n5. Environment variables related to auth\n6. Docker/deployment setup for the auth service itself\n7. Any example of how other apps integrate with this auth\n\nReport with: directory structure, auth flow description, middleware code, environment variable names, and integration patterns. This is a reference for building auth into a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"payments.js","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"continue","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Launching parallel exploration of all three reference projects.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore payment-logger app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/payments-logger directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How data is ingested (look at /ingest route especially)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore dsk-uploader app structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/dsk-uploader directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. Tech stack (frontend framework, backend framework, database, etc.)\n3. What the app does - its core functionality\n4. How file uploads work (what format, what processing happens)\n5. Database schema (what tables/collections exist)\n6. API routes and their purposes\n7. Frontend pages and components\n8. Docker setup\n9. Any auth/session handling\n\nPlease read key files: package.json files, main entry points, route files, database schema files, docker-compose.yml, and any frontend components. Be thorough - I need a complete picture to plan a new combined app.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore auth project structure","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Explore the /volume2/docker/finance/auth directory thoroughly. I need to understand:\n1. Full directory structure (tree)\n2. What authentication system is used (authentik integration details)\n3. How OAuth/OIDC flow works\n4. Any middleware or helper functions for protecting routes\n5. Session management approach\n6. How frontend handles auth state\n7. Any example of how other apps integrate with this auth system\n8. Docker setup and environment variables\n\nPlease read all files carefully - this auth system will be integrated into a new combined app. I need to understand exactly how to use it.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now I have a complete picture of all three. Let me design the plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Agent:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design combined app architecture","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Design a detailed implementation plan for a new combined web app that merges two existing applications. Here is full context:\n\n---\n\n## App 1: payments-logger (Node.js)\n- **Purpose**: Ingest Bulgarian bank SMS → parse → store in PostgreSQL → review/tag/notify in React UI\n- **Stack**: Node.js 20 + Express + Prisma 5 + PostgreSQL 16 + React 18 + Vite + Tailwind CSS\n- **Auth**: Custom JWT (bcryptjs + jose), tokens in localStorage\n- **Ingest**: POST /api/payments/ingest (public) — SMS text OR structured JSON (Apple Wallet)\n- **Schema** (PostgreSQL via Prisma):\n - `payments` table: id, raw_message, date, type (POS/ATM/INTERNET/ECOM/P2P/WALLET), card, recipient, amount, balance, status (UNPROCESSED/SENT/SKIPPED), notifyPhone, notifiedAt, created_at, updated_at\n - `tags` table: id, name, color — M2M with payments via `_PaymentToTag`\n - `users` table: id, username, hashed_password (this will be REMOVED)\n- **UI**: Single-page React app — PaymentTable (sortable, filterable, taggable), FilterBar, status actions (send/skip), notification system\n- **Parser** (backend/src/parser.js): Regex parser for Bulgarian DSK Bank SMS, extracts date/time (DD/MM/YYYY HH:MM), card mask, transaction type, recipient, amount, balance\n\n## App 2: dsk-uploader (Python/Flask)\n- **Purpose**: Upload DSK bank CSV exports → parse/normalize → upload to Notion database\n- **Stack**: Python 3.11 + Flask + Pandas + Custom Notion SDK + Bootstrap 5\n- **Auth**: None (open)\n- **CSV format** (DSK Bank Bulgarian format, columns):\n - `Дата` (date, DD.MM.YYYY)\n - `Вид на трансакцията` (transaction type, Bulgarian)\n - `Основание` (reason/description — contains card number regex: `^\\d{6}x{6}\\d{4}$`)\n - `Дебит BGN` (debit amount, may be empty)\n - `Кредит BGN` (credit amount, may be empty)\n - `Наредител/Получател` (orderer/recipient name)\n - `Номер сметка на наредителя / получателя` (account number)\n- **Processing**: merge multiple CSVs, normalize dates, extract card numbers from reason via regex, auto-generate tags (keyword heuristics: ЗАПЛАТА→Salary, NETFLIX→Subscriptions, etc.), filter internal transfers\n- **Output**: Notion database pages (this will be REPLACED with local PostgreSQL)\n\n## App 3: auth (Authentik)\n- **Mode**: Proxy mode via NPM (forward auth)\n- **How it works**: NPM intercepts all requests, calls Authentik outpost's auth endpoint. On success, NPM injects headers into proxied request:\n - `X-authentik-username` \n - `X-authentik-email`\n - `X-authentik-groups`\n- **No code integration needed** in the app itself — just trust these headers from NPM\n- **Logout**: Redirect user to `/outpost.goauthentik.io/sign_out`\n\n---\n\n## What the New Combined App Must Do\n\n1. **Single PostgreSQL database** for all transactions\n2. **SMS Ingest** (public endpoint) — same as payments-logger /ingest, source=INGEST\n3. **CSV Upload** (authenticated) — parse DSK CSV files, store transactions with source=UPLOAD into the same DB schema\n4. **Unified UI** — show all payments in one table regardless of source\n5. **Source indicator** in UI — badge showing \"INGEST\", \"UPLOAD\", or \"BOTH\" (if duplicate detection added)\n6. **Source filter** in FilterBar — filter by All/Ingest/Upload\n7. **Authentik auth** — remove custom JWT entirely; trust X-authentik-* headers from NPM\n8. **All existing payments-logger features**: tagging, send notification, skip, status tracking, filters, sorting, pagination\n9. **Remove Notion dependency entirely** — all data stays in local PostgreSQL\n\n---\n\n## Technical Constraints\n\n- Keep Node.js backend (not Python) — extend payments-logger's stack\n- CSV parsing: use `csv-parse` npm package (handles encoding, streaming)\n- File upload: use `multer` npm middleware\n- Auth middleware: read X-authentik-username header, 401 if missing (but /api/payments/ingest stays public)\n- Add `source` enum field (INGEST/UPLOAD) to payments schema\n- Add `currency` field (EUR for SMS ingest, BGN for CSV uploads) — or just store as-is\n- Remove `users` table from schema\n\n---\n\n## Please Design\n\n1. Complete folder structure for the new app (suggest name: \"finance-hub\" or similar — note this is a placeholder, user will confirm)\n2. Prisma schema with new fields (`source`, `currency`)\n3. All backend API routes\n4. CSV parser design in Node.js (port of the Python logic)\n5. Authentik auth middleware\n6. Frontend component structure (React) — what's reused from payments-logger, what's new\n7. Docker Compose setup\n8. Environment variables needed\n9. Step-by-step implementation order\n10. Verification checklist\n\nBe specific about file paths and code structure. This will be used to write actual implementation code.","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good plan. Let me ask the one thing I need before writing the final plan.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"AskUserQuestion","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"OUT","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"User has answered your questions: \"What should the new combined app be called? This will be the folder name under /volume2/docker/finance/ and the app branding.\"=\"finance-hub\". You can now continue with the user's answers in mind.","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Writing the final plan now.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"326 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# finance-hub — Implementation Plan\n\n## Context\n\nTwo separate finance apps exist as references and will be retired:\n- **payments-logger** (Node.js/React): Ingests Bulgarian bank SMS notifications, stores payments in PostgreSQL, provides a review/tag/notify UI.\n- **dsk-uploader** (Python/Flask): Uploads DSK bank CSV exports, parses them, sends to Notion.\n\nThe new app **finance-hub** (`/volume2/docker/finance/finance-hub/`) replaces both with a single unified system: all transactions (SMS-ingested and CSV-uploaded) land in one PostgreSQL database and one React UI. Authentication is delegated entirely to Authentik (proxy mode via NPM — no custom JWT).\n\n---\n\n## Tech Stack\n\n| Layer | Choice | Rationale |\n|-------|--------|-----------|\n| Backend | Node.js 20 + Express + Prisma 5 | Extends payments-logger; no Python needed |\n| CSV parsing | `csv-parse` + `iconv-lite` | Handles Bulgarian cp1251 encoding, RFC4180 quoted fields |\n| File upload | `multer` (memory storage) | Bank CSVs are small (<500 KB), no disk cleanup needed |\n| Database | PostgreSQL 16 | Same as payments-logger |\n| Frontend | React 18 + Vite + Tailwind CSS + Lucide React | Same as payments-logger |\n| Auth | Authentik proxy via NPM headers | No custom JWT; removes users table entirely |\n| Container | Docker Compose | Same pattern as both reference apps |\n\n**Removed vs payments-logger:** `bcryptjs`, `jose`, `users` table, login form, JWT storage. \n**Removed vs dsk-uploader:** Python/Flask, Pandas, Notion SDK, all Notion references. \n**Added:** `csv-parse`, `iconv-lite`, `multer`, `source` + `currency` fields, `UploadPanel` component.\n\n---\n\n## Folder Structure\n\n```\n/volume2/docker/finance/finance-hub/\n├── docker-compose.yml\n├── .env\n├── .env.example\n├── .gitignore\n├── backend/\n│ ├── Dockerfile\n│ ├── package.json\n│ ├── prisma/\n│ │ ├── schema.prisma\n│ │ └── migrations/\n│ │ ├── migration_lock.toml\n│ │ └── 20260508_init/\n│ │ └── migration.sql\n│ └── src/\n│ ├── index.js ← entry point (Authentik middleware wired here)\n│ ├── auth.js ← Authentik header middleware (replaces JWT auth)\n│ ├── parser.js ← SMS parser (copy verbatim from payments-logger)\n│ ├── csvParser.js ← NEW: DSK CSV parser (port of Python dskuploader.py)\n│ └── routes/\n│ ├── payments.js ← existing routes + source/currency additions\n│ └── upload.js ← NEW: POST /api/upload/csv\n└── frontend/\n ├── Dockerfile\n ├── package.json\n ├── vite.config.js\n ├── tailwind.config.js\n ├── postcss.config.js\n ├── index.html\n └── src/\n ├── main.jsx ← remove AuthProvider wrapper\n ├── index.css\n ├── App.jsx ← remove auth state, add Upload tab toggle\n └── components/\n ├── FilterBar.jsx ← add source filter select\n ├── PaymentTable.jsx ← add Source badge column + currency display\n ├── PaymentCard.jsx ← minor source badge addition\n ├── PaymentList.jsx ← unchanged\n └── UploadPanel.jsx ← NEW: drag-and-drop CSV upload UI\n```\n\n---\n\n## Database Schema (Prisma)\n\nFile: `backend/prisma/schema.prisma`\n\n```prisma\ngenerator client {\n provider = \"prisma-client-js\"\n}\n\ndatasource db {\n provider = \"postgresql\"\n url = env(\"DATABASE_URL\")\n}\n\nmodel Payment {\n id Int @id @default(autoincrement())\n rawMessage String @map(\"raw_message\")\n date DateTime?\n type String?\n card String?\n recipient String?\n amount Float?\n currency String? @default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status { UNPROCESSED SENT SKIPPED }\nenum Source { INGEST UPLOAD }\n```\n\n**Key decisions:**\n- No `User` model — Authentik owns identity.\n- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.\n- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.\n- `balance` is always null for CSV rows (DSK export does not include running balance).\n- Fresh consolidated migration — no data migration from reference apps required.\n\n---\n\n## API Routes\n\n| Method | Path | Auth | Description |\n|--------|------|------|-------------|\n| GET | /api/health | public | Health check |\n| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |\n| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |\n| GET | /api/payments/meta/tags | required | All tags |\n| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |\n| GET | /api/payments/:id | required | Single payment |\n| PATCH | /api/payments/:id | required | Update status |\n| DELETE | /api/payments/:id | required | Delete |\n| POST | /api/payments/:id/send | required | Send notification |\n| POST | /api/payments/:id/skip | required | Skip |\n| POST | /api/payments/:id/tags | required | Add/upsert tag |\n| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |\n| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |\n\n---\n\n## Key Implementation Details\n\n### auth.js (replaces entire old auth module)\n```js\nconst PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n const username = req.headers['x-authentik-username'];\n if (!username) return res.status(401).json({ error: 'Unauthorized' });\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),\n };\n next();\n}\nmodule.exports = { authentikMiddleware };\n```\n\n### csvParser.js (port of dskuploader.py)\n- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8\n- `csv-parse` parses the decoded text with `columns: true`\n- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`\n- Card extraction: regex `/^\\d{6}x{6}\\d{4}$/` on first token of `Основание`\n- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`\n- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`\n- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`\n\n### payments.js changes from payments-logger\n1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call\n2. Add `source` to the `GET /` where clause filter\n3. Add `sources` to `meta/filters` response\n4. Currency-aware amount formatting in notification message\n5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)\n\n### upload.js (new)\n- `multer` memory storage, max 10 files × 10 MB\n- Calls `parseDskCsv(buffer)` per file\n- Upserts tags via `prisma.tag.upsert` then connects\n- Returns `{ imported, skipped, errors, payments[] }`\n\n### Frontend changes\n- **Delete**: `auth.js`, `AuthProvider.jsx`\n- **main.jsx**: Remove `<AuthProvider>` wrapper\n- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add \"Payments\" / \"Upload CSV\" tab toggle\n- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols\n- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell\n- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`\n\n---\n\n## Docker Compose\n\n```yaml\nservices:\n db:\n image: postgres:16-alpine\n environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: ${DB_PASSWORD}, POSTGRES_DB: finance_hub }\n volumes: [pgdata:/var/lib/postgresql/data]\n healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }\n\n backend:\n build: ./backend\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports: [\"${BACKEND_PORT:-3001}:3001\"]\n depends_on: { db: { condition: service_healthy } }\n\n frontend:\n build: ./frontend\n ports: [\"${FRONTEND_PORT:-5175}:5173\"]\n depends_on: [backend]\n\nvolumes: { pgdata: }\n```\n\n**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.\n\n---\n\n## Environment Variables (.env)\n\n```bash\nDB_PASSWORD=change_me\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\nTZ=Europe/Sofia\nBACKEND_PORT=3001\nFRONTEND_PORT=5175\n```\n\nRemoved vs payments-logger: `JWT_SECRET`, `JWT_EXPIRE_MINUTES`.\n\n---\n\n## Implementation Order\n\n1. Create folder structure and write `docker-compose.yml`, `.env.example`, `.gitignore`\n2. Write `backend/prisma/schema.prisma` and migration SQL\n3. Write `backend/package.json` (add `csv-parse`, `iconv-lite`, `multer`; remove `bcryptjs`, `jose`)\n4. Write `backend/Dockerfile`\n5. Write `backend/src/auth.js` (Authentik middleware)\n6. Copy `backend/src/parser.js` verbatim from payments-logger\n7. Write `backend/src/csvParser.js` (Python port)\n8. Write `backend/src/routes/upload.js`\n9. Write `backend/src/routes/payments.js` (from payments-logger + 5 changes listed above)\n10. Write `backend/src/index.js`\n11. Copy frontend base from payments-logger; delete `auth.js` + `AuthProvider.jsx`\n12. Update `main.jsx`, `App.jsx`, `FilterBar.jsx`, `PaymentTable.jsx`\n13. Write `frontend/src/components/UploadPanel.jsx`\n14. Update `frontend/vite.config.js`\n15. `docker compose build && docker compose up -d`\n16. Run verification checklist\n\n---\n\n## Verification\n\n**Schema**\n- `payments` table has `source`, `currency`, `debit_bgn`, `credit_bgn`, `transaction_type`, `payer_account`\n- No `users` table; `Source` enum exists\n\n**Auth**\n- `GET /api/payments` → 401 without `x-authentik-username` header\n- `POST /api/payments/ingest` → 201 without any header\n- `curl -H \"x-authentik-username: test\" localhost:3001/api/payments` → 200\n\n**SMS Ingest**\n- DSK POS SMS → `source=INGEST`, `currency=EUR`, correct amount/card/recipient\n- Apple Wallet structured body → `type=WALLET`, `source=INGEST`\n- Rate limiter → 429 after 200 req/min\n\n**CSV Upload**\n- Single DSK CSV → rows with `source=UPLOAD`, `currency=BGN`\n- Multiple CSVs in one request → all merged\n- `ТРАНСФЕР СОБСТВЕНИ СМЕТКИ` rows counted in `skipped`, not imported\n- Card regex match from `Основание` column\n- Auto-tags applied (ЗАПЛАТА→Salary, LIDL→Groceries)\n- cp1251 file imports correctly\n\n**UI**\n- Source badge visible in payment table (SMS indigo, CSV emerald)\n- Source dropdown in FilterBar filters correctly\n- Amount shows correct currency per row\n- Upload Panel: drag-and-drop works, result summary shows counts\n- Logout redirects to Authentik sign_out\n- No login form shown (Authentik handles it at NPM level)\n- Tags, send, skip, delete all still work\n\n## Reference Files\n\n- `/volume2/docker/finance/payments-logger/backend/src/routes/payments.js`\n- `/volume2/docker/finance/payments-logger/backend/src/parser.js`\n- `/volume2/docker/finance/payments-logger/backend/src/index.js`\n- `/volume2/docker/finance/payments-logger/backend/src/auth.js`\n- `/volume2/docker/finance/payments-logger/backend/prisma/schema.prisma`\n- `/volume2/docker/finance/payments-logger/frontend/src/App.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/PaymentTable.jsx`\n- `/volume2/docker/finance/payments-logger/frontend/src/components/FilterBar.jsx`\n- `/volume2/docker/finance/dsk-uploader/dskuploader.py`\n- `/volume2/docker/finance/auth/docker-compose.yml`","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Claude’s Plan","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"ets-create-a-new-generic-sun.md","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ets-create-a-new-generic-sun.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Stayed in plan mode","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Good question. Here's the full breakdown:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Backend Tech Stack — Options","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Backend Tech Stack — Options","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option A: Node.js + Express + Prisma (my recommendation)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Why:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"payments-logger is already Node.js/Express/Prisma. The new app is 80% payments-logger with CSV upload added on top. Keeping the same stack means:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"verbatim, zero rewrite","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Copy the entire","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"routes/payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with minimal edits","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Same Prisma schema workflow, same migrations, same Docker image","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The CSV parsing logic (the only Python-specific thing) ports cleanly to","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"csv-parse","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— it's just regex + string manipulation, nothing pandas-specific","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Trade-off:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Have to port the Python CSV parsing to JS. It's ~150 lines and mostly string manipulation — straightforward.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option B: Python + FastAPI + SQLAlchemy","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option B: Python + FastAPI + SQLAlchemy","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rewrite everything in Python. dsk-uploader is Python, so CSV parsing is already done.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep the dsk-uploader CSV logic as-is (no porting). Python has better data science libraries if you later add analytics.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Lose the entire payments-logger backend (routes, parser, Prisma schema) — full rewrite. FastAPI + SQLAlchemy is a different mental model than Express + Prisma. Frontend stays React anyway, so the stack split doesn't simplify anything.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"More work overall, gains almost nothing.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option C: Hybrid microservices (Node.js backend + Python CSV service)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Keep Node.js as the main API, add a separate Python FastAPI service just for CSV parsing. They share the DB.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Zero porting — Python CSV code used as-is.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Two backend services to maintain, deploy, and keep in sync. Inter-service HTTP calls. Two Dockerfiles. For ~150 lines of CSV logic, this is massively over-engineered.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Not worth it.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Option D: Python + Flask (exactly like dsk-uploader)","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Extend dsk-uploader into a full payments app.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pro:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Pandas for CSV, no porting.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Con:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Jinja2 templates instead of React (or add React separately). Would need to reimplement the entire payments-logger (SMS parser, notification system, tag management, pagination/filtering). Flask's Jinja templating is far less capable than the existing React UI. The React frontend is the stronger UI foundation.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Verdict:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Worst of all options — rebuild the harder parts (UI, SMS parser, notification) for no gain.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"Summary","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"Summary","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"CSV porting effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"App rewrite effort","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Result quality","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"A (Node.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Medium (150 lines)","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Minimal","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Best","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"B (Python FastAPI)","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"None","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"High (full backend)","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Worse","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"C (Hybrid)","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"None","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Low + infra overhead","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Overkill","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"D (Python Flask)","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"None","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Very high","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Worst","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"A (Node.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"B (Python 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Everything else in the plan reuses payments-logger code directly. That's why Node.js is the clear winner here.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Want to adjust the stack, or shall I proceed with Option A?","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"ok sounds good. Implement all you suggested","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Starting implementation. Let me first read all the reference files I'll need to copy from.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"payments.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"payments.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":",","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"App.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"App.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"FilterBar.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"FilterBar.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentTable.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentTable.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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payments-logger.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.css","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.css","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"vite.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"vite.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"tailwind.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"tailwind.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"postcss.config.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"postcss.config.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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components.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentCard.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentCard.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaymentList.jsx","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaymentList.jsx","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"schema.prisma","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"schema.prisma","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure 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Let me set up the todo list and start building.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":false,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create finance-hub directory structure","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"mkdir -p /volume2/docker/finance/finance-hub/backend/src/routes \\\n /volume2/docker/finance/finance-hub/backend/prisma/migrations/20260508_init \\\n /volume2/docker/finance/finance-hub/frontend/src/components && echo \"done\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":24,"on_screen":false,"help_text":"Copy code","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"OUT","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"done","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"docker-compose.yml","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"docker-compose.yml","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"45 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"version: '3.8'\n\nservices:\n db:\n image: postgres:16-alpine\n restart: unless-stopped\n environment:\n POSTGRES_USER: finance\n POSTGRES_PASSWORD: ${DB_PASSWORD}\n POSTGRES_DB: finance_hub\n volumes:\n - pgdata:/var/lib/postgresql/data\n healthcheck:\n test: [\"CMD-SHELL\", \"pg_isready -U finance -d finance_hub\"]\n interval: 5s\n timeout: 5s\n retries: 5\n\n backend:\n build: ./backend\n restart: unless-stopped\n environment:\n DATABASE_URL: postgresql://finance:${DB_PASSWORD}@db:5432/finance_hub\n PORT: \"3001\"\n NOTIFIER_URL: ${NOTIFIER_URL}\n NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}\n NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}\n TZ: ${TZ:-Europe/Sofia}\n ports:\n - \"${BACKEND_PORT:-3001}:3001\"\n depends_on:\n db:\n condition: service_healthy\n\n frontend:\n build: ./frontend\n restart: unless-stopped\n ports:\n - \"${FRONTEND_PORT:-5175}:5173\"\n depends_on:\n - backend\n\nvolumes:\n pgdata:","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".env.example","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".env.example","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"15 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Database\nDB_PASSWORD=change_me_strong_password\n\n# Notifier service (for SMS payment notifications)\nNOTIFIER_URL=https://notifier.lakylak.xyz\nNOTIFIER_CHANNEL=viber\nNOTIFY_DEFAULT_PHONE=+359000000000\n\n# Timezone (used by SMS parser for Bulgarian bank timestamps)\nTZ=Europe/Sofia\n\n# Ports (optional — defaults shown)\nBACKEND_PORT=3001\nFRONTEND_PORT=5175","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":".gitignore","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":".gitignore","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"5 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env\nnode_modules/\ndist/\n*.log","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config 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@default(\"EUR\")\n balance Float?\n source Source @default(INGEST)\n status Status @default(UNPROCESSED)\n tags Tag[]\n notifiedAt DateTime? @map(\"notified_at\")\n notifyPhone String? @map(\"notify_phone\")\n debitBgn Float? @map(\"debit_bgn\")\n creditBgn Float? @map(\"credit_bgn\")\n transactionType String? @map(\"transaction_type\")\n payerAccount String? @map(\"payer_account\")\n createdAt DateTime @default(now()) @map(\"created_at\")\n updatedAt DateTime @updatedAt @map(\"updated_at\")\n\n @@map(\"payments\")\n}\n\nmodel Tag {\n id Int @id @default(autoincrement())\n name String @unique\n color String @default(\"#6b7280\")\n payments Payment[]\n\n @@map(\"tags\")\n}\n\nenum Status {\n UNPROCESSED\n SENT\n SKIPPED\n}\n\nenum Source {\n INGEST\n UPLOAD\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration.sql","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration.sql","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"55 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"-- CreateEnum\nCREATE TYPE \"Status\" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');\nCREATE TYPE \"Source\" AS ENUM ('INGEST', 'UPLOAD');\n\n-- CreateTable\nCREATE TABLE \"payments\" (\n \"id\" SERIAL PRIMARY KEY,\n \"raw_message\" TEXT NOT NULL,\n \"date\" TIMESTAMP(3),\n \"type\" TEXT,\n \"card\" TEXT,\n \"recipient\" TEXT,\n \"amount\" DOUBLE PRECISION,\n \"currency\" TEXT DEFAULT 'EUR',\n \"balance\" DOUBLE PRECISION,\n \"source\" \"Source\" NOT NULL DEFAULT 'INGEST',\n \"status\" \"Status\" NOT NULL DEFAULT 'UNPROCESSED',\n \"notified_at\" TIMESTAMP(3),\n \"notify_phone\" TEXT,\n \"debit_bgn\" DOUBLE PRECISION,\n \"credit_bgn\" DOUBLE PRECISION,\n \"transaction_type\" TEXT,\n \"payer_account\" TEXT,\n \"created_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,\n \"updated_at\" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP\n);\n\n-- CreateTable\nCREATE TABLE \"tags\" (\n \"id\" SERIAL PRIMARY KEY,\n \"name\" TEXT NOT NULL,\n \"color\" TEXT NOT NULL DEFAULT '#6b7280'\n);\n\n-- CreateUniqueIndex\nCREATE UNIQUE INDEX \"tags_name_key\" ON \"tags\"(\"name\");\n\n-- CreateTable (M2M join)\nCREATE TABLE \"_PaymentToTag\" (\n \"A\" INTEGER NOT NULL,\n \"B\" INTEGER NOT NULL,\n CONSTRAINT \"_PaymentToTag_AB_pkey\" PRIMARY KEY (\"A\", \"B\")\n);\n\nCREATE INDEX \"_PaymentToTag_B_index\" ON \"_PaymentToTag\"(\"B\");\n\n-- AddForeignKey\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_A_fkey\"\n FOREIGN KEY (\"A\") REFERENCES \"payments\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;\n\nALTER TABLE \"_PaymentToTag\"\n ADD CONSTRAINT \"_PaymentToTag_B_fkey\"\n FOREIGN KEY (\"B\") REFERENCES \"tags\"(\"id\") ON DELETE CASCADE ON UPDATE CASCADE;","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"migration_lock.toml","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"migration_lock.toml","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"4 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"# Please do not edit this file manually\n# It should be added in your version-control system (e.g., Git)\nprovider = \"postgresql\"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"package.json","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"package.json","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"26 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"{\n \"name\": \"finance-hub-backend\",\n \"version\": \"1.0.0\",\n \"main\": \"src/index.js\",\n \"scripts\": {\n \"start\": \"node src/index.js\",\n \"dev\": \"nodemon src/index.js\",\n \"prisma:generate\": \"prisma generate\",\n \"prisma:migrate\": \"prisma migrate deploy\"\n },\n \"dependencies\": {\n \"@prisma/client\": \"^5.22.0\",\n \"cors\": \"^2.8.5\",\n \"csv-parse\": \"^5.5.6\",\n \"express\": \"^4.21.1\",\n \"express-rate-limit\": \"^7.4.0\",\n \"iconv-lite\": \"^0.6.3\",\n \"morgan\": \"^1.10.0\",\n \"multer\": \"^1.4.5-lts.1\"\n },\n \"devDependencies\": {\n \"nodemon\": \"^3.1.7\",\n \"prisma\": \"^5.22.0\"\n }\n}","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"Dockerfile","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Dockerfile","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"18 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"FROM node:20-alpine\n\nRUN apk add --no-cache openssl\n\nWORKDIR /app\n\nCOPY package.json package-lock.json* ./\nRUN npm install\n\nCOPY prisma ./prisma\nRUN npx prisma generate\n\nCOPY src ./src\n\nEXPOSE 3001\n\nCMD [\"sh\", \"-c\", \"npx prisma migrate deploy && node src/index.js\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend routes (payments.js, upload.js)","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write frontend React components","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Build and verify with docker compose","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"auth.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"auth.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"27 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const PUBLIC_PATHS = new Set([\n '/api/health',\n '/api/payments/ingest',\n]);\n\nfunction authentikMiddleware(req, res, next) {\n if (PUBLIC_PATHS.has(req.path)) return next();\n\n const username = req.headers['x-authentik-username'];\n if (!username) {\n return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });\n }\n\n req.user = {\n username,\n email: req.headers['x-authentik-email'] || null,\n groups: (req.headers['x-authentik-groups'] || '')\n .split(',')\n .map(g => g.trim())\n .filter(Boolean),\n };\n\n next();\n}\n\nmodule.exports = { authentikMiddleware };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"parser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"parser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"104 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/**\n * Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)\n *\n * Supported formats:\n *\n * POS / INTERNET / ECOM / P2P payment:\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.\n *\n * ATM withdrawal:\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.\n *\n * ATM utility payment (amount may include fee as AMOUNT/FEE):\n * DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.\n */\n\nconst LOCAL_TZ = process.env.TZ || 'Europe/Sofia';\n\n/**\n * Convert a local-timezone date/time to a UTC Date object.\n * Uses Intl to resolve the actual UTC offset (DST-aware).\n */\nfunction localToUtc(year, month, day, hour, minute) {\n const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));\n\n const formatter = new Intl.DateTimeFormat('en-US', {\n timeZone: LOCAL_TZ,\n year: 'numeric', month: '2-digit', day: '2-digit',\n hour: '2-digit', minute: '2-digit', second: '2-digit',\n hour12: false,\n });\n\n const parts = {};\n formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });\n\n const localAtNaive = new Date(Date.UTC(\n parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),\n parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),\n ));\n\n const offsetMs = localAtNaive.getTime() - naive.getTime();\n return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);\n}\n\nfunction parsePaymentSms(message) {\n const result = {\n rawMessage: message,\n date: null,\n type: null,\n card: null,\n recipient: null,\n amount: null,\n balance: null,\n };\n\n // Date and time: \"Na DD/MM/YYYY v HH:MM\"\n const dateMatch = message.match(/Na (\\d{2})\\/(\\d{2})\\/(\\d{4}) v (\\d{2}):(\\d{2})/i);\n if (dateMatch) {\n const [, day, month, year, hour, minute] = dateMatch;\n result.date = localToUtc(\n parseInt(year), parseInt(month), parseInt(day),\n parseInt(hour), parseInt(minute),\n );\n }\n\n // Card mask: \"s karta 400915***4447\" or \"s karta 483890***7162\"\n const cardMatch = message.match(/s karta\\s+([\\d*]+)/i);\n if (cardMatch) {\n result.card = cardMatch[1];\n }\n\n // Transaction type: supports both prepositions\n // \"na POS\" / \"na ATM\" / \"na INTERNET\" etc. (payment)\n // \"ot ATM\" (withdrawal)\n const typeMatch = message.match(/(?:na|ot)\\s+(POS|ATM|INTERNET|ECOM|P2P)\\b/i);\n if (typeMatch) {\n result.type = typeMatch[1].toUpperCase();\n }\n\n // Recipient address: \"s adres: MERCHANT\" or \"s adres:MERCHANT\" (no space variant)\n const recipientMatch = message.match(/s adres:\\s*([^.]+)\\./i);\n if (recipientMatch) {\n result.recipient = recipientMatch[1].trim();\n }\n\n // Amount: handles both verbs and the AMOUNT/FEE suffix format\n // \"sa plateni 7.78 EUR\"\n // \"sa iztegleni 400.00 EUR\"\n // \"sa plateni 0.50 EUR/0.50 EUR\" → captures 0.50 (the charged amount, ignoring fee)\n const amountMatch = message.match(/sa (?:plateni|iztegleni)\\s+([\\d.,]+)\\s+[A-Z]{3}/i);\n if (amountMatch) {\n result.amount = parseFloat(amountMatch[1].replace(',', '.'));\n }\n\n // Balance: \"Nalichni: 2583.07 EUR.\"\n const balanceMatch = message.match(/Nalichni:\\s*([\\d.,]+)\\s+[A-Z]{3}/i);\n if (balanceMatch) {\n result.balance = parseFloat(balanceMatch[1].replace(',', '.'));\n }\n\n return result;\n}\n\nmodule.exports = { parsePaymentSms };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"csvParser.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"csvParser.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"175 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/**\n * DSK Bank CSV parser — Node.js port of dskuploader.py\n *\n * DSK Bank exports use Windows-1251 (cp1251) encoding.\n * Each row maps to a Payment record with source=UPLOAD, currency=BGN.\n */\n\nconst { parse } = require('csv-parse');\nconst iconv = require('iconv-lite');\n\nconst SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';\nconst CARD_REGEX = /^\\d{6}x{6}\\d{4}$/;\nconst POS_REGEX = /^\\s*ПЛАЩАНЕ\\s+НА\\s+ПОС\\s+\\d{2}\\.\\d{2}\\.\\d{4}\\s+\\d{2}:\\d{2}/;\n\nconst COL = {\n DATE: 'Дата',\n TYPE: 'Вид на трансакцията',\n REASON: 'Основание',\n DEBIT: 'Дебит BGN',\n CREDIT: 'Кредит BGN',\n PAYEE: 'Наредител/Получател',\n ACCT: 'Номер сметка на наредителя / получателя',\n};\n\nconst TAG_RULES = [\n ['reason', 'ЗАПЛАТА', 'Salary'],\n ['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],\n ['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],\n ['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],\n ['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],\n ['payee', 'VIVACOM', 'Subscriptions'],\n ['payee', 'Google', 'Subscriptions'],\n ['payee', 'SkyShowtime', 'Subscriptions'],\n ['payee', 'NETFLIX', 'Subscriptions'],\n ['payee', 'LUKOIL', 'Bills'],\n ['payee', 'CityGate', 'Bills'],\n ['payee', 'CBA', 'Groceries'],\n ['payee', 'FANTASTICO', 'Groceries'],\n ['payee', 'LIDL', 'Groceries'],\n];\n\nfunction parseNum(val) {\n if (val == null || val === '') return null;\n if (typeof val === 'number') return isNaN(val) ? null : val;\n const s = String(val).trim().replace(/\\xa0/g, '').replace(/ /g, '').replace(',', '.');\n const n = parseFloat(s);\n return isNaN(n) ? null : n;\n}\n\nfunction parseDate(val) {\n if (!val) return null;\n const s = String(val).trim();\n const m = s.match(/^(\\d{2})\\.(\\d{2})\\.(\\d{4})$/);\n if (m) {\n return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));\n }\n return null;\n}\n\nfunction processReasonAndCard(reason) {\n if (!reason || typeof reason !== 'string') return { reason: '', card: null };\n\n const parts = reason.trim().split(' ');\n let card = null;\n let cleanReason = reason.trim();\n\n if (parts[0] && CARD_REGEX.test(parts[0])) {\n card = parts[0];\n cleanReason = parts.slice(1).join(' ').trim();\n }\n\n if (POS_REGEX.test(cleanReason)) {\n const posParts = cleanReason.split('<br/>');\n try {\n const dateTime = posParts[0].split('ПОС ')[1];\n cleanReason = `POS PAYMENT ${dateTime}`;\n } catch (_) { /* keep original */ }\n }\n\n return { reason: cleanReason.replace(/\\s+/g, ' ').trim(), card };\n}\n\nfunction generateTags(fields) {\n const tags = new Set();\n for (const [field, keyword, tagName] of TAG_RULES) {\n if ((fields[field] || '').includes(keyword)) {\n tags.add(tagName);\n }\n }\n return Array.from(tags);\n}\n\nfunction processRow(row) {\n const transactionType = (row[COL.TYPE] || '').trim();\n if (transactionType === SKIP_TYPE) return null;\n\n const { reason, card } = processReasonAndCard(row[COL.REASON]);\n const payee = (row[COL.PAYEE] || '').trim();\n const payerAccount = (row[COL.ACCT] || '').trim();\n const debitBgn = parseNum(row[COL.DEBIT]);\n const creditBgn = parseNum(row[COL.CREDIT]);\n const date = parseDate(row[COL.DATE]);\n\n const autoTags = generateTags({ reason, transactionType, payee, debitBgn, creditBgn });\n\n const amount = debitBgn ?? creditBgn ?? null;\n\n const rawMessage = [\n row[COL.DATE] && `Date: ${row[COL.DATE]}`,\n transactionType && `Type: ${transactionType}`,\n payee && `Payee: ${payee}`,\n debitBgn != null && `Debit: ${debitBgn} BGN`,\n creditBgn != null && `Credit: ${creditBgn} BGN`,\n ].filter(Boolean).join(' | ');\n\n return {\n rawMessage,\n date,\n type: null,\n card,\n recipient: payee || null,\n amount,\n currency: 'BGN',\n balance: null,\n source: 'UPLOAD',\n debitBgn,\n creditBgn,\n transactionType: transactionType || null,\n payerAccount: payerAccount || null,\n autoTags,\n };\n}\n\n/**\n * Parse a Buffer containing a DSK Bank CSV (cp1251 or UTF-8).\n * Returns { rows, skipped, errors }.\n */\nasync function parseDskCsv(buffer) {\n // Try cp1251 first (DSK Bank export encoding), fall back to UTF-8\n let text = iconv.decode(buffer, 'cp1251');\n if (!text.includes(COL.DATE)) {\n text = buffer.toString('utf-8');\n }\n\n return new Promise((resolve, reject) => {\n const rows = [];\n const errors = [];\n let skipped = 0;\n\n const parser = parse(text, {\n columns: true,\n skip_empty_lines: true,\n trim: true,\n relax_column_count: true,\n });\n\n parser.on('readable', () => {\n let record;\n while ((record = parser.read()) !== null) {\n try {\n const row = processRow(record);\n if (row === null) { skipped++; } else { rows.push(row); }\n } catch (err) {\n errors.push(err.message);\n }\n }\n });\n\n parser.on('error', reject);\n parser.on('end', () => resolve({ rows, skipped, errors }));\n });\n}\n\nmodule.exports = { parseDskCsv };","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"index.js","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"index.js","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"39 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"const express = require('express');\nconst cors = require('cors');\nconst morgan = require('morgan');\nconst rateLimit = require('express-rate-limit');\nconst { authentikMiddleware } = require('./auth');\nconst paymentsRouter = require('./routes/payments');\nconst uploadRouter = require('./routes/upload');\n\nconst app = express();\nconst PORT = process.env.PORT || 3001;\n\napp.use(cors());\napp.use(express.json({ limit: '16kb' }));\napp.use(morgan('combined'));\n\n// Rate-limit the public ingest endpoint before auth middleware\nconst ingestLimiter = rateLimit({\n windowMs: 60 * 1000,\n max: 200,\n standardHeaders: true,\n legacyHeaders: false,\n message: { error: 'Too many requests, slow down' },\n});\napp.use('/api/payments/ingest', ingestLimiter);\n\n// Authentik header auth (skips /api/health and /api/payments/ingest)\napp.use(authentikMiddleware);\n\napp.get('/api/health', (_req, res) => {\n res.json({ status: 'ok', timestamp: new Date().toISOString() });\n});\n\napp.use('/api/payments', paymentsRouter);\napp.use('/api/upload', uploadRouter);\n\napp.listen(PORT, '0.0.0.0', () => {\n console.log(`Finance Hub API running on port ${PORT}`);\n});","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Update Todos","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Create folder structure and root config files","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend Prisma schema and migration","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend package.json and Dockerfile","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Write backend src files (auth, parser, csvParser, index)","depth":26,"on_screen":false,"role_description":"text"}]...
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Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: finance [SSH: nas]
Explorer Section: finance [SSH: nas]
FINANCE [SSH: NAS]
auth
dsk-uploader
finance-hub
backend
frontend
.env
.env.example
.gitignore
docker-compose.yml
payments-logger
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
docker-compose.yml, Editor Group 1
.env, Editor Group 1
# ── Database ───────────────────────────────────────────────────────────────────
[ENV_SECRET]
# ── Notifier service ──────────────────────────────────────────────────────────
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status { UNPROCESSED SENT SKIPPED }
enum Source { INGEST UPLOAD }
```
**Key decisions:**
- No `User` model — Authentik owns identity.
- `currency`: `EUR` for SMS ingest, `BGN` for CSV uploads.
- `debitBgn`, `creditBgn`, `transactionType`, `payerAccount`: nullable CSV-only columns; INGEST rows store nulls. Avoids a union query for the unified list view.
- `balance` is always null for CSV rows (DSK export does not include running balance).
- Fresh consolidated migration — no data migration from reference apps required.
---
## API Routes
| Method | Path | Auth | Description |
|--------|------|------|-------------|
| GET | /api/health | public | Health check |
| POST | /api/payments/ingest | public | SMS or structured ingest (source=INGEST) |
| GET | /api/payments | required | List with filters/sort/pagination (+ source filter) |
| GET | /api/payments/meta/tags | required | All tags |
| GET | /api/payments/meta/filters | required | Filter options incl. `sources` array |
| GET | /api/payments/:id | required | Single payment |
| PATCH | /api/payments/:id | required | Update status |
| DELETE | /api/payments/:id | required | Delete |
| POST | /api/payments/:id/send | required | Send notification |
| POST | /api/payments/:id/skip | required | Skip |
| POST | /api/payments/:id/tags | required | Add/upsert tag |
| DELETE | /api/payments/:id/tags/:tagId | required | Remove tag |
| POST | /api/upload/csv | required | DSK CSV file upload (source=UPLOAD) |
---
## Key Implementation Details
### auth.js (replaces entire old auth module)
```js
const PUBLIC_PATHS = new Set(['/api/health', '/api/payments/ingest']);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) return res.status(401).json({ error: 'Unauthorized' });
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '').split(',').map(g => g.trim()).filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
```
### csvParser.js (port of dskuploader.py)
- `iconv-lite` decodes buffer as cp1251 (DSK Bank export encoding), falls back to UTF-8
- `csv-parse` parses the decoded text with `columns: true`
- Columns: `Дата`, `Вид на трансакцията`, `Основание`, `Дебит BGN`, `Кредит BGN`, `Наредител/Получател`, `Номер сметка на наредителя / получателя`
- Card extraction: regex `/^\d{6}x{6}\d{4}$/` on first token of `Основание`
- Skips rows where `Вид на трансакцията === 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ'`
- Auto-tags via keyword rules (ЗАПЛАТА→Salary, LIDL→Groceries, NETFLIX→Subscriptions, etc.) — same logic as Python `generate_tags()`
- Returns `{ rows: PaymentData[], skipped: number, errors: string[] }`
### payments.js changes from payments-logger
1. Add `source: 'INGEST'` and `currency` to the `/ingest` create call
2. Add `source` to the `GET /` where clause filter
3. Add `sources` to `meta/filters` response
4. Currency-aware amount formatting in notification message
5. Remove all JWT/auth references (no `/auth/register`, `/auth/login`)
### upload.js (new)
- `multer` memory storage, max 10 files × 10 MB
- Calls `parseDskCsv(buffer)` per file
- Upserts tags via `prisma.tag.upsert` then connects
- Returns `{ imported, skipped, errors, payments[] }`
### Frontend changes
- **Delete**: `auth.js`, `AuthProvider.jsx`
- **main.jsx**: Remove `<AuthProvider>` wrapper
- **App.jsx**: Replace `authFetch` with plain `fetch` (Authentik session cookie travels automatically); logout → `window.location.href = '/outpost.goauthentik.io/sign_out'`; add "Payments" / "Upload CSV" tab toggle
- **FilterBar.jsx**: Add source `<select>` (All / SMS Ingest / CSV Upload); widen grid to 5 cols
- **PaymentTable.jsx**: Add `Source` column with `SMS` (indigo) / `CSV` (emerald) badge; show `${amount} ${currency}` in amount cell
- **UploadPanel.jsx** (new): Drag-and-drop zone + file list + import button + result summary with error accordion; calls `POST /api/upload/csv` with `FormData`
---
## Docker Compose
```yaml
services:
db:
image: postgres:16-alpine
environment: { POSTGRES_USER: finance, POSTGRES_PASSWORD: [PASSWORD] POSTGRES_DB: finance_hub }
volumes: [pgdata:/var/lib/postgresql/data]
healthcheck: { test: pg_isready -U finance -d finance_hub, interval: 5s }
backend:
build: ./backend
environment:
DATABASE_URL: [CONNECTION_STRING]
PORT: "3001"
NOTIFIER_URL: ${NOTIFIER_URL}
NOTIFIER_CHANNEL: ${NOTIFIER_CHANNEL:-viber}
NOTIFY_DEFAULT_PHONE: ${NOTIFY_DEFAULT_PHONE}
TZ: ${TZ:-Europe/Sofia}
ports: ["${BACKEND_PORT:-3001}:3001"]
depends_on: { db: { condition: service_healthy } }
frontend:
build: ./frontend
ports: ["${FRONTEND_PORT:-5175}:5173"]
depends_on: [backend]
volumes: { pgdata: }
```
**NPM setup:** Frontend port proxied through Authentik forward auth. Backend port exposed separately (unprotected) so the public `/api/payments/ingest` remains reachable by iOS Shortcuts / SMS gateways without login.
---
## Environment Variables (.env)
```bash
[ENV_SECRET]
NOTIFIER_URL=[URL_WITH_CREDENTIALS] @default(autoincrement())
rawMessage String @map("raw_message")
date DateTime?
type String?
card String?
recipient String?
amount Float?
currency String? @default("EUR")
balance Float?
source Source @default(INGEST)
status Status @default(UNPROCESSED)
tags Tag[]
notifiedAt DateTime? @map("notified_at")
notifyPhone String? @map("notify_phone")
debitBgn Float? @map("debit_bgn")
creditBgn Float? @map("credit_bgn")
transactionType String? @map("transaction_type")
payerAccount String? @map("payer_account")
createdAt DateTime @default(now()) @map("created_at")
updatedAt DateTime @updatedAt @map("updated_at")
@@map("payments")
}
model Tag {
id Int @id @default(autoincrement())
name String @unique
color String @default("#6b7280")
payments Payment[]
@@map("tags")
}
enum Status {
UNPROCESSED
SENT
SKIPPED
}
enum Source {
INGEST
UPLOAD
}
Write
migration.sql
migration.sql
55 lines
-- CreateEnum
CREATE TYPE "Status" AS ENUM ('UNPROCESSED', 'SENT', 'SKIPPED');
CREATE TYPE "Source" AS ENUM ('INGEST', 'UPLOAD');
-- CreateTable
CREATE TABLE "payments" (
"id" SERIAL PRIMARY KEY,
"raw_message" TEXT NOT NULL,
"date" TIMESTAMP(3),
"type" TEXT,
"card" TEXT,
"recipient" TEXT,
"amount" DOUBLE PRECISION,
"currency" TEXT DEFAULT 'EUR',
"balance" DOUBLE PRECISION,
"source" "Source" NOT NULL DEFAULT 'INGEST',
"status" "Status" NOT NULL DEFAULT 'UNPROCESSED',
"notified_at" TIMESTAMP(3),
"notify_phone" TEXT,
"debit_bgn" DOUBLE PRECISION,
"credit_bgn" DOUBLE PRECISION,
"transaction_type" TEXT,
"payer_account" TEXT,
"created_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP,
"updated_at" TIMESTAMP(3) NOT NULL DEFAULT CURRENT_TIMESTAMP
);
-- CreateTable
CREATE TABLE "tags" (
"id" SERIAL PRIMARY KEY,
"name" TEXT NOT NULL,
"color" TEXT NOT NULL DEFAULT '#6b7280'
);
-- CreateUniqueIndex
CREATE UNIQUE INDEX "tags_name_key" ON "tags"("name");
-- CreateTable (M2M join)
CREATE TABLE "_PaymentToTag" (
"A" INTEGER NOT NULL,
"B" INTEGER NOT NULL,
CONSTRAINT "_PaymentToTag_AB_pkey" PRIMARY KEY ("A", "B")
);
CREATE INDEX "_PaymentToTag_B_index" ON "_PaymentToTag"("B");
-- AddForeignKey
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_A_fkey"
FOREIGN KEY ("A") REFERENCES "payments"("id") ON DELETE CASCADE ON UPDATE CASCADE;
ALTER TABLE "_PaymentToTag"
ADD CONSTRAINT "_PaymentToTag_B_fkey"
FOREIGN KEY ("B") REFERENCES "tags"("id") ON DELETE CASCADE ON UPDATE CASCADE;
Write
migration_lock.toml
migration_lock.toml
4 lines
# Please do not edit this file manually
# It should be added in your version-control system (e.g., Git)
provider = "postgresql"
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
package.json
package.json
26 lines
{
"name": "finance-hub-backend",
"version": "1.0.0",
"main": "src/index.js",
"scripts": {
"start": "node src/index.js",
"dev": "nodemon src/index.js",
"prisma:generate": "prisma generate",
"prisma:migrate": "prisma migrate deploy"
},
"dependencies": {
"@prisma/client": "^5.22.0",
"cors": "^2.8.5",
"csv-parse": "^5.5.6",
"express": "^4.21.1",
"express-rate-limit": "^7.4.0",
"iconv-lite": "^0.6.3",
"morgan": "^1.10.0",
"multer": "^1.4.5-lts.1"
},
"devDependencies": {
"nodemon": "^3.1.7",
"prisma": "^5.22.0"
}
}
Write
Dockerfile
Dockerfile
18 lines
FROM node:20-alpine
RUN apk add --no-cache openssl
WORKDIR /app
COPY package.json package-lock.json* ./
RUN npm install
COPY prisma ./prisma
RUN npx prisma generate
COPY src ./src
EXPOSE 3001
CMD ["sh", "-c", "npx prisma migrate deploy && node src/index.js"]
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)
Write backend routes (payments.js, upload.js)
Write frontend config files
Write frontend React components
Build and verify with docker compose
Write
auth.js
auth.js
27 lines
const PUBLIC_PATHS = new Set([
'/api/health',
'/api/payments/ingest',
]);
function authentikMiddleware(req, res, next) {
if (PUBLIC_PATHS.has(req.path)) return next();
const username = req.headers['x-authentik-username'];
if (!username) {
return res.status(401).json({ error: 'Unauthorized — missing Authentik session' });
}
req.user = {
username,
email: req.headers['x-authentik-email'] || null,
groups: (req.headers['x-authentik-groups'] || '')
.split(',')
.map(g => g.trim())
.filter(Boolean),
};
next();
}
module.exports = { authentikMiddleware };
Write
parser.js
parser.js
104 lines
/**
* Parses SMS payment messages from Bulgarian banks (DSK Bank, etc.)
*
* Supported formats:
*
* POS / INTERNET / ECOM / P2P payment:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY s karta CARD na POS s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM withdrawal:
* DSK Bank. Na DD/MM/YYYY v HH:MM sa iztegleni AMOUNT CURRENCY s karta CARD ot ATM s adres: RECIPIENT. Nalichni: BALANCE CURRENCY.
*
* ATM utility payment (amount may include fee as AMOUNT/FEE):
* DSK Bank. Na DD/MM/YYYY v HH:MM sa plateni AMOUNT CURRENCY/FEE CURRENCY s karta CARD na ATM s adres:RECIPIENT. Nalichni: BALANCE CURRENCY.
*/
const LOCAL_TZ = process.env.TZ || 'Europe/Sofia';
/**
* Convert a local-timezone date/time to a UTC Date object.
* Uses Intl to resolve the actual UTC offset (DST-aware).
*/
function localToUtc(year, month, day, hour, minute) {
const naive = new Date(Date.UTC(year, month - 1, day, hour, minute, 0));
const formatter = new Intl.DateTimeFormat('en-US', {
timeZone: LOCAL_TZ,
year: 'numeric', month: '2-digit', day: '2-digit',
hour: '2-digit', minute: '2-digit', second: '2-digit',
hour12: false,
});
const parts = {};
formatter.formatToParts(naive).forEach(p => { parts[p.type] = p.value; });
const localAtNaive = new Date(Date.UTC(
parseInt(parts.year), parseInt(parts.month) - 1, parseInt(parts.day),
parseInt(parts.hour) % 24, parseInt(parts.minute), parseInt(parts.second),
));
const offsetMs = localAtNaive.getTime() - naive.getTime();
return new Date(Date.UTC(year, month - 1, day, hour, minute, 0) - offsetMs);
}
function parsePaymentSms(message) {
const result = {
rawMessage: message,
date: null,
type: null,
card: null,
recipient: null,
amount: null,
balance: null,
};
// Date and time: "Na DD/MM/YYYY v HH:MM"
const dateMatch = message.match(/Na (\d{2})\/(\d{2})\/(\d{4}) v (\d{2}):(\d{2})/i);
if (dateMatch) {
const [, day, month, year, hour, minute] = dateMatch;
result.date = localToUtc(
parseInt(year), parseInt(month), parseInt(day),
parseInt(hour), parseInt(minute),
);
}
// Card mask: "s karta 400915***4447" or "s karta 483890***7162"
const cardMatch = message.match(/s karta\s+([\d*]+)/i);
if (cardMatch) {
result.card = cardMatch[1];
}
// Transaction type: supports both prepositions
// "na POS" / "na ATM" / "na INTERNET" etc. (payment)
// "ot ATM" (withdrawal)
const typeMatch = message.match(/(?:na|ot)\s+(POS|ATM|INTERNET|ECOM|P2P)\b/i);
if (typeMatch) {
result.type = typeMatch[1].toUpperCase();
}
// Recipient address: "s adres: MERCHANT" or "s adres:MERCHANT" (no space variant)
const recipientMatch = message.match(/s adres:\s*([^.]+)\./i);
if (recipientMatch) {
result.recipient = recipientMatch[1].trim();
}
// Amount: handles both verbs and the AMOUNT/FEE suffix format
// "sa plateni 7.78 EUR"
// "sa iztegleni 400.00 EUR"
// "sa plateni 0.50 EUR/0.50 EUR" → captures 0.50 (the charged amount, ignoring fee)
const amountMatch = message.match(/sa (?:plateni|iztegleni)\s+([\d.,]+)\s+[A-Z]{3}/i);
if (amountMatch) {
result.amount = parseFloat(amountMatch[1].replace(',', '.'));
}
// Balance: "Nalichni: 2583.07 EUR."
const balanceMatch = message.match(/Nalichni:\s*([\d.,]+)\s+[A-Z]{3}/i);
if (balanceMatch) {
result.balance = parseFloat(balanceMatch[1].replace(',', '.'));
}
return result;
}
module.exports = { parsePaymentSms };
Write
csvParser.js
csvParser.js
175 lines
/**
* DSK Bank CSV parser — Node.js port of dskuploader.py
*
* DSK Bank exports use Windows-1251 (cp1251) encoding.
* Each row maps to a Payment record with source=UPLOAD, currency=BGN.
*/
const { parse } = require('csv-parse');
const iconv = require('iconv-lite');
const SKIP_TYPE = 'ТРАНСФЕР СОБСТВЕНИ СМЕТКИ';
const CARD_REGEX = /^\d{6}x{6}\d{4}$/;
const POS_REGEX = /^\s*ПЛАЩАНЕ\s+НА\s+ПОС\s+\d{2}\.\d{2}\.\d{4}\s+\d{2}:\d{2}/;
const COL = {
DATE: 'Дата',
TYPE: 'Вид на трансакцията',
REASON: 'Основание',
DEBIT: 'Дебит BGN',
CREDIT: 'Кредит BGN',
PAYEE: 'Наредител/Получател',
ACCT: 'Номер сметка на наредителя / получателя',
};
const TAG_RULES = [
['reason', 'ЗАПЛАТА', 'Salary'],
['reason', 'ТЕГЛЕНЕ НА ATM', 'ATM'],
['reason', 'ПЛАЩАНЕ ПО ЗАЕМ', 'Home Credit'],
['reason', 'АВТ.ТАКСА ОБСЛУЖВАНЕ', 'Bills'],
['transactionType', 'КОМУНАЛНИ УСЛУГИ', 'Bills'],
['payee', 'VIVACOM', 'Subscriptions'],
['payee', 'Google', 'Subscriptions'],
['payee', 'SkyShowtime', 'Subscriptions'],
['payee', 'NETFLIX', 'Subscriptions'],
['payee', 'LUKOIL', 'Bills'],
['payee', 'CityGate', 'Bills'],
['payee', 'CBA', 'Groceries'],
['payee', 'FANTASTICO', 'Groceries'],
['payee', 'LIDL', 'Groceries'],
];
function parseNum(val) {
if (val == null || val === '') return null;
if (typeof val === 'number') return isNaN(val) ? null : val;
const s = String(val).trim().replace(/\xa0/g, '').replace(/ /g, '').replace(',', '.');
const n = parseFloat(s);
return isNaN(n) ? null : n;
}
function parseDate(val) {
if (!val) return null;
const s = String(val).trim();
const m = s.match(/^(\d{2})\.(\d{2})\.(\d{4})$/);
if (m) {
return new Date(Date.UTC(parseInt(m[3]), parseInt(m[2]) - 1, parseInt(m[1])));
}
return null;
}
function processReasonAndCard(reason) {
if (!reason || typeof reason !== 'string') return { reason: '', card: null };
const parts = reason.trim().split(' ');
let card = null;
let cleanReason = reason.trim();
if (parts[0] && CARD_REGEX.test(parts[0])) {
card = parts[0];
cleanReason = parts.slice(1).join(' ').trim();
}
if (POS_REGEX.test(cleanReason)) {
const posParts = cleanReason.split('<br/>');
try {
const dateTime = posParts[0].split('ПОС ')[1];
cleanReason = `POS PAYMENT ${dateTime}`;
} catch (_) { /* keep original */ }
}
return { reason: cleanReason.replace(/\s+/g, ' ').trim(), card };
}
function generateTags(fields) {
const tags = new Set();
for (const [field, keyword, tagName] of TAG_RULES) {
if ((fields[field] || '').includes(keyword)) {
tags.add(tagName);
}
}
return Array.from(tags);
}
function processRow(row) {
const transactionType = (row[COL.TYPE] || '').trim();
if (transactionType === SKIP_TYPE) return null;
const { reason, card } = processReasonAndCard(row[COL.REASON]);
const payee = (row[COL.PAYEE] || '').trim();
const payerAccount = (row[COL.ACCT] || '').trim();
const debitBgn = parseNum(row[COL.DEBIT]);
const creditBgn = parseNum(row[COL.CREDIT]);
const date = parseDate(row[COL.DATE]);
const autoTags = generateTags({ reason, transactionType, payee, debitBgn, creditBgn });
const amount = debitBgn ?? creditBgn ?? null;
const rawMessage = [
row[COL.DATE] && `Date: ${row[COL.DATE]}`,
transactionType && `Type: ${transactionType}`,
payee && `Payee: ${payee}`,
debitBgn != null && `Debit: ${debitBgn} BGN`,
creditBgn != null && `Credit: ${creditBgn} BGN`,
].filter(Boolean).join(' | ');
return {
rawMessage,
date,
type: null,
card,
recipient: payee || null,
amount,
currency: 'BGN',
balance: null,
source: 'UPLOAD',
debitBgn,
creditBgn,
transactionType: transactionType || null,
payerAccount: payerAccount || null,
autoTags,
};
}
/**
* Parse a Buffer containing a DSK Bank CSV (cp1251 or UTF-8).
* Returns { rows, skipped, errors }.
*/
async function parseDskCsv(buffer) {
// Try cp1251 first (DSK Bank export encoding), fall back to UTF-8
let text = iconv.decode(buffer, 'cp1251');
if (!text.includes(COL.DATE)) {
text = buffer.toString('utf-8');
}
return new Promise((resolve, reject) => {
const rows = [];
const errors = [];
let skipped = 0;
const parser = parse(text, {
columns: true,
skip_empty_lines: true,
trim: true,
relax_column_count: true,
});
parser.on('readable', () => {
let record;
while ((record = parser.read()) !== null) {
try {
const row = processRow(record);
if (row === null) { skipped++; } else { rows.push(row); }
} catch (err) {
errors.push(err.message);
}
}
});
parser.on('error', reject);
parser.on('end', () => resolve({ rows, skipped, errors }));
});
}
module.exports = { parseDskCsv };
Write
index.js
index.js
39 lines
const express = require('express');
const cors = require('cors');
const morgan = require('morgan');
const rateLimit = require('express-rate-limit');
const { authentikMiddleware } = require('./auth');
const paymentsRouter = require('./routes/payments');
const uploadRouter = require('./routes/upload');
const app = express();
const PORT = process.env.PORT || 3001;
app.use(cors());
app.use(express.json({ limit: '16kb' }));
app.use(morgan('combined'));
// Rate-limit the public ingest endpoint before auth middleware
const ingestLimiter = rateLimit({
windowMs: 60 * 1000,
max: 200,
standardHeaders: true,
legacyHeaders: false,
message: { error: 'Too many requests, slow down' },
});
app.use('/api/payments/ingest', ingestLimiter);
// Authentik header auth (skips /api/health and /api/payments/ingest)
app.use(authentikMiddleware);
app.get('/api/health', (_req, res) => {
res.json({ status: 'ok', timestamp: new Date().toISOString() });
});
app.use('/api/payments', paymentsRouter);
app.use('/api/upload', uploadRouter);
app.listen(PORT, '[IP_ADDRESS]', () => {
console.log(`Finance Hub API running on port ${PORT}`);
});
Update Todos
Create folder structure and root config files
Write backend Prisma schema and migration
Write backend package.json and Dockerfile
Write backend src files (auth, parser, csvParser, index)...
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