|
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
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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":0.0,"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
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":0.27027926,"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
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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...
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Last login: Thu May 7 09:44:56 on ttys007
Poetry Last login: Thu May 7 09:44:56 on ttys007
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ git status
On branch master
Your branch is up to date with 'origin/master'.
Changes not staged for commit:
(use "git add <file>..." to update what will be committed)
(use "git restore <file>..." to discard changes in working directory)
modified: .env.local
modified: app/Console/Commands/JiminnyDebugCommand.php
modified: app/Jobs/Team/SyncToIntercom.php
modified: app/Services/PlaybackService.php
modified: config/logging.php
modified: resources/views/partials/crm/push-summary/html-assembly.blade.php
Untracked files:
(use "git add <file>..." to include in what will be committed)
.env.nikilocal
.env.other
WEBHOOK_FILTERING_IMPLEMENTATION.md
app/Console/Commands/Crm/Hubspot/SimulateWebhooksCommand.php
app/Console/Commands/Reports/CreateMockAskJiminnyReportResultCommand.php
ids.txt
public/favicon.ico
raw_sql_query.sql
tests/Unit/Policies/CanAccessAiReportsTest.php
no changes added to commit (use "git add" and/or "git commit -a")
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 1482, done.
remote: Counting objects: 100% (481/481), done.
remote: Compressing objects: 100% (191/191), done.
remote: Total 1482 (delta 349), reused 305 (delta 289), pack-reused 1001 (from 4)
Receiving objects: 100% (1482/1482), 1017.97 KiB | 1.44 MiB/s, done.
Resolving deltas: 100% (877/877), completed with 96 local objects.
From github.com:jiminny/app
83b628967a..ad2ce76737 master -> origin/master
1ee8cbcb7b..14f54b5be2 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3
5662c3b32f..b167b19973 JY-20289-api-tests -> origin/JY-20289-api-tests
b40408cfad..f23cfee7c3 JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null
* [new branch] JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import
* [new branch] JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall
* [new branch] JY-20662-remove-word-boost -> origin/JY-20662-remove-word-boost
* [new branch] JY-20742-mcp-poc -> origin/JY-20742-mcp-poc
* [new branch] make-claude-great-again -> origin/make-claude-great-again
* [new branch] secfix/composer-20260507 -> origin/secfix/composer-20260507
* [new branch] secfix/npm-20260507 -> origin/secfix/npm-20260507
Updating 83b628967a..ad2ce76737
error: Your local changes to the following files would be overwritten by merge:
app/Jobs/Team/SyncToIntercom.php
resources/views/partials/crm/push-summary/html-assembly.blade.php
Please commit your changes or stash them before you merge.
Aborting
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
Updating 83b628967a..ad2ce76737
error: Your local changes to the following files would be overwritten by merge:
app/Jobs/Team/SyncToIntercom.php
resources/views/partials/crm/push-summary/html-assembly.blade.php
Please commit your changes or stash them before you merge.
Aborting
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
Updating 83b628967a..ad2ce76737
error: Your local changes to the following files would be overwritten by merge:
app/Jobs/Team/SyncToIntercom.php
Please commit your changes or stash them before you merge.
Aborting
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
Updating 83b628967a..ad2ce76737
Fast-forward
.cursor/rules/frontend-conventions.mdc | 23 ++
.env.production-eu | 2 +-
.env.staging | 2 +-
Makefile | 10 +
app/Component/ActivityAnalytics/Service/ActivityAnalyticsService.php | 6 +-
app/Component/AiAutomation/Repositories/AiTemplateFieldsRepository.php | 32 +-
app/Component/AiCallScoring/Repositories/AiScorecardRepository.php | 56 ++--
app/Component/AskAnything/AskAnythingPromptService.php | 3 +
app/Component/Transcription/Job/FinishTranscriptionJob.php | 37 ++-
app/Component/Transcription/TranscriptionProcessor/Gong/Gong.php | 18 +-
app/Component/Twilio/Conference/ConferenceManager/SoftPhoneManager.php | 4 +-
app/Component/Twilio/Service/SoftPhoneService.php | 124 ++++---
app/Component/Twilio/TwilioRepository.php | 27 ++
app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php | 59 ----
app/Console/Commands/Reports/AutomatedReportsCommand.php | 122 +++++--
app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php | 200 ++++++++++++
app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php | 60 ----
app/Console/Commands/Users/SyncToIntercom.php | 4 +-
app/Console/Kernel.php | 3 +-
app/Contracts/ES/Events/UpdateMultipleEntities.php | 4 -
app/Contracts/ES/Events/UpdateSingleEntity.php | 4 -
app/Contracts/Repositories/TeamRepository.php | 3 +-
app/Events/Activities/ActivityUpdated.php | 10 +-
app/Events/Activities/Audio/RecordingEvent.php | 6 +-
app/Events/Activities/Softphone/Ended.php | 8 +-
app/Events/Activities/Softphone/SoftphoneEvent.php | 24 +-
app/Events/Activities/Softphone/Started.php | 8 +-
app/Http/Controllers/API/ActivityController.php | 17 +-
app/Http/Controllers/API/SoftphoneController.php | 9 +-
app/Http/Controllers/API/UserAutomatedReports/UserAutomatedReportsController.php | 19 +-
app/Http/Controllers/API/V2/AskAnythingController.php | 2 +-
app/Http/Controllers/Auth/SocialController.php | 6 +-
app/Http/Controllers/Kiosk/AutomatedReportsController.php | 38 ++-
app/Http/Controllers/Kiosk/OrganizationsController.php | 8 +-
app/Http/Controllers/Kiosk/PartnersController.php | 46 +++
app/Http/Controllers/Kiosk/SearchController.php | 8 +
app/Http/Controllers/Kiosk/Teams/OnboardController.php | 24 +-
app/Http/Controllers/Settings/Teams/IntegrationController.php | 6 +-
app/Http/Controllers/TeamSetupController.php | 4 +-
app/Http/Controllers/Telephony/TextMessaging/MessageController.php | 12 +-
app/Http/Controllers/Telephony/TextMessaging/WebhookController.php | 18 +-
app/Http/Requests/Settings/Teams/CreateTeamRequest.php | 1 +
app/Http/Requests/Settings/Teams/EditTeamRequest.php | 1 +
app/Http/Transformers/ActivityTransformer.php | 4 +-
app/Http/Transformers/OnDemandActivitiesTransformer.php | 2 +-
app/Http/Transformers/PartnerTransformer.php | 1 +
app/Http/Transformers/StageTransformer.php | 6 +-
app/Http/Transformers/UserTransformer.php | 11 +-
app/Interactions/Settings/Teams/CreateTeam.php | 3 +
app/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJob.php | 80 ++++-
app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php | 119 +++++++
app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php | 89 +++++
app/Jobs/Crm/Hubspot/ImportBatchJobTrait.php | 12 +-
app/Jobs/Crm/UpdateStage.php | 3 +
app/Jobs/Team/SyncToIntercom.php | 7 +-
app/Listeners/Teams/SyncIntercomCompany.php | 5 +-
app/Listeners/Teams/UpdateSalesforceAccount.php | 8 +-
app/Listeners/Users/SyncIntercom.php | 5 +-
app/Mail/Reports/AskJiminnyReportExpiringMail.php | 40 +++
app/Mail/Reports/ReportNotGenerated.php | 41 +++
app/Models/Activity.php | 25 +-
app/Models/Activity/Question.php | 14 +-
app/Models/Activity/Search.php | 7 +
app/Models/AskAnything/AskAnythingPrompt.php | 6 +
app/Models/AutomatedReport.php | 10 +
app/Models/CoachingFeedback.php | 44 ++-
app/Models/ElasticSearch/ActivityElasticSearchTrait.php | 86 +----
app/Models/ElasticSearch/OpportunityElasticSearchTrait.php | 71 ----
app/Models/ElasticSearch/SharedDocumentDeleteTrait.php | 27 --
app/Models/Partner.php | 13 +
app/Models/Playlist/Activity.php | 14 +-
app/Notifications/OwnerInvitedToTrial.php | 14 +-
app/Policies/UserPolicy.php | 16 +-
app/Queue/Worker/Worker.php | 3 +-
app/Repositories/ActivityRepository.php | 13 +-
app/Repositories/AutomatedReportsRepository.php | 42 ++-
app/Repositories/TeamRepository.php | 21 +-
app/Repositories/UserRepository.php | 2 +-
app/Services/Activity/MeetingBotService.php | 8 +-
app/Services/ActivityService.php | 111 ++-----
app/Services/Crm/Hubspot/Service.php | 36 +-
app/Services/Crm/Hubspot/ServiceTraits/OpportunitySyncTrait.php | 2 +-
app/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityService.php | 5 +-
app/Services/Kiosk/AutomatedReports/AutomatedReportsService.php | 49 +--
app/Services/Kiosk/KioskService.php | 7 +-
app/Services/Webhook/Triggers/AiScorecardCompletedTrigger.php | 13 +-
app/UseCases/TeamInsights/ConversationRowMapper.php | 78 +++++
app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php | 68 ++++
app/UseCases/TeamInsights/StrictConsentColumnResolver.php | 45 +++
app/UseCases/TeamInsights/TeamConversationsExport.php | 154 ++++-----
composer.json | 1 -
composer.lock | 95 +-----
config/secure-headers.php | 5 +-
database/mappings/mapping_activities.json | 16 +
database/migrations/2026_04_14_000000_add_rockeed_partner.php | 51 +++
database/migrations/2026_04_22_000000_add_success_email_to_partners.php | 26 ++
database/migrations/2026_04_27_000000_add_label_to_partners.php | 28 ++
database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php | 79 +++++
front-end/package.json | 5 +-
front-end/src/__mocks__/jiminny.js | 4 +-
front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js | 9 +
front-end/src/__mocks__/setup.js | 1 +
front-end/src/apps/ai-reports-promo.js | 22 ++
front-end/src/components/AiReports/AiReportsPromo.vue | 22 ++
front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue | 190 +++++++++++
front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue | 111 +++++++
front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue | 103 ++++++
front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js | 98 ++++++
.../src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html | 283 ++++++++++++++++
front-end/src/components/AiReports/Manage/ManageAiReports.vue | 8 +-
front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue | 228 +++++++++++++
front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js | 71 ++++
.../src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html | 217 ++++++++++++
front-end/src/components/AiReports/constants.js | 7 +
front-end/src/components/Settings/Kiosk/OrganizationSearch/Organizations.vue | 1 +
front-end/src/components/Settings/Kiosk/__mocks__/Jiminny.js | 1 +
front-end/src/components/Settings/Kiosk/modals/EditTeamModal/EditTeamModal.vue | 43 ++-
front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js | 203 ++++++++++++
front-end/src/components/Settings/Kiosk/shared/Navigation/Navigation.vue | 3 +
front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js | 67 ++++
front-end/src/components/TeamInsights/CoachingFrameworks/AICallScoring/aiCallScoringOverTime.ts | 4 +-
front-end/src/components/TeamInsights/CoachingFrameworks/UsersList.vue | 2 +-
front-end/src/components/layout/Sidebar/HelpMenu.vue | 25 +-
front-end/src/components/layout/Sidebar/Sidebar.vue | 27 +-
front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js | 94 ++++++
front-end/src/components/layout/Sidebar/__tests__/__snapshots__/Sidebar.spec.js.snap | 4 +-
front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js | 204 ++++++++++++
front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js | 49 +++
front-end/src/main.js | 1 +
front-end/src/store/modules/TeamInsights/util.js | 1 +
front-end/src/store/modules/platform/__tests__/getters.spec.js | 22 ++
front-end/src/store/modules/platform/getters.js | 3 +
front-end/src/utils/index.js | 11 +
front-end/yarn.lock | 21 +-
phpstan-baseline.neon | 60 ----
public/pdf/exec-reports/com/coaching-profiles.pdf | Bin 0 -> 1531178 bytes
public/pdf/exec-reports/com/exec-summary.pdf | Bin 0 -> 2237381 bytes
public/pdf/exec-reports/com/loss-report.pdf | Bin 0 -> 1955343 bytes
public/pdf/exec-reports/com/product-feedback.pdf | Bin 0 -> 2184417 bytes
public/pdf/exec-reports/eu/coaching-profiles.pdf | Bin 0 -> 1528704 bytes
public/pdf/exec-reports/eu/exec-summary.pdf | Bin 0 -> 2296741 bytes
public/pdf/exec-reports/eu/loss-report.pdf | Bin 0 -> 1955808 bytes
public/pdf/exec-reports/eu/product-feedback.pdf | Bin 0 -> 2184083 bytes
resources/views/emails/reports/ask-jiminny-report-expiring.blade.php | 22 ++
resources/views/emails/reports/report-not-generated.blade.php | 24 ++
resources/views/partials/crm/push-summary/html-assembly.blade.php | 2 +-
routes/api.php | 6 +
routes/web.php | 4 +
tests/Feature/Policies/UserPolicyTest.php | 90 ++++-
tests/Unit/Component/ActivityAnalytics/Service/ActivityAnalyticsServiceTest.php | 40 +++
tests/Unit/Component/AskAnything/AskAnythingPromptServiceTest.php | 26 ++
tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php | 276 ++++++++++++++++
tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php | 375 +++++++++++++++++++++
tests/Unit/Component/Twilio/Service/SoftPhoneServiceTest.php | 1014 +++++++++++++++++++++++++++++++++++++++++++++++++++++++--
tests/Unit/Console/Commands/Reports/AutomatedReportsCommandTest.php | 157 ++++++++-
tests/Unit/Events/Activities/Audio/RecordingEventTest.php | 72 ++++
tests/Unit/Events/Activities/Softphone/EndedTest.php | 86 +++++
tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php | 88 +++++
tests/Unit/Events/Activities/Softphone/StartedTest.php | 86 +++++
tests/Unit/Http/Controllers/Kiosk/AutomatedReportsControllerTest.php | 99 ++++++
tests/Unit/Http/Transformers/ActivityTransformerTest.php | 5 +-
tests/Unit/Http/Transformers/PartnerTransformerTest.php | 34 ++
tests/Unit/Interactions/Settings/Teams/CreateTeamTest.php | 49 +++
tests/Unit/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJobTest.php | 106 +++++-
tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php | 205 ++++++++++++
tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php | 188 +++++++++++
tests/Unit/Jobs/Crm/ImportOpportunityBatchTest.php | 2 +-
tests/Unit/Jobs/Team/SyncToIntercomTest.php | 6 +
tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php | 59 ++++
tests/Unit/Listeners/Teams/UpdateSalesforceAccountTest.php | 11 +-
tests/Unit/Listeners/Users/SyncIntercomTest.php | 59 ++++
tests/Unit/Mail/Reports/ReportNotGeneratedTest.php | 166 ++++++++++
tests/Unit/Models/PartnerTest.php | 28 ++
tests/Unit/Repositories/AutomatedReportsRepositoryTest.php | 68 ++++
tests/Unit/Services/Activity/MeetingBotServiceRequestRecordingToStopTest.php | 14 +-
tests/Unit/Services/ActivityServiceTest.php | 391 ++++++++++++++++++++++
tests/Unit/Services/Crm/Hubspot/ServiceResponseNormalizeTest.php | 68 ++--
tests/Unit/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityServiceTest.php | 48 +--
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceActivitiesCountTest.php | 16 +-
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceReportGenerationTest.php | 24 +-
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceTest.php | 130 ++++++++
tests/Unit/Services/KioskServiceTest.php | 8 +
tests/Unit/Services/Webhook/Triggers/AiScorecardCompletedTriggerTest.php | 6 +-
tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php | 119 +++++++
tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php | 108 ++++++
tests/Unit/UseCases/TeamInsights/TeamConversationsExportTest.php | 342 ++++++++++++++-----
186 files changed, 8538 insertions(+), 1233 deletions(-)
create mode 100644 app/Component/Twilio/TwilioRepository.php
delete mode 100644 app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php
create mode 100644 app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php
delete mode 100644 app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php
create mode 100644 app/Http/Controllers/Kiosk/PartnersController.php
create mode 100644 app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php
create mode 100644 app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php
create mode 100644 app/Mail/Reports/AskJiminnyReportExpiringMail.php
create mode 100644 app/Mail/Reports/ReportNotGenerated.php
delete mode 100644 app/Models/ElasticSearch/SharedDocumentDeleteTrait.php
create mode 100644 app/UseCases/TeamInsights/ConversationRowMapper.php
create mode 100644 app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php
create mode 100644 app/UseCases/TeamInsights/StrictConsentColumnResolver.php
create mode 100644 database/migrations/2026_04_14_000000_add_rockeed_partner.php
create mode 100644 database/migrations/2026_04_22_000000_add_success_email_to_partners.php
create mode 100644 database/migrations/2026_04_27_000000_add_label_to_partners.php
create mode 100644 database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php
create mode 100644 front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js
create mode 100644 front-end/src/apps/ai-reports-promo.js
create mode 100644 front-end/src/components/AiReports/AiReportsPromo.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html
create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue
create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js
create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html
create mode 100644 front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js
create mode 100644 front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js
create mode 100644 front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js
create mode 100644 front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js
create mode 100644 front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js
create mode 100644 front-end/src/store/modules/platform/__tests__/getters.spec.js
create mode 100644 public/pdf/exec-reports/com/coaching-profiles.pdf
create mode 100644 public/pdf/exec-reports/com/exec-summary.pdf
create mode 100644 public/pdf/exec-reports/com/loss-report.pdf
create mode 100644 public/pdf/exec-reports/com/product-feedback.pdf
create mode 100644 public/pdf/exec-reports/eu/coaching-profiles.pdf
create mode 100644 public/pdf/exec-reports/eu/exec-summary.pdf
create mode 100644 public/pdf/exec-reports/eu/loss-report.pdf
create mode 100644 public/pdf/exec-reports/eu/product-feedback.pdf
create mode 100644 resources/views/emails/reports/ask-jiminny-report-expiring.blade.php
create mode 100644 resources/views/emails/reports/report-not-generated.blade.php
create mode 100644 tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php
create mode 100644 tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php
create mode 100644 tests/Unit/Events/Activities/Audio/RecordingEventTest.php
create mode 100644 tests/Unit/Events/Activities/Softphone/EndedTest.php
create mode 100644 tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php
create mode 100644 tests/Unit/Events/Activities/Softphone/StartedTest.php
create mode 100644 tests/Unit/Http/Transformers/PartnerTransformerTest.php
create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php
create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php
create mode 100644 tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php
create mode 100644 tests/Unit/Listeners/Users/SyncIntercomTest.php
create mode 100644 tests/Unit/Mail/Reports/ReportNotGeneratedTest.php
create mode 100644 tests/Unit/Models/PartnerTest.php
create mode 100644 tests/Unit/Services/ActivityServiceTest.php
create mode 100644 tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php
create mode 100644 tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 628, done.
remote: Counting objects: 100% (331/331), done.
remote: Compressing objects: 100% (63/63), done.
remote: Total 628 (delta 280), reused 274 (delta 266), pack-reused 297 (from 1)
Receiving objects: 100% (628/628), 186.75 KiB | 1.23 MiB/s, done.
Resolving deltas: 100% (391/391), completed with 57 local objects.
From github.com:jiminny/app
ad2ce76737..12295204cf master -> origin/master
14f54b5be2..5e7646e5f9 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3
b167b19973..acba55cf38 JY-20289-api-tests -> origin/JY-20289-api-tests
f23cfee7c3..e5a3ec5dba JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null
af59d60926..766efba1c5 JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import
* [new branch] JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering
1737b7c528..c57e71e763 JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall
* [new branch] JY-20671-anyvan-twilio-s3-recordings-ftech -> origin/JY-20671-anyvan-twilio-s3-recordings-ftech
+ ba181441c6...20a74137b0 JY-20742-mcp-poc -> origin/JY-20742-mcp-poc (forced update)
* [new branch] JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue
* [new branch] JY-20816-calendar-events-diplication -> origin/JY-20816-calendar-events-diplication
* [new branch] desktop-app -> origin/desktop-app
4c4c974e46..185442c26e make-claude-great-again -> origin/make-claude-great-again
* [new branch] mcp-tools-schemas -> origin/mcp-tools-schemas
Updating ad2ce76737..12295204cf
Fast-forward
app/Component/Encoding/Job/AnalyzeTrackChannelsJob.php | 2 +-
app/Component/Transcription/TranscriptionProcessor/AssemblyAI/Services/SubmitAudioFileService.php | 66 ++----------------------------------------------------------------
app/Console/Commands/Tracks/CleanupActivityTracksCommand.php | 24 +++++++++++++++++-------
tests/Unit/Console/Commands/Tracks/CleanupActivityTracksCommandTest.php | 40 +++++++++++++++++++++++++++++-----------
tests/Unit/fixtures/assembly_ai_transcript_response.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_channel_diarization.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language_error.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language_not_ready.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language_post.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_without_utterances.json | 1 -
11 files changed, 49 insertions(+), 90 deletions(-)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20818-move-AJ-reports-to-separated-datadog-metric
Switched to a new branch 'JY-20818-move-AJ-reports-to-separated-datadog-metric'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix
docker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff
PHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.
PHP runtime: 8.3.30
Running analysis on 7 cores with 10 files per process.
Parallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!
Loaded config default from ".php-cs-fixer.dist.php".
5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%
Fixed 0 of 5663 files in 83.615 seconds, 67.00 MB memory used
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at [URL_WITH_CREDENTIALS] ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix
docker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff
PHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.
PHP runtime: 8.3.30
Running analysis on 7 cores with 10 files per process.
Parallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!
Loaded config default from ".php-cs-fixer.dist.php".
5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%
Fixed 0 of 5663 files in 42.875 seconds, 60.00 MB memory used
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at [URL_WITH_CREDENTIALS] ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 15, done.
remote: Counting objects: 100% (15/15), done.
remote: Compressing objects: 100% (2/2), done.
remote: Total 15 (delta 13), reused 15 (delta 13), pack-reused 0 (from 0)
Unpacking objects: 100% (15/15), 1.28 KiB | 72.00 KiB/s, done.
From github.com:jiminny/app
c57e71e763..8743fea32e JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall
* [new branch] JY-20819-increase-download-transctip-rate-limit -> origin/JY-20819-increase-download-transctip-rate-limit
Already up to date.
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 180, done.
remote: Counting objects: 100% (179/179), done.
remote: Compressing objects: 100% (55/55), done.
remote: Total 180 (delta 127), reused 165 (delta 119), pack-reused 1 (from 1)
Receiving objects: 100% (180/180), 57.50 KiB | 2.74 MiB/s, done.
Resolving deltas: 100% (127/127), completed with 47 local objects.
From github.com:jiminny/app
12295204cf..35f036ace6 master -> origin/master
* [new branch] JY-18091-upgrade-to-php-8-5 -> origin/JY-18091-upgrade-to-php-8-5
5f21965da8..497fbc85c2 JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering
f029263118..6ed9e2bb13 JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue
* [new branch] JY-20817-fix-deleting-s3-directories -> origin/JY-20817-fix-deleting-s3-directories
* [new branch] JY-20820-es-reindex-stream-model-hydration -> origin/JY-20820-es-reindex-stream-model-hydration
+ ca92730ec5...2c8a1d0856 desktop-app -> origin/desktop-app (forced update)
8425d4e0de..89b45ec8b0 mcp-tools-schemas -> origin/mcp-tools-schemas
Updating 12295204cf..35f036ace6
Fast-forward
app/Component/Datadog/Constants.php | 1 +
app/Providers/RouteServiceProvider.php | 2 +-
app/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackService.php | 13 +++++++++++++
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackServiceTest.php | 54 +++++++++++++++++++++++++++++++++++++++++++++++-------
4 files changed, 62 insertions(+), 8 deletions(-)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ gbr
* master
JY-20818-move-AJ-reports-to-separated-datadog-metric
JY-20773-fix-automated-reports-user-pilot-tracking
JY-20157-AJ-report-not-send-notification
JY-20508-notify-before-AJ-report-expiration
JY-20372-ai-reports-promotion-pages
JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null
JY-20738-debug-AJ-tracking-UP
a
JY-18909-automated-reports-ask-jiminny
JY-20692-fix-integration-app-[API_KEY]
JY-20553-debug-crm-sync-delays
JY-20698-fix-SF-activity-types-on-new-playbook
JY-20543-AJ-report-tracking
JY-20384-handle-auto-sync-with-no-access-to-event-type
JY-20458-ask-jiminny-user-definitions
JY-19666-fix-import-contacts-account-association
JY-19666-HS-import-contacts-and-accounts-batch-job
JY-20458-Ask-Jiminny-Reports
JY-20200-batch-update-CRM-objects-Salesforce
JY-19666-HS-webhooks-add-contact-and-company
JY-20348-trigger-setup-DI-layout-on-team-creation
JY-20326-refactor-info-message-in-command
JY-20317-fix-auto-log-delay-issue-on-all-channels-disabled
JY-20312-remove-on-update-change-last-synced-at-crm-configurations
JY-20306-SF-skip-auto-sync-for-task-based-playbook
JY-20192-remove-deleted-team-from-saved-search-filters
JY-20197-import-opportunity-batch-job
JY-20293-enable-status-field-for-pipedrive-deals
JY-20191-remove-commands-interactive-prompts
JY-20118-change-default-sync-strategy
JY-20183-add-cache-on-auto-log-delay
JY-20197-add-import-opportunity-batch-job
20118-hs-opportunity-make-webhook-strategy-default
JY-20118-make-default-hs-opportunity-sync-strategy-webhook-based
JY-20196-handle-opportunity-without-note
JY-20118-improve-opportunity-import
JY-20189-handle-activity-search-on-deleted-groups
JY-20160
JY-20145-filter-out-converted-leads-when-matching
JY-20150-skip-push-summary-on-summary-ready-if-autolog
JY-20132-fix-note-encoding
JY-19792-clean-logs
JY-20117-fix-sync-profile-fields-on-empty-fields
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20725-handle-HS-search-rate-limit
Switched to a new branch 'JY-20725-handle-HS-search-rate-limit'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ ;xd
docker exec -it docker_lamp_1 bash -c "mv /usr/local/etc/php/conf.d/xdebug.ini ~/xdebug.ini"
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at https://docs.docker.com/go/debug-cli/
docker exec -it docker_lamp_1 supervisorctl restart all
jiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: stopped
jiminny-worker-processing-2:jiminny-worker-processing-2_00: stopped
jiminny-worker-processing-3:jiminny-worker-processing-3_00: stopped
jiminny-worker-processing-4:jiminny-worker-processing-4_00: stopped
jiminny-worker-processing-5:jiminny-worker-processing-5_00: stopped
worker-analytics:worker-analytics_00: stopped
worker-crm-update:worker-crm-update_00: stopped
worker-download:worker-download_00: stopped
worker-nudges:worker-nudges_00: stopped
artisan-schedule:artisan-schedule_00: stopped
worker-emails:worker-emails_00: stopped
worker:worker_00: stopped
worker-calendar:worker-calendar_00: stopped
jiminny-worker-processing-1:jiminny-worker-processing-1_00: stopped
worker-crm-sync:worker-crm-sync_00: stopped
worker-audio:worker-audio_00: stopped
worker-conferences:worker-conferences_00: stopped
worker-es-update:worker-es-update_00: stopped
artisan-schedule:artisan-schedule_00: started
jiminny-worker-processing-1:jiminny-worker-processing-1_00: started
jiminny-worker-processing-2:jiminny-worker-processing-2_00: started
jiminny-worker-processing-3:jiminny-worker-processing-3_00: started
jiminny-worker-processing-4:jiminny-worker-processing-4_00: started
jiminny-worker-processing-5:jiminny-worker-processing-5_00: started
jiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: started
worker:worker_00: started
worker-analytics:worker-analytics_00: started
worker-audio:worker-audio_00: started
worker-calendar:worker-calendar_00: started
worker-conferences:worker-conferences_00: started
worker-crm-sync:worker-crm-sync_00: started
worker-crm-update:worker-crm-update_00: started
worker-download:worker-download_00: started
worker-emails:worker-emails_00: started
worker-es-update:worker-es-update_00: started
worker-nudges:worker-nudges_00: started
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at https://docs.docker.com/go/debug-cli/
docker exec -it docker_lamp_1 php -v
PHP 8.3.30 (cli) (built: Mar 16 2026 22:32:32) (NTS)
Copyright (c) The PHP Group
Zend En...
|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"Last login: Thu May 7 09:44:56 on ttys007\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ git status\nOn branch master\nYour branch is up to date with 'origin/master'.\n\nChanges not staged for commit:\n (use \"git add <file>...\" to update what will be committed)\n (use \"git restore <file>...\" to discard changes in working directory)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: .env.local\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: app/Console/Commands/JiminnyDebugCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: app/Jobs/Team/SyncToIntercom.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: app/Services/PlaybackService.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: config/logging.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: resources/views/partials/crm/push-summary/html-assembly.blade.php\n\nUntracked files:\n (use \"git add <file>...\" to include in what will be committed)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.nikilocal\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.other\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tWEBHOOK_FILTERING_IMPLEMENTATION.md\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Crm/Hubspot/SimulateWebhooksCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Reports/CreateMockAskJiminnyReportResultCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tids.txt\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tpublic/favicon.ico\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\traw_sql_query.sql\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\ttests/Unit/Policies/CanAccessAiReportsTest.php\n\nno changes added to commit (use \"git add\" and/or \"git commit -a\")\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nremote: Enumerating objects: 1482, done.\nremote: Counting objects: 100% (481/481), done.\nremote: Compressing objects: 100% (191/191), done.\nremote: Total 1482 (delta 349), reused 305 (delta 289), pack-reused 1001 (from 4)\nReceiving objects: 100% (1482/1482), 1017.97 KiB | 1.44 MiB/s, done.\nResolving deltas: 100% (877/877), completed with 96 local objects.\nFrom github.com:jiminny/app\n 83b628967a..ad2ce76737 master -> origin/master\n 1ee8cbcb7b..14f54b5be2 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3\n 5662c3b32f..b167b19973 JY-20289-api-tests -> origin/JY-20289-api-tests\n b40408cfad..f23cfee7c3 JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null\n * [new branch] JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import\n * [new branch] JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall\n * [new branch] JY-20662-remove-word-boost -> origin/JY-20662-remove-word-boost\n * [new branch] JY-20742-mcp-poc -> origin/JY-20742-mcp-poc\n * [new branch] make-claude-great-again -> origin/make-claude-great-again\n * [new branch] secfix/composer-20260507 -> origin/secfix/composer-20260507\n * [new branch] secfix/npm-20260507 -> origin/secfix/npm-20260507\nUpdating 83b628967a..ad2ce76737\nerror: Your local changes to the following files would be overwritten by merge:\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Jobs/Team/SyncToIntercom.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tresources/views/partials/crm/push-summary/html-assembly.blade.php\nPlease commit your changes or stash them before you merge.\nAborting\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nUpdating 83b628967a..ad2ce76737\nerror: Your local changes to the following files would be overwritten by merge:\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Jobs/Team/SyncToIntercom.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tresources/views/partials/crm/push-summary/html-assembly.blade.php\nPlease commit your changes or stash them before you merge.\nAborting\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nUpdating 83b628967a..ad2ce76737\nerror: Your local changes to the following files would be overwritten by merge:\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Jobs/Team/SyncToIntercom.php\nPlease commit your changes or stash them before you merge.\nAborting\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nUpdating 83b628967a..ad2ce76737\nFast-forward\n .cursor/rules/frontend-conventions.mdc | 23 ++\n .env.production-eu | 2 +-\n .env.staging | 2 +-\n Makefile | 10 +\n app/Component/ActivityAnalytics/Service/ActivityAnalyticsService.php | 6 +-\n app/Component/AiAutomation/Repositories/AiTemplateFieldsRepository.php | 32 +-\n app/Component/AiCallScoring/Repositories/AiScorecardRepository.php | 56 ++--\n app/Component/AskAnything/AskAnythingPromptService.php | 3 +\n app/Component/Transcription/Job/FinishTranscriptionJob.php | 37 ++-\n app/Component/Transcription/TranscriptionProcessor/Gong/Gong.php | 18 +-\n app/Component/Twilio/Conference/ConferenceManager/SoftPhoneManager.php | 4 +-\n app/Component/Twilio/Service/SoftPhoneService.php | 124 ++++---\n app/Component/Twilio/TwilioRepository.php | 27 ++\n app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php | 59 ----\n app/Console/Commands/Reports/AutomatedReportsCommand.php | 122 +++++--\n app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php | 200 ++++++++++++\n app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php | 60 ----\n app/Console/Commands/Users/SyncToIntercom.php | 4 +-\n app/Console/Kernel.php | 3 +-\n app/Contracts/ES/Events/UpdateMultipleEntities.php | 4 -\n app/Contracts/ES/Events/UpdateSingleEntity.php | 4 -\n app/Contracts/Repositories/TeamRepository.php | 3 +-\n app/Events/Activities/ActivityUpdated.php | 10 +-\n app/Events/Activities/Audio/RecordingEvent.php | 6 +-\n app/Events/Activities/Softphone/Ended.php | 8 +-\n app/Events/Activities/Softphone/SoftphoneEvent.php | 24 +-\n app/Events/Activities/Softphone/Started.php | 8 +-\n app/Http/Controllers/API/ActivityController.php | 17 +-\n app/Http/Controllers/API/SoftphoneController.php | 9 +-\n app/Http/Controllers/API/UserAutomatedReports/UserAutomatedReportsController.php | 19 +-\n app/Http/Controllers/API/V2/AskAnythingController.php | 2 +-\n app/Http/Controllers/Auth/SocialController.php | 6 +-\n app/Http/Controllers/Kiosk/AutomatedReportsController.php | 38 ++-\n app/Http/Controllers/Kiosk/OrganizationsController.php | 8 +-\n app/Http/Controllers/Kiosk/PartnersController.php | 46 +++\n app/Http/Controllers/Kiosk/SearchController.php | 8 +\n app/Http/Controllers/Kiosk/Teams/OnboardController.php | 24 +-\n app/Http/Controllers/Settings/Teams/IntegrationController.php | 6 +-\n app/Http/Controllers/TeamSetupController.php | 4 +-\n app/Http/Controllers/Telephony/TextMessaging/MessageController.php | 12 +-\n app/Http/Controllers/Telephony/TextMessaging/WebhookController.php | 18 +-\n app/Http/Requests/Settings/Teams/CreateTeamRequest.php | 1 +\n app/Http/Requests/Settings/Teams/EditTeamRequest.php | 1 +\n app/Http/Transformers/ActivityTransformer.php | 4 +-\n app/Http/Transformers/OnDemandActivitiesTransformer.php | 2 +-\n app/Http/Transformers/PartnerTransformer.php | 1 +\n app/Http/Transformers/StageTransformer.php | 6 +-\n app/Http/Transformers/UserTransformer.php | 11 +-\n app/Interactions/Settings/Teams/CreateTeam.php | 3 +\n app/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJob.php | 80 ++++-\n app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php | 119 +++++++\n app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php | 89 +++++\n app/Jobs/Crm/Hubspot/ImportBatchJobTrait.php | 12 +-\n app/Jobs/Crm/UpdateStage.php | 3 +\n app/Jobs/Team/SyncToIntercom.php | 7 +-\n app/Listeners/Teams/SyncIntercomCompany.php | 5 +-\n app/Listeners/Teams/UpdateSalesforceAccount.php | 8 +-\n app/Listeners/Users/SyncIntercom.php | 5 +-\n app/Mail/Reports/AskJiminnyReportExpiringMail.php | 40 +++\n app/Mail/Reports/ReportNotGenerated.php | 41 +++\n app/Models/Activity.php | 25 +-\n app/Models/Activity/Question.php | 14 +-\n app/Models/Activity/Search.php | 7 +\n app/Models/AskAnything/AskAnythingPrompt.php | 6 +\n app/Models/AutomatedReport.php | 10 +\n app/Models/CoachingFeedback.php | 44 ++-\n app/Models/ElasticSearch/ActivityElasticSearchTrait.php | 86 +----\n app/Models/ElasticSearch/OpportunityElasticSearchTrait.php | 71 ----\n app/Models/ElasticSearch/SharedDocumentDeleteTrait.php | 27 --\n app/Models/Partner.php | 13 +\n app/Models/Playlist/Activity.php | 14 +-\n app/Notifications/OwnerInvitedToTrial.php | 14 +-\n app/Policies/UserPolicy.php | 16 +-\n app/Queue/Worker/Worker.php | 3 +-\n app/Repositories/ActivityRepository.php | 13 +-\n app/Repositories/AutomatedReportsRepository.php | 42 ++-\n app/Repositories/TeamRepository.php | 21 +-\n app/Repositories/UserRepository.php | 2 +-\n app/Services/Activity/MeetingBotService.php | 8 +-\n app/Services/ActivityService.php | 111 ++-----\n app/Services/Crm/Hubspot/Service.php | 36 +-\n app/Services/Crm/Hubspot/ServiceTraits/OpportunitySyncTrait.php | 2 +-\n app/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityService.php | 5 +-\n app/Services/Kiosk/AutomatedReports/AutomatedReportsService.php | 49 +--\n app/Services/Kiosk/KioskService.php | 7 +-\n app/Services/Webhook/Triggers/AiScorecardCompletedTrigger.php | 13 +-\n app/UseCases/TeamInsights/ConversationRowMapper.php | 78 +++++\n app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php | 68 ++++\n app/UseCases/TeamInsights/StrictConsentColumnResolver.php | 45 +++\n app/UseCases/TeamInsights/TeamConversationsExport.php | 154 ++++-----\n composer.json | 1 -\n composer.lock | 95 +-----\n config/secure-headers.php | 5 +-\n database/mappings/mapping_activities.json | 16 +\n database/migrations/2026_04_14_000000_add_rockeed_partner.php | 51 +++\n database/migrations/2026_04_22_000000_add_success_email_to_partners.php | 26 ++\n database/migrations/2026_04_27_000000_add_label_to_partners.php | 28 ++\n database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php | 79 +++++\n front-end/package.json | 5 +-\n front-end/src/__mocks__/jiminny.js | 4 +-\n front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js | 9 +\n front-end/src/__mocks__/setup.js | 1 +\n front-end/src/apps/ai-reports-promo.js | 22 ++\n front-end/src/components/AiReports/AiReportsPromo.vue | 22 ++\n front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue | 190 +++++++++++\n front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue | 111 +++++++\n front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue | 103 ++++++\n front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js | 98 ++++++\n .../src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html | 283 ++++++++++++++++\n front-end/src/components/AiReports/Manage/ManageAiReports.vue | 8 +-\n front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue | 228 +++++++++++++\n front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js | 71 ++++\n .../src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html | 217 ++++++++++++\n front-end/src/components/AiReports/constants.js | 7 +\n front-end/src/components/Settings/Kiosk/OrganizationSearch/Organizations.vue | 1 +\n front-end/src/components/Settings/Kiosk/__mocks__/Jiminny.js | 1 +\n front-end/src/components/Settings/Kiosk/modals/EditTeamModal/EditTeamModal.vue | 43 ++-\n front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js | 203 ++++++++++++\n front-end/src/components/Settings/Kiosk/shared/Navigation/Navigation.vue | 3 +\n front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js | 67 ++++\n front-end/src/components/TeamInsights/CoachingFrameworks/AICallScoring/aiCallScoringOverTime.ts | 4 +-\n front-end/src/components/TeamInsights/CoachingFrameworks/UsersList.vue | 2 +-\n front-end/src/components/layout/Sidebar/HelpMenu.vue | 25 +-\n front-end/src/components/layout/Sidebar/Sidebar.vue | 27 +-\n front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js | 94 ++++++\n front-end/src/components/layout/Sidebar/__tests__/__snapshots__/Sidebar.spec.js.snap | 4 +-\n front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js | 204 ++++++++++++\n front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js | 49 +++\n front-end/src/main.js | 1 +\n front-end/src/store/modules/TeamInsights/util.js | 1 +\n front-end/src/store/modules/platform/__tests__/getters.spec.js | 22 ++\n front-end/src/store/modules/platform/getters.js | 3 +\n front-end/src/utils/index.js | 11 +\n front-end/yarn.lock | 21 +-\n phpstan-baseline.neon | 60 ----\n public/pdf/exec-reports/com/coaching-profiles.pdf | Bin 0 -> 1531178 bytes\n public/pdf/exec-reports/com/exec-summary.pdf | Bin 0 -> 2237381 bytes\n public/pdf/exec-reports/com/loss-report.pdf | Bin 0 -> 1955343 bytes\n public/pdf/exec-reports/com/product-feedback.pdf | Bin 0 -> 2184417 bytes\n public/pdf/exec-reports/eu/coaching-profiles.pdf | Bin 0 -> 1528704 bytes\n public/pdf/exec-reports/eu/exec-summary.pdf | Bin 0 -> 2296741 bytes\n public/pdf/exec-reports/eu/loss-report.pdf | Bin 0 -> 1955808 bytes\n public/pdf/exec-reports/eu/product-feedback.pdf | Bin 0 -> 2184083 bytes\n resources/views/emails/reports/ask-jiminny-report-expiring.blade.php | 22 ++\n resources/views/emails/reports/report-not-generated.blade.php | 24 ++\n resources/views/partials/crm/push-summary/html-assembly.blade.php | 2 +-\n routes/api.php | 6 +\n routes/web.php | 4 +\n tests/Feature/Policies/UserPolicyTest.php | 90 ++++-\n tests/Unit/Component/ActivityAnalytics/Service/ActivityAnalyticsServiceTest.php | 40 +++\n tests/Unit/Component/AskAnything/AskAnythingPromptServiceTest.php | 26 ++\n tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php | 276 ++++++++++++++++\n tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php | 375 +++++++++++++++++++++\n tests/Unit/Component/Twilio/Service/SoftPhoneServiceTest.php | 1014 +++++++++++++++++++++++++++++++++++++++++++++++++++++++--\n tests/Unit/Console/Commands/Reports/AutomatedReportsCommandTest.php | 157 ++++++++-\n tests/Unit/Events/Activities/Audio/RecordingEventTest.php | 72 ++++\n tests/Unit/Events/Activities/Softphone/EndedTest.php | 86 +++++\n tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php | 88 +++++\n tests/Unit/Events/Activities/Softphone/StartedTest.php | 86 +++++\n tests/Unit/Http/Controllers/Kiosk/AutomatedReportsControllerTest.php | 99 ++++++\n tests/Unit/Http/Transformers/ActivityTransformerTest.php | 5 +-\n tests/Unit/Http/Transformers/PartnerTransformerTest.php | 34 ++\n tests/Unit/Interactions/Settings/Teams/CreateTeamTest.php | 49 +++\n tests/Unit/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJobTest.php | 106 +++++-\n tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php | 205 ++++++++++++\n tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php | 188 +++++++++++\n tests/Unit/Jobs/Crm/ImportOpportunityBatchTest.php | 2 +-\n tests/Unit/Jobs/Team/SyncToIntercomTest.php | 6 +\n tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php | 59 ++++\n tests/Unit/Listeners/Teams/UpdateSalesforceAccountTest.php | 11 +-\n tests/Unit/Listeners/Users/SyncIntercomTest.php | 59 ++++\n tests/Unit/Mail/Reports/ReportNotGeneratedTest.php | 166 ++++++++++\n tests/Unit/Models/PartnerTest.php | 28 ++\n tests/Unit/Repositories/AutomatedReportsRepositoryTest.php | 68 ++++\n tests/Unit/Services/Activity/MeetingBotServiceRequestRecordingToStopTest.php | 14 +-\n tests/Unit/Services/ActivityServiceTest.php | 391 ++++++++++++++++++++++\n tests/Unit/Services/Crm/Hubspot/ServiceResponseNormalizeTest.php | 68 ++--\n tests/Unit/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityServiceTest.php | 48 +--\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceActivitiesCountTest.php | 16 +-\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceReportGenerationTest.php | 24 +-\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceTest.php | 130 ++++++++\n tests/Unit/Services/KioskServiceTest.php | 8 +\n tests/Unit/Services/Webhook/Triggers/AiScorecardCompletedTriggerTest.php | 6 +-\n tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php | 119 +++++++\n tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php | 108 ++++++\n tests/Unit/UseCases/TeamInsights/TeamConversationsExportTest.php | 342 ++++++++++++++-----\n 186 files changed, 8538 insertions(+), 1233 deletions(-)\n create mode 100644 app/Component/Twilio/TwilioRepository.php\n delete mode 100644 app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php\n create mode 100644 app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php\n delete mode 100644 app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php\n create mode 100644 app/Http/Controllers/Kiosk/PartnersController.php\n create mode 100644 app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php\n create mode 100644 app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php\n create mode 100644 app/Mail/Reports/AskJiminnyReportExpiringMail.php\n create mode 100644 app/Mail/Reports/ReportNotGenerated.php\n delete mode 100644 app/Models/ElasticSearch/SharedDocumentDeleteTrait.php\n create mode 100644 app/UseCases/TeamInsights/ConversationRowMapper.php\n create mode 100644 app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php\n create mode 100644 app/UseCases/TeamInsights/StrictConsentColumnResolver.php\n create mode 100644 database/migrations/2026_04_14_000000_add_rockeed_partner.php\n create mode 100644 database/migrations/2026_04_22_000000_add_success_email_to_partners.php\n create mode 100644 database/migrations/2026_04_27_000000_add_label_to_partners.php\n create mode 100644 database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php\n create mode 100644 front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js\n create mode 100644 front-end/src/apps/ai-reports-promo.js\n create mode 100644 front-end/src/components/AiReports/AiReportsPromo.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html\n create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue\n create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js\n create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html\n create mode 100644 front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js\n create mode 100644 front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js\n create mode 100644 front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js\n create mode 100644 front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js\n create mode 100644 front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js\n create mode 100644 front-end/src/store/modules/platform/__tests__/getters.spec.js\n create mode 100644 public/pdf/exec-reports/com/coaching-profiles.pdf\n create mode 100644 public/pdf/exec-reports/com/exec-summary.pdf\n create mode 100644 public/pdf/exec-reports/com/loss-report.pdf\n create mode 100644 public/pdf/exec-reports/com/product-feedback.pdf\n create mode 100644 public/pdf/exec-reports/eu/coaching-profiles.pdf\n create mode 100644 public/pdf/exec-reports/eu/exec-summary.pdf\n create mode 100644 public/pdf/exec-reports/eu/loss-report.pdf\n create mode 100644 public/pdf/exec-reports/eu/product-feedback.pdf\n create mode 100644 resources/views/emails/reports/ask-jiminny-report-expiring.blade.php\n create mode 100644 resources/views/emails/reports/report-not-generated.blade.php\n create mode 100644 tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php\n create mode 100644 tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php\n create mode 100644 tests/Unit/Events/Activities/Audio/RecordingEventTest.php\n create mode 100644 tests/Unit/Events/Activities/Softphone/EndedTest.php\n create mode 100644 tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php\n create mode 100644 tests/Unit/Events/Activities/Softphone/StartedTest.php\n create mode 100644 tests/Unit/Http/Transformers/PartnerTransformerTest.php\n create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php\n create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php\n create mode 100644 tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php\n create mode 100644 tests/Unit/Listeners/Users/SyncIntercomTest.php\n create mode 100644 tests/Unit/Mail/Reports/ReportNotGeneratedTest.php\n create mode 100644 tests/Unit/Models/PartnerTest.php\n create mode 100644 tests/Unit/Services/ActivityServiceTest.php\n create mode 100644 tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php\n create mode 100644 tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull \nremote: Enumerating objects: 628, done.\nremote: Counting objects: 100% (331/331), done.\nremote: Compressing objects: 100% (63/63), done.\nremote: Total 628 (delta 280), reused 274 (delta 266), pack-reused 297 (from 1)\nReceiving objects: 100% (628/628), 186.75 KiB | 1.23 MiB/s, done.\nResolving deltas: 100% (391/391), completed with 57 local objects.\nFrom github.com:jiminny/app\n ad2ce76737..12295204cf master -> origin/master\n 14f54b5be2..5e7646e5f9 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3\n b167b19973..acba55cf38 JY-20289-api-tests -> origin/JY-20289-api-tests\n f23cfee7c3..e5a3ec5dba JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null\n af59d60926..766efba1c5 JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import\n * [new branch] JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering\n 1737b7c528..c57e71e763 JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall\n * [new branch] JY-20671-anyvan-twilio-s3-recordings-ftech -> origin/JY-20671-anyvan-twilio-s3-recordings-ftech\n + ba181441c6...20a74137b0 JY-20742-mcp-poc -> origin/JY-20742-mcp-poc (forced update)\n * [new branch] JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue\n * [new branch] JY-20816-calendar-events-diplication -> origin/JY-20816-calendar-events-diplication\n * [new branch] desktop-app -> origin/desktop-app\n 4c4c974e46..185442c26e make-claude-great-again -> origin/make-claude-great-again\n * [new branch] mcp-tools-schemas -> origin/mcp-tools-schemas\nUpdating ad2ce76737..12295204cf\nFast-forward\n app/Component/Encoding/Job/AnalyzeTrackChannelsJob.php | 2 +-\n app/Component/Transcription/TranscriptionProcessor/AssemblyAI/Services/SubmitAudioFileService.php | 66 ++----------------------------------------------------------------\n app/Console/Commands/Tracks/CleanupActivityTracksCommand.php | 24 +++++++++++++++++-------\n tests/Unit/Console/Commands/Tracks/CleanupActivityTracksCommandTest.php | 40 +++++++++++++++++++++++++++++-----------\n tests/Unit/fixtures/assembly_ai_transcript_response.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_channel_diarization.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language_error.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language_not_ready.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language_post.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_without_utterances.json | 1 -\n 11 files changed, 49 insertions(+), 90 deletions(-)\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20818-move-AJ-reports-to-separated-datadog-metric\nSwitched to a new branch 'JY-20818-move-AJ-reports-to-separated-datadog-metric'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5663 files in 83.615 seconds, 67.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ ;xd\ndocker exec -it docker_lamp_1 bash -c \"mv /usr/local/etc/php/conf.d/xdebug.ini ~/xdebug.ini\"\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 supervisorctl restart all\njiminny-worker-processing-2:jiminny-worker-processing-2_00: stopped\njiminny-worker-processing-3:jiminny-worker-processing-3_00: stopped\njiminny-worker-processing-4:jiminny-worker-processing-4_00: stopped\njiminny-worker-processing-5:jiminny-worker-processing-5_00: stopped\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: stopped\nworker-analytics:worker-analytics_00: stopped\nworker-crm-update:worker-crm-update_00: stopped\nworker-download:worker-download_00: stopped\nworker-nudges:worker-nudges_00: stopped\nartisan-schedule:artisan-schedule_00: stopped\nworker-calendar:worker-calendar_00: stopped\nworker-crm-sync:worker-crm-sync_00: stopped\njiminny-worker-processing-1:jiminny-worker-processing-1_00: stopped\nworker:worker_00: stopped\nworker-emails:worker-emails_00: stopped\nworker-audio:worker-audio_00: stopped\nworker-conferences:worker-conferences_00: stopped\nworker-es-update:worker-es-update_00: stopped\nartisan-schedule:artisan-schedule_00: started\njiminny-worker-processing-1:jiminny-worker-processing-1_00: started\njiminny-worker-processing-2:jiminny-worker-processing-2_00: started\njiminny-worker-processing-3:jiminny-worker-processing-3_00: started\njiminny-worker-processing-4:jiminny-worker-processing-4_00: started\njiminny-worker-processing-5:jiminny-worker-processing-5_00: started\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: started\nworker:worker_00: started\nworker-analytics:worker-analytics_00: started\nworker-audio:worker-audio_00: started\nworker-calendar:worker-calendar_00: started\nworker-conferences:worker-conferences_00: started\nworker-crm-sync:worker-crm-sync_00: started\nworker-crm-update:worker-crm-update_00: started\nworker-download:worker-download_00: started\nworker-emails:worker-emails_00: started\nworker-es-update:worker-es-update_00: started\nworker-nudges:worker-nudges_00: started\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 php -v\nPHP 8.3.30 (cli) (built: Mar 16 2026 22:32:32) (NTS)\nCopyright (c) The PHP Group\nZend Engine v4.3.30, Copyright (c) Zend Technologies\n with Zend OPcache v8.3.30, Copyright (c), by Zend Technologies\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5663 files in 42.875 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ git status\nOn branch master\nYour branch is up to date with 'origin/master'.\n\nChanges not staged for commit:\n (use \"git add <file>...\" to update what will be committed)\n (use \"git restore <file>...\" to discard changes in working directory)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: .env.local\n\nUntracked files:\n (use \"git add <file>...\" to include in what will be committed)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.nikilocal\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.other\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tWEBHOOK_FILTERING_IMPLEMENTATION.md\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Crm/Hubspot/SimulateWebhooksCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Reports/CreateMockAskJiminnyReportResultCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tids.txt\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tpublic/favicon.ico\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\traw_sql_query.sql\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\ttests/Unit/Policies/CanAccessAiReportsTest.php\n\nno changes added to commit (use \"git add\" and/or \"git commit -a\")\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nremote: Enumerating objects: 15, done.\nremote: Counting objects: 100% (15/15), done.\nremote: Compressing objects: 100% (2/2), done.\nremote: Total 15 (delta 13), reused 15 (delta 13), pack-reused 0 (from 0)\nUnpacking objects: 100% (15/15), 1.28 KiB | 72.00 KiB/s, done.\nFrom github.com:jiminny/app\n c57e71e763..8743fea32e JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall\n * [new branch] JY-20819-increase-download-transctip-rate-limit -> origin/JY-20819-increase-download-transctip-rate-limit\nAlready up to date.\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull \nremote: Enumerating objects: 180, done.\nremote: Counting objects: 100% (179/179), done.\nremote: Compressing objects: 100% (55/55), done.\nremote: Total 180 (delta 127), reused 165 (delta 119), pack-reused 1 (from 1)\nReceiving objects: 100% (180/180), 57.50 KiB | 2.74 MiB/s, done.\nResolving deltas: 100% (127/127), completed with 47 local objects.\nFrom github.com:jiminny/app\n 12295204cf..35f036ace6 master -> origin/master\n * [new branch] JY-18091-upgrade-to-php-8-5 -> origin/JY-18091-upgrade-to-php-8-5\n 5f21965da8..497fbc85c2 JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering\n f029263118..6ed9e2bb13 JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue\n * [new branch] JY-20817-fix-deleting-s3-directories -> origin/JY-20817-fix-deleting-s3-directories\n * [new branch] JY-20820-es-reindex-stream-model-hydration -> origin/JY-20820-es-reindex-stream-model-hydration\n + ca92730ec5...2c8a1d0856 desktop-app -> origin/desktop-app (forced update)\n 8425d4e0de..89b45ec8b0 mcp-tools-schemas -> origin/mcp-tools-schemas\nUpdating 12295204cf..35f036ace6\nFast-forward\n app/Component/Datadog/Constants.php | 1 +\n app/Providers/RouteServiceProvider.php | 2 +-\n app/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackService.php | 13 +++++++++++++\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackServiceTest.php | 54 +++++++++++++++++++++++++++++++++++++++++++++++-------\n 4 files changed, 62 insertions(+), 8 deletions(-)\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ gbr \n* master\n JY-20818-move-AJ-reports-to-separated-datadog-metric\n JY-20773-fix-automated-reports-user-pilot-tracking\n JY-20157-AJ-report-not-send-notification\n JY-20508-notify-before-AJ-report-expiration\n JY-20372-ai-reports-promotion-pages\n JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null\n JY-20738-debug-AJ-tracking-UP\n a\n JY-18909-automated-reports-ask-jiminny\n JY-20692-fix-integration-app-token-auth-response-change\n JY-20553-debug-crm-sync-delays\n JY-20698-fix-SF-activity-types-on-new-playbook\n JY-20543-AJ-report-tracking\n JY-20384-handle-auto-sync-with-no-access-to-event-type\n JY-20458-ask-jiminny-user-definitions\n JY-19666-fix-import-contacts-account-association\n JY-19666-HS-import-contacts-and-accounts-batch-job\n JY-20458-Ask-Jiminny-Reports\n JY-20200-batch-update-CRM-objects-Salesforce\n JY-19666-HS-webhooks-add-contact-and-company\n JY-20348-trigger-setup-DI-layout-on-team-creation\n JY-20326-refactor-info-message-in-command\n JY-20317-fix-auto-log-delay-issue-on-all-channels-disabled\n JY-20312-remove-on-update-change-last-synced-at-crm-configurations\n JY-20306-SF-skip-auto-sync-for-task-based-playbook\n JY-20192-remove-deleted-team-from-saved-search-filters\n JY-20197-import-opportunity-batch-job\n JY-20293-enable-status-field-for-pipedrive-deals\n JY-20191-remove-commands-interactive-prompts\n JY-20118-change-default-sync-strategy\n JY-20183-add-cache-on-auto-log-delay\n JY-20197-add-import-opportunity-batch-job\n 20118-hs-opportunity-make-webhook-strategy-default\n JY-20118-make-default-hs-opportunity-sync-strategy-webhook-based\n JY-20196-handle-opportunity-without-note\n JY-20118-improve-opportunity-import\n JY-20189-handle-activity-search-on-deleted-groups\n JY-20160\n JY-20145-filter-out-converted-leads-when-matching\n JY-20150-skip-push-summary-on-summary-ready-if-autolog\n JY-20132-fix-note-encoding\n JY-19792-clean-logs\n JY-20117-fix-sync-profile-fields-on-empty-fields\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20725-handle-HS-search-rate-limit \nSwitched to a new branch 'JY-20725-handle-HS-search-rate-limit'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ ;xd\ndocker exec -it docker_lamp_1 bash -c \"mv /usr/local/etc/php/conf.d/xdebug.ini ~/xdebug.ini\"\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 supervisorctl restart all\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: stopped\njiminny-worker-processing-2:jiminny-worker-processing-2_00: stopped\njiminny-worker-processing-3:jiminny-worker-processing-3_00: stopped\njiminny-worker-processing-4:jiminny-worker-processing-4_00: stopped\njiminny-worker-processing-5:jiminny-worker-processing-5_00: stopped\nworker-analytics:worker-analytics_00: stopped\nworker-crm-update:worker-crm-update_00: stopped\nworker-download:worker-download_00: stopped\nworker-nudges:worker-nudges_00: stopped\nartisan-schedule:artisan-schedule_00: stopped\nworker-emails:worker-emails_00: stopped\nworker:worker_00: stopped\nworker-calendar:worker-calendar_00: stopped\njiminny-worker-processing-1:jiminny-worker-processing-1_00: stopped\nworker-crm-sync:worker-crm-sync_00: stopped\nworker-audio:worker-audio_00: stopped\nworker-conferences:worker-conferences_00: stopped\nworker-es-update:worker-es-update_00: stopped\nartisan-schedule:artisan-schedule_00: started\njiminny-worker-processing-1:jiminny-worker-processing-1_00: started\njiminny-worker-processing-2:jiminny-worker-processing-2_00: started\njiminny-worker-processing-3:jiminny-worker-processing-3_00: started\njiminny-worker-processing-4:jiminny-worker-processing-4_00: started\njiminny-worker-processing-5:jiminny-worker-processing-5_00: started\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: started\nworker:worker_00: started\nworker-analytics:worker-analytics_00: started\nworker-audio:worker-audio_00: started\nworker-calendar:worker-calendar_00: started\nworker-conferences:worker-conferences_00: started\nworker-crm-sync:worker-crm-sync_00: started\nworker-crm-update:worker-crm-update_00: started\nworker-download:worker-download_00: started\nworker-emails:worker-emails_00: started\nworker-es-update:worker-es-update_00: started\nworker-nudges:worker-nudges_00: started\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 php -v\nPHP 8.3.30 (cli) (built: Mar 16 2026 22:32:32) (NTS)\nCopyright (c) The PHP Group\nZend Engine v4.3.30, Copyright (c) Zend Technologies\n with Zend OPcache v8.3.30, Copyright (c), by Zend Technologies\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5666/5666 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n 1) app/Jobs/Crm/MatchActivityCrmData.php (ordered_class_elements)\n ---------- begin diff ----------\n--- /home/jiminny/app/Jobs/Crm/MatchActivityCrmData.php\n+++ /home/jiminny/app/Jobs/Crm/MatchActivityCrmData.php\n@@ -29,24 +29,14 @@\n use InteractsWithQueue;\n use SerializesModels;\n \n+ private const int RETRY_WINDOW_MINUTES = 120;\n+\n public int $maxExceptions = 3;\n \n- private const int RETRY_WINDOW_MINUTES = 120;\n-\n private int $activityId;\n private ?Configuration $fromConfiguration;\n private bool $remoteSearch;\n \n- public function middleware(): array\n- {\n- return [new HandleHubspotRateLimit()];\n- }\n-\n- public function retryUntil(): \\DateTimeInterface\n- {\n- return now()->addMinutes(self::RETRY_WINDOW_MINUTES);\n- }\n-\n public function __construct(\n int $activityId,\n ?Configuration $fromConfiguration = null,\n@@ -57,6 +47,16 @@\n $this->remoteSearch = $remoteSearch;\n \n $this->onQueue(Constants::QUEUE_ANALYTICS_LOW);\n+ }\n+\n+ public function middleware(): array\n+ {\n+ return [new HandleHubspotRateLimit()];\n+ }\n+\n+ public function retryUntil(): \\DateTimeInterface\n+ {\n+ return now()->addMinutes(self::RETRY_WINDOW_MINUTES);\n }\n \n public function uniqueId(): string\n\n ----------- end diff -----------\n\n 2) app/Services/Crm/Hubspot/HubspotClientInterface.php (phpdoc_order, phpdoc_separation)\n ---------- begin diff ----------\n--- /home/jiminny/app/Services/Crm/Hubspot/HubspotClientInterface.php\n+++ /home/jiminny/app/Services/Crm/Hubspot/HubspotClientInterface.php\n@@ -46,9 +46,11 @@\n *\n * @param string $objectType The object type ('deals', 'companies', 'contacts', 'calls')\n * @param array<string, mixed> $payload The search payload with filters, sorts, properties, etc.\n- * @return array The search response with 'results', 'total', 'paging' keys\n+ *\n * @throws RateLimitException When rate limit is hit\n * @throws HubspotException On API errors\n+ *\n+ * @return array The search response with 'results', 'total', 'paging' keys\n */\n public function search(string $objectType, array $payload): array;\n }\n\n ----------- end diff -----------\n\n 3) app/Services/Crm/Hubspot/Client.php (phpdoc_order, phpdoc_separation, blank_line_before_statement)\n ---------- begin diff ----------\n--- /home/jiminny/app/Services/Crm/Hubspot/Client.php\n+++ /home/jiminny/app/Services/Crm/Hubspot/Client.php\n@@ -69,10 +69,12 @@\n * the cache near expiry are not delayed longer than necessary.\n *\n * @template T\n+ *\n * @param callable(): T $apiCall The API call to execute\n- * @return T The result of the API call\n *\n * @throws RateLimitException When rate limit is hit or cached rate limit is active\n+ *\n+ * @return T The result of the API call\n */\n private function executeRequest(callable $apiCall)\n {\n@@ -81,6 +83,7 @@\n $cachedExpiresAt = Redis::get($cacheKey);\n if (is_string($cachedExpiresAt) && is_numeric($cachedExpiresAt)) {\n $remaining = max(1, (int) $cachedExpiresAt - time());\n+\n throw new RateLimitException(\n 'Hubspot rate limit (cached circuit-breaker)',\n $remaining,\n@@ -232,9 +235,11 @@\n *\n * @param string $objectType The object type ('deals', 'companies', 'contacts', 'calls')\n * @param array<string, mixed> $payload The search payload with filters, sorts, properties, etc.\n- * @return array The search response with 'results', 'total', 'paging' keys\n+ *\n * @throws RateLimitException When rate limit is hit\n * @throws HubspotException On API errors\n+ *\n+ * @return array The search response with 'results', 'total', 'paging' keys\n */\n public function search(string $objectType, array $payload): array\n {\n\n ----------- end diff -----------\n\n 4) app/Console/Commands/JiminnyDebugCommand.php (statement_indentation)\n ---------- begin diff ----------\n--- /home/jiminny/app/Console/Commands/JiminnyDebugCommand.php\n+++ /home/jiminny/app/Console/Commands/JiminnyDebugCommand.php\n@@ -359,11 +359,11 @@\n $crmService = $crmResolver->prepareCrmService();\n \n for ($i = 0 ; $i < 3; $i++) {\n-// if ($i % 25 === 0) {\n-// $this->info(\"Syncing opportunity {$i}\");\n- $this->info(\"Matching contact {$i}\");\n-// }\n-// $crmService->syncOpportunity('374720564');\n+ // if ($i % 25 === 0) {\n+ // $this->info(\"Syncing opportunity {$i}\");\n+ $this->info(\"Matching contact {$i}\");\n+ // }\n+ // $crmService->syncOpportunity('374720564');\n $crmService->matchByName('Robot');\n }\n }\n\n ----------- end diff -----------\n\n\nFixed 4 of 5666 files in 146.870 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ csfix \ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5666/5666 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5666 files in 106.192 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5666/5666 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5666 files in 66.457 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $","depth":4,"on_screen":true,"value":"Last login: Thu May 7 09:44:56 on ttys007\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ git status\nOn branch master\nYour branch is up to date with 'origin/master'.\n\nChanges not staged for commit:\n (use \"git add <file>...\" to update what will be committed)\n (use \"git restore <file>...\" to discard changes in working directory)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: .env.local\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: app/Console/Commands/JiminnyDebugCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: app/Jobs/Team/SyncToIntercom.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: app/Services/PlaybackService.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: config/logging.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: resources/views/partials/crm/push-summary/html-assembly.blade.php\n\nUntracked files:\n (use \"git add <file>...\" to include in what will be committed)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.nikilocal\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.other\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tWEBHOOK_FILTERING_IMPLEMENTATION.md\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Crm/Hubspot/SimulateWebhooksCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Reports/CreateMockAskJiminnyReportResultCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tids.txt\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tpublic/favicon.ico\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\traw_sql_query.sql\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\ttests/Unit/Policies/CanAccessAiReportsTest.php\n\nno changes added to commit (use \"git add\" and/or \"git commit -a\")\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nremote: Enumerating objects: 1482, done.\nremote: Counting objects: 100% (481/481), done.\nremote: Compressing objects: 100% (191/191), done.\nremote: Total 1482 (delta 349), reused 305 (delta 289), pack-reused 1001 (from 4)\nReceiving objects: 100% (1482/1482), 1017.97 KiB | 1.44 MiB/s, done.\nResolving deltas: 100% (877/877), completed with 96 local objects.\nFrom github.com:jiminny/app\n 83b628967a..ad2ce76737 master -> origin/master\n 1ee8cbcb7b..14f54b5be2 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3\n 5662c3b32f..b167b19973 JY-20289-api-tests -> origin/JY-20289-api-tests\n b40408cfad..f23cfee7c3 JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null\n * [new branch] JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import\n * [new branch] JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall\n * [new branch] JY-20662-remove-word-boost -> origin/JY-20662-remove-word-boost\n * [new branch] JY-20742-mcp-poc -> origin/JY-20742-mcp-poc\n * [new branch] make-claude-great-again -> origin/make-claude-great-again\n * [new branch] secfix/composer-20260507 -> origin/secfix/composer-20260507\n * [new branch] secfix/npm-20260507 -> origin/secfix/npm-20260507\nUpdating 83b628967a..ad2ce76737\nerror: Your local changes to the following files would be overwritten by merge:\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Jobs/Team/SyncToIntercom.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tresources/views/partials/crm/push-summary/html-assembly.blade.php\nPlease commit your changes or stash them before you merge.\nAborting\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nUpdating 83b628967a..ad2ce76737\nerror: Your local changes to the following files would be overwritten by merge:\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Jobs/Team/SyncToIntercom.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tresources/views/partials/crm/push-summary/html-assembly.blade.php\nPlease commit your changes or stash them before you merge.\nAborting\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nUpdating 83b628967a..ad2ce76737\nerror: Your local changes to the following files would be overwritten by merge:\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Jobs/Team/SyncToIntercom.php\nPlease commit your changes or stash them before you merge.\nAborting\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nUpdating 83b628967a..ad2ce76737\nFast-forward\n .cursor/rules/frontend-conventions.mdc | 23 ++\n .env.production-eu | 2 +-\n .env.staging | 2 +-\n Makefile | 10 +\n app/Component/ActivityAnalytics/Service/ActivityAnalyticsService.php | 6 +-\n app/Component/AiAutomation/Repositories/AiTemplateFieldsRepository.php | 32 +-\n app/Component/AiCallScoring/Repositories/AiScorecardRepository.php | 56 ++--\n app/Component/AskAnything/AskAnythingPromptService.php | 3 +\n app/Component/Transcription/Job/FinishTranscriptionJob.php | 37 ++-\n app/Component/Transcription/TranscriptionProcessor/Gong/Gong.php | 18 +-\n app/Component/Twilio/Conference/ConferenceManager/SoftPhoneManager.php | 4 +-\n app/Component/Twilio/Service/SoftPhoneService.php | 124 ++++---\n app/Component/Twilio/TwilioRepository.php | 27 ++\n app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php | 59 ----\n app/Console/Commands/Reports/AutomatedReportsCommand.php | 122 +++++--\n app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php | 200 ++++++++++++\n app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php | 60 ----\n app/Console/Commands/Users/SyncToIntercom.php | 4 +-\n app/Console/Kernel.php | 3 +-\n app/Contracts/ES/Events/UpdateMultipleEntities.php | 4 -\n app/Contracts/ES/Events/UpdateSingleEntity.php | 4 -\n app/Contracts/Repositories/TeamRepository.php | 3 +-\n app/Events/Activities/ActivityUpdated.php | 10 +-\n app/Events/Activities/Audio/RecordingEvent.php | 6 +-\n app/Events/Activities/Softphone/Ended.php | 8 +-\n app/Events/Activities/Softphone/SoftphoneEvent.php | 24 +-\n app/Events/Activities/Softphone/Started.php | 8 +-\n app/Http/Controllers/API/ActivityController.php | 17 +-\n app/Http/Controllers/API/SoftphoneController.php | 9 +-\n app/Http/Controllers/API/UserAutomatedReports/UserAutomatedReportsController.php | 19 +-\n app/Http/Controllers/API/V2/AskAnythingController.php | 2 +-\n app/Http/Controllers/Auth/SocialController.php | 6 +-\n app/Http/Controllers/Kiosk/AutomatedReportsController.php | 38 ++-\n app/Http/Controllers/Kiosk/OrganizationsController.php | 8 +-\n app/Http/Controllers/Kiosk/PartnersController.php | 46 +++\n app/Http/Controllers/Kiosk/SearchController.php | 8 +\n app/Http/Controllers/Kiosk/Teams/OnboardController.php | 24 +-\n app/Http/Controllers/Settings/Teams/IntegrationController.php | 6 +-\n app/Http/Controllers/TeamSetupController.php | 4 +-\n app/Http/Controllers/Telephony/TextMessaging/MessageController.php | 12 +-\n app/Http/Controllers/Telephony/TextMessaging/WebhookController.php | 18 +-\n app/Http/Requests/Settings/Teams/CreateTeamRequest.php | 1 +\n app/Http/Requests/Settings/Teams/EditTeamRequest.php | 1 +\n app/Http/Transformers/ActivityTransformer.php | 4 +-\n app/Http/Transformers/OnDemandActivitiesTransformer.php | 2 +-\n app/Http/Transformers/PartnerTransformer.php | 1 +\n app/Http/Transformers/StageTransformer.php | 6 +-\n app/Http/Transformers/UserTransformer.php | 11 +-\n app/Interactions/Settings/Teams/CreateTeam.php | 3 +\n app/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJob.php | 80 ++++-\n app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php | 119 +++++++\n app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php | 89 +++++\n app/Jobs/Crm/Hubspot/ImportBatchJobTrait.php | 12 +-\n app/Jobs/Crm/UpdateStage.php | 3 +\n app/Jobs/Team/SyncToIntercom.php | 7 +-\n app/Listeners/Teams/SyncIntercomCompany.php | 5 +-\n app/Listeners/Teams/UpdateSalesforceAccount.php | 8 +-\n app/Listeners/Users/SyncIntercom.php | 5 +-\n app/Mail/Reports/AskJiminnyReportExpiringMail.php | 40 +++\n app/Mail/Reports/ReportNotGenerated.php | 41 +++\n app/Models/Activity.php | 25 +-\n app/Models/Activity/Question.php | 14 +-\n app/Models/Activity/Search.php | 7 +\n app/Models/AskAnything/AskAnythingPrompt.php | 6 +\n app/Models/AutomatedReport.php | 10 +\n app/Models/CoachingFeedback.php | 44 ++-\n app/Models/ElasticSearch/ActivityElasticSearchTrait.php | 86 +----\n app/Models/ElasticSearch/OpportunityElasticSearchTrait.php | 71 ----\n app/Models/ElasticSearch/SharedDocumentDeleteTrait.php | 27 --\n app/Models/Partner.php | 13 +\n app/Models/Playlist/Activity.php | 14 +-\n app/Notifications/OwnerInvitedToTrial.php | 14 +-\n app/Policies/UserPolicy.php | 16 +-\n app/Queue/Worker/Worker.php | 3 +-\n app/Repositories/ActivityRepository.php | 13 +-\n app/Repositories/AutomatedReportsRepository.php | 42 ++-\n app/Repositories/TeamRepository.php | 21 +-\n app/Repositories/UserRepository.php | 2 +-\n app/Services/Activity/MeetingBotService.php | 8 +-\n app/Services/ActivityService.php | 111 ++-----\n app/Services/Crm/Hubspot/Service.php | 36 +-\n app/Services/Crm/Hubspot/ServiceTraits/OpportunitySyncTrait.php | 2 +-\n app/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityService.php | 5 +-\n app/Services/Kiosk/AutomatedReports/AutomatedReportsService.php | 49 +--\n app/Services/Kiosk/KioskService.php | 7 +-\n app/Services/Webhook/Triggers/AiScorecardCompletedTrigger.php | 13 +-\n app/UseCases/TeamInsights/ConversationRowMapper.php | 78 +++++\n app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php | 68 ++++\n app/UseCases/TeamInsights/StrictConsentColumnResolver.php | 45 +++\n app/UseCases/TeamInsights/TeamConversationsExport.php | 154 ++++-----\n composer.json | 1 -\n composer.lock | 95 +-----\n config/secure-headers.php | 5 +-\n database/mappings/mapping_activities.json | 16 +\n database/migrations/2026_04_14_000000_add_rockeed_partner.php | 51 +++\n database/migrations/2026_04_22_000000_add_success_email_to_partners.php | 26 ++\n database/migrations/2026_04_27_000000_add_label_to_partners.php | 28 ++\n database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php | 79 +++++\n front-end/package.json | 5 +-\n front-end/src/__mocks__/jiminny.js | 4 +-\n front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js | 9 +\n front-end/src/__mocks__/setup.js | 1 +\n front-end/src/apps/ai-reports-promo.js | 22 ++\n front-end/src/components/AiReports/AiReportsPromo.vue | 22 ++\n front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue | 190 +++++++++++\n front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue | 111 +++++++\n front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue | 103 ++++++\n front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js | 98 ++++++\n .../src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html | 283 ++++++++++++++++\n front-end/src/components/AiReports/Manage/ManageAiReports.vue | 8 +-\n front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue | 228 +++++++++++++\n front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js | 71 ++++\n .../src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html | 217 ++++++++++++\n front-end/src/components/AiReports/constants.js | 7 +\n front-end/src/components/Settings/Kiosk/OrganizationSearch/Organizations.vue | 1 +\n front-end/src/components/Settings/Kiosk/__mocks__/Jiminny.js | 1 +\n front-end/src/components/Settings/Kiosk/modals/EditTeamModal/EditTeamModal.vue | 43 ++-\n front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js | 203 ++++++++++++\n front-end/src/components/Settings/Kiosk/shared/Navigation/Navigation.vue | 3 +\n front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js | 67 ++++\n front-end/src/components/TeamInsights/CoachingFrameworks/AICallScoring/aiCallScoringOverTime.ts | 4 +-\n front-end/src/components/TeamInsights/CoachingFrameworks/UsersList.vue | 2 +-\n front-end/src/components/layout/Sidebar/HelpMenu.vue | 25 +-\n front-end/src/components/layout/Sidebar/Sidebar.vue | 27 +-\n front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js | 94 ++++++\n front-end/src/components/layout/Sidebar/__tests__/__snapshots__/Sidebar.spec.js.snap | 4 +-\n front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js | 204 ++++++++++++\n front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js | 49 +++\n front-end/src/main.js | 1 +\n front-end/src/store/modules/TeamInsights/util.js | 1 +\n front-end/src/store/modules/platform/__tests__/getters.spec.js | 22 ++\n front-end/src/store/modules/platform/getters.js | 3 +\n front-end/src/utils/index.js | 11 +\n front-end/yarn.lock | 21 +-\n phpstan-baseline.neon | 60 ----\n public/pdf/exec-reports/com/coaching-profiles.pdf | Bin 0 -> 1531178 bytes\n public/pdf/exec-reports/com/exec-summary.pdf | Bin 0 -> 2237381 bytes\n public/pdf/exec-reports/com/loss-report.pdf | Bin 0 -> 1955343 bytes\n public/pdf/exec-reports/com/product-feedback.pdf | Bin 0 -> 2184417 bytes\n public/pdf/exec-reports/eu/coaching-profiles.pdf | Bin 0 -> 1528704 bytes\n public/pdf/exec-reports/eu/exec-summary.pdf | Bin 0 -> 2296741 bytes\n public/pdf/exec-reports/eu/loss-report.pdf | Bin 0 -> 1955808 bytes\n public/pdf/exec-reports/eu/product-feedback.pdf | Bin 0 -> 2184083 bytes\n resources/views/emails/reports/ask-jiminny-report-expiring.blade.php | 22 ++\n resources/views/emails/reports/report-not-generated.blade.php | 24 ++\n resources/views/partials/crm/push-summary/html-assembly.blade.php | 2 +-\n routes/api.php | 6 +\n routes/web.php | 4 +\n tests/Feature/Policies/UserPolicyTest.php | 90 ++++-\n tests/Unit/Component/ActivityAnalytics/Service/ActivityAnalyticsServiceTest.php | 40 +++\n tests/Unit/Component/AskAnything/AskAnythingPromptServiceTest.php | 26 ++\n tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php | 276 ++++++++++++++++\n tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php | 375 +++++++++++++++++++++\n tests/Unit/Component/Twilio/Service/SoftPhoneServiceTest.php | 1014 +++++++++++++++++++++++++++++++++++++++++++++++++++++++--\n tests/Unit/Console/Commands/Reports/AutomatedReportsCommandTest.php | 157 ++++++++-\n tests/Unit/Events/Activities/Audio/RecordingEventTest.php | 72 ++++\n tests/Unit/Events/Activities/Softphone/EndedTest.php | 86 +++++\n tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php | 88 +++++\n tests/Unit/Events/Activities/Softphone/StartedTest.php | 86 +++++\n tests/Unit/Http/Controllers/Kiosk/AutomatedReportsControllerTest.php | 99 ++++++\n tests/Unit/Http/Transformers/ActivityTransformerTest.php | 5 +-\n tests/Unit/Http/Transformers/PartnerTransformerTest.php | 34 ++\n tests/Unit/Interactions/Settings/Teams/CreateTeamTest.php | 49 +++\n tests/Unit/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJobTest.php | 106 +++++-\n tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php | 205 ++++++++++++\n tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php | 188 +++++++++++\n tests/Unit/Jobs/Crm/ImportOpportunityBatchTest.php | 2 +-\n tests/Unit/Jobs/Team/SyncToIntercomTest.php | 6 +\n tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php | 59 ++++\n tests/Unit/Listeners/Teams/UpdateSalesforceAccountTest.php | 11 +-\n tests/Unit/Listeners/Users/SyncIntercomTest.php | 59 ++++\n tests/Unit/Mail/Reports/ReportNotGeneratedTest.php | 166 ++++++++++\n tests/Unit/Models/PartnerTest.php | 28 ++\n tests/Unit/Repositories/AutomatedReportsRepositoryTest.php | 68 ++++\n tests/Unit/Services/Activity/MeetingBotServiceRequestRecordingToStopTest.php | 14 +-\n tests/Unit/Services/ActivityServiceTest.php | 391 ++++++++++++++++++++++\n tests/Unit/Services/Crm/Hubspot/ServiceResponseNormalizeTest.php | 68 ++--\n tests/Unit/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityServiceTest.php | 48 +--\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceActivitiesCountTest.php | 16 +-\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceReportGenerationTest.php | 24 +-\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceTest.php | 130 ++++++++\n tests/Unit/Services/KioskServiceTest.php | 8 +\n tests/Unit/Services/Webhook/Triggers/AiScorecardCompletedTriggerTest.php | 6 +-\n tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php | 119 +++++++\n tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php | 108 ++++++\n tests/Unit/UseCases/TeamInsights/TeamConversationsExportTest.php | 342 ++++++++++++++-----\n 186 files changed, 8538 insertions(+), 1233 deletions(-)\n create mode 100644 app/Component/Twilio/TwilioRepository.php\n delete mode 100644 app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php\n create mode 100644 app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php\n delete mode 100644 app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php\n create mode 100644 app/Http/Controllers/Kiosk/PartnersController.php\n create mode 100644 app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php\n create mode 100644 app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php\n create mode 100644 app/Mail/Reports/AskJiminnyReportExpiringMail.php\n create mode 100644 app/Mail/Reports/ReportNotGenerated.php\n delete mode 100644 app/Models/ElasticSearch/SharedDocumentDeleteTrait.php\n create mode 100644 app/UseCases/TeamInsights/ConversationRowMapper.php\n create mode 100644 app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php\n create mode 100644 app/UseCases/TeamInsights/StrictConsentColumnResolver.php\n create mode 100644 database/migrations/2026_04_14_000000_add_rockeed_partner.php\n create mode 100644 database/migrations/2026_04_22_000000_add_success_email_to_partners.php\n create mode 100644 database/migrations/2026_04_27_000000_add_label_to_partners.php\n create mode 100644 database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php\n create mode 100644 front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js\n create mode 100644 front-end/src/apps/ai-reports-promo.js\n create mode 100644 front-end/src/components/AiReports/AiReportsPromo.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html\n create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue\n create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js\n create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html\n create mode 100644 front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js\n create mode 100644 front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js\n create mode 100644 front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js\n create mode 100644 front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js\n create mode 100644 front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js\n create mode 100644 front-end/src/store/modules/platform/__tests__/getters.spec.js\n create mode 100644 public/pdf/exec-reports/com/coaching-profiles.pdf\n create mode 100644 public/pdf/exec-reports/com/exec-summary.pdf\n create mode 100644 public/pdf/exec-reports/com/loss-report.pdf\n create mode 100644 public/pdf/exec-reports/com/product-feedback.pdf\n create mode 100644 public/pdf/exec-reports/eu/coaching-profiles.pdf\n create mode 100644 public/pdf/exec-reports/eu/exec-summary.pdf\n create mode 100644 public/pdf/exec-reports/eu/loss-report.pdf\n create mode 100644 public/pdf/exec-reports/eu/product-feedback.pdf\n create mode 100644 resources/views/emails/reports/ask-jiminny-report-expiring.blade.php\n create mode 100644 resources/views/emails/reports/report-not-generated.blade.php\n create mode 100644 tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php\n create mode 100644 tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php\n create mode 100644 tests/Unit/Events/Activities/Audio/RecordingEventTest.php\n create mode 100644 tests/Unit/Events/Activities/Softphone/EndedTest.php\n create mode 100644 tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php\n create mode 100644 tests/Unit/Events/Activities/Softphone/StartedTest.php\n create mode 100644 tests/Unit/Http/Transformers/PartnerTransformerTest.php\n create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php\n create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php\n create mode 100644 tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php\n create mode 100644 tests/Unit/Listeners/Users/SyncIntercomTest.php\n create mode 100644 tests/Unit/Mail/Reports/ReportNotGeneratedTest.php\n create mode 100644 tests/Unit/Models/PartnerTest.php\n create mode 100644 tests/Unit/Services/ActivityServiceTest.php\n create mode 100644 tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php\n create mode 100644 tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull \nremote: Enumerating objects: 628, done.\nremote: Counting objects: 100% (331/331), done.\nremote: Compressing objects: 100% (63/63), done.\nremote: Total 628 (delta 280), reused 274 (delta 266), pack-reused 297 (from 1)\nReceiving objects: 100% (628/628), 186.75 KiB | 1.23 MiB/s, done.\nResolving deltas: 100% (391/391), completed with 57 local objects.\nFrom github.com:jiminny/app\n ad2ce76737..12295204cf master -> origin/master\n 14f54b5be2..5e7646e5f9 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3\n b167b19973..acba55cf38 JY-20289-api-tests -> origin/JY-20289-api-tests\n f23cfee7c3..e5a3ec5dba JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null\n af59d60926..766efba1c5 JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import\n * [new branch] JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering\n 1737b7c528..c57e71e763 JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall\n * [new branch] JY-20671-anyvan-twilio-s3-recordings-ftech -> origin/JY-20671-anyvan-twilio-s3-recordings-ftech\n + ba181441c6...20a74137b0 JY-20742-mcp-poc -> origin/JY-20742-mcp-poc (forced update)\n * [new branch] JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue\n * [new branch] JY-20816-calendar-events-diplication -> origin/JY-20816-calendar-events-diplication\n * [new branch] desktop-app -> origin/desktop-app\n 4c4c974e46..185442c26e make-claude-great-again -> origin/make-claude-great-again\n * [new branch] mcp-tools-schemas -> origin/mcp-tools-schemas\nUpdating ad2ce76737..12295204cf\nFast-forward\n app/Component/Encoding/Job/AnalyzeTrackChannelsJob.php | 2 +-\n app/Component/Transcription/TranscriptionProcessor/AssemblyAI/Services/SubmitAudioFileService.php | 66 ++----------------------------------------------------------------\n app/Console/Commands/Tracks/CleanupActivityTracksCommand.php | 24 +++++++++++++++++-------\n tests/Unit/Console/Commands/Tracks/CleanupActivityTracksCommandTest.php | 40 +++++++++++++++++++++++++++++-----------\n tests/Unit/fixtures/assembly_ai_transcript_response.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_channel_diarization.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language_error.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language_not_ready.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language_post.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_without_utterances.json | 1 -\n 11 files changed, 49 insertions(+), 90 deletions(-)\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20818-move-AJ-reports-to-separated-datadog-metric\nSwitched to a new branch 'JY-20818-move-AJ-reports-to-separated-datadog-metric'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5663 files in 83.615 seconds, 67.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ ;xd\ndocker exec -it docker_lamp_1 bash -c \"mv /usr/local/etc/php/conf.d/xdebug.ini ~/xdebug.ini\"\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 supervisorctl restart all\njiminny-worker-processing-2:jiminny-worker-processing-2_00: stopped\njiminny-worker-processing-3:jiminny-worker-processing-3_00: stopped\njiminny-worker-processing-4:jiminny-worker-processing-4_00: stopped\njiminny-worker-processing-5:jiminny-worker-processing-5_00: stopped\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: stopped\nworker-analytics:worker-analytics_00: stopped\nworker-crm-update:worker-crm-update_00: stopped\nworker-download:worker-download_00: stopped\nworker-nudges:worker-nudges_00: stopped\nartisan-schedule:artisan-schedule_00: stopped\nworker-calendar:worker-calendar_00: stopped\nworker-crm-sync:worker-crm-sync_00: stopped\njiminny-worker-processing-1:jiminny-worker-processing-1_00: stopped\nworker:worker_00: stopped\nworker-emails:worker-emails_00: stopped\nworker-audio:worker-audio_00: stopped\nworker-conferences:worker-conferences_00: stopped\nworker-es-update:worker-es-update_00: stopped\nartisan-schedule:artisan-schedule_00: started\njiminny-worker-processing-1:jiminny-worker-processing-1_00: started\njiminny-worker-processing-2:jiminny-worker-processing-2_00: started\njiminny-worker-processing-3:jiminny-worker-processing-3_00: started\njiminny-worker-processing-4:jiminny-worker-processing-4_00: started\njiminny-worker-processing-5:jiminny-worker-processing-5_00: started\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: started\nworker:worker_00: started\nworker-analytics:worker-analytics_00: started\nworker-audio:worker-audio_00: started\nworker-calendar:worker-calendar_00: started\nworker-conferences:worker-conferences_00: started\nworker-crm-sync:worker-crm-sync_00: started\nworker-crm-update:worker-crm-update_00: started\nworker-download:worker-download_00: started\nworker-emails:worker-emails_00: started\nworker-es-update:worker-es-update_00: started\nworker-nudges:worker-nudges_00: started\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 php -v\nPHP 8.3.30 (cli) (built: Mar 16 2026 22:32:32) (NTS)\nCopyright (c) The PHP Group\nZend Engine v4.3.30, Copyright (c) Zend Technologies\n with Zend OPcache v8.3.30, Copyright (c), by Zend Technologies\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5663 files in 42.875 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ git status\nOn branch master\nYour branch is up to date with 'origin/master'.\n\nChanges not staged for commit:\n (use \"git add <file>...\" to update what will be committed)\n (use \"git restore <file>...\" to discard changes in working directory)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: .env.local\n\nUntracked files:\n (use \"git add <file>...\" to include in what will be committed)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.nikilocal\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.other\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tWEBHOOK_FILTERING_IMPLEMENTATION.md\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Crm/Hubspot/SimulateWebhooksCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Reports/CreateMockAskJiminnyReportResultCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tids.txt\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tpublic/favicon.ico\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\traw_sql_query.sql\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\ttests/Unit/Policies/CanAccessAiReportsTest.php\n\nno changes added to commit (use \"git add\" and/or \"git commit -a\")\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nremote: Enumerating objects: 15, done.\nremote: Counting objects: 100% (15/15), done.\nremote: Compressing objects: 100% (2/2), done.\nremote: Total 15 (delta 13), reused 15 (delta 13), pack-reused 0 (from 0)\nUnpacking objects: 100% (15/15), 1.28 KiB | 72.00 KiB/s, done.\nFrom github.com:jiminny/app\n c57e71e763..8743fea32e JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall\n * [new branch] JY-20819-increase-download-transctip-rate-limit -> origin/JY-20819-increase-download-transctip-rate-limit\nAlready up to date.\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull \nremote: Enumerating objects: 180, done.\nremote: Counting objects: 100% (179/179), done.\nremote: Compressing objects: 100% (55/55), done.\nremote: Total 180 (delta 127), reused 165 (delta 119), pack-reused 1 (from 1)\nReceiving objects: 100% (180/180), 57.50 KiB | 2.74 MiB/s, done.\nResolving deltas: 100% (127/127), completed with 47 local objects.\nFrom github.com:jiminny/app\n 12295204cf..35f036ace6 master -> origin/master\n * [new branch] JY-18091-upgrade-to-php-8-5 -> origin/JY-18091-upgrade-to-php-8-5\n 5f21965da8..497fbc85c2 JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering\n f029263118..6ed9e2bb13 JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue\n * [new branch] JY-20817-fix-deleting-s3-directories -> origin/JY-20817-fix-deleting-s3-directories\n * [new branch] JY-20820-es-reindex-stream-model-hydration -> origin/JY-20820-es-reindex-stream-model-hydration\n + ca92730ec5...2c8a1d0856 desktop-app -> origin/desktop-app (forced update)\n 8425d4e0de..89b45ec8b0 mcp-tools-schemas -> origin/mcp-tools-schemas\nUpdating 12295204cf..35f036ace6\nFast-forward\n app/Component/Datadog/Constants.php | 1 +\n app/Providers/RouteServiceProvider.php | 2 +-\n app/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackService.php | 13 +++++++++++++\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackServiceTest.php | 54 +++++++++++++++++++++++++++++++++++++++++++++++-------\n 4 files changed, 62 insertions(+), 8 deletions(-)\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ gbr \n* master\n JY-20818-move-AJ-reports-to-separated-datadog-metric\n JY-20773-fix-automated-reports-user-pilot-tracking\n JY-20157-AJ-report-not-send-notification\n JY-20508-notify-before-AJ-report-expiration\n JY-20372-ai-reports-promotion-pages\n JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null\n JY-20738-debug-AJ-tracking-UP\n a\n JY-18909-automated-reports-ask-jiminny\n JY-20692-fix-integration-app-token-auth-response-change\n JY-20553-debug-crm-sync-delays\n JY-20698-fix-SF-activity-types-on-new-playbook\n JY-20543-AJ-report-tracking\n JY-20384-handle-auto-sync-with-no-access-to-event-type\n JY-20458-ask-jiminny-user-definitions\n JY-19666-fix-import-contacts-account-association\n JY-19666-HS-import-contacts-and-accounts-batch-job\n JY-20458-Ask-Jiminny-Reports\n JY-20200-batch-update-CRM-objects-Salesforce\n JY-19666-HS-webhooks-add-contact-and-company\n JY-20348-trigger-setup-DI-layout-on-team-creation\n JY-20326-refactor-info-message-in-command\n JY-20317-fix-auto-log-delay-issue-on-all-channels-disabled\n JY-20312-remove-on-update-change-last-synced-at-crm-configurations\n JY-20306-SF-skip-auto-sync-for-task-based-playbook\n JY-20192-remove-deleted-team-from-saved-search-filters\n JY-20197-import-opportunity-batch-job\n JY-20293-enable-status-field-for-pipedrive-deals\n JY-20191-remove-commands-interactive-prompts\n JY-20118-change-default-sync-strategy\n JY-20183-add-cache-on-auto-log-delay\n JY-20197-add-import-opportunity-batch-job\n 20118-hs-opportunity-make-webhook-strategy-default\n JY-20118-make-default-hs-opportunity-sync-strategy-webhook-based\n JY-20196-handle-opportunity-without-note\n JY-20118-improve-opportunity-import\n JY-20189-handle-activity-search-on-deleted-groups\n JY-20160\n JY-20145-filter-out-converted-leads-when-matching\n JY-20150-skip-push-summary-on-summary-ready-if-autolog\n JY-20132-fix-note-encoding\n JY-19792-clean-logs\n JY-20117-fix-sync-profile-fields-on-empty-fields\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20725-handle-HS-search-rate-limit \nSwitched to a new branch 'JY-20725-handle-HS-search-rate-limit'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ ;xd\ndocker exec -it docker_lamp_1 bash -c \"mv /usr/local/etc/php/conf.d/xdebug.ini ~/xdebug.ini\"\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 supervisorctl restart all\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: stopped\njiminny-worker-processing-2:jiminny-worker-processing-2_00: stopped\njiminny-worker-processing-3:jiminny-worker-processing-3_00: stopped\njiminny-worker-processing-4:jiminny-worker-processing-4_00: stopped\njiminny-worker-processing-5:jiminny-worker-processing-5_00: stopped\nworker-analytics:worker-analytics_00: stopped\nworker-crm-update:worker-crm-update_00: stopped\nworker-download:worker-download_00: stopped\nworker-nudges:worker-nudges_00: stopped\nartisan-schedule:artisan-schedule_00: stopped\nworker-emails:worker-emails_00: stopped\nworker:worker_00: stopped\nworker-calendar:worker-calendar_00: stopped\njiminny-worker-processing-1:jiminny-worker-processing-1_00: stopped\nworker-crm-sync:worker-crm-sync_00: stopped\nworker-audio:worker-audio_00: stopped\nworker-conferences:worker-conferences_00: stopped\nworker-es-update:worker-es-update_00: stopped\nartisan-schedule:artisan-schedule_00: started\njiminny-worker-processing-1:jiminny-worker-processing-1_00: started\njiminny-worker-processing-2:jiminny-worker-processing-2_00: started\njiminny-worker-processing-3:jiminny-worker-processing-3_00: started\njiminny-worker-processing-4:jiminny-worker-processing-4_00: started\njiminny-worker-processing-5:jiminny-worker-processing-5_00: started\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: started\nworker:worker_00: started\nworker-analytics:worker-analytics_00: started\nworker-audio:worker-audio_00: started\nworker-calendar:worker-calendar_00: started\nworker-conferences:worker-conferences_00: started\nworker-crm-sync:worker-crm-sync_00: started\nworker-crm-update:worker-crm-update_00: started\nworker-download:worker-download_00: started\nworker-emails:worker-emails_00: started\nworker-es-update:worker-es-update_00: started\nworker-nudges:worker-nudges_00: started\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 php -v\nPHP 8.3.30 (cli) (built: Mar 16 2026 22:32:32) (NTS)\nCopyright (c) The PHP Group\nZend Engine v4.3.30, Copyright (c) Zend Technologies\n with Zend OPcache v8.3.30, Copyright (c), by Zend Technologies\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5666/5666 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n 1) app/Jobs/Crm/MatchActivityCrmData.php (ordered_class_elements)\n ---------- begin diff ----------\n--- /home/jiminny/app/Jobs/Crm/MatchActivityCrmData.php\n+++ /home/jiminny/app/Jobs/Crm/MatchActivityCrmData.php\n@@ -29,24 +29,14 @@\n use InteractsWithQueue;\n use SerializesModels;\n \n+ private const int RETRY_WINDOW_MINUTES = 120;\n+\n public int $maxExceptions = 3;\n \n- private const int RETRY_WINDOW_MINUTES = 120;\n-\n private int $activityId;\n private ?Configuration $fromConfiguration;\n private bool $remoteSearch;\n \n- public function middleware(): array\n- {\n- return [new HandleHubspotRateLimit()];\n- }\n-\n- public function retryUntil(): \\DateTimeInterface\n- {\n- return now()->addMinutes(self::RETRY_WINDOW_MINUTES);\n- }\n-\n public function __construct(\n int $activityId,\n ?Configuration $fromConfiguration = null,\n@@ -57,6 +47,16 @@\n $this->remoteSearch = $remoteSearch;\n \n $this->onQueue(Constants::QUEUE_ANALYTICS_LOW);\n+ }\n+\n+ public function middleware(): array\n+ {\n+ return [new HandleHubspotRateLimit()];\n+ }\n+\n+ public function retryUntil(): \\DateTimeInterface\n+ {\n+ return now()->addMinutes(self::RETRY_WINDOW_MINUTES);\n }\n \n public function uniqueId(): string\n\n ----------- end diff -----------\n\n 2) app/Services/Crm/Hubspot/HubspotClientInterface.php (phpdoc_order, phpdoc_separation)\n ---------- begin diff ----------\n--- /home/jiminny/app/Services/Crm/Hubspot/HubspotClientInterface.php\n+++ /home/jiminny/app/Services/Crm/Hubspot/HubspotClientInterface.php\n@@ -46,9 +46,11 @@\n *\n * @param string $objectType The object type ('deals', 'companies', 'contacts', 'calls')\n * @param array<string, mixed> $payload The search payload with filters, sorts, properties, etc.\n- * @return array The search response with 'results', 'total', 'paging' keys\n+ *\n * @throws RateLimitException When rate limit is hit\n * @throws HubspotException On API errors\n+ *\n+ * @return array The search response with 'results', 'total', 'paging' keys\n */\n public function search(string $objectType, array $payload): array;\n }\n\n ----------- end diff -----------\n\n 3) app/Services/Crm/Hubspot/Client.php (phpdoc_order, phpdoc_separation, blank_line_before_statement)\n ---------- begin diff ----------\n--- /home/jiminny/app/Services/Crm/Hubspot/Client.php\n+++ /home/jiminny/app/Services/Crm/Hubspot/Client.php\n@@ -69,10 +69,12 @@\n * the cache near expiry are not delayed longer than necessary.\n *\n * @template T\n+ *\n * @param callable(): T $apiCall The API call to execute\n- * @return T The result of the API call\n *\n * @throws RateLimitException When rate limit is hit or cached rate limit is active\n+ *\n+ * @return T The result of the API call\n */\n private function executeRequest(callable $apiCall)\n {\n@@ -81,6 +83,7 @@\n $cachedExpiresAt = Redis::get($cacheKey);\n if (is_string($cachedExpiresAt) && is_numeric($cachedExpiresAt)) {\n $remaining = max(1, (int) $cachedExpiresAt - time());\n+\n throw new RateLimitException(\n 'Hubspot rate limit (cached circuit-breaker)',\n $remaining,\n@@ -232,9 +235,11 @@\n *\n * @param string $objectType The object type ('deals', 'companies', 'contacts', 'calls')\n * @param array<string, mixed> $payload The search payload with filters, sorts, properties, etc.\n- * @return array The search response with 'results', 'total', 'paging' keys\n+ *\n * @throws RateLimitException When rate limit is hit\n * @throws HubspotException On API errors\n+ *\n+ * @return array The search response with 'results', 'total', 'paging' keys\n */\n public function search(string $objectType, array $payload): array\n {\n\n ----------- end diff -----------\n\n 4) app/Console/Commands/JiminnyDebugCommand.php (statement_indentation)\n ---------- begin diff ----------\n--- /home/jiminny/app/Console/Commands/JiminnyDebugCommand.php\n+++ /home/jiminny/app/Console/Commands/JiminnyDebugCommand.php\n@@ -359,11 +359,11 @@\n $crmService = $crmResolver->prepareCrmService();\n \n for ($i = 0 ; $i < 3; $i++) {\n-// if ($i % 25 === 0) {\n-// $this->info(\"Syncing opportunity {$i}\");\n- $this->info(\"Matching contact {$i}\");\n-// }\n-// $crmService->syncOpportunity('374720564');\n+ // if ($i % 25 === 0) {\n+ // $this->info(\"Syncing opportunity {$i}\");\n+ $this->info(\"Matching contact {$i}\");\n+ // }\n+ // $crmService->syncOpportunity('374720564');\n $crmService->matchByName('Robot');\n }\n }\n\n ----------- end diff -----------\n\n\nFixed 4 of 5666 files in 146.870 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ csfix \ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5666/5666 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5666 files in 106.192 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5666/5666 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5666 files in 66.457 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $","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":"APP (-zsh)","depth":1,"bounds":{"left":0.47430557,"top":0.033333335,"width":0.05138889,"height":0.017777778},"on_screen":true,"role_description":"text"}]...
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visual_change
|
accessibility
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NULL
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Last login: Thu May 7 09:44:56 on ttys007
Poetry Last login: Thu May 7 09:44:56 on ttys007
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ git status
On branch master
Your branch is up to date with 'origin/master'.
Changes not staged for commit:
(use "git add <file>..." to update what will be committed)
(use "git restore <file>..." to discard changes in working directory)
modified: .env.local
modified: app/Console/Commands/JiminnyDebugCommand.php
modified: app/Jobs/Team/SyncToIntercom.php
modified: app/Services/PlaybackService.php
modified: config/logging.php
modified: resources/views/partials/crm/push-summary/html-assembly.blade.php
Untracked files:
(use "git add <file>..." to include in what will be committed)
.env.nikilocal
.env.other
WEBHOOK_FILTERING_IMPLEMENTATION.md
app/Console/Commands/Crm/Hubspot/SimulateWebhooksCommand.php
app/Console/Commands/Reports/CreateMockAskJiminnyReportResultCommand.php
ids.txt
public/favicon.ico
raw_sql_query.sql
tests/Unit/Policies/CanAccessAiReportsTest.php
no changes added to commit (use "git add" and/or "git commit -a")
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 1482, done.
remote: Counting objects: 100% (481/481), done.
remote: Compressing objects: 100% (191/191), done.
remote: Total 1482 (delta 349), reused 305 (delta 289), pack-reused 1001 (from 4)
Receiving objects: 100% (1482/1482), 1017.97 KiB | 1.44 MiB/s, done.
Resolving deltas: 100% (877/877), completed with 96 local objects.
From github.com:jiminny/app
83b628967a..ad2ce76737 master -> origin/master
1ee8cbcb7b..14f54b5be2 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3
5662c3b32f..b167b19973 JY-20289-api-tests -> origin/JY-20289-api-tests
b40408cfad..f23cfee7c3 JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null
* [new branch] JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import
* [new branch] JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall
* [new branch] JY-20662-remove-word-boost -> origin/JY-20662-remove-word-boost
* [new branch] JY-20742-mcp-poc -> origin/JY-20742-mcp-poc
* [new branch] make-claude-great-again -> origin/make-claude-great-again
* [new branch] secfix/composer-20260507 -> origin/secfix/composer-20260507
* [new branch] secfix/npm-20260507 -> origin/secfix/npm-20260507
Updating 83b628967a..ad2ce76737
error: Your local changes to the following files would be overwritten by merge:
app/Jobs/Team/SyncToIntercom.php
resources/views/partials/crm/push-summary/html-assembly.blade.php
Please commit your changes or stash them before you merge.
Aborting
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
Updating 83b628967a..ad2ce76737
error: Your local changes to the following files would be overwritten by merge:
app/Jobs/Team/SyncToIntercom.php
resources/views/partials/crm/push-summary/html-assembly.blade.php
Please commit your changes or stash them before you merge.
Aborting
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
Updating 83b628967a..ad2ce76737
error: Your local changes to the following files would be overwritten by merge:
app/Jobs/Team/SyncToIntercom.php
Please commit your changes or stash them before you merge.
Aborting
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
Updating 83b628967a..ad2ce76737
Fast-forward
.cursor/rules/frontend-conventions.mdc | 23 ++
.env.production-eu | 2 +-
.env.staging | 2 +-
Makefile | 10 +
app/Component/ActivityAnalytics/Service/ActivityAnalyticsService.php | 6 +-
app/Component/AiAutomation/Repositories/AiTemplateFieldsRepository.php | 32 +-
app/Component/AiCallScoring/Repositories/AiScorecardRepository.php | 56 ++--
app/Component/AskAnything/AskAnythingPromptService.php | 3 +
app/Component/Transcription/Job/FinishTranscriptionJob.php | 37 ++-
app/Component/Transcription/TranscriptionProcessor/Gong/Gong.php | 18 +-
app/Component/Twilio/Conference/ConferenceManager/SoftPhoneManager.php | 4 +-
app/Component/Twilio/Service/SoftPhoneService.php | 124 ++++---
app/Component/Twilio/TwilioRepository.php | 27 ++
app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php | 59 ----
app/Console/Commands/Reports/AutomatedReportsCommand.php | 122 +++++--
app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php | 200 ++++++++++++
app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php | 60 ----
app/Console/Commands/Users/SyncToIntercom.php | 4 +-
app/Console/Kernel.php | 3 +-
app/Contracts/ES/Events/UpdateMultipleEntities.php | 4 -
app/Contracts/ES/Events/UpdateSingleEntity.php | 4 -
app/Contracts/Repositories/TeamRepository.php | 3 +-
app/Events/Activities/ActivityUpdated.php | 10 +-
app/Events/Activities/Audio/RecordingEvent.php | 6 +-
app/Events/Activities/Softphone/Ended.php | 8 +-
app/Events/Activities/Softphone/SoftphoneEvent.php | 24 +-
app/Events/Activities/Softphone/Started.php | 8 +-
app/Http/Controllers/API/ActivityController.php | 17 +-
app/Http/Controllers/API/SoftphoneController.php | 9 +-
app/Http/Controllers/API/UserAutomatedReports/UserAutomatedReportsController.php | 19 +-
app/Http/Controllers/API/V2/AskAnythingController.php | 2 +-
app/Http/Controllers/Auth/SocialController.php | 6 +-
app/Http/Controllers/Kiosk/AutomatedReportsController.php | 38 ++-
app/Http/Controllers/Kiosk/OrganizationsController.php | 8 +-
app/Http/Controllers/Kiosk/PartnersController.php | 46 +++
app/Http/Controllers/Kiosk/SearchController.php | 8 +
app/Http/Controllers/Kiosk/Teams/OnboardController.php | 24 +-
app/Http/Controllers/Settings/Teams/IntegrationController.php | 6 +-
app/Http/Controllers/TeamSetupController.php | 4 +-
app/Http/Controllers/Telephony/TextMessaging/MessageController.php | 12 +-
app/Http/Controllers/Telephony/TextMessaging/WebhookController.php | 18 +-
app/Http/Requests/Settings/Teams/CreateTeamRequest.php | 1 +
app/Http/Requests/Settings/Teams/EditTeamRequest.php | 1 +
app/Http/Transformers/ActivityTransformer.php | 4 +-
app/Http/Transformers/OnDemandActivitiesTransformer.php | 2 +-
app/Http/Transformers/PartnerTransformer.php | 1 +
app/Http/Transformers/StageTransformer.php | 6 +-
app/Http/Transformers/UserTransformer.php | 11 +-
app/Interactions/Settings/Teams/CreateTeam.php | 3 +
app/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJob.php | 80 ++++-
app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php | 119 +++++++
app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php | 89 +++++
app/Jobs/Crm/Hubspot/ImportBatchJobTrait.php | 12 +-
app/Jobs/Crm/UpdateStage.php | 3 +
app/Jobs/Team/SyncToIntercom.php | 7 +-
app/Listeners/Teams/SyncIntercomCompany.php | 5 +-
app/Listeners/Teams/UpdateSalesforceAccount.php | 8 +-
app/Listeners/Users/SyncIntercom.php | 5 +-
app/Mail/Reports/AskJiminnyReportExpiringMail.php | 40 +++
app/Mail/Reports/ReportNotGenerated.php | 41 +++
app/Models/Activity.php | 25 +-
app/Models/Activity/Question.php | 14 +-
app/Models/Activity/Search.php | 7 +
app/Models/AskAnything/AskAnythingPrompt.php | 6 +
app/Models/AutomatedReport.php | 10 +
app/Models/CoachingFeedback.php | 44 ++-
app/Models/ElasticSearch/ActivityElasticSearchTrait.php | 86 +----
app/Models/ElasticSearch/OpportunityElasticSearchTrait.php | 71 ----
app/Models/ElasticSearch/SharedDocumentDeleteTrait.php | 27 --
app/Models/Partner.php | 13 +
app/Models/Playlist/Activity.php | 14 +-
app/Notifications/OwnerInvitedToTrial.php | 14 +-
app/Policies/UserPolicy.php | 16 +-
app/Queue/Worker/Worker.php | 3 +-
app/Repositories/ActivityRepository.php | 13 +-
app/Repositories/AutomatedReportsRepository.php | 42 ++-
app/Repositories/TeamRepository.php | 21 +-
app/Repositories/UserRepository.php | 2 +-
app/Services/Activity/MeetingBotService.php | 8 +-
app/Services/ActivityService.php | 111 ++-----
app/Services/Crm/Hubspot/Service.php | 36 +-
app/Services/Crm/Hubspot/ServiceTraits/OpportunitySyncTrait.php | 2 +-
app/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityService.php | 5 +-
app/Services/Kiosk/AutomatedReports/AutomatedReportsService.php | 49 +--
app/Services/Kiosk/KioskService.php | 7 +-
app/Services/Webhook/Triggers/AiScorecardCompletedTrigger.php | 13 +-
app/UseCases/TeamInsights/ConversationRowMapper.php | 78 +++++
app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php | 68 ++++
app/UseCases/TeamInsights/StrictConsentColumnResolver.php | 45 +++
app/UseCases/TeamInsights/TeamConversationsExport.php | 154 ++++-----
composer.json | 1 -
composer.lock | 95 +-----
config/secure-headers.php | 5 +-
database/mappings/mapping_activities.json | 16 +
database/migrations/2026_04_14_000000_add_rockeed_partner.php | 51 +++
database/migrations/2026_04_22_000000_add_success_email_to_partners.php | 26 ++
database/migrations/2026_04_27_000000_add_label_to_partners.php | 28 ++
database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php | 79 +++++
front-end/package.json | 5 +-
front-end/src/__mocks__/jiminny.js | 4 +-
front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js | 9 +
front-end/src/__mocks__/setup.js | 1 +
front-end/src/apps/ai-reports-promo.js | 22 ++
front-end/src/components/AiReports/AiReportsPromo.vue | 22 ++
front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue | 190 +++++++++++
front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue | 111 +++++++
front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue | 103 ++++++
front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js | 98 ++++++
.../src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html | 283 ++++++++++++++++
front-end/src/components/AiReports/Manage/ManageAiReports.vue | 8 +-
front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue | 228 +++++++++++++
front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js | 71 ++++
.../src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html | 217 ++++++++++++
front-end/src/components/AiReports/constants.js | 7 +
front-end/src/components/Settings/Kiosk/OrganizationSearch/Organizations.vue | 1 +
front-end/src/components/Settings/Kiosk/__mocks__/Jiminny.js | 1 +
front-end/src/components/Settings/Kiosk/modals/EditTeamModal/EditTeamModal.vue | 43 ++-
front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js | 203 ++++++++++++
front-end/src/components/Settings/Kiosk/shared/Navigation/Navigation.vue | 3 +
front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js | 67 ++++
front-end/src/components/TeamInsights/CoachingFrameworks/AICallScoring/aiCallScoringOverTime.ts | 4 +-
front-end/src/components/TeamInsights/CoachingFrameworks/UsersList.vue | 2 +-
front-end/src/components/layout/Sidebar/HelpMenu.vue | 25 +-
front-end/src/components/layout/Sidebar/Sidebar.vue | 27 +-
front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js | 94 ++++++
front-end/src/components/layout/Sidebar/__tests__/__snapshots__/Sidebar.spec.js.snap | 4 +-
front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js | 204 ++++++++++++
front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js | 49 +++
front-end/src/main.js | 1 +
front-end/src/store/modules/TeamInsights/util.js | 1 +
front-end/src/store/modules/platform/__tests__/getters.spec.js | 22 ++
front-end/src/store/modules/platform/getters.js | 3 +
front-end/src/utils/index.js | 11 +
front-end/yarn.lock | 21 +-
phpstan-baseline.neon | 60 ----
public/pdf/exec-reports/com/coaching-profiles.pdf | Bin 0 -> 1531178 bytes
public/pdf/exec-reports/com/exec-summary.pdf | Bin 0 -> 2237381 bytes
public/pdf/exec-reports/com/loss-report.pdf | Bin 0 -> 1955343 bytes
public/pdf/exec-reports/com/product-feedback.pdf | Bin 0 -> 2184417 bytes
public/pdf/exec-reports/eu/coaching-profiles.pdf | Bin 0 -> 1528704 bytes
public/pdf/exec-reports/eu/exec-summary.pdf | Bin 0 -> 2296741 bytes
public/pdf/exec-reports/eu/loss-report.pdf | Bin 0 -> 1955808 bytes
public/pdf/exec-reports/eu/product-feedback.pdf | Bin 0 -> 2184083 bytes
resources/views/emails/reports/ask-jiminny-report-expiring.blade.php | 22 ++
resources/views/emails/reports/report-not-generated.blade.php | 24 ++
resources/views/partials/crm/push-summary/html-assembly.blade.php | 2 +-
routes/api.php | 6 +
routes/web.php | 4 +
tests/Feature/Policies/UserPolicyTest.php | 90 ++++-
tests/Unit/Component/ActivityAnalytics/Service/ActivityAnalyticsServiceTest.php | 40 +++
tests/Unit/Component/AskAnything/AskAnythingPromptServiceTest.php | 26 ++
tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php | 276 ++++++++++++++++
tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php | 375 +++++++++++++++++++++
tests/Unit/Component/Twilio/Service/SoftPhoneServiceTest.php | 1014 +++++++++++++++++++++++++++++++++++++++++++++++++++++++--
tests/Unit/Console/Commands/Reports/AutomatedReportsCommandTest.php | 157 ++++++++-
tests/Unit/Events/Activities/Audio/RecordingEventTest.php | 72 ++++
tests/Unit/Events/Activities/Softphone/EndedTest.php | 86 +++++
tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php | 88 +++++
tests/Unit/Events/Activities/Softphone/StartedTest.php | 86 +++++
tests/Unit/Http/Controllers/Kiosk/AutomatedReportsControllerTest.php | 99 ++++++
tests/Unit/Http/Transformers/ActivityTransformerTest.php | 5 +-
tests/Unit/Http/Transformers/PartnerTransformerTest.php | 34 ++
tests/Unit/Interactions/Settings/Teams/CreateTeamTest.php | 49 +++
tests/Unit/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJobTest.php | 106 +++++-
tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php | 205 ++++++++++++
tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php | 188 +++++++++++
tests/Unit/Jobs/Crm/ImportOpportunityBatchTest.php | 2 +-
tests/Unit/Jobs/Team/SyncToIntercomTest.php | 6 +
tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php | 59 ++++
tests/Unit/Listeners/Teams/UpdateSalesforceAccountTest.php | 11 +-
tests/Unit/Listeners/Users/SyncIntercomTest.php | 59 ++++
tests/Unit/Mail/Reports/ReportNotGeneratedTest.php | 166 ++++++++++
tests/Unit/Models/PartnerTest.php | 28 ++
tests/Unit/Repositories/AutomatedReportsRepositoryTest.php | 68 ++++
tests/Unit/Services/Activity/MeetingBotServiceRequestRecordingToStopTest.php | 14 +-
tests/Unit/Services/ActivityServiceTest.php | 391 ++++++++++++++++++++++
tests/Unit/Services/Crm/Hubspot/ServiceResponseNormalizeTest.php | 68 ++--
tests/Unit/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityServiceTest.php | 48 +--
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceActivitiesCountTest.php | 16 +-
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceReportGenerationTest.php | 24 +-
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceTest.php | 130 ++++++++
tests/Unit/Services/KioskServiceTest.php | 8 +
tests/Unit/Services/Webhook/Triggers/AiScorecardCompletedTriggerTest.php | 6 +-
tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php | 119 +++++++
tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php | 108 ++++++
tests/Unit/UseCases/TeamInsights/TeamConversationsExportTest.php | 342 ++++++++++++++-----
186 files changed, 8538 insertions(+), 1233 deletions(-)
create mode 100644 app/Component/Twilio/TwilioRepository.php
delete mode 100644 app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php
create mode 100644 app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php
delete mode 100644 app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php
create mode 100644 app/Http/Controllers/Kiosk/PartnersController.php
create mode 100644 app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php
create mode 100644 app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php
create mode 100644 app/Mail/Reports/AskJiminnyReportExpiringMail.php
create mode 100644 app/Mail/Reports/ReportNotGenerated.php
delete mode 100644 app/Models/ElasticSearch/SharedDocumentDeleteTrait.php
create mode 100644 app/UseCases/TeamInsights/ConversationRowMapper.php
create mode 100644 app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php
create mode 100644 app/UseCases/TeamInsights/StrictConsentColumnResolver.php
create mode 100644 database/migrations/2026_04_14_000000_add_rockeed_partner.php
create mode 100644 database/migrations/2026_04_22_000000_add_success_email_to_partners.php
create mode 100644 database/migrations/2026_04_27_000000_add_label_to_partners.php
create mode 100644 database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php
create mode 100644 front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js
create mode 100644 front-end/src/apps/ai-reports-promo.js
create mode 100644 front-end/src/components/AiReports/AiReportsPromo.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html
create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue
create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js
create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html
create mode 100644 front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js
create mode 100644 front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js
create mode 100644 front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js
create mode 100644 front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js
create mode 100644 front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js
create mode 100644 front-end/src/store/modules/platform/__tests__/getters.spec.js
create mode 100644 public/pdf/exec-reports/com/coaching-profiles.pdf
create mode 100644 public/pdf/exec-reports/com/exec-summary.pdf
create mode 100644 public/pdf/exec-reports/com/loss-report.pdf
create mode 100644 public/pdf/exec-reports/com/product-feedback.pdf
create mode 100644 public/pdf/exec-reports/eu/coaching-profiles.pdf
create mode 100644 public/pdf/exec-reports/eu/exec-summary.pdf
create mode 100644 public/pdf/exec-reports/eu/loss-report.pdf
create mode 100644 public/pdf/exec-reports/eu/product-feedback.pdf
create mode 100644 resources/views/emails/reports/ask-jiminny-report-expiring.blade.php
create mode 100644 resources/views/emails/reports/report-not-generated.blade.php
create mode 100644 tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php
create mode 100644 tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php
create mode 100644 tests/Unit/Events/Activities/Audio/RecordingEventTest.php
create mode 100644 tests/Unit/Events/Activities/Softphone/EndedTest.php
create mode 100644 tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php
create mode 100644 tests/Unit/Events/Activities/Softphone/StartedTest.php
create mode 100644 tests/Unit/Http/Transformers/PartnerTransformerTest.php
create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php
create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php
create mode 100644 tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php
create mode 100644 tests/Unit/Listeners/Users/SyncIntercomTest.php
create mode 100644 tests/Unit/Mail/Reports/ReportNotGeneratedTest.php
create mode 100644 tests/Unit/Models/PartnerTest.php
create mode 100644 tests/Unit/Services/ActivityServiceTest.php
create mode 100644 tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php
create mode 100644 tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 628, done.
remote: Counting objects: 100% (331/331), done.
remote: Compressing objects: 100% (63/63), done.
remote: Total 628 (delta 280), reused 274 (delta 266), pack-reused 297 (from 1)
Receiving objects: 100% (628/628), 186.75 KiB | 1.23 MiB/s, done.
Resolving deltas: 100% (391/391), completed with 57 local objects.
From github.com:jiminny/app
ad2ce76737..12295204cf master -> origin/master
14f54b5be2..5e7646e5f9 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3
b167b19973..acba55cf38 JY-20289-api-tests -> origin/JY-20289-api-tests
f23cfee7c3..e5a3ec5dba JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null
af59d60926..766efba1c5 JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import
* [new branch] JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering
1737b7c528..c57e71e763 JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall
* [new branch] JY-20671-anyvan-twilio-s3-recordings-ftech -> origin/JY-20671-anyvan-twilio-s3-recordings-ftech
+ ba181441c6...20a74137b0 JY-20742-mcp-poc -> origin/JY-20742-mcp-poc (forced update)
* [new branch] JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue
* [new branch] JY-20816-calendar-events-diplication -> origin/JY-20816-calendar-events-diplication
* [new branch] desktop-app -> origin/desktop-app
4c4c974e46..185442c26e make-claude-great-again -> origin/make-claude-great-again
* [new branch] mcp-tools-schemas -> origin/mcp-tools-schemas
Updating ad2ce76737..12295204cf
Fast-forward
app/Component/Encoding/Job/AnalyzeTrackChannelsJob.php | 2 +-
app/Component/Transcription/TranscriptionProcessor/AssemblyAI/Services/SubmitAudioFileService.php | 66 ++----------------------------------------------------------------
app/Console/Commands/Tracks/CleanupActivityTracksCommand.php | 24 +++++++++++++++++-------
tests/Unit/Console/Commands/Tracks/CleanupActivityTracksCommandTest.php | 40 +++++++++++++++++++++++++++++-----------
tests/Unit/fixtures/assembly_ai_transcript_response.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_channel_diarization.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language_error.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language_not_ready.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language_post.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_without_utterances.json | 1 -
11 files changed, 49 insertions(+), 90 deletions(-)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20818-move-AJ-reports-to-separated-datadog-metric
Switched to a new branch 'JY-20818-move-AJ-reports-to-separated-datadog-metric'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix
docker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff
PHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.
PHP runtime: 8.3.30
Running analysis on 7 cores with 10 files per process.
Parallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!
Loaded config default from ".php-cs-fixer.dist.php".
5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%
Fixed 0 of 5663 files in 83.615 seconds, 67.00 MB memory used
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at [URL_WITH_CREDENTIALS] ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix
docker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff
PHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.
PHP runtime: 8.3.30
Running analysis on 7 cores with 10 files per process.
Parallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!
Loaded config default from ".php-cs-fixer.dist.php".
5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%
Fixed 0 of 5663 files in 42.875 seconds, 60.00 MB memory used
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at [URL_WITH_CREDENTIALS] ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 15, done.
remote: Counting objects: 100% (15/15), done.
remote: Compressing objects: 100% (2/2), done.
remote: Total 15 (delta 13), reused 15 (delta 13), pack-reused 0 (from 0)
Unpacking objects: 100% (15/15), 1.28 KiB | 72.00 KiB/s, done.
From github.com:jiminny/app
c57e71e763..8743fea32e JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall
* [new branch] JY-20819-increase-download-transctip-rate-limit -> origin/JY-20819-increase-download-transctip-rate-limit
Already up to date.
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 180, done.
remote: Counting objects: 100% (179/179), done.
remote: Compressing objects: 100% (55/55), done.
remote: Total 180 (delta 127), reused 165 (delta 119), pack-reused 1 (from 1)
Receiving objects: 100% (180/180), 57.50 KiB | 2.74 MiB/s, done.
Resolving deltas: 100% (127/127), completed with 47 local objects.
From github.com:jiminny/app
12295204cf..35f036ace6 master -> origin/master
* [new branch] JY-18091-upgrade-to-php-8-5 -> origin/JY-18091-upgrade-to-php-8-5
5f21965da8..497fbc85c2 JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering
f029263118..6ed9e2bb13 JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue
* [new branch] JY-20817-fix-deleting-s3-directories -> origin/JY-20817-fix-deleting-s3-directories
* [new branch] JY-20820-es-reindex-stream-model-hydration -> origin/JY-20820-es-reindex-stream-model-hydration
+ ca92730ec5...2c8a1d0856 desktop-app -> origin/desktop-app (forced update)
8425d4e0de..89b45ec8b0 mcp-tools-schemas -> origin/mcp-tools-schemas
Updating 12295204cf..35f036ace6
Fast-forward
app/Component/Datadog/Constants.php | 1 +
app/Providers/RouteServiceProvider.php | 2 +-
app/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackService.php | 13 +++++++++++++
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackServiceTest.php | 54 +++++++++++++++++++++++++++++++++++++++++++++++-------
4 files changed, 62 insertions(+), 8 deletions(-)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ gbr
* master
JY-20818-move-AJ-reports-to-separated-datadog-metric
JY-20773-fix-automated-reports-user-pilot-tracking
JY-20157-AJ-report-not-send-notification
JY-20508-notify-before-AJ-report-expiration
JY-20372-ai-reports-promotion-pages
JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null
JY-20738-debug-AJ-tracking-UP
a
JY-18909-automated-reports-ask-jiminny
JY-20692-fix-integration-app-[API_KEY]
JY-20553-debug-crm-sync-delays
JY-20698-fix-SF-activity-types-on-new-playbook
JY-20543-AJ-report-tracking
JY-20384-handle-auto-sync-with-no-access-to-event-type
JY-20458-ask-jiminny-user-definitions
JY-19666-fix-import-contacts-account-association
JY-19666-HS-import-contacts-and-accounts-batch-job
JY-20458-Ask-Jiminny-Reports
JY-20200-batch-update-CRM-objects-Salesforce
JY-19666-HS-webhooks-add-contact-and-company
JY-20348-trigger-setup-DI-layout-on-team-creation
JY-20326-refactor-info-message-in-command
JY-20317-fix-auto-log-delay-issue-on-all-channels-disabled
JY-20312-remove-on-update-change-last-synced-at-crm-configurations
JY-20306-SF-skip-auto-sync-for-task-based-playbook
JY-20192-remove-deleted-team-from-saved-search-filters
JY-20197-import-opportunity-batch-job
JY-20293-enable-status-field-for-pipedrive-deals
JY-20191-remove-commands-interactive-prompts
JY-20118-change-default-sync-strategy
JY-20183-add-cache-on-auto-log-delay
JY-20197-add-import-opportunity-batch-job
20118-hs-opportunity-make-webhook-strategy-default
JY-20118-make-default-hs-opportunity-sync-strategy-webhook-based
JY-20196-handle-opportunity-without-note
JY-20118-improve-opportunity-import
JY-20189-handle-activity-search-on-deleted-groups
JY-20160
JY-20145-filter-out-converted-leads-when-matching
JY-20150-skip-push-summary-on-summary-ready-if-autolog
JY-20132-fix-note-encoding
JY-19792-clean-logs
JY-20117-fix-sync-profile-fields-on-empty-fields
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20725-handle-HS-search-rate-limit
Switched to a new branch 'JY-20725-handle-HS-search-rate-limit'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ ;xd
docker exec -it docker_lamp_1 bash -c "mv /usr/local/etc/php/conf.d/xdebug.ini ~/xdebug.ini"
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at https://docs.docker.com/go/debug-cli/
docker exec -it docker_lamp_1 supervisorctl restart all
jiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: stopped
jiminny-worker-processing-2:jiminny-worker-processing-2_00: stopped
jiminny-worker-processing-3:jiminny-worker-processing-3_00: stopped
jiminny-worker-processing-4:jiminny-worker-processing-4_00: stopped
jiminny-worker-processing-5:jiminny-worker-processing-5_00: stopped
worker-analytics:worker-analytics_00: stopped
worker-crm-update:worker-crm-update_00: stopped
worker-download:worker-download_00: stopped
worker-nudges:worker-nudges_00: stopped
artisan-schedule:artisan-schedule_00: stopped
worker-emails:worker-emails_00: stopped
worker:worker_00: stopped
worker-calendar:worker-calendar_00: stopped
jiminny-worker-processing-1:jiminny-worker-processing-1_00: stopped
worker-crm-sync:worker-crm-sync_00: stopped
worker-audio:worker-audio_00: stopped
worker-conferences:worker-conferences_00: stopped
worker-es-update:worker-es-update_00: stopped
artisan-schedule:artisan-schedule_00: started
jiminny-worker-processing-1:jiminny-worker-processing-1_00: started
jiminny-worker-processing-2:jiminny-worker-processing-2_00: started
jiminny-worker-processing-3:jiminny-worker-processing-3_00: started
jiminny-worker-processing-4:jiminny-worker-processing-4_00: started
jiminny-worker-processing-5:jiminny-worker-processing-5_00: started
jiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: started
worker:worker_00: started
worker-analytics:worker-analytics_00: started
worker-audio:worker-audio_00: started
worker-calendar:worker-calendar_00: started
worker-conferences:worker-conferences_00: started
worker-crm-sync:worker-crm-sync_00: started
worker-crm-update:worker-crm-update_00: started
worker-download:worker-download_00: started
worker-emails:worker-emails_00: started
worker-es-update:worker-es-update_00: started
worker-nudges:worker-nudges_00: started
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at https://docs.docker.com/go/debug-cli/
docker exec -it docker_lamp_1 php -v
PHP 8.3.30 (cli) (built: Mar 16 2026 22:32:32) (NTS)
Copyright (c) The PHP Group
Zend En...
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2026-05-11T17:11:15.490004+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519475490_m2.jpg...
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iTerm2
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APP (-zsh)
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True
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monitor_2
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Last login: Thu May 7 09:44:56 on ttys007
Poetry Last login: Thu May 7 09:44:56 on ttys007
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ git status
On branch master
Your branch is up to date with 'origin/master'.
Changes not staged for commit:
(use "git add <file>..." to update what will be committed)
(use "git restore <file>..." to discard changes in working directory)
modified: .env.local
modified: app/Console/Commands/JiminnyDebugCommand.php
modified: app/Jobs/Team/SyncToIntercom.php
modified: app/Services/PlaybackService.php
modified: config/logging.php
modified: resources/views/partials/crm/push-summary/html-assembly.blade.php
Untracked files:
(use "git add <file>..." to include in what will be committed)
.env.nikilocal
.env.other
WEBHOOK_FILTERING_IMPLEMENTATION.md
app/Console/Commands/Crm/Hubspot/SimulateWebhooksCommand.php
app/Console/Commands/Reports/CreateMockAskJiminnyReportResultCommand.php
ids.txt
public/favicon.ico
raw_sql_query.sql
tests/Unit/Policies/CanAccessAiReportsTest.php
no changes added to commit (use "git add" and/or "git commit -a")
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 1482, done.
remote: Counting objects: 100% (481/481), done.
remote: Compressing objects: 100% (191/191), done.
remote: Total 1482 (delta 349), reused 305 (delta 289), pack-reused 1001 (from 4)
Receiving objects: 100% (1482/1482), 1017.97 KiB | 1.44 MiB/s, done.
Resolving deltas: 100% (877/877), completed with 96 local objects.
From github.com:jiminny/app
83b628967a..ad2ce76737 master -> origin/master
1ee8cbcb7b..14f54b5be2 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3
5662c3b32f..b167b19973 JY-20289-api-tests -> origin/JY-20289-api-tests
b40408cfad..f23cfee7c3 JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null
* [new branch] JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import
* [new branch] JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall
* [new branch] JY-20662-remove-word-boost -> origin/JY-20662-remove-word-boost
* [new branch] JY-20742-mcp-poc -> origin/JY-20742-mcp-poc
* [new branch] make-claude-great-again -> origin/make-claude-great-again
* [new branch] secfix/composer-20260507 -> origin/secfix/composer-20260507
* [new branch] secfix/npm-20260507 -> origin/secfix/npm-20260507
Updating 83b628967a..ad2ce76737
error: Your local changes to the following files would be overwritten by merge:
app/Jobs/Team/SyncToIntercom.php
resources/views/partials/crm/push-summary/html-assembly.blade.php
Please commit your changes or stash them before you merge.
Aborting
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
Updating 83b628967a..ad2ce76737
error: Your local changes to the following files would be overwritten by merge:
app/Jobs/Team/SyncToIntercom.php
resources/views/partials/crm/push-summary/html-assembly.blade.php
Please commit your changes or stash them before you merge.
Aborting
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
Updating 83b628967a..ad2ce76737
error: Your local changes to the following files would be overwritten by merge:
app/Jobs/Team/SyncToIntercom.php
Please commit your changes or stash them before you merge.
Aborting
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
Updating 83b628967a..ad2ce76737
Fast-forward
.cursor/rules/frontend-conventions.mdc | 23 ++
.env.production-eu | 2 +-
.env.staging | 2 +-
Makefile | 10 +
app/Component/ActivityAnalytics/Service/ActivityAnalyticsService.php | 6 +-
app/Component/AiAutomation/Repositories/AiTemplateFieldsRepository.php | 32 +-
app/Component/AiCallScoring/Repositories/AiScorecardRepository.php | 56 ++--
app/Component/AskAnything/AskAnythingPromptService.php | 3 +
app/Component/Transcription/Job/FinishTranscriptionJob.php | 37 ++-
app/Component/Transcription/TranscriptionProcessor/Gong/Gong.php | 18 +-
app/Component/Twilio/Conference/ConferenceManager/SoftPhoneManager.php | 4 +-
app/Component/Twilio/Service/SoftPhoneService.php | 124 ++++---
app/Component/Twilio/TwilioRepository.php | 27 ++
app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php | 59 ----
app/Console/Commands/Reports/AutomatedReportsCommand.php | 122 +++++--
app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php | 200 ++++++++++++
app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php | 60 ----
app/Console/Commands/Users/SyncToIntercom.php | 4 +-
app/Console/Kernel.php | 3 +-
app/Contracts/ES/Events/UpdateMultipleEntities.php | 4 -
app/Contracts/ES/Events/UpdateSingleEntity.php | 4 -
app/Contracts/Repositories/TeamRepository.php | 3 +-
app/Events/Activities/ActivityUpdated.php | 10 +-
app/Events/Activities/Audio/RecordingEvent.php | 6 +-
app/Events/Activities/Softphone/Ended.php | 8 +-
app/Events/Activities/Softphone/SoftphoneEvent.php | 24 +-
app/Events/Activities/Softphone/Started.php | 8 +-
app/Http/Controllers/API/ActivityController.php | 17 +-
app/Http/Controllers/API/SoftphoneController.php | 9 +-
app/Http/Controllers/API/UserAutomatedReports/UserAutomatedReportsController.php | 19 +-
app/Http/Controllers/API/V2/AskAnythingController.php | 2 +-
app/Http/Controllers/Auth/SocialController.php | 6 +-
app/Http/Controllers/Kiosk/AutomatedReportsController.php | 38 ++-
app/Http/Controllers/Kiosk/OrganizationsController.php | 8 +-
app/Http/Controllers/Kiosk/PartnersController.php | 46 +++
app/Http/Controllers/Kiosk/SearchController.php | 8 +
app/Http/Controllers/Kiosk/Teams/OnboardController.php | 24 +-
app/Http/Controllers/Settings/Teams/IntegrationController.php | 6 +-
app/Http/Controllers/TeamSetupController.php | 4 +-
app/Http/Controllers/Telephony/TextMessaging/MessageController.php | 12 +-
app/Http/Controllers/Telephony/TextMessaging/WebhookController.php | 18 +-
app/Http/Requests/Settings/Teams/CreateTeamRequest.php | 1 +
app/Http/Requests/Settings/Teams/EditTeamRequest.php | 1 +
app/Http/Transformers/ActivityTransformer.php | 4 +-
app/Http/Transformers/OnDemandActivitiesTransformer.php | 2 +-
app/Http/Transformers/PartnerTransformer.php | 1 +
app/Http/Transformers/StageTransformer.php | 6 +-
app/Http/Transformers/UserTransformer.php | 11 +-
app/Interactions/Settings/Teams/CreateTeam.php | 3 +
app/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJob.php | 80 ++++-
app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php | 119 +++++++
app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php | 89 +++++
app/Jobs/Crm/Hubspot/ImportBatchJobTrait.php | 12 +-
app/Jobs/Crm/UpdateStage.php | 3 +
app/Jobs/Team/SyncToIntercom.php | 7 +-
app/Listeners/Teams/SyncIntercomCompany.php | 5 +-
app/Listeners/Teams/UpdateSalesforceAccount.php | 8 +-
app/Listeners/Users/SyncIntercom.php | 5 +-
app/Mail/Reports/AskJiminnyReportExpiringMail.php | 40 +++
app/Mail/Reports/ReportNotGenerated.php | 41 +++
app/Models/Activity.php | 25 +-
app/Models/Activity/Question.php | 14 +-
app/Models/Activity/Search.php | 7 +
app/Models/AskAnything/AskAnythingPrompt.php | 6 +
app/Models/AutomatedReport.php | 10 +
app/Models/CoachingFeedback.php | 44 ++-
app/Models/ElasticSearch/ActivityElasticSearchTrait.php | 86 +----
app/Models/ElasticSearch/OpportunityElasticSearchTrait.php | 71 ----
app/Models/ElasticSearch/SharedDocumentDeleteTrait.php | 27 --
app/Models/Partner.php | 13 +
app/Models/Playlist/Activity.php | 14 +-
app/Notifications/OwnerInvitedToTrial.php | 14 +-
app/Policies/UserPolicy.php | 16 +-
app/Queue/Worker/Worker.php | 3 +-
app/Repositories/ActivityRepository.php | 13 +-
app/Repositories/AutomatedReportsRepository.php | 42 ++-
app/Repositories/TeamRepository.php | 21 +-
app/Repositories/UserRepository.php | 2 +-
app/Services/Activity/MeetingBotService.php | 8 +-
app/Services/ActivityService.php | 111 ++-----
app/Services/Crm/Hubspot/Service.php | 36 +-
app/Services/Crm/Hubspot/ServiceTraits/OpportunitySyncTrait.php | 2 +-
app/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityService.php | 5 +-
app/Services/Kiosk/AutomatedReports/AutomatedReportsService.php | 49 +--
app/Services/Kiosk/KioskService.php | 7 +-
app/Services/Webhook/Triggers/AiScorecardCompletedTrigger.php | 13 +-
app/UseCases/TeamInsights/ConversationRowMapper.php | 78 +++++
app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php | 68 ++++
app/UseCases/TeamInsights/StrictConsentColumnResolver.php | 45 +++
app/UseCases/TeamInsights/TeamConversationsExport.php | 154 ++++-----
composer.json | 1 -
composer.lock | 95 +-----
config/secure-headers.php | 5 +-
database/mappings/mapping_activities.json | 16 +
database/migrations/2026_04_14_000000_add_rockeed_partner.php | 51 +++
database/migrations/2026_04_22_000000_add_success_email_to_partners.php | 26 ++
database/migrations/2026_04_27_000000_add_label_to_partners.php | 28 ++
database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php | 79 +++++
front-end/package.json | 5 +-
front-end/src/__mocks__/jiminny.js | 4 +-
front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js | 9 +
front-end/src/__mocks__/setup.js | 1 +
front-end/src/apps/ai-reports-promo.js | 22 ++
front-end/src/components/AiReports/AiReportsPromo.vue | 22 ++
front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue | 190 +++++++++++
front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue | 111 +++++++
front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue | 103 ++++++
front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js | 98 ++++++
.../src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html | 283 ++++++++++++++++
front-end/src/components/AiReports/Manage/ManageAiReports.vue | 8 +-
front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue | 228 +++++++++++++
front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js | 71 ++++
.../src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html | 217 ++++++++++++
front-end/src/components/AiReports/constants.js | 7 +
front-end/src/components/Settings/Kiosk/OrganizationSearch/Organizations.vue | 1 +
front-end/src/components/Settings/Kiosk/__mocks__/Jiminny.js | 1 +
front-end/src/components/Settings/Kiosk/modals/EditTeamModal/EditTeamModal.vue | 43 ++-
front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js | 203 ++++++++++++
front-end/src/components/Settings/Kiosk/shared/Navigation/Navigation.vue | 3 +
front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js | 67 ++++
front-end/src/components/TeamInsights/CoachingFrameworks/AICallScoring/aiCallScoringOverTime.ts | 4 +-
front-end/src/components/TeamInsights/CoachingFrameworks/UsersList.vue | 2 +-
front-end/src/components/layout/Sidebar/HelpMenu.vue | 25 +-
front-end/src/components/layout/Sidebar/Sidebar.vue | 27 +-
front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js | 94 ++++++
front-end/src/components/layout/Sidebar/__tests__/__snapshots__/Sidebar.spec.js.snap | 4 +-
front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js | 204 ++++++++++++
front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js | 49 +++
front-end/src/main.js | 1 +
front-end/src/store/modules/TeamInsights/util.js | 1 +
front-end/src/store/modules/platform/__tests__/getters.spec.js | 22 ++
front-end/src/store/modules/platform/getters.js | 3 +
front-end/src/utils/index.js | 11 +
front-end/yarn.lock | 21 +-
phpstan-baseline.neon | 60 ----
public/pdf/exec-reports/com/coaching-profiles.pdf | Bin 0 -> 1531178 bytes
public/pdf/exec-reports/com/exec-summary.pdf | Bin 0 -> 2237381 bytes
public/pdf/exec-reports/com/loss-report.pdf | Bin 0 -> 1955343 bytes
public/pdf/exec-reports/com/product-feedback.pdf | Bin 0 -> 2184417 bytes
public/pdf/exec-reports/eu/coaching-profiles.pdf | Bin 0 -> 1528704 bytes
public/pdf/exec-reports/eu/exec-summary.pdf | Bin 0 -> 2296741 bytes
public/pdf/exec-reports/eu/loss-report.pdf | Bin 0 -> 1955808 bytes
public/pdf/exec-reports/eu/product-feedback.pdf | Bin 0 -> 2184083 bytes
resources/views/emails/reports/ask-jiminny-report-expiring.blade.php | 22 ++
resources/views/emails/reports/report-not-generated.blade.php | 24 ++
resources/views/partials/crm/push-summary/html-assembly.blade.php | 2 +-
routes/api.php | 6 +
routes/web.php | 4 +
tests/Feature/Policies/UserPolicyTest.php | 90 ++++-
tests/Unit/Component/ActivityAnalytics/Service/ActivityAnalyticsServiceTest.php | 40 +++
tests/Unit/Component/AskAnything/AskAnythingPromptServiceTest.php | 26 ++
tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php | 276 ++++++++++++++++
tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php | 375 +++++++++++++++++++++
tests/Unit/Component/Twilio/Service/SoftPhoneServiceTest.php | 1014 +++++++++++++++++++++++++++++++++++++++++++++++++++++++--
tests/Unit/Console/Commands/Reports/AutomatedReportsCommandTest.php | 157 ++++++++-
tests/Unit/Events/Activities/Audio/RecordingEventTest.php | 72 ++++
tests/Unit/Events/Activities/Softphone/EndedTest.php | 86 +++++
tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php | 88 +++++
tests/Unit/Events/Activities/Softphone/StartedTest.php | 86 +++++
tests/Unit/Http/Controllers/Kiosk/AutomatedReportsControllerTest.php | 99 ++++++
tests/Unit/Http/Transformers/ActivityTransformerTest.php | 5 +-
tests/Unit/Http/Transformers/PartnerTransformerTest.php | 34 ++
tests/Unit/Interactions/Settings/Teams/CreateTeamTest.php | 49 +++
tests/Unit/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJobTest.php | 106 +++++-
tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php | 205 ++++++++++++
tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php | 188 +++++++++++
tests/Unit/Jobs/Crm/ImportOpportunityBatchTest.php | 2 +-
tests/Unit/Jobs/Team/SyncToIntercomTest.php | 6 +
tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php | 59 ++++
tests/Unit/Listeners/Teams/UpdateSalesforceAccountTest.php | 11 +-
tests/Unit/Listeners/Users/SyncIntercomTest.php | 59 ++++
tests/Unit/Mail/Reports/ReportNotGeneratedTest.php | 166 ++++++++++
tests/Unit/Models/PartnerTest.php | 28 ++
tests/Unit/Repositories/AutomatedReportsRepositoryTest.php | 68 ++++
tests/Unit/Services/Activity/MeetingBotServiceRequestRecordingToStopTest.php | 14 +-
tests/Unit/Services/ActivityServiceTest.php | 391 ++++++++++++++++++++++
tests/Unit/Services/Crm/Hubspot/ServiceResponseNormalizeTest.php | 68 ++--
tests/Unit/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityServiceTest.php | 48 +--
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceActivitiesCountTest.php | 16 +-
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceReportGenerationTest.php | 24 +-
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceTest.php | 130 ++++++++
tests/Unit/Services/KioskServiceTest.php | 8 +
tests/Unit/Services/Webhook/Triggers/AiScorecardCompletedTriggerTest.php | 6 +-
tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php | 119 +++++++
tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php | 108 ++++++
tests/Unit/UseCases/TeamInsights/TeamConversationsExportTest.php | 342 ++++++++++++++-----
186 files changed, 8538 insertions(+), 1233 deletions(-)
create mode 100644 app/Component/Twilio/TwilioRepository.php
delete mode 100644 app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php
create mode 100644 app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php
delete mode 100644 app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php
create mode 100644 app/Http/Controllers/Kiosk/PartnersController.php
create mode 100644 app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php
create mode 100644 app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php
create mode 100644 app/Mail/Reports/AskJiminnyReportExpiringMail.php
create mode 100644 app/Mail/Reports/ReportNotGenerated.php
delete mode 100644 app/Models/ElasticSearch/SharedDocumentDeleteTrait.php
create mode 100644 app/UseCases/TeamInsights/ConversationRowMapper.php
create mode 100644 app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php
create mode 100644 app/UseCases/TeamInsights/StrictConsentColumnResolver.php
create mode 100644 database/migrations/2026_04_14_000000_add_rockeed_partner.php
create mode 100644 database/migrations/2026_04_22_000000_add_success_email_to_partners.php
create mode 100644 database/migrations/2026_04_27_000000_add_label_to_partners.php
create mode 100644 database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php
create mode 100644 front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js
create mode 100644 front-end/src/apps/ai-reports-promo.js
create mode 100644 front-end/src/components/AiReports/AiReportsPromo.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html
create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue
create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js
create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html
create mode 100644 front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js
create mode 100644 front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js
create mode 100644 front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js
create mode 100644 front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js
create mode 100644 front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js
create mode 100644 front-end/src/store/modules/platform/__tests__/getters.spec.js
create mode 100644 public/pdf/exec-reports/com/coaching-profiles.pdf
create mode 100644 public/pdf/exec-reports/com/exec-summary.pdf
create mode 100644 public/pdf/exec-reports/com/loss-report.pdf
create mode 100644 public/pdf/exec-reports/com/product-feedback.pdf
create mode 100644 public/pdf/exec-reports/eu/coaching-profiles.pdf
create mode 100644 public/pdf/exec-reports/eu/exec-summary.pdf
create mode 100644 public/pdf/exec-reports/eu/loss-report.pdf
create mode 100644 public/pdf/exec-reports/eu/product-feedback.pdf
create mode 100644 resources/views/emails/reports/ask-jiminny-report-expiring.blade.php
create mode 100644 resources/views/emails/reports/report-not-generated.blade.php
create mode 100644 tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php
create mode 100644 tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php
create mode 100644 tests/Unit/Events/Activities/Audio/RecordingEventTest.php
create mode 100644 tests/Unit/Events/Activities/Softphone/EndedTest.php
create mode 100644 tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php
create mode 100644 tests/Unit/Events/Activities/Softphone/StartedTest.php
create mode 100644 tests/Unit/Http/Transformers/PartnerTransformerTest.php
create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php
create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php
create mode 100644 tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php
create mode 100644 tests/Unit/Listeners/Users/SyncIntercomTest.php
create mode 100644 tests/Unit/Mail/Reports/ReportNotGeneratedTest.php
create mode 100644 tests/Unit/Models/PartnerTest.php
create mode 100644 tests/Unit/Services/ActivityServiceTest.php
create mode 100644 tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php
create mode 100644 tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 628, done.
remote: Counting objects: 100% (331/331), done.
remote: Compressing objects: 100% (63/63), done.
remote: Total 628 (delta 280), reused 274 (delta 266), pack-reused 297 (from 1)
Receiving objects: 100% (628/628), 186.75 KiB | 1.23 MiB/s, done.
Resolving deltas: 100% (391/391), completed with 57 local objects.
From github.com:jiminny/app
ad2ce76737..12295204cf master -> origin/master
14f54b5be2..5e7646e5f9 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3
b167b19973..acba55cf38 JY-20289-api-tests -> origin/JY-20289-api-tests
f23cfee7c3..e5a3ec5dba JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null
af59d60926..766efba1c5 JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import
* [new branch] JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering
1737b7c528..c57e71e763 JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall
* [new branch] JY-20671-anyvan-twilio-s3-recordings-ftech -> origin/JY-20671-anyvan-twilio-s3-recordings-ftech
+ ba181441c6...20a74137b0 JY-20742-mcp-poc -> origin/JY-20742-mcp-poc (forced update)
* [new branch] JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue
* [new branch] JY-20816-calendar-events-diplication -> origin/JY-20816-calendar-events-diplication
* [new branch] desktop-app -> origin/desktop-app
4c4c974e46..185442c26e make-claude-great-again -> origin/make-claude-great-again
* [new branch] mcp-tools-schemas -> origin/mcp-tools-schemas
Updating ad2ce76737..12295204cf
Fast-forward
app/Component/Encoding/Job/AnalyzeTrackChannelsJob.php | 2 +-
app/Component/Transcription/TranscriptionProcessor/AssemblyAI/Services/SubmitAudioFileService.php | 66 ++----------------------------------------------------------------
app/Console/Commands/Tracks/CleanupActivityTracksCommand.php | 24 +++++++++++++++++-------
tests/Unit/Console/Commands/Tracks/CleanupActivityTracksCommandTest.php | 40 +++++++++++++++++++++++++++++-----------
tests/Unit/fixtures/assembly_ai_transcript_response.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_channel_diarization.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language_error.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language_not_ready.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language_post.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_without_utterances.json | 1 -
11 files changed, 49 insertions(+), 90 deletions(-)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20818-move-AJ-reports-to-separated-datadog-metric
Switched to a new branch 'JY-20818-move-AJ-reports-to-separated-datadog-metric'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix
docker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff
PHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.
PHP runtime: 8.3.30
Running analysis on 7 cores with 10 files per process.
Parallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!
Loaded config default from ".php-cs-fixer.dist.php".
5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%
Fixed 0 of 5663 files in 83.615 seconds, 67.00 MB memory used
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at [URL_WITH_CREDENTIALS] ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix
docker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff
PHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.
PHP runtime: 8.3.30
Running analysis on 7 cores with 10 files per process.
Parallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!
Loaded config default from ".php-cs-fixer.dist.php".
5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%
Fixed 0 of 5663 files in 42.875 seconds, 60.00 MB memory used
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at [URL_WITH_CREDENTIALS] ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 15, done.
remote: Counting objects: 100% (15/15), done.
remote: Compressing objects: 100% (2/2), done.
remote: Total 15 (delta 13), reused 15 (delta 13), pack-reused 0 (from 0)
Unpacking objects: 100% (15/15), 1.28 KiB | 72.00 KiB/s, done.
From github.com:jiminny/app
c57e71e763..8743fea32e JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall
* [new branch] JY-20819-increase-download-transctip-rate-limit -> origin/JY-20819-increase-download-transctip-rate-limit
Already up to date.
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 180, done.
remote: Counting objects: 100% (179/179), done.
remote: Compressing objects: 100% (55/55), done.
remote: Total 180 (delta 127), reused 165 (delta 119), pack-reused 1 (from 1)
Receiving objects: 100% (180/180), 57.50 KiB | 2.74 MiB/s, done.
Resolving deltas: 100% (127/127), completed with 47 local objects.
From github.com:jiminny/app
12295204cf..35f036ace6 master -> origin/master
* [new branch] JY-18091-upgrade-to-php-8-5 -> origin/JY-18091-upgrade-to-php-8-5
5f21965da8..497fbc85c2 JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering
f029263118..6ed9e2bb13 JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue
* [new branch] JY-20817-fix-deleting-s3-directories -> origin/JY-20817-fix-deleting-s3-directories
* [new branch] JY-20820-es-reindex-stream-model-hydration -> origin/JY-20820-es-reindex-stream-model-hydration
+ ca92730ec5...2c8a1d0856 desktop-app -> origin/desktop-app (forced update)
8425d4e0de..89b45ec8b0 mcp-tools-schemas -> origin/mcp-tools-schemas
Updating 12295204cf..35f036ace6
Fast-forward
app/Component/Datadog/Constants.php | 1 +
app/Providers/RouteServiceProvider.php | 2 +-
app/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackService.php | 13 +++++++++++++
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackServiceTest.php | 54 +++++++++++++++++++++++++++++++++++++++++++++++-------
4 files changed, 62 insertions(+), 8 deletions(-)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ gbr
* master
JY-20818-move-AJ-reports-to-separated-datadog-metric
JY-20773-fix-automated-reports-user-pilot-tracking
JY-20157-AJ-report-not-send-notification
JY-20508-notify-before-AJ-report-expiration
JY-20372-ai-reports-promotion-pages
JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null
JY-20738-debug-AJ-tracking-UP
a
JY-18909-automated-reports-ask-jiminny
JY-20692-fix-integration-app-[API_KEY]
JY-20553-debug-crm-sync-delays
JY-20698-fix-SF-activity-types-on-new-playbook
JY-20543-AJ-report-tracking
JY-20384-handle-auto-sync-with-no-access-to-event-type
JY-20458-ask-jiminny-user-definitions
JY-19666-fix-import-contacts-account-association
JY-19666-HS-import-contacts-and-accounts-batch-job
JY-20458-Ask-Jiminny-Reports
JY-20200-batch-update-CRM-objects-Salesforce
JY-19666-HS-webhooks-add-contact-and-company
JY-20348-trigger-setup-DI-layout-on-team-creation
JY-20326-refactor-info-message-in-command
JY-20317-fix-auto-log-delay-issue-on-all-channels-disabled
JY-20312-remove-on-update-change-last-synced-at-crm-configurations
JY-20306-SF-skip-auto-sync-for-task-based-playbook
JY-20192-remove-deleted-team-from-saved-search-filters
JY-20197-import-opportunity-batch-job
JY-20293-enable-status-field-for-pipedrive-deals
JY-20191-remove-commands-interactive-prompts
JY-20118-change-default-sync-strategy
JY-20183-add-cache-on-auto-log-delay
JY-20197-add-import-opportunity-batch-job
20118-hs-opportunity-make-webhook-strategy-default
JY-20118-make-default-hs-opportunity-sync-strategy-webhook-based
JY-20196-handle-opportunity-without-note
JY-20118-improve-opportunity-import
JY-20189-handle-activity-search-on-deleted-groups
JY-20160
JY-20145-filter-out-converted-leads-when-matching
JY-20150-skip-push-summary-on-summary-ready-if-autolog
JY-20132-fix-note-encoding
JY-19792-clean-logs
JY-20117-fix-sync-profile-fields-on-empty-fields
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20725-handle-HS-search-rate-limit
Switched to a new branch 'JY-20725-handle-HS-search-rate-limit'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ ;xd
docker exec -it docker_lamp_1 bash -c "mv /usr/local/etc/php/conf.d/xdebug.ini ~/xdebug.ini"
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at https://docs.docker.com/go/debug-cli/
docker exec -it docker_lamp_1 supervisorctl restart all
jiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: stopped
jiminny-worker-processing-2:jiminny-worker-processing-2_00: stopped
jiminny-worker-processing-3:jiminny-worker-processing-3_00: stopped
jiminny-worker-processing-4:jiminny-worker-processing-4_00: stopped
jiminny-worker-processing-5:jiminny-worker-processing-5_00: stopped
worker-analytics:worker-analytics_00: stopped
worker-crm-update:worker-crm-update_00: stopped
worker-download:worker-download_00: stopped
worker-nudges:worker-nudges_00: stopped
artisan-schedule:artisan-schedule_00: stopped
worker-emails:worker-emails_00: stopped
worker:worker_00: stopped
worker-calendar:worker-calendar_00: stopped
jiminny-worker-processing-1:jiminny-worker-processing-1_00: stopped
worker-crm-sync:worker-crm-sync_00: stopped
worker-audio:worker-audio_00: stopped
worker-conferences:worker-conferences_00: stopped
worker-es-update:worker-es-update_00: stopped
artisan-schedule:artisan-schedule_00: started
jiminny-worker-processing-1:jiminny-worker-processing-1_00: started
jiminny-worker-processing-2:jiminny-worker-processing-2_00: started
jiminny-worker-processing-3:jiminny-worker-processing-3_00: started
jiminny-worker-processing-4:jiminny-worker-processing-4_00: started
jiminny-worker-processing-5:jiminny-worker-processing-5_00: started
jiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: started
worker:worker_00: started
worker-analytics:worker-analytics_00: started
worker-audio:worker-audio_00: started
worker-calendar:worker-calendar_00: started
worker-conferences:worker-conferences_00: started
worker-crm-sync:worker-crm-sync_00: started
worker-crm-update:worker-crm-update_00: started
worker-download:worker-download_00: started
worker-emails:worker-emails_00: started
worker-es-update:worker-es-update_00: started
worker-nudges:worker-nudges_00: started
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at https://docs.docker.com/go/debug-cli/
docker exec -it docker_lamp_1 php -v
PHP 8.3.30 (cli) (built: Mar 16 2026 22:32:32) (NTS)
Copyright (c) The PHP Group
Zend En...
|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"Last login: Thu May 7 09:44:56 on ttys007\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ git status\nOn branch master\nYour branch is up to date with 'origin/master'.\n\nChanges not staged for commit:\n (use \"git add <file>...\" to update what will be committed)\n (use \"git restore <file>...\" to discard changes in working directory)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: .env.local\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: app/Console/Commands/JiminnyDebugCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: app/Jobs/Team/SyncToIntercom.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: app/Services/PlaybackService.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: config/logging.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: resources/views/partials/crm/push-summary/html-assembly.blade.php\n\nUntracked files:\n (use \"git add <file>...\" to include in what will be committed)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.nikilocal\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.other\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tWEBHOOK_FILTERING_IMPLEMENTATION.md\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Crm/Hubspot/SimulateWebhooksCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Reports/CreateMockAskJiminnyReportResultCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tids.txt\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tpublic/favicon.ico\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\traw_sql_query.sql\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\ttests/Unit/Policies/CanAccessAiReportsTest.php\n\nno changes added to commit (use \"git add\" and/or \"git commit -a\")\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nremote: Enumerating objects: 1482, done.\nremote: Counting objects: 100% (481/481), done.\nremote: Compressing objects: 100% (191/191), done.\nremote: Total 1482 (delta 349), reused 305 (delta 289), pack-reused 1001 (from 4)\nReceiving objects: 100% (1482/1482), 1017.97 KiB | 1.44 MiB/s, done.\nResolving deltas: 100% (877/877), completed with 96 local objects.\nFrom github.com:jiminny/app\n 83b628967a..ad2ce76737 master -> origin/master\n 1ee8cbcb7b..14f54b5be2 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3\n 5662c3b32f..b167b19973 JY-20289-api-tests -> origin/JY-20289-api-tests\n b40408cfad..f23cfee7c3 JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null\n * [new branch] JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import\n * [new branch] JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall\n * [new branch] JY-20662-remove-word-boost -> origin/JY-20662-remove-word-boost\n * [new branch] JY-20742-mcp-poc -> origin/JY-20742-mcp-poc\n * [new branch] make-claude-great-again -> origin/make-claude-great-again\n * [new branch] secfix/composer-20260507 -> origin/secfix/composer-20260507\n * [new branch] secfix/npm-20260507 -> origin/secfix/npm-20260507\nUpdating 83b628967a..ad2ce76737\nerror: Your local changes to the following files would be overwritten by merge:\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Jobs/Team/SyncToIntercom.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tresources/views/partials/crm/push-summary/html-assembly.blade.php\nPlease commit your changes or stash them before you merge.\nAborting\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nUpdating 83b628967a..ad2ce76737\nerror: Your local changes to the following files would be overwritten by merge:\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Jobs/Team/SyncToIntercom.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tresources/views/partials/crm/push-summary/html-assembly.blade.php\nPlease commit your changes or stash them before you merge.\nAborting\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nUpdating 83b628967a..ad2ce76737\nerror: Your local changes to the following files would be overwritten by merge:\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Jobs/Team/SyncToIntercom.php\nPlease commit your changes or stash them before you merge.\nAborting\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nUpdating 83b628967a..ad2ce76737\nFast-forward\n .cursor/rules/frontend-conventions.mdc | 23 ++\n .env.production-eu | 2 +-\n .env.staging | 2 +-\n Makefile | 10 +\n app/Component/ActivityAnalytics/Service/ActivityAnalyticsService.php | 6 +-\n app/Component/AiAutomation/Repositories/AiTemplateFieldsRepository.php | 32 +-\n app/Component/AiCallScoring/Repositories/AiScorecardRepository.php | 56 ++--\n app/Component/AskAnything/AskAnythingPromptService.php | 3 +\n app/Component/Transcription/Job/FinishTranscriptionJob.php | 37 ++-\n app/Component/Transcription/TranscriptionProcessor/Gong/Gong.php | 18 +-\n app/Component/Twilio/Conference/ConferenceManager/SoftPhoneManager.php | 4 +-\n app/Component/Twilio/Service/SoftPhoneService.php | 124 ++++---\n app/Component/Twilio/TwilioRepository.php | 27 ++\n app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php | 59 ----\n app/Console/Commands/Reports/AutomatedReportsCommand.php | 122 +++++--\n app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php | 200 ++++++++++++\n app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php | 60 ----\n app/Console/Commands/Users/SyncToIntercom.php | 4 +-\n app/Console/Kernel.php | 3 +-\n app/Contracts/ES/Events/UpdateMultipleEntities.php | 4 -\n app/Contracts/ES/Events/UpdateSingleEntity.php | 4 -\n app/Contracts/Repositories/TeamRepository.php | 3 +-\n app/Events/Activities/ActivityUpdated.php | 10 +-\n app/Events/Activities/Audio/RecordingEvent.php | 6 +-\n app/Events/Activities/Softphone/Ended.php | 8 +-\n app/Events/Activities/Softphone/SoftphoneEvent.php | 24 +-\n app/Events/Activities/Softphone/Started.php | 8 +-\n app/Http/Controllers/API/ActivityController.php | 17 +-\n app/Http/Controllers/API/SoftphoneController.php | 9 +-\n app/Http/Controllers/API/UserAutomatedReports/UserAutomatedReportsController.php | 19 +-\n app/Http/Controllers/API/V2/AskAnythingController.php | 2 +-\n app/Http/Controllers/Auth/SocialController.php | 6 +-\n app/Http/Controllers/Kiosk/AutomatedReportsController.php | 38 ++-\n app/Http/Controllers/Kiosk/OrganizationsController.php | 8 +-\n app/Http/Controllers/Kiosk/PartnersController.php | 46 +++\n app/Http/Controllers/Kiosk/SearchController.php | 8 +\n app/Http/Controllers/Kiosk/Teams/OnboardController.php | 24 +-\n app/Http/Controllers/Settings/Teams/IntegrationController.php | 6 +-\n app/Http/Controllers/TeamSetupController.php | 4 +-\n app/Http/Controllers/Telephony/TextMessaging/MessageController.php | 12 +-\n app/Http/Controllers/Telephony/TextMessaging/WebhookController.php | 18 +-\n app/Http/Requests/Settings/Teams/CreateTeamRequest.php | 1 +\n app/Http/Requests/Settings/Teams/EditTeamRequest.php | 1 +\n app/Http/Transformers/ActivityTransformer.php | 4 +-\n app/Http/Transformers/OnDemandActivitiesTransformer.php | 2 +-\n app/Http/Transformers/PartnerTransformer.php | 1 +\n app/Http/Transformers/StageTransformer.php | 6 +-\n app/Http/Transformers/UserTransformer.php | 11 +-\n app/Interactions/Settings/Teams/CreateTeam.php | 3 +\n app/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJob.php | 80 ++++-\n app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php | 119 +++++++\n app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php | 89 +++++\n app/Jobs/Crm/Hubspot/ImportBatchJobTrait.php | 12 +-\n app/Jobs/Crm/UpdateStage.php | 3 +\n app/Jobs/Team/SyncToIntercom.php | 7 +-\n app/Listeners/Teams/SyncIntercomCompany.php | 5 +-\n app/Listeners/Teams/UpdateSalesforceAccount.php | 8 +-\n app/Listeners/Users/SyncIntercom.php | 5 +-\n app/Mail/Reports/AskJiminnyReportExpiringMail.php | 40 +++\n app/Mail/Reports/ReportNotGenerated.php | 41 +++\n app/Models/Activity.php | 25 +-\n app/Models/Activity/Question.php | 14 +-\n app/Models/Activity/Search.php | 7 +\n app/Models/AskAnything/AskAnythingPrompt.php | 6 +\n app/Models/AutomatedReport.php | 10 +\n app/Models/CoachingFeedback.php | 44 ++-\n app/Models/ElasticSearch/ActivityElasticSearchTrait.php | 86 +----\n app/Models/ElasticSearch/OpportunityElasticSearchTrait.php | 71 ----\n app/Models/ElasticSearch/SharedDocumentDeleteTrait.php | 27 --\n app/Models/Partner.php | 13 +\n app/Models/Playlist/Activity.php | 14 +-\n app/Notifications/OwnerInvitedToTrial.php | 14 +-\n app/Policies/UserPolicy.php | 16 +-\n app/Queue/Worker/Worker.php | 3 +-\n app/Repositories/ActivityRepository.php | 13 +-\n app/Repositories/AutomatedReportsRepository.php | 42 ++-\n app/Repositories/TeamRepository.php | 21 +-\n app/Repositories/UserRepository.php | 2 +-\n app/Services/Activity/MeetingBotService.php | 8 +-\n app/Services/ActivityService.php | 111 ++-----\n app/Services/Crm/Hubspot/Service.php | 36 +-\n app/Services/Crm/Hubspot/ServiceTraits/OpportunitySyncTrait.php | 2 +-\n app/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityService.php | 5 +-\n app/Services/Kiosk/AutomatedReports/AutomatedReportsService.php | 49 +--\n app/Services/Kiosk/KioskService.php | 7 +-\n app/Services/Webhook/Triggers/AiScorecardCompletedTrigger.php | 13 +-\n app/UseCases/TeamInsights/ConversationRowMapper.php | 78 +++++\n app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php | 68 ++++\n app/UseCases/TeamInsights/StrictConsentColumnResolver.php | 45 +++\n app/UseCases/TeamInsights/TeamConversationsExport.php | 154 ++++-----\n composer.json | 1 -\n composer.lock | 95 +-----\n config/secure-headers.php | 5 +-\n database/mappings/mapping_activities.json | 16 +\n database/migrations/2026_04_14_000000_add_rockeed_partner.php | 51 +++\n database/migrations/2026_04_22_000000_add_success_email_to_partners.php | 26 ++\n database/migrations/2026_04_27_000000_add_label_to_partners.php | 28 ++\n database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php | 79 +++++\n front-end/package.json | 5 +-\n front-end/src/__mocks__/jiminny.js | 4 +-\n front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js | 9 +\n front-end/src/__mocks__/setup.js | 1 +\n front-end/src/apps/ai-reports-promo.js | 22 ++\n front-end/src/components/AiReports/AiReportsPromo.vue | 22 ++\n front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue | 190 +++++++++++\n front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue | 111 +++++++\n front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue | 103 ++++++\n front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js | 98 ++++++\n .../src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html | 283 ++++++++++++++++\n front-end/src/components/AiReports/Manage/ManageAiReports.vue | 8 +-\n front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue | 228 +++++++++++++\n front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js | 71 ++++\n .../src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html | 217 ++++++++++++\n front-end/src/components/AiReports/constants.js | 7 +\n front-end/src/components/Settings/Kiosk/OrganizationSearch/Organizations.vue | 1 +\n front-end/src/components/Settings/Kiosk/__mocks__/Jiminny.js | 1 +\n front-end/src/components/Settings/Kiosk/modals/EditTeamModal/EditTeamModal.vue | 43 ++-\n front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js | 203 ++++++++++++\n front-end/src/components/Settings/Kiosk/shared/Navigation/Navigation.vue | 3 +\n front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js | 67 ++++\n front-end/src/components/TeamInsights/CoachingFrameworks/AICallScoring/aiCallScoringOverTime.ts | 4 +-\n front-end/src/components/TeamInsights/CoachingFrameworks/UsersList.vue | 2 +-\n front-end/src/components/layout/Sidebar/HelpMenu.vue | 25 +-\n front-end/src/components/layout/Sidebar/Sidebar.vue | 27 +-\n front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js | 94 ++++++\n front-end/src/components/layout/Sidebar/__tests__/__snapshots__/Sidebar.spec.js.snap | 4 +-\n front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js | 204 ++++++++++++\n front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js | 49 +++\n front-end/src/main.js | 1 +\n front-end/src/store/modules/TeamInsights/util.js | 1 +\n front-end/src/store/modules/platform/__tests__/getters.spec.js | 22 ++\n front-end/src/store/modules/platform/getters.js | 3 +\n front-end/src/utils/index.js | 11 +\n front-end/yarn.lock | 21 +-\n phpstan-baseline.neon | 60 ----\n public/pdf/exec-reports/com/coaching-profiles.pdf | Bin 0 -> 1531178 bytes\n public/pdf/exec-reports/com/exec-summary.pdf | Bin 0 -> 2237381 bytes\n public/pdf/exec-reports/com/loss-report.pdf | Bin 0 -> 1955343 bytes\n public/pdf/exec-reports/com/product-feedback.pdf | Bin 0 -> 2184417 bytes\n public/pdf/exec-reports/eu/coaching-profiles.pdf | Bin 0 -> 1528704 bytes\n public/pdf/exec-reports/eu/exec-summary.pdf | Bin 0 -> 2296741 bytes\n public/pdf/exec-reports/eu/loss-report.pdf | Bin 0 -> 1955808 bytes\n public/pdf/exec-reports/eu/product-feedback.pdf | Bin 0 -> 2184083 bytes\n resources/views/emails/reports/ask-jiminny-report-expiring.blade.php | 22 ++\n resources/views/emails/reports/report-not-generated.blade.php | 24 ++\n resources/views/partials/crm/push-summary/html-assembly.blade.php | 2 +-\n routes/api.php | 6 +\n routes/web.php | 4 +\n tests/Feature/Policies/UserPolicyTest.php | 90 ++++-\n tests/Unit/Component/ActivityAnalytics/Service/ActivityAnalyticsServiceTest.php | 40 +++\n tests/Unit/Component/AskAnything/AskAnythingPromptServiceTest.php | 26 ++\n tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php | 276 ++++++++++++++++\n tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php | 375 +++++++++++++++++++++\n tests/Unit/Component/Twilio/Service/SoftPhoneServiceTest.php | 1014 +++++++++++++++++++++++++++++++++++++++++++++++++++++++--\n tests/Unit/Console/Commands/Reports/AutomatedReportsCommandTest.php | 157 ++++++++-\n tests/Unit/Events/Activities/Audio/RecordingEventTest.php | 72 ++++\n tests/Unit/Events/Activities/Softphone/EndedTest.php | 86 +++++\n tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php | 88 +++++\n tests/Unit/Events/Activities/Softphone/StartedTest.php | 86 +++++\n tests/Unit/Http/Controllers/Kiosk/AutomatedReportsControllerTest.php | 99 ++++++\n tests/Unit/Http/Transformers/ActivityTransformerTest.php | 5 +-\n tests/Unit/Http/Transformers/PartnerTransformerTest.php | 34 ++\n tests/Unit/Interactions/Settings/Teams/CreateTeamTest.php | 49 +++\n tests/Unit/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJobTest.php | 106 +++++-\n tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php | 205 ++++++++++++\n tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php | 188 +++++++++++\n tests/Unit/Jobs/Crm/ImportOpportunityBatchTest.php | 2 +-\n tests/Unit/Jobs/Team/SyncToIntercomTest.php | 6 +\n tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php | 59 ++++\n tests/Unit/Listeners/Teams/UpdateSalesforceAccountTest.php | 11 +-\n tests/Unit/Listeners/Users/SyncIntercomTest.php | 59 ++++\n tests/Unit/Mail/Reports/ReportNotGeneratedTest.php | 166 ++++++++++\n tests/Unit/Models/PartnerTest.php | 28 ++\n tests/Unit/Repositories/AutomatedReportsRepositoryTest.php | 68 ++++\n tests/Unit/Services/Activity/MeetingBotServiceRequestRecordingToStopTest.php | 14 +-\n tests/Unit/Services/ActivityServiceTest.php | 391 ++++++++++++++++++++++\n tests/Unit/Services/Crm/Hubspot/ServiceResponseNormalizeTest.php | 68 ++--\n tests/Unit/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityServiceTest.php | 48 +--\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceActivitiesCountTest.php | 16 +-\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceReportGenerationTest.php | 24 +-\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceTest.php | 130 ++++++++\n tests/Unit/Services/KioskServiceTest.php | 8 +\n tests/Unit/Services/Webhook/Triggers/AiScorecardCompletedTriggerTest.php | 6 +-\n tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php | 119 +++++++\n tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php | 108 ++++++\n tests/Unit/UseCases/TeamInsights/TeamConversationsExportTest.php | 342 ++++++++++++++-----\n 186 files changed, 8538 insertions(+), 1233 deletions(-)\n create mode 100644 app/Component/Twilio/TwilioRepository.php\n delete mode 100644 app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php\n create mode 100644 app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php\n delete mode 100644 app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php\n create mode 100644 app/Http/Controllers/Kiosk/PartnersController.php\n create mode 100644 app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php\n create mode 100644 app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php\n create mode 100644 app/Mail/Reports/AskJiminnyReportExpiringMail.php\n create mode 100644 app/Mail/Reports/ReportNotGenerated.php\n delete mode 100644 app/Models/ElasticSearch/SharedDocumentDeleteTrait.php\n create mode 100644 app/UseCases/TeamInsights/ConversationRowMapper.php\n create mode 100644 app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php\n create mode 100644 app/UseCases/TeamInsights/StrictConsentColumnResolver.php\n create mode 100644 database/migrations/2026_04_14_000000_add_rockeed_partner.php\n create mode 100644 database/migrations/2026_04_22_000000_add_success_email_to_partners.php\n create mode 100644 database/migrations/2026_04_27_000000_add_label_to_partners.php\n create mode 100644 database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php\n create mode 100644 front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js\n create mode 100644 front-end/src/apps/ai-reports-promo.js\n create mode 100644 front-end/src/components/AiReports/AiReportsPromo.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html\n create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue\n create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js\n create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html\n create mode 100644 front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js\n create mode 100644 front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js\n create mode 100644 front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js\n create mode 100644 front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js\n create mode 100644 front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js\n create mode 100644 front-end/src/store/modules/platform/__tests__/getters.spec.js\n create mode 100644 public/pdf/exec-reports/com/coaching-profiles.pdf\n create mode 100644 public/pdf/exec-reports/com/exec-summary.pdf\n create mode 100644 public/pdf/exec-reports/com/loss-report.pdf\n create mode 100644 public/pdf/exec-reports/com/product-feedback.pdf\n create mode 100644 public/pdf/exec-reports/eu/coaching-profiles.pdf\n create mode 100644 public/pdf/exec-reports/eu/exec-summary.pdf\n create mode 100644 public/pdf/exec-reports/eu/loss-report.pdf\n create mode 100644 public/pdf/exec-reports/eu/product-feedback.pdf\n create mode 100644 resources/views/emails/reports/ask-jiminny-report-expiring.blade.php\n create mode 100644 resources/views/emails/reports/report-not-generated.blade.php\n create mode 100644 tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php\n create mode 100644 tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php\n create mode 100644 tests/Unit/Events/Activities/Audio/RecordingEventTest.php\n create mode 100644 tests/Unit/Events/Activities/Softphone/EndedTest.php\n create mode 100644 tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php\n create mode 100644 tests/Unit/Events/Activities/Softphone/StartedTest.php\n create mode 100644 tests/Unit/Http/Transformers/PartnerTransformerTest.php\n create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php\n create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php\n create mode 100644 tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php\n create mode 100644 tests/Unit/Listeners/Users/SyncIntercomTest.php\n create mode 100644 tests/Unit/Mail/Reports/ReportNotGeneratedTest.php\n create mode 100644 tests/Unit/Models/PartnerTest.php\n create mode 100644 tests/Unit/Services/ActivityServiceTest.php\n create mode 100644 tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php\n create mode 100644 tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull \nremote: Enumerating objects: 628, done.\nremote: Counting objects: 100% (331/331), done.\nremote: Compressing objects: 100% (63/63), done.\nremote: Total 628 (delta 280), reused 274 (delta 266), pack-reused 297 (from 1)\nReceiving objects: 100% (628/628), 186.75 KiB | 1.23 MiB/s, done.\nResolving deltas: 100% (391/391), completed with 57 local objects.\nFrom github.com:jiminny/app\n ad2ce76737..12295204cf master -> origin/master\n 14f54b5be2..5e7646e5f9 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3\n b167b19973..acba55cf38 JY-20289-api-tests -> origin/JY-20289-api-tests\n f23cfee7c3..e5a3ec5dba JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null\n af59d60926..766efba1c5 JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import\n * [new branch] JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering\n 1737b7c528..c57e71e763 JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall\n * [new branch] JY-20671-anyvan-twilio-s3-recordings-ftech -> origin/JY-20671-anyvan-twilio-s3-recordings-ftech\n + ba181441c6...20a74137b0 JY-20742-mcp-poc -> origin/JY-20742-mcp-poc (forced update)\n * [new branch] JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue\n * [new branch] JY-20816-calendar-events-diplication -> origin/JY-20816-calendar-events-diplication\n * [new branch] desktop-app -> origin/desktop-app\n 4c4c974e46..185442c26e make-claude-great-again -> origin/make-claude-great-again\n * [new branch] mcp-tools-schemas -> origin/mcp-tools-schemas\nUpdating ad2ce76737..12295204cf\nFast-forward\n app/Component/Encoding/Job/AnalyzeTrackChannelsJob.php | 2 +-\n app/Component/Transcription/TranscriptionProcessor/AssemblyAI/Services/SubmitAudioFileService.php | 66 ++----------------------------------------------------------------\n app/Console/Commands/Tracks/CleanupActivityTracksCommand.php | 24 +++++++++++++++++-------\n tests/Unit/Console/Commands/Tracks/CleanupActivityTracksCommandTest.php | 40 +++++++++++++++++++++++++++++-----------\n tests/Unit/fixtures/assembly_ai_transcript_response.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_channel_diarization.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language_error.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language_not_ready.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language_post.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_without_utterances.json | 1 -\n 11 files changed, 49 insertions(+), 90 deletions(-)\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20818-move-AJ-reports-to-separated-datadog-metric\nSwitched to a new branch 'JY-20818-move-AJ-reports-to-separated-datadog-metric'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5663 files in 83.615 seconds, 67.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ ;xd\ndocker exec -it docker_lamp_1 bash -c \"mv /usr/local/etc/php/conf.d/xdebug.ini ~/xdebug.ini\"\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 supervisorctl restart all\njiminny-worker-processing-2:jiminny-worker-processing-2_00: stopped\njiminny-worker-processing-3:jiminny-worker-processing-3_00: stopped\njiminny-worker-processing-4:jiminny-worker-processing-4_00: stopped\njiminny-worker-processing-5:jiminny-worker-processing-5_00: stopped\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: stopped\nworker-analytics:worker-analytics_00: stopped\nworker-crm-update:worker-crm-update_00: stopped\nworker-download:worker-download_00: stopped\nworker-nudges:worker-nudges_00: stopped\nartisan-schedule:artisan-schedule_00: stopped\nworker-calendar:worker-calendar_00: stopped\nworker-crm-sync:worker-crm-sync_00: stopped\njiminny-worker-processing-1:jiminny-worker-processing-1_00: stopped\nworker:worker_00: stopped\nworker-emails:worker-emails_00: stopped\nworker-audio:worker-audio_00: stopped\nworker-conferences:worker-conferences_00: stopped\nworker-es-update:worker-es-update_00: stopped\nartisan-schedule:artisan-schedule_00: started\njiminny-worker-processing-1:jiminny-worker-processing-1_00: started\njiminny-worker-processing-2:jiminny-worker-processing-2_00: started\njiminny-worker-processing-3:jiminny-worker-processing-3_00: started\njiminny-worker-processing-4:jiminny-worker-processing-4_00: started\njiminny-worker-processing-5:jiminny-worker-processing-5_00: started\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: started\nworker:worker_00: started\nworker-analytics:worker-analytics_00: started\nworker-audio:worker-audio_00: started\nworker-calendar:worker-calendar_00: started\nworker-conferences:worker-conferences_00: started\nworker-crm-sync:worker-crm-sync_00: started\nworker-crm-update:worker-crm-update_00: started\nworker-download:worker-download_00: started\nworker-emails:worker-emails_00: started\nworker-es-update:worker-es-update_00: started\nworker-nudges:worker-nudges_00: started\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 php -v\nPHP 8.3.30 (cli) (built: Mar 16 2026 22:32:32) (NTS)\nCopyright (c) The PHP Group\nZend Engine v4.3.30, Copyright (c) Zend Technologies\n with Zend OPcache v8.3.30, Copyright (c), by Zend Technologies\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5663 files in 42.875 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ git status\nOn branch master\nYour branch is up to date with 'origin/master'.\n\nChanges not staged for commit:\n (use \"git add <file>...\" to update what will be committed)\n (use \"git restore <file>...\" to discard changes in working directory)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: .env.local\n\nUntracked files:\n (use \"git add <file>...\" to include in what will be committed)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.nikilocal\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.other\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tWEBHOOK_FILTERING_IMPLEMENTATION.md\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Crm/Hubspot/SimulateWebhooksCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Reports/CreateMockAskJiminnyReportResultCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tids.txt\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tpublic/favicon.ico\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\traw_sql_query.sql\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\ttests/Unit/Policies/CanAccessAiReportsTest.php\n\nno changes added to commit (use \"git add\" and/or \"git commit -a\")\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nremote: Enumerating objects: 15, done.\nremote: Counting objects: 100% (15/15), done.\nremote: Compressing objects: 100% (2/2), done.\nremote: Total 15 (delta 13), reused 15 (delta 13), pack-reused 0 (from 0)\nUnpacking objects: 100% (15/15), 1.28 KiB | 72.00 KiB/s, done.\nFrom github.com:jiminny/app\n c57e71e763..8743fea32e JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall\n * [new branch] JY-20819-increase-download-transctip-rate-limit -> origin/JY-20819-increase-download-transctip-rate-limit\nAlready up to date.\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull \nremote: Enumerating objects: 180, done.\nremote: Counting objects: 100% (179/179), done.\nremote: Compressing objects: 100% (55/55), done.\nremote: Total 180 (delta 127), reused 165 (delta 119), pack-reused 1 (from 1)\nReceiving objects: 100% (180/180), 57.50 KiB | 2.74 MiB/s, done.\nResolving deltas: 100% (127/127), completed with 47 local objects.\nFrom github.com:jiminny/app\n 12295204cf..35f036ace6 master -> origin/master\n * [new branch] JY-18091-upgrade-to-php-8-5 -> origin/JY-18091-upgrade-to-php-8-5\n 5f21965da8..497fbc85c2 JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering\n f029263118..6ed9e2bb13 JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue\n * [new branch] JY-20817-fix-deleting-s3-directories -> origin/JY-20817-fix-deleting-s3-directories\n * [new branch] JY-20820-es-reindex-stream-model-hydration -> origin/JY-20820-es-reindex-stream-model-hydration\n + ca92730ec5...2c8a1d0856 desktop-app -> origin/desktop-app (forced update)\n 8425d4e0de..89b45ec8b0 mcp-tools-schemas -> origin/mcp-tools-schemas\nUpdating 12295204cf..35f036ace6\nFast-forward\n app/Component/Datadog/Constants.php | 1 +\n app/Providers/RouteServiceProvider.php | 2 +-\n app/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackService.php | 13 +++++++++++++\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackServiceTest.php | 54 +++++++++++++++++++++++++++++++++++++++++++++++-------\n 4 files changed, 62 insertions(+), 8 deletions(-)\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ gbr \n* master\n JY-20818-move-AJ-reports-to-separated-datadog-metric\n JY-20773-fix-automated-reports-user-pilot-tracking\n JY-20157-AJ-report-not-send-notification\n JY-20508-notify-before-AJ-report-expiration\n JY-20372-ai-reports-promotion-pages\n JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null\n JY-20738-debug-AJ-tracking-UP\n a\n JY-18909-automated-reports-ask-jiminny\n JY-20692-fix-integration-app-token-auth-response-change\n JY-20553-debug-crm-sync-delays\n JY-20698-fix-SF-activity-types-on-new-playbook\n JY-20543-AJ-report-tracking\n JY-20384-handle-auto-sync-with-no-access-to-event-type\n JY-20458-ask-jiminny-user-definitions\n JY-19666-fix-import-contacts-account-association\n JY-19666-HS-import-contacts-and-accounts-batch-job\n JY-20458-Ask-Jiminny-Reports\n JY-20200-batch-update-CRM-objects-Salesforce\n JY-19666-HS-webhooks-add-contact-and-company\n JY-20348-trigger-setup-DI-layout-on-team-creation\n JY-20326-refactor-info-message-in-command\n JY-20317-fix-auto-log-delay-issue-on-all-channels-disabled\n JY-20312-remove-on-update-change-last-synced-at-crm-configurations\n JY-20306-SF-skip-auto-sync-for-task-based-playbook\n JY-20192-remove-deleted-team-from-saved-search-filters\n JY-20197-import-opportunity-batch-job\n JY-20293-enable-status-field-for-pipedrive-deals\n JY-20191-remove-commands-interactive-prompts\n JY-20118-change-default-sync-strategy\n JY-20183-add-cache-on-auto-log-delay\n JY-20197-add-import-opportunity-batch-job\n 20118-hs-opportunity-make-webhook-strategy-default\n JY-20118-make-default-hs-opportunity-sync-strategy-webhook-based\n JY-20196-handle-opportunity-without-note\n JY-20118-improve-opportunity-import\n JY-20189-handle-activity-search-on-deleted-groups\n JY-20160\n JY-20145-filter-out-converted-leads-when-matching\n JY-20150-skip-push-summary-on-summary-ready-if-autolog\n JY-20132-fix-note-encoding\n JY-19792-clean-logs\n JY-20117-fix-sync-profile-fields-on-empty-fields\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20725-handle-HS-search-rate-limit \nSwitched to a new branch 'JY-20725-handle-HS-search-rate-limit'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ ;xd\ndocker exec -it docker_lamp_1 bash -c \"mv /usr/local/etc/php/conf.d/xdebug.ini ~/xdebug.ini\"\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 supervisorctl restart all\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: stopped\njiminny-worker-processing-2:jiminny-worker-processing-2_00: stopped\njiminny-worker-processing-3:jiminny-worker-processing-3_00: stopped\njiminny-worker-processing-4:jiminny-worker-processing-4_00: stopped\njiminny-worker-processing-5:jiminny-worker-processing-5_00: stopped\nworker-analytics:worker-analytics_00: stopped\nworker-crm-update:worker-crm-update_00: stopped\nworker-download:worker-download_00: stopped\nworker-nudges:worker-nudges_00: stopped\nartisan-schedule:artisan-schedule_00: stopped\nworker-emails:worker-emails_00: stopped\nworker:worker_00: stopped\nworker-calendar:worker-calendar_00: stopped\njiminny-worker-processing-1:jiminny-worker-processing-1_00: stopped\nworker-crm-sync:worker-crm-sync_00: stopped\nworker-audio:worker-audio_00: stopped\nworker-conferences:worker-conferences_00: stopped\nworker-es-update:worker-es-update_00: stopped\nartisan-schedule:artisan-schedule_00: started\njiminny-worker-processing-1:jiminny-worker-processing-1_00: started\njiminny-worker-processing-2:jiminny-worker-processing-2_00: started\njiminny-worker-processing-3:jiminny-worker-processing-3_00: started\njiminny-worker-processing-4:jiminny-worker-processing-4_00: started\njiminny-worker-processing-5:jiminny-worker-processing-5_00: started\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: started\nworker:worker_00: started\nworker-analytics:worker-analytics_00: started\nworker-audio:worker-audio_00: started\nworker-calendar:worker-calendar_00: started\nworker-conferences:worker-conferences_00: started\nworker-crm-sync:worker-crm-sync_00: started\nworker-crm-update:worker-crm-update_00: started\nworker-download:worker-download_00: started\nworker-emails:worker-emails_00: started\nworker-es-update:worker-es-update_00: started\nworker-nudges:worker-nudges_00: started\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 php -v\nPHP 8.3.30 (cli) (built: Mar 16 2026 22:32:32) (NTS)\nCopyright (c) The PHP Group\nZend Engine v4.3.30, Copyright (c) Zend Technologies\n with Zend OPcache v8.3.30, Copyright (c), by Zend Technologies\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5666/5666 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n 1) app/Jobs/Crm/MatchActivityCrmData.php (ordered_class_elements)\n ---------- begin diff ----------\n--- /home/jiminny/app/Jobs/Crm/MatchActivityCrmData.php\n+++ /home/jiminny/app/Jobs/Crm/MatchActivityCrmData.php\n@@ -29,24 +29,14 @@\n use InteractsWithQueue;\n use SerializesModels;\n \n+ private const int RETRY_WINDOW_MINUTES = 120;\n+\n public int $maxExceptions = 3;\n \n- private const int RETRY_WINDOW_MINUTES = 120;\n-\n private int $activityId;\n private ?Configuration $fromConfiguration;\n private bool $remoteSearch;\n \n- public function middleware(): array\n- {\n- return [new HandleHubspotRateLimit()];\n- }\n-\n- public function retryUntil(): \\DateTimeInterface\n- {\n- return now()->addMinutes(self::RETRY_WINDOW_MINUTES);\n- }\n-\n public function __construct(\n int $activityId,\n ?Configuration $fromConfiguration = null,\n@@ -57,6 +47,16 @@\n $this->remoteSearch = $remoteSearch;\n \n $this->onQueue(Constants::QUEUE_ANALYTICS_LOW);\n+ }\n+\n+ public function middleware(): array\n+ {\n+ return [new HandleHubspotRateLimit()];\n+ }\n+\n+ public function retryUntil(): \\DateTimeInterface\n+ {\n+ return now()->addMinutes(self::RETRY_WINDOW_MINUTES);\n }\n \n public function uniqueId(): string\n\n ----------- end diff -----------\n\n 2) app/Services/Crm/Hubspot/HubspotClientInterface.php (phpdoc_order, phpdoc_separation)\n ---------- begin diff ----------\n--- /home/jiminny/app/Services/Crm/Hubspot/HubspotClientInterface.php\n+++ /home/jiminny/app/Services/Crm/Hubspot/HubspotClientInterface.php\n@@ -46,9 +46,11 @@\n *\n * @param string $objectType The object type ('deals', 'companies', 'contacts', 'calls')\n * @param array<string, mixed> $payload The search payload with filters, sorts, properties, etc.\n- * @return array The search response with 'results', 'total', 'paging' keys\n+ *\n * @throws RateLimitException When rate limit is hit\n * @throws HubspotException On API errors\n+ *\n+ * @return array The search response with 'results', 'total', 'paging' keys\n */\n public function search(string $objectType, array $payload): array;\n }\n\n ----------- end diff -----------\n\n 3) app/Services/Crm/Hubspot/Client.php (phpdoc_order, phpdoc_separation, blank_line_before_statement)\n ---------- begin diff ----------\n--- /home/jiminny/app/Services/Crm/Hubspot/Client.php\n+++ /home/jiminny/app/Services/Crm/Hubspot/Client.php\n@@ -69,10 +69,12 @@\n * the cache near expiry are not delayed longer than necessary.\n *\n * @template T\n+ *\n * @param callable(): T $apiCall The API call to execute\n- * @return T The result of the API call\n *\n * @throws RateLimitException When rate limit is hit or cached rate limit is active\n+ *\n+ * @return T The result of the API call\n */\n private function executeRequest(callable $apiCall)\n {\n@@ -81,6 +83,7 @@\n $cachedExpiresAt = Redis::get($cacheKey);\n if (is_string($cachedExpiresAt) && is_numeric($cachedExpiresAt)) {\n $remaining = max(1, (int) $cachedExpiresAt - time());\n+\n throw new RateLimitException(\n 'Hubspot rate limit (cached circuit-breaker)',\n $remaining,\n@@ -232,9 +235,11 @@\n *\n * @param string $objectType The object type ('deals', 'companies', 'contacts', 'calls')\n * @param array<string, mixed> $payload The search payload with filters, sorts, properties, etc.\n- * @return array The search response with 'results', 'total', 'paging' keys\n+ *\n * @throws RateLimitException When rate limit is hit\n * @throws HubspotException On API errors\n+ *\n+ * @return array The search response with 'results', 'total', 'paging' keys\n */\n public function search(string $objectType, array $payload): array\n {\n\n ----------- end diff -----------\n\n 4) app/Console/Commands/JiminnyDebugCommand.php (statement_indentation)\n ---------- begin diff ----------\n--- /home/jiminny/app/Console/Commands/JiminnyDebugCommand.php\n+++ /home/jiminny/app/Console/Commands/JiminnyDebugCommand.php\n@@ -359,11 +359,11 @@\n $crmService = $crmResolver->prepareCrmService();\n \n for ($i = 0 ; $i < 3; $i++) {\n-// if ($i % 25 === 0) {\n-// $this->info(\"Syncing opportunity {$i}\");\n- $this->info(\"Matching contact {$i}\");\n-// }\n-// $crmService->syncOpportunity('374720564');\n+ // if ($i % 25 === 0) {\n+ // $this->info(\"Syncing opportunity {$i}\");\n+ $this->info(\"Matching contact {$i}\");\n+ // }\n+ // $crmService->syncOpportunity('374720564');\n $crmService->matchByName('Robot');\n }\n }\n\n ----------- end diff -----------\n\n\nFixed 4 of 5666 files in 146.870 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ csfix \ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5666/5666 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5666 files in 106.192 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5666/5666 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5666 files in 66.457 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $","depth":4,"on_screen":true,"value":"Last login: Thu May 7 09:44:56 on ttys007\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ git status\nOn branch master\nYour branch is up to date with 'origin/master'.\n\nChanges not staged for commit:\n (use \"git add <file>...\" to update what will be committed)\n (use \"git restore <file>...\" to discard changes in working directory)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: .env.local\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: app/Console/Commands/JiminnyDebugCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: app/Jobs/Team/SyncToIntercom.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: app/Services/PlaybackService.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: config/logging.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: resources/views/partials/crm/push-summary/html-assembly.blade.php\n\nUntracked files:\n (use \"git add <file>...\" to include in what will be committed)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.nikilocal\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.other\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tWEBHOOK_FILTERING_IMPLEMENTATION.md\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Crm/Hubspot/SimulateWebhooksCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Reports/CreateMockAskJiminnyReportResultCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tids.txt\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tpublic/favicon.ico\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\traw_sql_query.sql\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\ttests/Unit/Policies/CanAccessAiReportsTest.php\n\nno changes added to commit (use \"git add\" and/or \"git commit -a\")\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nremote: Enumerating objects: 1482, done.\nremote: Counting objects: 100% (481/481), done.\nremote: Compressing objects: 100% (191/191), done.\nremote: Total 1482 (delta 349), reused 305 (delta 289), pack-reused 1001 (from 4)\nReceiving objects: 100% (1482/1482), 1017.97 KiB | 1.44 MiB/s, done.\nResolving deltas: 100% (877/877), completed with 96 local objects.\nFrom github.com:jiminny/app\n 83b628967a..ad2ce76737 master -> origin/master\n 1ee8cbcb7b..14f54b5be2 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3\n 5662c3b32f..b167b19973 JY-20289-api-tests -> origin/JY-20289-api-tests\n b40408cfad..f23cfee7c3 JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null\n * [new branch] JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import\n * [new branch] JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall\n * [new branch] JY-20662-remove-word-boost -> origin/JY-20662-remove-word-boost\n * [new branch] JY-20742-mcp-poc -> origin/JY-20742-mcp-poc\n * [new branch] make-claude-great-again -> origin/make-claude-great-again\n * [new branch] secfix/composer-20260507 -> origin/secfix/composer-20260507\n * [new branch] secfix/npm-20260507 -> origin/secfix/npm-20260507\nUpdating 83b628967a..ad2ce76737\nerror: Your local changes to the following files would be overwritten by merge:\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Jobs/Team/SyncToIntercom.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tresources/views/partials/crm/push-summary/html-assembly.blade.php\nPlease commit your changes or stash them before you merge.\nAborting\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nUpdating 83b628967a..ad2ce76737\nerror: Your local changes to the following files would be overwritten by merge:\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Jobs/Team/SyncToIntercom.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tresources/views/partials/crm/push-summary/html-assembly.blade.php\nPlease commit your changes or stash them before you merge.\nAborting\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nUpdating 83b628967a..ad2ce76737\nerror: Your local changes to the following files would be overwritten by merge:\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Jobs/Team/SyncToIntercom.php\nPlease commit your changes or stash them before you merge.\nAborting\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nUpdating 83b628967a..ad2ce76737\nFast-forward\n .cursor/rules/frontend-conventions.mdc | 23 ++\n .env.production-eu | 2 +-\n .env.staging | 2 +-\n Makefile | 10 +\n app/Component/ActivityAnalytics/Service/ActivityAnalyticsService.php | 6 +-\n app/Component/AiAutomation/Repositories/AiTemplateFieldsRepository.php | 32 +-\n app/Component/AiCallScoring/Repositories/AiScorecardRepository.php | 56 ++--\n app/Component/AskAnything/AskAnythingPromptService.php | 3 +\n app/Component/Transcription/Job/FinishTranscriptionJob.php | 37 ++-\n app/Component/Transcription/TranscriptionProcessor/Gong/Gong.php | 18 +-\n app/Component/Twilio/Conference/ConferenceManager/SoftPhoneManager.php | 4 +-\n app/Component/Twilio/Service/SoftPhoneService.php | 124 ++++---\n app/Component/Twilio/TwilioRepository.php | 27 ++\n app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php | 59 ----\n app/Console/Commands/Reports/AutomatedReportsCommand.php | 122 +++++--\n app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php | 200 ++++++++++++\n app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php | 60 ----\n app/Console/Commands/Users/SyncToIntercom.php | 4 +-\n app/Console/Kernel.php | 3 +-\n app/Contracts/ES/Events/UpdateMultipleEntities.php | 4 -\n app/Contracts/ES/Events/UpdateSingleEntity.php | 4 -\n app/Contracts/Repositories/TeamRepository.php | 3 +-\n app/Events/Activities/ActivityUpdated.php | 10 +-\n app/Events/Activities/Audio/RecordingEvent.php | 6 +-\n app/Events/Activities/Softphone/Ended.php | 8 +-\n app/Events/Activities/Softphone/SoftphoneEvent.php | 24 +-\n app/Events/Activities/Softphone/Started.php | 8 +-\n app/Http/Controllers/API/ActivityController.php | 17 +-\n app/Http/Controllers/API/SoftphoneController.php | 9 +-\n app/Http/Controllers/API/UserAutomatedReports/UserAutomatedReportsController.php | 19 +-\n app/Http/Controllers/API/V2/AskAnythingController.php | 2 +-\n app/Http/Controllers/Auth/SocialController.php | 6 +-\n app/Http/Controllers/Kiosk/AutomatedReportsController.php | 38 ++-\n app/Http/Controllers/Kiosk/OrganizationsController.php | 8 +-\n app/Http/Controllers/Kiosk/PartnersController.php | 46 +++\n app/Http/Controllers/Kiosk/SearchController.php | 8 +\n app/Http/Controllers/Kiosk/Teams/OnboardController.php | 24 +-\n app/Http/Controllers/Settings/Teams/IntegrationController.php | 6 +-\n app/Http/Controllers/TeamSetupController.php | 4 +-\n app/Http/Controllers/Telephony/TextMessaging/MessageController.php | 12 +-\n app/Http/Controllers/Telephony/TextMessaging/WebhookController.php | 18 +-\n app/Http/Requests/Settings/Teams/CreateTeamRequest.php | 1 +\n app/Http/Requests/Settings/Teams/EditTeamRequest.php | 1 +\n app/Http/Transformers/ActivityTransformer.php | 4 +-\n app/Http/Transformers/OnDemandActivitiesTransformer.php | 2 +-\n app/Http/Transformers/PartnerTransformer.php | 1 +\n app/Http/Transformers/StageTransformer.php | 6 +-\n app/Http/Transformers/UserTransformer.php | 11 +-\n app/Interactions/Settings/Teams/CreateTeam.php | 3 +\n app/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJob.php | 80 ++++-\n app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php | 119 +++++++\n app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php | 89 +++++\n app/Jobs/Crm/Hubspot/ImportBatchJobTrait.php | 12 +-\n app/Jobs/Crm/UpdateStage.php | 3 +\n app/Jobs/Team/SyncToIntercom.php | 7 +-\n app/Listeners/Teams/SyncIntercomCompany.php | 5 +-\n app/Listeners/Teams/UpdateSalesforceAccount.php | 8 +-\n app/Listeners/Users/SyncIntercom.php | 5 +-\n app/Mail/Reports/AskJiminnyReportExpiringMail.php | 40 +++\n app/Mail/Reports/ReportNotGenerated.php | 41 +++\n app/Models/Activity.php | 25 +-\n app/Models/Activity/Question.php | 14 +-\n app/Models/Activity/Search.php | 7 +\n app/Models/AskAnything/AskAnythingPrompt.php | 6 +\n app/Models/AutomatedReport.php | 10 +\n app/Models/CoachingFeedback.php | 44 ++-\n app/Models/ElasticSearch/ActivityElasticSearchTrait.php | 86 +----\n app/Models/ElasticSearch/OpportunityElasticSearchTrait.php | 71 ----\n app/Models/ElasticSearch/SharedDocumentDeleteTrait.php | 27 --\n app/Models/Partner.php | 13 +\n app/Models/Playlist/Activity.php | 14 +-\n app/Notifications/OwnerInvitedToTrial.php | 14 +-\n app/Policies/UserPolicy.php | 16 +-\n app/Queue/Worker/Worker.php | 3 +-\n app/Repositories/ActivityRepository.php | 13 +-\n app/Repositories/AutomatedReportsRepository.php | 42 ++-\n app/Repositories/TeamRepository.php | 21 +-\n app/Repositories/UserRepository.php | 2 +-\n app/Services/Activity/MeetingBotService.php | 8 +-\n app/Services/ActivityService.php | 111 ++-----\n app/Services/Crm/Hubspot/Service.php | 36 +-\n app/Services/Crm/Hubspot/ServiceTraits/OpportunitySyncTrait.php | 2 +-\n app/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityService.php | 5 +-\n app/Services/Kiosk/AutomatedReports/AutomatedReportsService.php | 49 +--\n app/Services/Kiosk/KioskService.php | 7 +-\n app/Services/Webhook/Triggers/AiScorecardCompletedTrigger.php | 13 +-\n app/UseCases/TeamInsights/ConversationRowMapper.php | 78 +++++\n app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php | 68 ++++\n app/UseCases/TeamInsights/StrictConsentColumnResolver.php | 45 +++\n app/UseCases/TeamInsights/TeamConversationsExport.php | 154 ++++-----\n composer.json | 1 -\n composer.lock | 95 +-----\n config/secure-headers.php | 5 +-\n database/mappings/mapping_activities.json | 16 +\n database/migrations/2026_04_14_000000_add_rockeed_partner.php | 51 +++\n database/migrations/2026_04_22_000000_add_success_email_to_partners.php | 26 ++\n database/migrations/2026_04_27_000000_add_label_to_partners.php | 28 ++\n database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php | 79 +++++\n front-end/package.json | 5 +-\n front-end/src/__mocks__/jiminny.js | 4 +-\n front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js | 9 +\n front-end/src/__mocks__/setup.js | 1 +\n front-end/src/apps/ai-reports-promo.js | 22 ++\n front-end/src/components/AiReports/AiReportsPromo.vue | 22 ++\n front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue | 190 +++++++++++\n front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue | 111 +++++++\n front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue | 103 ++++++\n front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js | 98 ++++++\n .../src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html | 283 ++++++++++++++++\n front-end/src/components/AiReports/Manage/ManageAiReports.vue | 8 +-\n front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue | 228 +++++++++++++\n front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js | 71 ++++\n .../src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html | 217 ++++++++++++\n front-end/src/components/AiReports/constants.js | 7 +\n front-end/src/components/Settings/Kiosk/OrganizationSearch/Organizations.vue | 1 +\n front-end/src/components/Settings/Kiosk/__mocks__/Jiminny.js | 1 +\n front-end/src/components/Settings/Kiosk/modals/EditTeamModal/EditTeamModal.vue | 43 ++-\n front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js | 203 ++++++++++++\n front-end/src/components/Settings/Kiosk/shared/Navigation/Navigation.vue | 3 +\n front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js | 67 ++++\n front-end/src/components/TeamInsights/CoachingFrameworks/AICallScoring/aiCallScoringOverTime.ts | 4 +-\n front-end/src/components/TeamInsights/CoachingFrameworks/UsersList.vue | 2 +-\n front-end/src/components/layout/Sidebar/HelpMenu.vue | 25 +-\n front-end/src/components/layout/Sidebar/Sidebar.vue | 27 +-\n front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js | 94 ++++++\n front-end/src/components/layout/Sidebar/__tests__/__snapshots__/Sidebar.spec.js.snap | 4 +-\n front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js | 204 ++++++++++++\n front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js | 49 +++\n front-end/src/main.js | 1 +\n front-end/src/store/modules/TeamInsights/util.js | 1 +\n front-end/src/store/modules/platform/__tests__/getters.spec.js | 22 ++\n front-end/src/store/modules/platform/getters.js | 3 +\n front-end/src/utils/index.js | 11 +\n front-end/yarn.lock | 21 +-\n phpstan-baseline.neon | 60 ----\n public/pdf/exec-reports/com/coaching-profiles.pdf | Bin 0 -> 1531178 bytes\n public/pdf/exec-reports/com/exec-summary.pdf | Bin 0 -> 2237381 bytes\n public/pdf/exec-reports/com/loss-report.pdf | Bin 0 -> 1955343 bytes\n public/pdf/exec-reports/com/product-feedback.pdf | Bin 0 -> 2184417 bytes\n public/pdf/exec-reports/eu/coaching-profiles.pdf | Bin 0 -> 1528704 bytes\n public/pdf/exec-reports/eu/exec-summary.pdf | Bin 0 -> 2296741 bytes\n public/pdf/exec-reports/eu/loss-report.pdf | Bin 0 -> 1955808 bytes\n public/pdf/exec-reports/eu/product-feedback.pdf | Bin 0 -> 2184083 bytes\n resources/views/emails/reports/ask-jiminny-report-expiring.blade.php | 22 ++\n resources/views/emails/reports/report-not-generated.blade.php | 24 ++\n resources/views/partials/crm/push-summary/html-assembly.blade.php | 2 +-\n routes/api.php | 6 +\n routes/web.php | 4 +\n tests/Feature/Policies/UserPolicyTest.php | 90 ++++-\n tests/Unit/Component/ActivityAnalytics/Service/ActivityAnalyticsServiceTest.php | 40 +++\n tests/Unit/Component/AskAnything/AskAnythingPromptServiceTest.php | 26 ++\n tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php | 276 ++++++++++++++++\n tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php | 375 +++++++++++++++++++++\n tests/Unit/Component/Twilio/Service/SoftPhoneServiceTest.php | 1014 +++++++++++++++++++++++++++++++++++++++++++++++++++++++--\n tests/Unit/Console/Commands/Reports/AutomatedReportsCommandTest.php | 157 ++++++++-\n tests/Unit/Events/Activities/Audio/RecordingEventTest.php | 72 ++++\n tests/Unit/Events/Activities/Softphone/EndedTest.php | 86 +++++\n tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php | 88 +++++\n tests/Unit/Events/Activities/Softphone/StartedTest.php | 86 +++++\n tests/Unit/Http/Controllers/Kiosk/AutomatedReportsControllerTest.php | 99 ++++++\n tests/Unit/Http/Transformers/ActivityTransformerTest.php | 5 +-\n tests/Unit/Http/Transformers/PartnerTransformerTest.php | 34 ++\n tests/Unit/Interactions/Settings/Teams/CreateTeamTest.php | 49 +++\n tests/Unit/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJobTest.php | 106 +++++-\n tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php | 205 ++++++++++++\n tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php | 188 +++++++++++\n tests/Unit/Jobs/Crm/ImportOpportunityBatchTest.php | 2 +-\n tests/Unit/Jobs/Team/SyncToIntercomTest.php | 6 +\n tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php | 59 ++++\n tests/Unit/Listeners/Teams/UpdateSalesforceAccountTest.php | 11 +-\n tests/Unit/Listeners/Users/SyncIntercomTest.php | 59 ++++\n tests/Unit/Mail/Reports/ReportNotGeneratedTest.php | 166 ++++++++++\n tests/Unit/Models/PartnerTest.php | 28 ++\n tests/Unit/Repositories/AutomatedReportsRepositoryTest.php | 68 ++++\n tests/Unit/Services/Activity/MeetingBotServiceRequestRecordingToStopTest.php | 14 +-\n tests/Unit/Services/ActivityServiceTest.php | 391 ++++++++++++++++++++++\n tests/Unit/Services/Crm/Hubspot/ServiceResponseNormalizeTest.php | 68 ++--\n tests/Unit/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityServiceTest.php | 48 +--\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceActivitiesCountTest.php | 16 +-\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceReportGenerationTest.php | 24 +-\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceTest.php | 130 ++++++++\n tests/Unit/Services/KioskServiceTest.php | 8 +\n tests/Unit/Services/Webhook/Triggers/AiScorecardCompletedTriggerTest.php | 6 +-\n tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php | 119 +++++++\n tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php | 108 ++++++\n tests/Unit/UseCases/TeamInsights/TeamConversationsExportTest.php | 342 ++++++++++++++-----\n 186 files changed, 8538 insertions(+), 1233 deletions(-)\n create mode 100644 app/Component/Twilio/TwilioRepository.php\n delete mode 100644 app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php\n create mode 100644 app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php\n delete mode 100644 app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php\n create mode 100644 app/Http/Controllers/Kiosk/PartnersController.php\n create mode 100644 app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php\n create mode 100644 app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php\n create mode 100644 app/Mail/Reports/AskJiminnyReportExpiringMail.php\n create mode 100644 app/Mail/Reports/ReportNotGenerated.php\n delete mode 100644 app/Models/ElasticSearch/SharedDocumentDeleteTrait.php\n create mode 100644 app/UseCases/TeamInsights/ConversationRowMapper.php\n create mode 100644 app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php\n create mode 100644 app/UseCases/TeamInsights/StrictConsentColumnResolver.php\n create mode 100644 database/migrations/2026_04_14_000000_add_rockeed_partner.php\n create mode 100644 database/migrations/2026_04_22_000000_add_success_email_to_partners.php\n create mode 100644 database/migrations/2026_04_27_000000_add_label_to_partners.php\n create mode 100644 database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php\n create mode 100644 front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js\n create mode 100644 front-end/src/apps/ai-reports-promo.js\n create mode 100644 front-end/src/components/AiReports/AiReportsPromo.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html\n create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue\n create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js\n create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html\n create mode 100644 front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js\n create mode 100644 front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js\n create mode 100644 front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js\n create mode 100644 front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js\n create mode 100644 front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js\n create mode 100644 front-end/src/store/modules/platform/__tests__/getters.spec.js\n create mode 100644 public/pdf/exec-reports/com/coaching-profiles.pdf\n create mode 100644 public/pdf/exec-reports/com/exec-summary.pdf\n create mode 100644 public/pdf/exec-reports/com/loss-report.pdf\n create mode 100644 public/pdf/exec-reports/com/product-feedback.pdf\n create mode 100644 public/pdf/exec-reports/eu/coaching-profiles.pdf\n create mode 100644 public/pdf/exec-reports/eu/exec-summary.pdf\n create mode 100644 public/pdf/exec-reports/eu/loss-report.pdf\n create mode 100644 public/pdf/exec-reports/eu/product-feedback.pdf\n create mode 100644 resources/views/emails/reports/ask-jiminny-report-expiring.blade.php\n create mode 100644 resources/views/emails/reports/report-not-generated.blade.php\n create mode 100644 tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php\n create mode 100644 tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php\n create mode 100644 tests/Unit/Events/Activities/Audio/RecordingEventTest.php\n create mode 100644 tests/Unit/Events/Activities/Softphone/EndedTest.php\n create mode 100644 tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php\n create mode 100644 tests/Unit/Events/Activities/Softphone/StartedTest.php\n create mode 100644 tests/Unit/Http/Transformers/PartnerTransformerTest.php\n create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php\n create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php\n create mode 100644 tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php\n create mode 100644 tests/Unit/Listeners/Users/SyncIntercomTest.php\n create mode 100644 tests/Unit/Mail/Reports/ReportNotGeneratedTest.php\n create mode 100644 tests/Unit/Models/PartnerTest.php\n create mode 100644 tests/Unit/Services/ActivityServiceTest.php\n create mode 100644 tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php\n create mode 100644 tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull \nremote: Enumerating objects: 628, done.\nremote: Counting objects: 100% (331/331), done.\nremote: Compressing objects: 100% (63/63), done.\nremote: Total 628 (delta 280), reused 274 (delta 266), pack-reused 297 (from 1)\nReceiving objects: 100% (628/628), 186.75 KiB | 1.23 MiB/s, done.\nResolving deltas: 100% (391/391), completed with 57 local objects.\nFrom github.com:jiminny/app\n ad2ce76737..12295204cf master -> origin/master\n 14f54b5be2..5e7646e5f9 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3\n b167b19973..acba55cf38 JY-20289-api-tests -> origin/JY-20289-api-tests\n f23cfee7c3..e5a3ec5dba JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null\n af59d60926..766efba1c5 JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import\n * [new branch] JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering\n 1737b7c528..c57e71e763 JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall\n * [new branch] JY-20671-anyvan-twilio-s3-recordings-ftech -> origin/JY-20671-anyvan-twilio-s3-recordings-ftech\n + ba181441c6...20a74137b0 JY-20742-mcp-poc -> origin/JY-20742-mcp-poc (forced update)\n * [new branch] JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue\n * [new branch] JY-20816-calendar-events-diplication -> origin/JY-20816-calendar-events-diplication\n * [new branch] desktop-app -> origin/desktop-app\n 4c4c974e46..185442c26e make-claude-great-again -> origin/make-claude-great-again\n * [new branch] mcp-tools-schemas -> origin/mcp-tools-schemas\nUpdating ad2ce76737..12295204cf\nFast-forward\n app/Component/Encoding/Job/AnalyzeTrackChannelsJob.php | 2 +-\n app/Component/Transcription/TranscriptionProcessor/AssemblyAI/Services/SubmitAudioFileService.php | 66 ++----------------------------------------------------------------\n app/Console/Commands/Tracks/CleanupActivityTracksCommand.php | 24 +++++++++++++++++-------\n tests/Unit/Console/Commands/Tracks/CleanupActivityTracksCommandTest.php | 40 +++++++++++++++++++++++++++++-----------\n tests/Unit/fixtures/assembly_ai_transcript_response.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_channel_diarization.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language_error.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language_not_ready.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language_post.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_without_utterances.json | 1 -\n 11 files changed, 49 insertions(+), 90 deletions(-)\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20818-move-AJ-reports-to-separated-datadog-metric\nSwitched to a new branch 'JY-20818-move-AJ-reports-to-separated-datadog-metric'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5663 files in 83.615 seconds, 67.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ ;xd\ndocker exec -it docker_lamp_1 bash -c \"mv /usr/local/etc/php/conf.d/xdebug.ini ~/xdebug.ini\"\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 supervisorctl restart all\njiminny-worker-processing-2:jiminny-worker-processing-2_00: stopped\njiminny-worker-processing-3:jiminny-worker-processing-3_00: stopped\njiminny-worker-processing-4:jiminny-worker-processing-4_00: stopped\njiminny-worker-processing-5:jiminny-worker-processing-5_00: stopped\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: stopped\nworker-analytics:worker-analytics_00: stopped\nworker-crm-update:worker-crm-update_00: stopped\nworker-download:worker-download_00: stopped\nworker-nudges:worker-nudges_00: stopped\nartisan-schedule:artisan-schedule_00: stopped\nworker-calendar:worker-calendar_00: stopped\nworker-crm-sync:worker-crm-sync_00: stopped\njiminny-worker-processing-1:jiminny-worker-processing-1_00: stopped\nworker:worker_00: stopped\nworker-emails:worker-emails_00: stopped\nworker-audio:worker-audio_00: stopped\nworker-conferences:worker-conferences_00: stopped\nworker-es-update:worker-es-update_00: stopped\nartisan-schedule:artisan-schedule_00: started\njiminny-worker-processing-1:jiminny-worker-processing-1_00: started\njiminny-worker-processing-2:jiminny-worker-processing-2_00: started\njiminny-worker-processing-3:jiminny-worker-processing-3_00: started\njiminny-worker-processing-4:jiminny-worker-processing-4_00: started\njiminny-worker-processing-5:jiminny-worker-processing-5_00: started\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: started\nworker:worker_00: started\nworker-analytics:worker-analytics_00: started\nworker-audio:worker-audio_00: started\nworker-calendar:worker-calendar_00: started\nworker-conferences:worker-conferences_00: started\nworker-crm-sync:worker-crm-sync_00: started\nworker-crm-update:worker-crm-update_00: started\nworker-download:worker-download_00: started\nworker-emails:worker-emails_00: started\nworker-es-update:worker-es-update_00: started\nworker-nudges:worker-nudges_00: started\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 php -v\nPHP 8.3.30 (cli) (built: Mar 16 2026 22:32:32) (NTS)\nCopyright (c) The PHP Group\nZend Engine v4.3.30, Copyright (c) Zend Technologies\n with Zend OPcache v8.3.30, Copyright (c), by Zend Technologies\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5663 files in 42.875 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ git status\nOn branch master\nYour branch is up to date with 'origin/master'.\n\nChanges not staged for commit:\n (use \"git add <file>...\" to update what will be committed)\n (use \"git restore <file>...\" to discard changes in working directory)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: .env.local\n\nUntracked files:\n (use \"git add <file>...\" to include in what will be committed)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.nikilocal\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.other\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tWEBHOOK_FILTERING_IMPLEMENTATION.md\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Crm/Hubspot/SimulateWebhooksCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Reports/CreateMockAskJiminnyReportResultCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tids.txt\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tpublic/favicon.ico\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\traw_sql_query.sql\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\ttests/Unit/Policies/CanAccessAiReportsTest.php\n\nno changes added to commit (use \"git add\" and/or \"git commit -a\")\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nremote: Enumerating objects: 15, done.\nremote: Counting objects: 100% (15/15), done.\nremote: Compressing objects: 100% (2/2), done.\nremote: Total 15 (delta 13), reused 15 (delta 13), pack-reused 0 (from 0)\nUnpacking objects: 100% (15/15), 1.28 KiB | 72.00 KiB/s, done.\nFrom github.com:jiminny/app\n c57e71e763..8743fea32e JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall\n * [new branch] JY-20819-increase-download-transctip-rate-limit -> origin/JY-20819-increase-download-transctip-rate-limit\nAlready up to date.\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull \nremote: Enumerating objects: 180, done.\nremote: Counting objects: 100% (179/179), done.\nremote: Compressing objects: 100% (55/55), done.\nremote: Total 180 (delta 127), reused 165 (delta 119), pack-reused 1 (from 1)\nReceiving objects: 100% (180/180), 57.50 KiB | 2.74 MiB/s, done.\nResolving deltas: 100% (127/127), completed with 47 local objects.\nFrom github.com:jiminny/app\n 12295204cf..35f036ace6 master -> origin/master\n * [new branch] JY-18091-upgrade-to-php-8-5 -> origin/JY-18091-upgrade-to-php-8-5\n 5f21965da8..497fbc85c2 JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering\n f029263118..6ed9e2bb13 JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue\n * [new branch] JY-20817-fix-deleting-s3-directories -> origin/JY-20817-fix-deleting-s3-directories\n * [new branch] JY-20820-es-reindex-stream-model-hydration -> origin/JY-20820-es-reindex-stream-model-hydration\n + ca92730ec5...2c8a1d0856 desktop-app -> origin/desktop-app (forced update)\n 8425d4e0de..89b45ec8b0 mcp-tools-schemas -> origin/mcp-tools-schemas\nUpdating 12295204cf..35f036ace6\nFast-forward\n app/Component/Datadog/Constants.php | 1 +\n app/Providers/RouteServiceProvider.php | 2 +-\n app/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackService.php | 13 +++++++++++++\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackServiceTest.php | 54 +++++++++++++++++++++++++++++++++++++++++++++++-------\n 4 files changed, 62 insertions(+), 8 deletions(-)\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ gbr \n* master\n JY-20818-move-AJ-reports-to-separated-datadog-metric\n JY-20773-fix-automated-reports-user-pilot-tracking\n JY-20157-AJ-report-not-send-notification\n JY-20508-notify-before-AJ-report-expiration\n JY-20372-ai-reports-promotion-pages\n JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null\n JY-20738-debug-AJ-tracking-UP\n a\n JY-18909-automated-reports-ask-jiminny\n JY-20692-fix-integration-app-token-auth-response-change\n JY-20553-debug-crm-sync-delays\n JY-20698-fix-SF-activity-types-on-new-playbook\n JY-20543-AJ-report-tracking\n JY-20384-handle-auto-sync-with-no-access-to-event-type\n JY-20458-ask-jiminny-user-definitions\n JY-19666-fix-import-contacts-account-association\n JY-19666-HS-import-contacts-and-accounts-batch-job\n JY-20458-Ask-Jiminny-Reports\n JY-20200-batch-update-CRM-objects-Salesforce\n JY-19666-HS-webhooks-add-contact-and-company\n JY-20348-trigger-setup-DI-layout-on-team-creation\n JY-20326-refactor-info-message-in-command\n JY-20317-fix-auto-log-delay-issue-on-all-channels-disabled\n JY-20312-remove-on-update-change-last-synced-at-crm-configurations\n JY-20306-SF-skip-auto-sync-for-task-based-playbook\n JY-20192-remove-deleted-team-from-saved-search-filters\n JY-20197-import-opportunity-batch-job\n JY-20293-enable-status-field-for-pipedrive-deals\n JY-20191-remove-commands-interactive-prompts\n JY-20118-change-default-sync-strategy\n JY-20183-add-cache-on-auto-log-delay\n JY-20197-add-import-opportunity-batch-job\n 20118-hs-opportunity-make-webhook-strategy-default\n JY-20118-make-default-hs-opportunity-sync-strategy-webhook-based\n JY-20196-handle-opportunity-without-note\n JY-20118-improve-opportunity-import\n JY-20189-handle-activity-search-on-deleted-groups\n JY-20160\n JY-20145-filter-out-converted-leads-when-matching\n JY-20150-skip-push-summary-on-summary-ready-if-autolog\n JY-20132-fix-note-encoding\n JY-19792-clean-logs\n JY-20117-fix-sync-profile-fields-on-empty-fields\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20725-handle-HS-search-rate-limit \nSwitched to a new branch 'JY-20725-handle-HS-search-rate-limit'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ ;xd\ndocker exec -it docker_lamp_1 bash -c \"mv /usr/local/etc/php/conf.d/xdebug.ini ~/xdebug.ini\"\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 supervisorctl restart all\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: stopped\njiminny-worker-processing-2:jiminny-worker-processing-2_00: stopped\njiminny-worker-processing-3:jiminny-worker-processing-3_00: stopped\njiminny-worker-processing-4:jiminny-worker-processing-4_00: stopped\njiminny-worker-processing-5:jiminny-worker-processing-5_00: stopped\nworker-analytics:worker-analytics_00: stopped\nworker-crm-update:worker-crm-update_00: stopped\nworker-download:worker-download_00: stopped\nworker-nudges:worker-nudges_00: stopped\nartisan-schedule:artisan-schedule_00: stopped\nworker-emails:worker-emails_00: stopped\nworker:worker_00: stopped\nworker-calendar:worker-calendar_00: stopped\njiminny-worker-processing-1:jiminny-worker-processing-1_00: stopped\nworker-crm-sync:worker-crm-sync_00: stopped\nworker-audio:worker-audio_00: stopped\nworker-conferences:worker-conferences_00: stopped\nworker-es-update:worker-es-update_00: stopped\nartisan-schedule:artisan-schedule_00: started\njiminny-worker-processing-1:jiminny-worker-processing-1_00: started\njiminny-worker-processing-2:jiminny-worker-processing-2_00: started\njiminny-worker-processing-3:jiminny-worker-processing-3_00: started\njiminny-worker-processing-4:jiminny-worker-processing-4_00: started\njiminny-worker-processing-5:jiminny-worker-processing-5_00: started\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: started\nworker:worker_00: started\nworker-analytics:worker-analytics_00: started\nworker-audio:worker-audio_00: started\nworker-calendar:worker-calendar_00: started\nworker-conferences:worker-conferences_00: started\nworker-crm-sync:worker-crm-sync_00: started\nworker-crm-update:worker-crm-update_00: started\nworker-download:worker-download_00: started\nworker-emails:worker-emails_00: started\nworker-es-update:worker-es-update_00: started\nworker-nudges:worker-nudges_00: started\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 php -v\nPHP 8.3.30 (cli) (built: Mar 16 2026 22:32:32) (NTS)\nCopyright (c) The PHP Group\nZend Engine v4.3.30, Copyright (c) Zend Technologies\n with Zend OPcache v8.3.30, Copyright (c), by Zend Technologies\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5666/5666 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n 1) app/Jobs/Crm/MatchActivityCrmData.php (ordered_class_elements)\n ---------- begin diff ----------\n--- /home/jiminny/app/Jobs/Crm/MatchActivityCrmData.php\n+++ /home/jiminny/app/Jobs/Crm/MatchActivityCrmData.php\n@@ -29,24 +29,14 @@\n use InteractsWithQueue;\n use SerializesModels;\n \n+ private const int RETRY_WINDOW_MINUTES = 120;\n+\n public int $maxExceptions = 3;\n \n- private const int RETRY_WINDOW_MINUTES = 120;\n-\n private int $activityId;\n private ?Configuration $fromConfiguration;\n private bool $remoteSearch;\n \n- public function middleware(): array\n- {\n- return [new HandleHubspotRateLimit()];\n- }\n-\n- public function retryUntil(): \\DateTimeInterface\n- {\n- return now()->addMinutes(self::RETRY_WINDOW_MINUTES);\n- }\n-\n public function __construct(\n int $activityId,\n ?Configuration $fromConfiguration = null,\n@@ -57,6 +47,16 @@\n $this->remoteSearch = $remoteSearch;\n \n $this->onQueue(Constants::QUEUE_ANALYTICS_LOW);\n+ }\n+\n+ public function middleware(): array\n+ {\n+ return [new HandleHubspotRateLimit()];\n+ }\n+\n+ public function retryUntil(): \\DateTimeInterface\n+ {\n+ return now()->addMinutes(self::RETRY_WINDOW_MINUTES);\n }\n \n public function uniqueId(): string\n\n ----------- end diff -----------\n\n 2) app/Services/Crm/Hubspot/HubspotClientInterface.php (phpdoc_order, phpdoc_separation)\n ---------- begin diff ----------\n--- /home/jiminny/app/Services/Crm/Hubspot/HubspotClientInterface.php\n+++ /home/jiminny/app/Services/Crm/Hubspot/HubspotClientInterface.php\n@@ -46,9 +46,11 @@\n *\n * @param string $objectType The object type ('deals', 'companies', 'contacts', 'calls')\n * @param array<string, mixed> $payload The search payload with filters, sorts, properties, etc.\n- * @return array The search response with 'results', 'total', 'paging' keys\n+ *\n * @throws RateLimitException When rate limit is hit\n * @throws HubspotException On API errors\n+ *\n+ * @return array The search response with 'results', 'total', 'paging' keys\n */\n public function search(string $objectType, array $payload): array;\n }\n\n ----------- end diff -----------\n\n 3) app/Services/Crm/Hubspot/Client.php (phpdoc_order, phpdoc_separation, blank_line_before_statement)\n ---------- begin diff ----------\n--- /home/jiminny/app/Services/Crm/Hubspot/Client.php\n+++ /home/jiminny/app/Services/Crm/Hubspot/Client.php\n@@ -69,10 +69,12 @@\n * the cache near expiry are not delayed longer than necessary.\n *\n * @template T\n+ *\n * @param callable(): T $apiCall The API call to execute\n- * @return T The result of the API call\n *\n * @throws RateLimitException When rate limit is hit or cached rate limit is active\n+ *\n+ * @return T The result of the API call\n */\n private function executeRequest(callable $apiCall)\n {\n@@ -81,6 +83,7 @@\n $cachedExpiresAt = Redis::get($cacheKey);\n if (is_string($cachedExpiresAt) && is_numeric($cachedExpiresAt)) {\n $remaining = max(1, (int) $cachedExpiresAt - time());\n+\n throw new RateLimitException(\n 'Hubspot rate limit (cached circuit-breaker)',\n $remaining,\n@@ -232,9 +235,11 @@\n *\n * @param string $objectType The object type ('deals', 'companies', 'contacts', 'calls')\n * @param array<string, mixed> $payload The search payload with filters, sorts, properties, etc.\n- * @return array The search response with 'results', 'total', 'paging' keys\n+ *\n * @throws RateLimitException When rate limit is hit\n * @throws HubspotException On API errors\n+ *\n+ * @return array The search response with 'results', 'total', 'paging' keys\n */\n public function search(string $objectType, array $payload): array\n {\n\n ----------- end diff -----------\n\n 4) app/Console/Commands/JiminnyDebugCommand.php (statement_indentation)\n ---------- begin diff ----------\n--- /home/jiminny/app/Console/Commands/JiminnyDebugCommand.php\n+++ /home/jiminny/app/Console/Commands/JiminnyDebugCommand.php\n@@ -359,11 +359,11 @@\n $crmService = $crmResolver->prepareCrmService();\n \n for ($i = 0 ; $i < 3; $i++) {\n-// if ($i % 25 === 0) {\n-// $this->info(\"Syncing opportunity {$i}\");\n- $this->info(\"Matching contact {$i}\");\n-// }\n-// $crmService->syncOpportunity('374720564');\n+ // if ($i % 25 === 0) {\n+ // $this->info(\"Syncing opportunity {$i}\");\n+ $this->info(\"Matching contact {$i}\");\n+ // }\n+ // $crmService->syncOpportunity('374720564');\n $crmService->matchByName('Robot');\n }\n }\n\n ----------- end diff -----------\n\n\nFixed 4 of 5666 files in 146.870 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ csfix \ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5666/5666 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5666 files in 106.192 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5666/5666 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5666 files in 66.457 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $","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":"APP (-zsh)","depth":1,"bounds":{"left":0.4973404,"top":1.0,"width":0.024601065,"height":-0.02394259},"on_screen":true,"role_description":"text"}]...
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accessibility
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Last login: Thu May 7 09:44:56 on ttys007
Poetry Last login: Thu May 7 09:44:56 on ttys007
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ git status
On branch master
Your branch is up to date with 'origin/master'.
Changes not staged for commit:
(use "git add <file>..." to update what will be committed)
(use "git restore <file>..." to discard changes in working directory)
modified: .env.local
modified: app/Console/Commands/JiminnyDebugCommand.php
modified: app/Jobs/Team/SyncToIntercom.php
modified: app/Services/PlaybackService.php
modified: config/logging.php
modified: resources/views/partials/crm/push-summary/html-assembly.blade.php
Untracked files:
(use "git add <file>..." to include in what will be committed)
.env.nikilocal
.env.other
WEBHOOK_FILTERING_IMPLEMENTATION.md
app/Console/Commands/Crm/Hubspot/SimulateWebhooksCommand.php
app/Console/Commands/Reports/CreateMockAskJiminnyReportResultCommand.php
ids.txt
public/favicon.ico
raw_sql_query.sql
tests/Unit/Policies/CanAccessAiReportsTest.php
no changes added to commit (use "git add" and/or "git commit -a")
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 1482, done.
remote: Counting objects: 100% (481/481), done.
remote: Compressing objects: 100% (191/191), done.
remote: Total 1482 (delta 349), reused 305 (delta 289), pack-reused 1001 (from 4)
Receiving objects: 100% (1482/1482), 1017.97 KiB | 1.44 MiB/s, done.
Resolving deltas: 100% (877/877), completed with 96 local objects.
From github.com:jiminny/app
83b628967a..ad2ce76737 master -> origin/master
1ee8cbcb7b..14f54b5be2 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3
5662c3b32f..b167b19973 JY-20289-api-tests -> origin/JY-20289-api-tests
b40408cfad..f23cfee7c3 JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null
* [new branch] JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import
* [new branch] JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall
* [new branch] JY-20662-remove-word-boost -> origin/JY-20662-remove-word-boost
* [new branch] JY-20742-mcp-poc -> origin/JY-20742-mcp-poc
* [new branch] make-claude-great-again -> origin/make-claude-great-again
* [new branch] secfix/composer-20260507 -> origin/secfix/composer-20260507
* [new branch] secfix/npm-20260507 -> origin/secfix/npm-20260507
Updating 83b628967a..ad2ce76737
error: Your local changes to the following files would be overwritten by merge:
app/Jobs/Team/SyncToIntercom.php
resources/views/partials/crm/push-summary/html-assembly.blade.php
Please commit your changes or stash them before you merge.
Aborting
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
Updating 83b628967a..ad2ce76737
error: Your local changes to the following files would be overwritten by merge:
app/Jobs/Team/SyncToIntercom.php
resources/views/partials/crm/push-summary/html-assembly.blade.php
Please commit your changes or stash them before you merge.
Aborting
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
Updating 83b628967a..ad2ce76737
error: Your local changes to the following files would be overwritten by merge:
app/Jobs/Team/SyncToIntercom.php
Please commit your changes or stash them before you merge.
Aborting
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
Updating 83b628967a..ad2ce76737
Fast-forward
.cursor/rules/frontend-conventions.mdc | 23 ++
.env.production-eu | 2 +-
.env.staging | 2 +-
Makefile | 10 +
app/Component/ActivityAnalytics/Service/ActivityAnalyticsService.php | 6 +-
app/Component/AiAutomation/Repositories/AiTemplateFieldsRepository.php | 32 +-
app/Component/AiCallScoring/Repositories/AiScorecardRepository.php | 56 ++--
app/Component/AskAnything/AskAnythingPromptService.php | 3 +
app/Component/Transcription/Job/FinishTranscriptionJob.php | 37 ++-
app/Component/Transcription/TranscriptionProcessor/Gong/Gong.php | 18 +-
app/Component/Twilio/Conference/ConferenceManager/SoftPhoneManager.php | 4 +-
app/Component/Twilio/Service/SoftPhoneService.php | 124 ++++---
app/Component/Twilio/TwilioRepository.php | 27 ++
app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php | 59 ----
app/Console/Commands/Reports/AutomatedReportsCommand.php | 122 +++++--
app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php | 200 ++++++++++++
app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php | 60 ----
app/Console/Commands/Users/SyncToIntercom.php | 4 +-
app/Console/Kernel.php | 3 +-
app/Contracts/ES/Events/UpdateMultipleEntities.php | 4 -
app/Contracts/ES/Events/UpdateSingleEntity.php | 4 -
app/Contracts/Repositories/TeamRepository.php | 3 +-
app/Events/Activities/ActivityUpdated.php | 10 +-
app/Events/Activities/Audio/RecordingEvent.php | 6 +-
app/Events/Activities/Softphone/Ended.php | 8 +-
app/Events/Activities/Softphone/SoftphoneEvent.php | 24 +-
app/Events/Activities/Softphone/Started.php | 8 +-
app/Http/Controllers/API/ActivityController.php | 17 +-
app/Http/Controllers/API/SoftphoneController.php | 9 +-
app/Http/Controllers/API/UserAutomatedReports/UserAutomatedReportsController.php | 19 +-
app/Http/Controllers/API/V2/AskAnythingController.php | 2 +-
app/Http/Controllers/Auth/SocialController.php | 6 +-
app/Http/Controllers/Kiosk/AutomatedReportsController.php | 38 ++-
app/Http/Controllers/Kiosk/OrganizationsController.php | 8 +-
app/Http/Controllers/Kiosk/PartnersController.php | 46 +++
app/Http/Controllers/Kiosk/SearchController.php | 8 +
app/Http/Controllers/Kiosk/Teams/OnboardController.php | 24 +-
app/Http/Controllers/Settings/Teams/IntegrationController.php | 6 +-
app/Http/Controllers/TeamSetupController.php | 4 +-
app/Http/Controllers/Telephony/TextMessaging/MessageController.php | 12 +-
app/Http/Controllers/Telephony/TextMessaging/WebhookController.php | 18 +-
app/Http/Requests/Settings/Teams/CreateTeamRequest.php | 1 +
app/Http/Requests/Settings/Teams/EditTeamRequest.php | 1 +
app/Http/Transformers/ActivityTransformer.php | 4 +-
app/Http/Transformers/OnDemandActivitiesTransformer.php | 2 +-
app/Http/Transformers/PartnerTransformer.php | 1 +
app/Http/Transformers/StageTransformer.php | 6 +-
app/Http/Transformers/UserTransformer.php | 11 +-
app/Interactions/Settings/Teams/CreateTeam.php | 3 +
app/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJob.php | 80 ++++-
app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php | 119 +++++++
app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php | 89 +++++
app/Jobs/Crm/Hubspot/ImportBatchJobTrait.php | 12 +-
app/Jobs/Crm/UpdateStage.php | 3 +
app/Jobs/Team/SyncToIntercom.php | 7 +-
app/Listeners/Teams/SyncIntercomCompany.php | 5 +-
app/Listeners/Teams/UpdateSalesforceAccount.php | 8 +-
app/Listeners/Users/SyncIntercom.php | 5 +-
app/Mail/Reports/AskJiminnyReportExpiringMail.php | 40 +++
app/Mail/Reports/ReportNotGenerated.php | 41 +++
app/Models/Activity.php | 25 +-
app/Models/Activity/Question.php | 14 +-
app/Models/Activity/Search.php | 7 +
app/Models/AskAnything/AskAnythingPrompt.php | 6 +
app/Models/AutomatedReport.php | 10 +
app/Models/CoachingFeedback.php | 44 ++-
app/Models/ElasticSearch/ActivityElasticSearchTrait.php | 86 +----
app/Models/ElasticSearch/OpportunityElasticSearchTrait.php | 71 ----
app/Models/ElasticSearch/SharedDocumentDeleteTrait.php | 27 --
app/Models/Partner.php | 13 +
app/Models/Playlist/Activity.php | 14 +-
app/Notifications/OwnerInvitedToTrial.php | 14 +-
app/Policies/UserPolicy.php | 16 +-
app/Queue/Worker/Worker.php | 3 +-
app/Repositories/ActivityRepository.php | 13 +-
app/Repositories/AutomatedReportsRepository.php | 42 ++-
app/Repositories/TeamRepository.php | 21 +-
app/Repositories/UserRepository.php | 2 +-
app/Services/Activity/MeetingBotService.php | 8 +-
app/Services/ActivityService.php | 111 ++-----
app/Services/Crm/Hubspot/Service.php | 36 +-
app/Services/Crm/Hubspot/ServiceTraits/OpportunitySyncTrait.php | 2 +-
app/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityService.php | 5 +-
app/Services/Kiosk/AutomatedReports/AutomatedReportsService.php | 49 +--
app/Services/Kiosk/KioskService.php | 7 +-
app/Services/Webhook/Triggers/AiScorecardCompletedTrigger.php | 13 +-
app/UseCases/TeamInsights/ConversationRowMapper.php | 78 +++++
app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php | 68 ++++
app/UseCases/TeamInsights/StrictConsentColumnResolver.php | 45 +++
app/UseCases/TeamInsights/TeamConversationsExport.php | 154 ++++-----
composer.json | 1 -
composer.lock | 95 +-----
config/secure-headers.php | 5 +-
database/mappings/mapping_activities.json | 16 +
database/migrations/2026_04_14_000000_add_rockeed_partner.php | 51 +++
database/migrations/2026_04_22_000000_add_success_email_to_partners.php | 26 ++
database/migrations/2026_04_27_000000_add_label_to_partners.php | 28 ++
database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php | 79 +++++
front-end/package.json | 5 +-
front-end/src/__mocks__/jiminny.js | 4 +-
front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js | 9 +
front-end/src/__mocks__/setup.js | 1 +
front-end/src/apps/ai-reports-promo.js | 22 ++
front-end/src/components/AiReports/AiReportsPromo.vue | 22 ++
front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue | 190 +++++++++++
front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue | 111 +++++++
front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue | 103 ++++++
front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js | 98 ++++++
.../src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html | 283 ++++++++++++++++
front-end/src/components/AiReports/Manage/ManageAiReports.vue | 8 +-
front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue | 228 +++++++++++++
front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js | 71 ++++
.../src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html | 217 ++++++++++++
front-end/src/components/AiReports/constants.js | 7 +
front-end/src/components/Settings/Kiosk/OrganizationSearch/Organizations.vue | 1 +
front-end/src/components/Settings/Kiosk/__mocks__/Jiminny.js | 1 +
front-end/src/components/Settings/Kiosk/modals/EditTeamModal/EditTeamModal.vue | 43 ++-
front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js | 203 ++++++++++++
front-end/src/components/Settings/Kiosk/shared/Navigation/Navigation.vue | 3 +
front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js | 67 ++++
front-end/src/components/TeamInsights/CoachingFrameworks/AICallScoring/aiCallScoringOverTime.ts | 4 +-
front-end/src/components/TeamInsights/CoachingFrameworks/UsersList.vue | 2 +-
front-end/src/components/layout/Sidebar/HelpMenu.vue | 25 +-
front-end/src/components/layout/Sidebar/Sidebar.vue | 27 +-
front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js | 94 ++++++
front-end/src/components/layout/Sidebar/__tests__/__snapshots__/Sidebar.spec.js.snap | 4 +-
front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js | 204 ++++++++++++
front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js | 49 +++
front-end/src/main.js | 1 +
front-end/src/store/modules/TeamInsights/util.js | 1 +
front-end/src/store/modules/platform/__tests__/getters.spec.js | 22 ++
front-end/src/store/modules/platform/getters.js | 3 +
front-end/src/utils/index.js | 11 +
front-end/yarn.lock | 21 +-
phpstan-baseline.neon | 60 ----
public/pdf/exec-reports/com/coaching-profiles.pdf | Bin 0 -> 1531178 bytes
public/pdf/exec-reports/com/exec-summary.pdf | Bin 0 -> 2237381 bytes
public/pdf/exec-reports/com/loss-report.pdf | Bin 0 -> 1955343 bytes
public/pdf/exec-reports/com/product-feedback.pdf | Bin 0 -> 2184417 bytes
public/pdf/exec-reports/eu/coaching-profiles.pdf | Bin 0 -> 1528704 bytes
public/pdf/exec-reports/eu/exec-summary.pdf | Bin 0 -> 2296741 bytes
public/pdf/exec-reports/eu/loss-report.pdf | Bin 0 -> 1955808 bytes
public/pdf/exec-reports/eu/product-feedback.pdf | Bin 0 -> 2184083 bytes
resources/views/emails/reports/ask-jiminny-report-expiring.blade.php | 22 ++
resources/views/emails/reports/report-not-generated.blade.php | 24 ++
resources/views/partials/crm/push-summary/html-assembly.blade.php | 2 +-
routes/api.php | 6 +
routes/web.php | 4 +
tests/Feature/Policies/UserPolicyTest.php | 90 ++++-
tests/Unit/Component/ActivityAnalytics/Service/ActivityAnalyticsServiceTest.php | 40 +++
tests/Unit/Component/AskAnything/AskAnythingPromptServiceTest.php | 26 ++
tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php | 276 ++++++++++++++++
tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php | 375 +++++++++++++++++++++
tests/Unit/Component/Twilio/Service/SoftPhoneServiceTest.php | 1014 +++++++++++++++++++++++++++++++++++++++++++++++++++++++--
tests/Unit/Console/Commands/Reports/AutomatedReportsCommandTest.php | 157 ++++++++-
tests/Unit/Events/Activities/Audio/RecordingEventTest.php | 72 ++++
tests/Unit/Events/Activities/Softphone/EndedTest.php | 86 +++++
tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php | 88 +++++
tests/Unit/Events/Activities/Softphone/StartedTest.php | 86 +++++
tests/Unit/Http/Controllers/Kiosk/AutomatedReportsControllerTest.php | 99 ++++++
tests/Unit/Http/Transformers/ActivityTransformerTest.php | 5 +-
tests/Unit/Http/Transformers/PartnerTransformerTest.php | 34 ++
tests/Unit/Interactions/Settings/Teams/CreateTeamTest.php | 49 +++
tests/Unit/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJobTest.php | 106 +++++-
tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php | 205 ++++++++++++
tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php | 188 +++++++++++
tests/Unit/Jobs/Crm/ImportOpportunityBatchTest.php | 2 +-
tests/Unit/Jobs/Team/SyncToIntercomTest.php | 6 +
tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php | 59 ++++
tests/Unit/Listeners/Teams/UpdateSalesforceAccountTest.php | 11 +-
tests/Unit/Listeners/Users/SyncIntercomTest.php | 59 ++++
tests/Unit/Mail/Reports/ReportNotGeneratedTest.php | 166 ++++++++++
tests/Unit/Models/PartnerTest.php | 28 ++
tests/Unit/Repositories/AutomatedReportsRepositoryTest.php | 68 ++++
tests/Unit/Services/Activity/MeetingBotServiceRequestRecordingToStopTest.php | 14 +-
tests/Unit/Services/ActivityServiceTest.php | 391 ++++++++++++++++++++++
tests/Unit/Services/Crm/Hubspot/ServiceResponseNormalizeTest.php | 68 ++--
tests/Unit/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityServiceTest.php | 48 +--
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceActivitiesCountTest.php | 16 +-
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceReportGenerationTest.php | 24 +-
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceTest.php | 130 ++++++++
tests/Unit/Services/KioskServiceTest.php | 8 +
tests/Unit/Services/Webhook/Triggers/AiScorecardCompletedTriggerTest.php | 6 +-
tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php | 119 +++++++
tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php | 108 ++++++
tests/Unit/UseCases/TeamInsights/TeamConversationsExportTest.php | 342 ++++++++++++++-----
186 files changed, 8538 insertions(+), 1233 deletions(-)
create mode 100644 app/Component/Twilio/TwilioRepository.php
delete mode 100644 app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php
create mode 100644 app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php
delete mode 100644 app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php
create mode 100644 app/Http/Controllers/Kiosk/PartnersController.php
create mode 100644 app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php
create mode 100644 app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php
create mode 100644 app/Mail/Reports/AskJiminnyReportExpiringMail.php
create mode 100644 app/Mail/Reports/ReportNotGenerated.php
delete mode 100644 app/Models/ElasticSearch/SharedDocumentDeleteTrait.php
create mode 100644 app/UseCases/TeamInsights/ConversationRowMapper.php
create mode 100644 app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php
create mode 100644 app/UseCases/TeamInsights/StrictConsentColumnResolver.php
create mode 100644 database/migrations/2026_04_14_000000_add_rockeed_partner.php
create mode 100644 database/migrations/2026_04_22_000000_add_success_email_to_partners.php
create mode 100644 database/migrations/2026_04_27_000000_add_label_to_partners.php
create mode 100644 database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php
create mode 100644 front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js
create mode 100644 front-end/src/apps/ai-reports-promo.js
create mode 100644 front-end/src/components/AiReports/AiReportsPromo.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html
create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue
create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js
create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html
create mode 100644 front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js
create mode 100644 front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js
create mode 100644 front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js
create mode 100644 front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js
create mode 100644 front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js
create mode 100644 front-end/src/store/modules/platform/__tests__/getters.spec.js
create mode 100644 public/pdf/exec-reports/com/coaching-profiles.pdf
create mode 100644 public/pdf/exec-reports/com/exec-summary.pdf
create mode 100644 public/pdf/exec-reports/com/loss-report.pdf
create mode 100644 public/pdf/exec-reports/com/product-feedback.pdf
create mode 100644 public/pdf/exec-reports/eu/coaching-profiles.pdf
create mode 100644 public/pdf/exec-reports/eu/exec-summary.pdf
create mode 100644 public/pdf/exec-reports/eu/loss-report.pdf
create mode 100644 public/pdf/exec-reports/eu/product-feedback.pdf
create mode 100644 resources/views/emails/reports/ask-jiminny-report-expiring.blade.php
create mode 100644 resources/views/emails/reports/report-not-generated.blade.php
create mode 100644 tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php
create mode 100644 tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php
create mode 100644 tests/Unit/Events/Activities/Audio/RecordingEventTest.php
create mode 100644 tests/Unit/Events/Activities/Softphone/EndedTest.php
create mode 100644 tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php
create mode 100644 tests/Unit/Events/Activities/Softphone/StartedTest.php
create mode 100644 tests/Unit/Http/Transformers/PartnerTransformerTest.php
create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php
create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php
create mode 100644 tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php
create mode 100644 tests/Unit/Listeners/Users/SyncIntercomTest.php
create mode 100644 tests/Unit/Mail/Reports/ReportNotGeneratedTest.php
create mode 100644 tests/Unit/Models/PartnerTest.php
create mode 100644 tests/Unit/Services/ActivityServiceTest.php
create mode 100644 tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php
create mode 100644 tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 628, done.
remote: Counting objects: 100% (331/331), done.
remote: Compressing objects: 100% (63/63), done.
remote: Total 628 (delta 280), reused 274 (delta 266), pack-reused 297 (from 1)
Receiving objects: 100% (628/628), 186.75 KiB | 1.23 MiB/s, done.
Resolving deltas: 100% (391/391), completed with 57 local objects.
From github.com:jiminny/app
ad2ce76737..12295204cf master -> origin/master
14f54b5be2..5e7646e5f9 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3
b167b19973..acba55cf38 JY-20289-api-tests -> origin/JY-20289-api-tests
f23cfee7c3..e5a3ec5dba JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null
af59d60926..766efba1c5 JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import
* [new branch] JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering
1737b7c528..c57e71e763 JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall
* [new branch] JY-20671-anyvan-twilio-s3-recordings-ftech -> origin/JY-20671-anyvan-twilio-s3-recordings-ftech
+ ba181441c6...20a74137b0 JY-20742-mcp-poc -> origin/JY-20742-mcp-poc (forced update)
* [new branch] JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue
* [new branch] JY-20816-calendar-events-diplication -> origin/JY-20816-calendar-events-diplication
* [new branch] desktop-app -> origin/desktop-app
4c4c974e46..185442c26e make-claude-great-again -> origin/make-claude-great-again
* [new branch] mcp-tools-schemas -> origin/mcp-tools-schemas
Updating ad2ce76737..12295204cf
Fast-forward
app/Component/Encoding/Job/AnalyzeTrackChannelsJob.php | 2 +-
app/Component/Transcription/TranscriptionProcessor/AssemblyAI/Services/SubmitAudioFileService.php | 66 ++----------------------------------------------------------------
app/Console/Commands/Tracks/CleanupActivityTracksCommand.php | 24 +++++++++++++++++-------
tests/Unit/Console/Commands/Tracks/CleanupActivityTracksCommandTest.php | 40 +++++++++++++++++++++++++++++-----------
tests/Unit/fixtures/assembly_ai_transcript_response.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_channel_diarization.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language_error.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language_not_ready.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language_post.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_without_utterances.json | 1 -
11 files changed, 49 insertions(+), 90 deletions(-)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20818-move-AJ-reports-to-separated-datadog-metric
Switched to a new branch 'JY-20818-move-AJ-reports-to-separated-datadog-metric'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix
docker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff
PHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.
PHP runtime: 8.3.30
Running analysis on 7 cores with 10 files per process.
Parallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!
Loaded config default from ".php-cs-fixer.dist.php".
5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%
Fixed 0 of 5663 files in 83.615 seconds, 67.00 MB memory used
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at [URL_WITH_CREDENTIALS] ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix
docker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff
PHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.
PHP runtime: 8.3.30
Running analysis on 7 cores with 10 files per process.
Parallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!
Loaded config default from ".php-cs-fixer.dist.php".
5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%
Fixed 0 of 5663 files in 42.875 seconds, 60.00 MB memory used
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at [URL_WITH_CREDENTIALS] ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 15, done.
remote: Counting objects: 100% (15/15), done.
remote: Compressing objects: 100% (2/2), done.
remote: Total 15 (delta 13), reused 15 (delta 13), pack-reused 0 (from 0)
Unpacking objects: 100% (15/15), 1.28 KiB | 72.00 KiB/s, done.
From github.com:jiminny/app
c57e71e763..8743fea32e JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall
* [new branch] JY-20819-increase-download-transctip-rate-limit -> origin/JY-20819-increase-download-transctip-rate-limit
Already up to date.
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 180, done.
remote: Counting objects: 100% (179/179), done.
remote: Compressing objects: 100% (55/55), done.
remote: Total 180 (delta 127), reused 165 (delta 119), pack-reused 1 (from 1)
Receiving objects: 100% (180/180), 57.50 KiB | 2.74 MiB/s, done.
Resolving deltas: 100% (127/127), completed with 47 local objects.
From github.com:jiminny/app
12295204cf..35f036ace6 master -> origin/master
* [new branch] JY-18091-upgrade-to-php-8-5 -> origin/JY-18091-upgrade-to-php-8-5
5f21965da8..497fbc85c2 JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering
f029263118..6ed9e2bb13 JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue
* [new branch] JY-20817-fix-deleting-s3-directories -> origin/JY-20817-fix-deleting-s3-directories
* [new branch] JY-20820-es-reindex-stream-model-hydration -> origin/JY-20820-es-reindex-stream-model-hydration
+ ca92730ec5...2c8a1d0856 desktop-app -> origin/desktop-app (forced update)
8425d4e0de..89b45ec8b0 mcp-tools-schemas -> origin/mcp-tools-schemas
Updating 12295204cf..35f036ace6
Fast-forward
app/Component/Datadog/Constants.php | 1 +
app/Providers/RouteServiceProvider.php | 2 +-
app/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackService.php | 13 +++++++++++++
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackServiceTest.php | 54 +++++++++++++++++++++++++++++++++++++++++++++++-------
4 files changed, 62 insertions(+), 8 deletions(-)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ gbr
* master
JY-20818-move-AJ-reports-to-separated-datadog-metric
JY-20773-fix-automated-reports-user-pilot-tracking
JY-20157-AJ-report-not-send-notification
JY-20508-notify-before-AJ-report-expiration
JY-20372-ai-reports-promotion-pages
JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null
JY-20738-debug-AJ-tracking-UP
a
JY-18909-automated-reports-ask-jiminny
JY-20692-fix-integration-app-[API_KEY]
JY-20553-debug-crm-sync-delays
JY-20698-fix-SF-activity-types-on-new-playbook
JY-20543-AJ-report-tracking
JY-20384-handle-auto-sync-with-no-access-to-event-type
JY-20458-ask-jiminny-user-definitions
JY-19666-fix-import-contacts-account-association
JY-19666-HS-import-contacts-and-accounts-batch-job
JY-20458-Ask-Jiminny-Reports
JY-20200-batch-update-CRM-objects-Salesforce
JY-19666-HS-webhooks-add-contact-and-company
JY-20348-trigger-setup-DI-layout-on-team-creation
JY-20326-refactor-info-message-in-command
JY-20317-fix-auto-log-delay-issue-on-all-channels-disabled
JY-20312-remove-on-update-change-last-synced-at-crm-configurations
JY-20306-SF-skip-auto-sync-for-task-based-playbook
JY-20192-remove-deleted-team-from-saved-search-filters
JY-20197-import-opportunity-batch-job
JY-20293-enable-status-field-for-pipedrive-deals
JY-20191-remove-commands-interactive-prompts
JY-20118-change-default-sync-strategy
JY-20183-add-cache-on-auto-log-delay
JY-20197-add-import-opportunity-batch-job
20118-hs-opportunity-make-webhook-strategy-default
JY-20118-make-default-hs-opportunity-sync-strategy-webhook-based
JY-20196-handle-opportunity-without-note
JY-20118-improve-opportunity-import
JY-20189-handle-activity-search-on-deleted-groups
JY-20160
JY-20145-filter-out-converted-leads-when-matching
JY-20150-skip-push-summary-on-summary-ready-if-autolog
JY-20132-fix-note-encoding
JY-19792-clean-logs
JY-20117-fix-sync-profile-fields-on-empty-fields
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20725-handle-HS-search-rate-limit
Switched to a new branch 'JY-20725-handle-HS-search-rate-limit'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ ;xd
docker exec -it docker_lamp_1 bash -c "mv /usr/local/etc/php/conf.d/xdebug.ini ~/xdebug.ini"
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at https://docs.docker.com/go/debug-cli/
docker exec -it docker_lamp_1 supervisorctl restart all
jiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: stopped
jiminny-worker-processing-2:jiminny-worker-processing-2_00: stopped
jiminny-worker-processing-3:jiminny-worker-processing-3_00: stopped
jiminny-worker-processing-4:jiminny-worker-processing-4_00: stopped
jiminny-worker-processing-5:jiminny-worker-processing-5_00: stopped
worker-analytics:worker-analytics_00: stopped
worker-crm-update:worker-crm-update_00: stopped
worker-download:worker-download_00: stopped
worker-nudges:worker-nudges_00: stopped
artisan-schedule:artisan-schedule_00: stopped
worker-emails:worker-emails_00: stopped
worker:worker_00: stopped
worker-calendar:worker-calendar_00: stopped
jiminny-worker-processing-1:jiminny-worker-processing-1_00: stopped
worker-crm-sync:worker-crm-sync_00: stopped
worker-audio:worker-audio_00: stopped
worker-conferences:worker-conferences_00: stopped
worker-es-update:worker-es-update_00: stopped
artisan-schedule:artisan-schedule_00: started
jiminny-worker-processing-1:jiminny-worker-processing-1_00: started
jiminny-worker-processing-2:jiminny-worker-processing-2_00: started
jiminny-worker-processing-3:jiminny-worker-processing-3_00: started
jiminny-worker-processing-4:jiminny-worker-processing-4_00: started
jiminny-worker-processing-5:jiminny-worker-processing-5_00: started
jiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: started
worker:worker_00: started
worker-analytics:worker-analytics_00: started
worker-audio:worker-audio_00: started
worker-calendar:worker-calendar_00: started
worker-conferences:worker-conferences_00: started
worker-crm-sync:worker-crm-sync_00: started
worker-crm-update:worker-crm-update_00: started
worker-download:worker-download_00: started
worker-emails:worker-emails_00: started
worker-es-update:worker-es-update_00: started
worker-nudges:worker-nudges_00: started
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at https://docs.docker.com/go/debug-cli/
docker exec -it docker_lamp_1 php -v
PHP 8.3.30 (cli) (built: Mar 16 2026 22:32:32) (NTS)
Copyright (c) The PHP Group
Zend En...
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NULL
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NULL
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922
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2
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2026-05-11T17:11:15.440546+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519475440_m1.jpg...
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iTerm2
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APP (-zsh)
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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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Last login: Thu May 7 09:44:56 on ttys007
Poetry Last login: Thu May 7 09:44:56 on ttys007
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ git status
On branch master
Your branch is up to date with 'origin/master'.
Changes not staged for commit:
(use "git add <file>..." to update what will be committed)
(use "git restore <file>..." to discard changes in working directory)
modified: .env.local
modified: app/Console/Commands/JiminnyDebugCommand.php
modified: app/Jobs/Team/SyncToIntercom.php
modified: app/Services/PlaybackService.php
modified: config/logging.php
modified: resources/views/partials/crm/push-summary/html-assembly.blade.php
Untracked files:
(use "git add <file>..." to include in what will be committed)
.env.nikilocal
.env.other
WEBHOOK_FILTERING_IMPLEMENTATION.md
app/Console/Commands/Crm/Hubspot/SimulateWebhooksCommand.php
app/Console/Commands/Reports/CreateMockAskJiminnyReportResultCommand.php
ids.txt
public/favicon.ico
raw_sql_query.sql
tests/Unit/Policies/CanAccessAiReportsTest.php
no changes added to commit (use "git add" and/or "git commit -a")
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 1482, done.
remote: Counting objects: 100% (481/481), done.
remote: Compressing objects: 100% (191/191), done.
remote: Total 1482 (delta 349), reused 305 (delta 289), pack-reused 1001 (from 4)
Receiving objects: 100% (1482/1482), 1017.97 KiB | 1.44 MiB/s, done.
Resolving deltas: 100% (877/877), completed with 96 local objects.
From github.com:jiminny/app
83b628967a..ad2ce76737 master -> origin/master
1ee8cbcb7b..14f54b5be2 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3
5662c3b32f..b167b19973 JY-20289-api-tests -> origin/JY-20289-api-tests
b40408cfad..f23cfee7c3 JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null
* [new branch] JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import
* [new branch] JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall
* [new branch] JY-20662-remove-word-boost -> origin/JY-20662-remove-word-boost
* [new branch] JY-20742-mcp-poc -> origin/JY-20742-mcp-poc
* [new branch] make-claude-great-again -> origin/make-claude-great-again
* [new branch] secfix/composer-20260507 -> origin/secfix/composer-20260507
* [new branch] secfix/npm-20260507 -> origin/secfix/npm-20260507
Updating 83b628967a..ad2ce76737
error: Your local changes to the following files would be overwritten by merge:
app/Jobs/Team/SyncToIntercom.php
resources/views/partials/crm/push-summary/html-assembly.blade.php
Please commit your changes or stash them before you merge.
Aborting
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
Updating 83b628967a..ad2ce76737
error: Your local changes to the following files would be overwritten by merge:
app/Jobs/Team/SyncToIntercom.php
resources/views/partials/crm/push-summary/html-assembly.blade.php
Please commit your changes or stash them before you merge.
Aborting
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
Updating 83b628967a..ad2ce76737
error: Your local changes to the following files would be overwritten by merge:
app/Jobs/Team/SyncToIntercom.php
Please commit your changes or stash them before you merge.
Aborting
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
Updating 83b628967a..ad2ce76737
Fast-forward
.cursor/rules/frontend-conventions.mdc | 23 ++
.env.production-eu | 2 +-
.env.staging | 2 +-
Makefile | 10 +
app/Component/ActivityAnalytics/Service/ActivityAnalyticsService.php | 6 +-
app/Component/AiAutomation/Repositories/AiTemplateFieldsRepository.php | 32 +-
app/Component/AiCallScoring/Repositories/AiScorecardRepository.php | 56 ++--
app/Component/AskAnything/AskAnythingPromptService.php | 3 +
app/Component/Transcription/Job/FinishTranscriptionJob.php | 37 ++-
app/Component/Transcription/TranscriptionProcessor/Gong/Gong.php | 18 +-
app/Component/Twilio/Conference/ConferenceManager/SoftPhoneManager.php | 4 +-
app/Component/Twilio/Service/SoftPhoneService.php | 124 ++++---
app/Component/Twilio/TwilioRepository.php | 27 ++
app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php | 59 ----
app/Console/Commands/Reports/AutomatedReportsCommand.php | 122 +++++--
app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php | 200 ++++++++++++
app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php | 60 ----
app/Console/Commands/Users/SyncToIntercom.php | 4 +-
app/Console/Kernel.php | 3 +-
app/Contracts/ES/Events/UpdateMultipleEntities.php | 4 -
app/Contracts/ES/Events/UpdateSingleEntity.php | 4 -
app/Contracts/Repositories/TeamRepository.php | 3 +-
app/Events/Activities/ActivityUpdated.php | 10 +-
app/Events/Activities/Audio/RecordingEvent.php | 6 +-
app/Events/Activities/Softphone/Ended.php | 8 +-
app/Events/Activities/Softphone/SoftphoneEvent.php | 24 +-
app/Events/Activities/Softphone/Started.php | 8 +-
app/Http/Controllers/API/ActivityController.php | 17 +-
app/Http/Controllers/API/SoftphoneController.php | 9 +-
app/Http/Controllers/API/UserAutomatedReports/UserAutomatedReportsController.php | 19 +-
app/Http/Controllers/API/V2/AskAnythingController.php | 2 +-
app/Http/Controllers/Auth/SocialController.php | 6 +-
app/Http/Controllers/Kiosk/AutomatedReportsController.php | 38 ++-
app/Http/Controllers/Kiosk/OrganizationsController.php | 8 +-
app/Http/Controllers/Kiosk/PartnersController.php | 46 +++
app/Http/Controllers/Kiosk/SearchController.php | 8 +
app/Http/Controllers/Kiosk/Teams/OnboardController.php | 24 +-
app/Http/Controllers/Settings/Teams/IntegrationController.php | 6 +-
app/Http/Controllers/TeamSetupController.php | 4 +-
app/Http/Controllers/Telephony/TextMessaging/MessageController.php | 12 +-
app/Http/Controllers/Telephony/TextMessaging/WebhookController.php | 18 +-
app/Http/Requests/Settings/Teams/CreateTeamRequest.php | 1 +
app/Http/Requests/Settings/Teams/EditTeamRequest.php | 1 +
app/Http/Transformers/ActivityTransformer.php | 4 +-
app/Http/Transformers/OnDemandActivitiesTransformer.php | 2 +-
app/Http/Transformers/PartnerTransformer.php | 1 +
app/Http/Transformers/StageTransformer.php | 6 +-
app/Http/Transformers/UserTransformer.php | 11 +-
app/Interactions/Settings/Teams/CreateTeam.php | 3 +
app/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJob.php | 80 ++++-
app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php | 119 +++++++
app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php | 89 +++++
app/Jobs/Crm/Hubspot/ImportBatchJobTrait.php | 12 +-
app/Jobs/Crm/UpdateStage.php | 3 +
app/Jobs/Team/SyncToIntercom.php | 7 +-
app/Listeners/Teams/SyncIntercomCompany.php | 5 +-
app/Listeners/Teams/UpdateSalesforceAccount.php | 8 +-
app/Listeners/Users/SyncIntercom.php | 5 +-
app/Mail/Reports/AskJiminnyReportExpiringMail.php | 40 +++
app/Mail/Reports/ReportNotGenerated.php | 41 +++
app/Models/Activity.php | 25 +-
app/Models/Activity/Question.php | 14 +-
app/Models/Activity/Search.php | 7 +
app/Models/AskAnything/AskAnythingPrompt.php | 6 +
app/Models/AutomatedReport.php | 10 +
app/Models/CoachingFeedback.php | 44 ++-
app/Models/ElasticSearch/ActivityElasticSearchTrait.php | 86 +----
app/Models/ElasticSearch/OpportunityElasticSearchTrait.php | 71 ----
app/Models/ElasticSearch/SharedDocumentDeleteTrait.php | 27 --
app/Models/Partner.php | 13 +
app/Models/Playlist/Activity.php | 14 +-
app/Notifications/OwnerInvitedToTrial.php | 14 +-
app/Policies/UserPolicy.php | 16 +-
app/Queue/Worker/Worker.php | 3 +-
app/Repositories/ActivityRepository.php | 13 +-
app/Repositories/AutomatedReportsRepository.php | 42 ++-
app/Repositories/TeamRepository.php | 21 +-
app/Repositories/UserRepository.php | 2 +-
app/Services/Activity/MeetingBotService.php | 8 +-
app/Services/ActivityService.php | 111 ++-----
app/Services/Crm/Hubspot/Service.php | 36 +-
app/Services/Crm/Hubspot/ServiceTraits/OpportunitySyncTrait.php | 2 +-
app/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityService.php | 5 +-
app/Services/Kiosk/AutomatedReports/AutomatedReportsService.php | 49 +--
app/Services/Kiosk/KioskService.php | 7 +-
app/Services/Webhook/Triggers/AiScorecardCompletedTrigger.php | 13 +-
app/UseCases/TeamInsights/ConversationRowMapper.php | 78 +++++
app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php | 68 ++++
app/UseCases/TeamInsights/StrictConsentColumnResolver.php | 45 +++
app/UseCases/TeamInsights/TeamConversationsExport.php | 154 ++++-----
composer.json | 1 -
composer.lock | 95 +-----
config/secure-headers.php | 5 +-
database/mappings/mapping_activities.json | 16 +
database/migrations/2026_04_14_000000_add_rockeed_partner.php | 51 +++
database/migrations/2026_04_22_000000_add_success_email_to_partners.php | 26 ++
database/migrations/2026_04_27_000000_add_label_to_partners.php | 28 ++
database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php | 79 +++++
front-end/package.json | 5 +-
front-end/src/__mocks__/jiminny.js | 4 +-
front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js | 9 +
front-end/src/__mocks__/setup.js | 1 +
front-end/src/apps/ai-reports-promo.js | 22 ++
front-end/src/components/AiReports/AiReportsPromo.vue | 22 ++
front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue | 190 +++++++++++
front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue | 111 +++++++
front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue | 103 ++++++
front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js | 98 ++++++
.../src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html | 283 ++++++++++++++++
front-end/src/components/AiReports/Manage/ManageAiReports.vue | 8 +-
front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue | 228 +++++++++++++
front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js | 71 ++++
.../src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html | 217 ++++++++++++
front-end/src/components/AiReports/constants.js | 7 +
front-end/src/components/Settings/Kiosk/OrganizationSearch/Organizations.vue | 1 +
front-end/src/components/Settings/Kiosk/__mocks__/Jiminny.js | 1 +
front-end/src/components/Settings/Kiosk/modals/EditTeamModal/EditTeamModal.vue | 43 ++-
front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js | 203 ++++++++++++
front-end/src/components/Settings/Kiosk/shared/Navigation/Navigation.vue | 3 +
front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js | 67 ++++
front-end/src/components/TeamInsights/CoachingFrameworks/AICallScoring/aiCallScoringOverTime.ts | 4 +-
front-end/src/components/TeamInsights/CoachingFrameworks/UsersList.vue | 2 +-
front-end/src/components/layout/Sidebar/HelpMenu.vue | 25 +-
front-end/src/components/layout/Sidebar/Sidebar.vue | 27 +-
front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js | 94 ++++++
front-end/src/components/layout/Sidebar/__tests__/__snapshots__/Sidebar.spec.js.snap | 4 +-
front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js | 204 ++++++++++++
front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js | 49 +++
front-end/src/main.js | 1 +
front-end/src/store/modules/TeamInsights/util.js | 1 +
front-end/src/store/modules/platform/__tests__/getters.spec.js | 22 ++
front-end/src/store/modules/platform/getters.js | 3 +
front-end/src/utils/index.js | 11 +
front-end/yarn.lock | 21 +-
phpstan-baseline.neon | 60 ----
public/pdf/exec-reports/com/coaching-profiles.pdf | Bin 0 -> 1531178 bytes
public/pdf/exec-reports/com/exec-summary.pdf | Bin 0 -> 2237381 bytes
public/pdf/exec-reports/com/loss-report.pdf | Bin 0 -> 1955343 bytes
public/pdf/exec-reports/com/product-feedback.pdf | Bin 0 -> 2184417 bytes
public/pdf/exec-reports/eu/coaching-profiles.pdf | Bin 0 -> 1528704 bytes
public/pdf/exec-reports/eu/exec-summary.pdf | Bin 0 -> 2296741 bytes
public/pdf/exec-reports/eu/loss-report.pdf | Bin 0 -> 1955808 bytes
public/pdf/exec-reports/eu/product-feedback.pdf | Bin 0 -> 2184083 bytes
resources/views/emails/reports/ask-jiminny-report-expiring.blade.php | 22 ++
resources/views/emails/reports/report-not-generated.blade.php | 24 ++
resources/views/partials/crm/push-summary/html-assembly.blade.php | 2 +-
routes/api.php | 6 +
routes/web.php | 4 +
tests/Feature/Policies/UserPolicyTest.php | 90 ++++-
tests/Unit/Component/ActivityAnalytics/Service/ActivityAnalyticsServiceTest.php | 40 +++
tests/Unit/Component/AskAnything/AskAnythingPromptServiceTest.php | 26 ++
tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php | 276 ++++++++++++++++
tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php | 375 +++++++++++++++++++++
tests/Unit/Component/Twilio/Service/SoftPhoneServiceTest.php | 1014 +++++++++++++++++++++++++++++++++++++++++++++++++++++++--
tests/Unit/Console/Commands/Reports/AutomatedReportsCommandTest.php | 157 ++++++++-
tests/Unit/Events/Activities/Audio/RecordingEventTest.php | 72 ++++
tests/Unit/Events/Activities/Softphone/EndedTest.php | 86 +++++
tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php | 88 +++++
tests/Unit/Events/Activities/Softphone/StartedTest.php | 86 +++++
tests/Unit/Http/Controllers/Kiosk/AutomatedReportsControllerTest.php | 99 ++++++
tests/Unit/Http/Transformers/ActivityTransformerTest.php | 5 +-
tests/Unit/Http/Transformers/PartnerTransformerTest.php | 34 ++
tests/Unit/Interactions/Settings/Teams/CreateTeamTest.php | 49 +++
tests/Unit/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJobTest.php | 106 +++++-
tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php | 205 ++++++++++++
tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php | 188 +++++++++++
tests/Unit/Jobs/Crm/ImportOpportunityBatchTest.php | 2 +-
tests/Unit/Jobs/Team/SyncToIntercomTest.php | 6 +
tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php | 59 ++++
tests/Unit/Listeners/Teams/UpdateSalesforceAccountTest.php | 11 +-
tests/Unit/Listeners/Users/SyncIntercomTest.php | 59 ++++
tests/Unit/Mail/Reports/ReportNotGeneratedTest.php | 166 ++++++++++
tests/Unit/Models/PartnerTest.php | 28 ++
tests/Unit/Repositories/AutomatedReportsRepositoryTest.php | 68 ++++
tests/Unit/Services/Activity/MeetingBotServiceRequestRecordingToStopTest.php | 14 +-
tests/Unit/Services/ActivityServiceTest.php | 391 ++++++++++++++++++++++
tests/Unit/Services/Crm/Hubspot/ServiceResponseNormalizeTest.php | 68 ++--
tests/Unit/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityServiceTest.php | 48 +--
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceActivitiesCountTest.php | 16 +-
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceReportGenerationTest.php | 24 +-
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceTest.php | 130 ++++++++
tests/Unit/Services/KioskServiceTest.php | 8 +
tests/Unit/Services/Webhook/Triggers/AiScorecardCompletedTriggerTest.php | 6 +-
tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php | 119 +++++++
tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php | 108 ++++++
tests/Unit/UseCases/TeamInsights/TeamConversationsExportTest.php | 342 ++++++++++++++-----
186 files changed, 8538 insertions(+), 1233 deletions(-)
create mode 100644 app/Component/Twilio/TwilioRepository.php
delete mode 100644 app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php
create mode 100644 app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php
delete mode 100644 app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php
create mode 100644 app/Http/Controllers/Kiosk/PartnersController.php
create mode 100644 app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php
create mode 100644 app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php
create mode 100644 app/Mail/Reports/AskJiminnyReportExpiringMail.php
create mode 100644 app/Mail/Reports/ReportNotGenerated.php
delete mode 100644 app/Models/ElasticSearch/SharedDocumentDeleteTrait.php
create mode 100644 app/UseCases/TeamInsights/ConversationRowMapper.php
create mode 100644 app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php
create mode 100644 app/UseCases/TeamInsights/StrictConsentColumnResolver.php
create mode 100644 database/migrations/2026_04_14_000000_add_rockeed_partner.php
create mode 100644 database/migrations/2026_04_22_000000_add_success_email_to_partners.php
create mode 100644 database/migrations/2026_04_27_000000_add_label_to_partners.php
create mode 100644 database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php
create mode 100644 front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js
create mode 100644 front-end/src/apps/ai-reports-promo.js
create mode 100644 front-end/src/components/AiReports/AiReportsPromo.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html
create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue
create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js
create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html
create mode 100644 front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js
create mode 100644 front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js
create mode 100644 front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js
create mode 100644 front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js
create mode 100644 front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js
create mode 100644 front-end/src/store/modules/platform/__tests__/getters.spec.js
create mode 100644 public/pdf/exec-reports/com/coaching-profiles.pdf
create mode 100644 public/pdf/exec-reports/com/exec-summary.pdf
create mode 100644 public/pdf/exec-reports/com/loss-report.pdf
create mode 100644 public/pdf/exec-reports/com/product-feedback.pdf
create mode 100644 public/pdf/exec-reports/eu/coaching-profiles.pdf
create mode 100644 public/pdf/exec-reports/eu/exec-summary.pdf
create mode 100644 public/pdf/exec-reports/eu/loss-report.pdf
create mode 100644 public/pdf/exec-reports/eu/product-feedback.pdf
create mode 100644 resources/views/emails/reports/ask-jiminny-report-expiring.blade.php
create mode 100644 resources/views/emails/reports/report-not-generated.blade.php
create mode 100644 tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php
create mode 100644 tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php
create mode 100644 tests/Unit/Events/Activities/Audio/RecordingEventTest.php
create mode 100644 tests/Unit/Events/Activities/Softphone/EndedTest.php
create mode 100644 tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php
create mode 100644 tests/Unit/Events/Activities/Softphone/StartedTest.php
create mode 100644 tests/Unit/Http/Transformers/PartnerTransformerTest.php
create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php
create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php
create mode 100644 tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php
create mode 100644 tests/Unit/Listeners/Users/SyncIntercomTest.php
create mode 100644 tests/Unit/Mail/Reports/ReportNotGeneratedTest.php
create mode 100644 tests/Unit/Models/PartnerTest.php
create mode 100644 tests/Unit/Services/ActivityServiceTest.php
create mode 100644 tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php
create mode 100644 tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 628, done.
remote: Counting objects: 100% (331/331), done.
remote: Compressing objects: 100% (63/63), done.
remote: Total 628 (delta 280), reused 274 (delta 266), pack-reused 297 (from 1)
Receiving objects: 100% (628/628), 186.75 KiB | 1.23 MiB/s, done.
Resolving deltas: 100% (391/391), completed with 57 local objects.
From github.com:jiminny/app
ad2ce76737..12295204cf master -> origin/master
14f54b5be2..5e7646e5f9 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3
b167b19973..acba55cf38 JY-20289-api-tests -> origin/JY-20289-api-tests
f23cfee7c3..e5a3ec5dba JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null
af59d60926..766efba1c5 JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import
* [new branch] JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering
1737b7c528..c57e71e763 JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall
* [new branch] JY-20671-anyvan-twilio-s3-recordings-ftech -> origin/JY-20671-anyvan-twilio-s3-recordings-ftech
+ ba181441c6...20a74137b0 JY-20742-mcp-poc -> origin/JY-20742-mcp-poc (forced update)
* [new branch] JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue
* [new branch] JY-20816-calendar-events-diplication -> origin/JY-20816-calendar-events-diplication
* [new branch] desktop-app -> origin/desktop-app
4c4c974e46..185442c26e make-claude-great-again -> origin/make-claude-great-again
* [new branch] mcp-tools-schemas -> origin/mcp-tools-schemas
Updating ad2ce76737..12295204cf
Fast-forward
app/Component/Encoding/Job/AnalyzeTrackChannelsJob.php | 2 +-
app/Component/Transcription/TranscriptionProcessor/AssemblyAI/Services/SubmitAudioFileService.php | 66 ++----------------------------------------------------------------
app/Console/Commands/Tracks/CleanupActivityTracksCommand.php | 24 +++++++++++++++++-------
tests/Unit/Console/Commands/Tracks/CleanupActivityTracksCommandTest.php | 40 +++++++++++++++++++++++++++++-----------
tests/Unit/fixtures/assembly_ai_transcript_response.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_channel_diarization.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language_error.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language_not_ready.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language_post.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_without_utterances.json | 1 -
11 files changed, 49 insertions(+), 90 deletions(-)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20818-move-AJ-reports-to-separated-datadog-metric
Switched to a new branch 'JY-20818-move-AJ-reports-to-separated-datadog-metric'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix
docker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff
PHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.
PHP runtime: 8.3.30
Running analysis on 7 cores with 10 files per process.
Parallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!
Loaded config default from ".php-cs-fixer.dist.php".
5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%
Fixed 0 of 5663 files in 83.615 seconds, 67.00 MB memory used
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at [URL_WITH_CREDENTIALS] ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix
docker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff
PHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.
PHP runtime: 8.3.30
Running analysis on 7 cores with 10 files per process.
Parallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!
Loaded config default from ".php-cs-fixer.dist.php".
5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%
Fixed 0 of 5663 files in 42.875 seconds, 60.00 MB memory used
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at [URL_WITH_CREDENTIALS] ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 15, done.
remote: Counting objects: 100% (15/15), done.
remote: Compressing objects: 100% (2/2), done.
remote: Total 15 (delta 13), reused 15 (delta 13), pack-reused 0 (from 0)
Unpacking objects: 100% (15/15), 1.28 KiB | 72.00 KiB/s, done.
From github.com:jiminny/app
c57e71e763..8743fea32e JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall
* [new branch] JY-20819-increase-download-transctip-rate-limit -> origin/JY-20819-increase-download-transctip-rate-limit
Already up to date.
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 180, done.
remote: Counting objects: 100% (179/179), done.
remote: Compressing objects: 100% (55/55), done.
remote: Total 180 (delta 127), reused 165 (delta 119), pack-reused 1 (from 1)
Receiving objects: 100% (180/180), 57.50 KiB | 2.74 MiB/s, done.
Resolving deltas: 100% (127/127), completed with 47 local objects.
From github.com:jiminny/app
12295204cf..35f036ace6 master -> origin/master
* [new branch] JY-18091-upgrade-to-php-8-5 -> origin/JY-18091-upgrade-to-php-8-5
5f21965da8..497fbc85c2 JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering
f029263118..6ed9e2bb13 JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue
* [new branch] JY-20817-fix-deleting-s3-directories -> origin/JY-20817-fix-deleting-s3-directories
* [new branch] JY-20820-es-reindex-stream-model-hydration -> origin/JY-20820-es-reindex-stream-model-hydration
+ ca92730ec5...2c8a1d0856 desktop-app -> origin/desktop-app (forced update)
8425d4e0de..89b45ec8b0 mcp-tools-schemas -> origin/mcp-tools-schemas
Updating 12295204cf..35f036ace6
Fast-forward
app/Component/Datadog/Constants.php | 1 +
app/Providers/RouteServiceProvider.php | 2 +-
app/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackService.php | 13 +++++++++++++
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackServiceTest.php | 54 +++++++++++++++++++++++++++++++++++++++++++++++-------
4 files changed, 62 insertions(+), 8 deletions(-)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ gbr
* master
JY-20818-move-AJ-reports-to-separated-datadog-metric
JY-20773-fix-automated-reports-user-pilot-tracking
JY-20157-AJ-report-not-send-notification
JY-20508-notify-before-AJ-report-expiration
JY-20372-ai-reports-promotion-pages
JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null
JY-20738-debug-AJ-tracking-UP
a
JY-18909-automated-reports-ask-jiminny
JY-20692-fix-integration-app-[API_KEY]
JY-20553-debug-crm-sync-delays
JY-20698-fix-SF-activity-types-on-new-playbook
JY-20543-AJ-report-tracking
JY-20384-handle-auto-sync-with-no-access-to-event-type
JY-20458-ask-jiminny-user-definitions
JY-19666-fix-import-contacts-account-association
JY-19666-HS-import-contacts-and-accounts-batch-job
JY-20458-Ask-Jiminny-Reports
JY-20200-batch-update-CRM-objects-Salesforce
JY-19666-HS-webhooks-add-contact-and-company
JY-20348-trigger-setup-DI-layout-on-team-creation
JY-20326-refactor-info-message-in-command
JY-20317-fix-auto-log-delay-issue-on-all-channels-disabled
JY-20312-remove-on-update-change-last-synced-at-crm-configurations
JY-20306-SF-skip-auto-sync-for-task-based-playbook
JY-20192-remove-deleted-team-from-saved-search-filters
JY-20197-import-opportunity-batch-job
JY-20293-enable-status-field-for-pipedrive-deals
JY-20191-remove-commands-interactive-prompts
JY-20118-change-default-sync-strategy
JY-20183-add-cache-on-auto-log-delay
JY-20197-add-import-opportunity-batch-job
20118-hs-opportunity-make-webhook-strategy-default
JY-20118-make-default-hs-opportunity-sync-strategy-webhook-based
JY-20196-handle-opportunity-without-note
JY-20118-improve-opportunity-import
JY-20189-handle-activity-search-on-deleted-groups
JY-20160
JY-20145-filter-out-converted-leads-when-matching
JY-20150-skip-push-summary-on-summary-ready-if-autolog
JY-20132-fix-note-encoding
JY-19792-clean-logs
JY-20117-fix-sync-profile-fields-on-empty-fields
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20725-handle-HS-search-rate-limit
Switched to a new branch 'JY-20725-handle-HS-search-rate-limit'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ ;xd
docker exec -it docker_lamp_1 bash -c "mv /usr/local/etc/php/conf.d/xdebug.ini ~/xdebug.ini"
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at https://docs.docker.com/go/debug-cli/
docker exec -it docker_lamp_1 supervisorctl restart all
jiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: stopped
jiminny-worker-processing-2:jiminny-worker-processing-2_00: stopped
jiminny-worker-processing-3:jiminny-worker-processing-3_00: stopped
jiminny-worker-processing-4:jiminny-worker-processing-4_00: stopped
jiminny-worker-processing-5:jiminny-worker-processing-5_00: stopped
worker-analytics:worker-analytics_00: stopped
worker-crm-update:worker-crm-update_00: stopped
worker-download:worker-download_00: stopped
worker-nudges:worker-nudges_00: stopped
artisan-schedule:artisan-schedule_00: stopped
worker-emails:worker-emails_00: stopped
worker:worker_00: stopped
worker-calendar:worker-calendar_00: stopped
jiminny-worker-processing-1:jiminny-worker-processing-1_00: stopped
worker-crm-sync:worker-crm-sync_00: stopped
worker-audio:worker-audio_00: stopped
worker-conferences:worker-conferences_00: stopped
worker-es-update:worker-es-update_00: stopped
artisan-schedule:artisan-schedule_00: started
jiminny-worker-processing-1:jiminny-worker-processing-1_00: started
jiminny-worker-processing-2:jiminny-worker-processing-2_00: started
jiminny-worker-processing-3:jiminny-worker-processing-3_00: started
jiminny-worker-processing-4:jiminny-worker-processing-4_00: started
jiminny-worker-processing-5:jiminny-worker-processing-5_00: started
jiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: started
worker:worker_00: started
worker-analytics:worker-analytics_00: started
worker-audio:worker-audio_00: started
worker-calendar:worker-calendar_00: started
worker-conferences:worker-conferences_00: started
worker-crm-sync:worker-crm-sync_00: started
worker-crm-update:worker-crm-update_00: started
worker-download:worker-download_00: started
worker-emails:worker-emails_00: started
worker-es-update:worker-es-update_00: started
worker-nudges:worker-nudges_00: started
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at https://docs.docker.com/go/debug-cli/
docker exec -it docker_lamp_1 php -v
PHP 8.3.30 (cli) (built: Mar 16 2026 22:32:32) (NTS)
Copyright (c) The PHP Group
Zend En...
|
[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"Last login: Thu May 7 09:44:56 on ttys007\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ git status\nOn branch master\nYour branch is up to date with 'origin/master'.\n\nChanges not staged for commit:\n (use \"git add <file>...\" to update what will be committed)\n (use \"git restore <file>...\" to discard changes in working directory)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: .env.local\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: app/Console/Commands/JiminnyDebugCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: app/Jobs/Team/SyncToIntercom.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: app/Services/PlaybackService.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: config/logging.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: resources/views/partials/crm/push-summary/html-assembly.blade.php\n\nUntracked files:\n (use \"git add <file>...\" to include in what will be committed)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.nikilocal\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.other\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tWEBHOOK_FILTERING_IMPLEMENTATION.md\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Crm/Hubspot/SimulateWebhooksCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Reports/CreateMockAskJiminnyReportResultCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tids.txt\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tpublic/favicon.ico\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\traw_sql_query.sql\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\ttests/Unit/Policies/CanAccessAiReportsTest.php\n\nno changes added to commit (use \"git add\" and/or \"git commit -a\")\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nremote: Enumerating objects: 1482, done.\nremote: Counting objects: 100% (481/481), done.\nremote: Compressing objects: 100% (191/191), done.\nremote: Total 1482 (delta 349), reused 305 (delta 289), pack-reused 1001 (from 4)\nReceiving objects: 100% (1482/1482), 1017.97 KiB | 1.44 MiB/s, done.\nResolving deltas: 100% (877/877), completed with 96 local objects.\nFrom github.com:jiminny/app\n 83b628967a..ad2ce76737 master -> origin/master\n 1ee8cbcb7b..14f54b5be2 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3\n 5662c3b32f..b167b19973 JY-20289-api-tests -> origin/JY-20289-api-tests\n b40408cfad..f23cfee7c3 JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null\n * [new branch] JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import\n * [new branch] JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall\n * [new branch] JY-20662-remove-word-boost -> origin/JY-20662-remove-word-boost\n * [new branch] JY-20742-mcp-poc -> origin/JY-20742-mcp-poc\n * [new branch] make-claude-great-again -> origin/make-claude-great-again\n * [new branch] secfix/composer-20260507 -> origin/secfix/composer-20260507\n * [new branch] secfix/npm-20260507 -> origin/secfix/npm-20260507\nUpdating 83b628967a..ad2ce76737\nerror: Your local changes to the following files would be overwritten by merge:\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Jobs/Team/SyncToIntercom.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tresources/views/partials/crm/push-summary/html-assembly.blade.php\nPlease commit your changes or stash them before you merge.\nAborting\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nUpdating 83b628967a..ad2ce76737\nerror: Your local changes to the following files would be overwritten by merge:\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Jobs/Team/SyncToIntercom.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tresources/views/partials/crm/push-summary/html-assembly.blade.php\nPlease commit your changes or stash them before you merge.\nAborting\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nUpdating 83b628967a..ad2ce76737\nerror: Your local changes to the following files would be overwritten by merge:\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Jobs/Team/SyncToIntercom.php\nPlease commit your changes or stash them before you merge.\nAborting\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nUpdating 83b628967a..ad2ce76737\nFast-forward\n .cursor/rules/frontend-conventions.mdc | 23 ++\n .env.production-eu | 2 +-\n .env.staging | 2 +-\n Makefile | 10 +\n app/Component/ActivityAnalytics/Service/ActivityAnalyticsService.php | 6 +-\n app/Component/AiAutomation/Repositories/AiTemplateFieldsRepository.php | 32 +-\n app/Component/AiCallScoring/Repositories/AiScorecardRepository.php | 56 ++--\n app/Component/AskAnything/AskAnythingPromptService.php | 3 +\n app/Component/Transcription/Job/FinishTranscriptionJob.php | 37 ++-\n app/Component/Transcription/TranscriptionProcessor/Gong/Gong.php | 18 +-\n app/Component/Twilio/Conference/ConferenceManager/SoftPhoneManager.php | 4 +-\n app/Component/Twilio/Service/SoftPhoneService.php | 124 ++++---\n app/Component/Twilio/TwilioRepository.php | 27 ++\n app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php | 59 ----\n app/Console/Commands/Reports/AutomatedReportsCommand.php | 122 +++++--\n app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php | 200 ++++++++++++\n app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php | 60 ----\n app/Console/Commands/Users/SyncToIntercom.php | 4 +-\n app/Console/Kernel.php | 3 +-\n app/Contracts/ES/Events/UpdateMultipleEntities.php | 4 -\n app/Contracts/ES/Events/UpdateSingleEntity.php | 4 -\n app/Contracts/Repositories/TeamRepository.php | 3 +-\n app/Events/Activities/ActivityUpdated.php | 10 +-\n app/Events/Activities/Audio/RecordingEvent.php | 6 +-\n app/Events/Activities/Softphone/Ended.php | 8 +-\n app/Events/Activities/Softphone/SoftphoneEvent.php | 24 +-\n app/Events/Activities/Softphone/Started.php | 8 +-\n app/Http/Controllers/API/ActivityController.php | 17 +-\n app/Http/Controllers/API/SoftphoneController.php | 9 +-\n app/Http/Controllers/API/UserAutomatedReports/UserAutomatedReportsController.php | 19 +-\n app/Http/Controllers/API/V2/AskAnythingController.php | 2 +-\n app/Http/Controllers/Auth/SocialController.php | 6 +-\n app/Http/Controllers/Kiosk/AutomatedReportsController.php | 38 ++-\n app/Http/Controllers/Kiosk/OrganizationsController.php | 8 +-\n app/Http/Controllers/Kiosk/PartnersController.php | 46 +++\n app/Http/Controllers/Kiosk/SearchController.php | 8 +\n app/Http/Controllers/Kiosk/Teams/OnboardController.php | 24 +-\n app/Http/Controllers/Settings/Teams/IntegrationController.php | 6 +-\n app/Http/Controllers/TeamSetupController.php | 4 +-\n app/Http/Controllers/Telephony/TextMessaging/MessageController.php | 12 +-\n app/Http/Controllers/Telephony/TextMessaging/WebhookController.php | 18 +-\n app/Http/Requests/Settings/Teams/CreateTeamRequest.php | 1 +\n app/Http/Requests/Settings/Teams/EditTeamRequest.php | 1 +\n app/Http/Transformers/ActivityTransformer.php | 4 +-\n app/Http/Transformers/OnDemandActivitiesTransformer.php | 2 +-\n app/Http/Transformers/PartnerTransformer.php | 1 +\n app/Http/Transformers/StageTransformer.php | 6 +-\n app/Http/Transformers/UserTransformer.php | 11 +-\n app/Interactions/Settings/Teams/CreateTeam.php | 3 +\n app/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJob.php | 80 ++++-\n app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php | 119 +++++++\n app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php | 89 +++++\n app/Jobs/Crm/Hubspot/ImportBatchJobTrait.php | 12 +-\n app/Jobs/Crm/UpdateStage.php | 3 +\n app/Jobs/Team/SyncToIntercom.php | 7 +-\n app/Listeners/Teams/SyncIntercomCompany.php | 5 +-\n app/Listeners/Teams/UpdateSalesforceAccount.php | 8 +-\n app/Listeners/Users/SyncIntercom.php | 5 +-\n app/Mail/Reports/AskJiminnyReportExpiringMail.php | 40 +++\n app/Mail/Reports/ReportNotGenerated.php | 41 +++\n app/Models/Activity.php | 25 +-\n app/Models/Activity/Question.php | 14 +-\n app/Models/Activity/Search.php | 7 +\n app/Models/AskAnything/AskAnythingPrompt.php | 6 +\n app/Models/AutomatedReport.php | 10 +\n app/Models/CoachingFeedback.php | 44 ++-\n app/Models/ElasticSearch/ActivityElasticSearchTrait.php | 86 +----\n app/Models/ElasticSearch/OpportunityElasticSearchTrait.php | 71 ----\n app/Models/ElasticSearch/SharedDocumentDeleteTrait.php | 27 --\n app/Models/Partner.php | 13 +\n app/Models/Playlist/Activity.php | 14 +-\n app/Notifications/OwnerInvitedToTrial.php | 14 +-\n app/Policies/UserPolicy.php | 16 +-\n app/Queue/Worker/Worker.php | 3 +-\n app/Repositories/ActivityRepository.php | 13 +-\n app/Repositories/AutomatedReportsRepository.php | 42 ++-\n app/Repositories/TeamRepository.php | 21 +-\n app/Repositories/UserRepository.php | 2 +-\n app/Services/Activity/MeetingBotService.php | 8 +-\n app/Services/ActivityService.php | 111 ++-----\n app/Services/Crm/Hubspot/Service.php | 36 +-\n app/Services/Crm/Hubspot/ServiceTraits/OpportunitySyncTrait.php | 2 +-\n app/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityService.php | 5 +-\n app/Services/Kiosk/AutomatedReports/AutomatedReportsService.php | 49 +--\n app/Services/Kiosk/KioskService.php | 7 +-\n app/Services/Webhook/Triggers/AiScorecardCompletedTrigger.php | 13 +-\n app/UseCases/TeamInsights/ConversationRowMapper.php | 78 +++++\n app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php | 68 ++++\n app/UseCases/TeamInsights/StrictConsentColumnResolver.php | 45 +++\n app/UseCases/TeamInsights/TeamConversationsExport.php | 154 ++++-----\n composer.json | 1 -\n composer.lock | 95 +-----\n config/secure-headers.php | 5 +-\n database/mappings/mapping_activities.json | 16 +\n database/migrations/2026_04_14_000000_add_rockeed_partner.php | 51 +++\n database/migrations/2026_04_22_000000_add_success_email_to_partners.php | 26 ++\n database/migrations/2026_04_27_000000_add_label_to_partners.php | 28 ++\n database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php | 79 +++++\n front-end/package.json | 5 +-\n front-end/src/__mocks__/jiminny.js | 4 +-\n front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js | 9 +\n front-end/src/__mocks__/setup.js | 1 +\n front-end/src/apps/ai-reports-promo.js | 22 ++\n front-end/src/components/AiReports/AiReportsPromo.vue | 22 ++\n front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue | 190 +++++++++++\n front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue | 111 +++++++\n front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue | 103 ++++++\n front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js | 98 ++++++\n .../src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html | 283 ++++++++++++++++\n front-end/src/components/AiReports/Manage/ManageAiReports.vue | 8 +-\n front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue | 228 +++++++++++++\n front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js | 71 ++++\n .../src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html | 217 ++++++++++++\n front-end/src/components/AiReports/constants.js | 7 +\n front-end/src/components/Settings/Kiosk/OrganizationSearch/Organizations.vue | 1 +\n front-end/src/components/Settings/Kiosk/__mocks__/Jiminny.js | 1 +\n front-end/src/components/Settings/Kiosk/modals/EditTeamModal/EditTeamModal.vue | 43 ++-\n front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js | 203 ++++++++++++\n front-end/src/components/Settings/Kiosk/shared/Navigation/Navigation.vue | 3 +\n front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js | 67 ++++\n front-end/src/components/TeamInsights/CoachingFrameworks/AICallScoring/aiCallScoringOverTime.ts | 4 +-\n front-end/src/components/TeamInsights/CoachingFrameworks/UsersList.vue | 2 +-\n front-end/src/components/layout/Sidebar/HelpMenu.vue | 25 +-\n front-end/src/components/layout/Sidebar/Sidebar.vue | 27 +-\n front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js | 94 ++++++\n front-end/src/components/layout/Sidebar/__tests__/__snapshots__/Sidebar.spec.js.snap | 4 +-\n front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js | 204 ++++++++++++\n front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js | 49 +++\n front-end/src/main.js | 1 +\n front-end/src/store/modules/TeamInsights/util.js | 1 +\n front-end/src/store/modules/platform/__tests__/getters.spec.js | 22 ++\n front-end/src/store/modules/platform/getters.js | 3 +\n front-end/src/utils/index.js | 11 +\n front-end/yarn.lock | 21 +-\n phpstan-baseline.neon | 60 ----\n public/pdf/exec-reports/com/coaching-profiles.pdf | Bin 0 -> 1531178 bytes\n public/pdf/exec-reports/com/exec-summary.pdf | Bin 0 -> 2237381 bytes\n public/pdf/exec-reports/com/loss-report.pdf | Bin 0 -> 1955343 bytes\n public/pdf/exec-reports/com/product-feedback.pdf | Bin 0 -> 2184417 bytes\n public/pdf/exec-reports/eu/coaching-profiles.pdf | Bin 0 -> 1528704 bytes\n public/pdf/exec-reports/eu/exec-summary.pdf | Bin 0 -> 2296741 bytes\n public/pdf/exec-reports/eu/loss-report.pdf | Bin 0 -> 1955808 bytes\n public/pdf/exec-reports/eu/product-feedback.pdf | Bin 0 -> 2184083 bytes\n resources/views/emails/reports/ask-jiminny-report-expiring.blade.php | 22 ++\n resources/views/emails/reports/report-not-generated.blade.php | 24 ++\n resources/views/partials/crm/push-summary/html-assembly.blade.php | 2 +-\n routes/api.php | 6 +\n routes/web.php | 4 +\n tests/Feature/Policies/UserPolicyTest.php | 90 ++++-\n tests/Unit/Component/ActivityAnalytics/Service/ActivityAnalyticsServiceTest.php | 40 +++\n tests/Unit/Component/AskAnything/AskAnythingPromptServiceTest.php | 26 ++\n tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php | 276 ++++++++++++++++\n tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php | 375 +++++++++++++++++++++\n tests/Unit/Component/Twilio/Service/SoftPhoneServiceTest.php | 1014 +++++++++++++++++++++++++++++++++++++++++++++++++++++++--\n tests/Unit/Console/Commands/Reports/AutomatedReportsCommandTest.php | 157 ++++++++-\n tests/Unit/Events/Activities/Audio/RecordingEventTest.php | 72 ++++\n tests/Unit/Events/Activities/Softphone/EndedTest.php | 86 +++++\n tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php | 88 +++++\n tests/Unit/Events/Activities/Softphone/StartedTest.php | 86 +++++\n tests/Unit/Http/Controllers/Kiosk/AutomatedReportsControllerTest.php | 99 ++++++\n tests/Unit/Http/Transformers/ActivityTransformerTest.php | 5 +-\n tests/Unit/Http/Transformers/PartnerTransformerTest.php | 34 ++\n tests/Unit/Interactions/Settings/Teams/CreateTeamTest.php | 49 +++\n tests/Unit/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJobTest.php | 106 +++++-\n tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php | 205 ++++++++++++\n tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php | 188 +++++++++++\n tests/Unit/Jobs/Crm/ImportOpportunityBatchTest.php | 2 +-\n tests/Unit/Jobs/Team/SyncToIntercomTest.php | 6 +\n tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php | 59 ++++\n tests/Unit/Listeners/Teams/UpdateSalesforceAccountTest.php | 11 +-\n tests/Unit/Listeners/Users/SyncIntercomTest.php | 59 ++++\n tests/Unit/Mail/Reports/ReportNotGeneratedTest.php | 166 ++++++++++\n tests/Unit/Models/PartnerTest.php | 28 ++\n tests/Unit/Repositories/AutomatedReportsRepositoryTest.php | 68 ++++\n tests/Unit/Services/Activity/MeetingBotServiceRequestRecordingToStopTest.php | 14 +-\n tests/Unit/Services/ActivityServiceTest.php | 391 ++++++++++++++++++++++\n tests/Unit/Services/Crm/Hubspot/ServiceResponseNormalizeTest.php | 68 ++--\n tests/Unit/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityServiceTest.php | 48 +--\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceActivitiesCountTest.php | 16 +-\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceReportGenerationTest.php | 24 +-\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceTest.php | 130 ++++++++\n tests/Unit/Services/KioskServiceTest.php | 8 +\n tests/Unit/Services/Webhook/Triggers/AiScorecardCompletedTriggerTest.php | 6 +-\n tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php | 119 +++++++\n tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php | 108 ++++++\n tests/Unit/UseCases/TeamInsights/TeamConversationsExportTest.php | 342 ++++++++++++++-----\n 186 files changed, 8538 insertions(+), 1233 deletions(-)\n create mode 100644 app/Component/Twilio/TwilioRepository.php\n delete mode 100644 app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php\n create mode 100644 app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php\n delete mode 100644 app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php\n create mode 100644 app/Http/Controllers/Kiosk/PartnersController.php\n create mode 100644 app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php\n create mode 100644 app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php\n create mode 100644 app/Mail/Reports/AskJiminnyReportExpiringMail.php\n create mode 100644 app/Mail/Reports/ReportNotGenerated.php\n delete mode 100644 app/Models/ElasticSearch/SharedDocumentDeleteTrait.php\n create mode 100644 app/UseCases/TeamInsights/ConversationRowMapper.php\n create mode 100644 app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php\n create mode 100644 app/UseCases/TeamInsights/StrictConsentColumnResolver.php\n create mode 100644 database/migrations/2026_04_14_000000_add_rockeed_partner.php\n create mode 100644 database/migrations/2026_04_22_000000_add_success_email_to_partners.php\n create mode 100644 database/migrations/2026_04_27_000000_add_label_to_partners.php\n create mode 100644 database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php\n create mode 100644 front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js\n create mode 100644 front-end/src/apps/ai-reports-promo.js\n create mode 100644 front-end/src/components/AiReports/AiReportsPromo.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html\n create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue\n create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js\n create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html\n create mode 100644 front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js\n create mode 100644 front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js\n create mode 100644 front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js\n create mode 100644 front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js\n create mode 100644 front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js\n create mode 100644 front-end/src/store/modules/platform/__tests__/getters.spec.js\n create mode 100644 public/pdf/exec-reports/com/coaching-profiles.pdf\n create mode 100644 public/pdf/exec-reports/com/exec-summary.pdf\n create mode 100644 public/pdf/exec-reports/com/loss-report.pdf\n create mode 100644 public/pdf/exec-reports/com/product-feedback.pdf\n create mode 100644 public/pdf/exec-reports/eu/coaching-profiles.pdf\n create mode 100644 public/pdf/exec-reports/eu/exec-summary.pdf\n create mode 100644 public/pdf/exec-reports/eu/loss-report.pdf\n create mode 100644 public/pdf/exec-reports/eu/product-feedback.pdf\n create mode 100644 resources/views/emails/reports/ask-jiminny-report-expiring.blade.php\n create mode 100644 resources/views/emails/reports/report-not-generated.blade.php\n create mode 100644 tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php\n create mode 100644 tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php\n create mode 100644 tests/Unit/Events/Activities/Audio/RecordingEventTest.php\n create mode 100644 tests/Unit/Events/Activities/Softphone/EndedTest.php\n create mode 100644 tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php\n create mode 100644 tests/Unit/Events/Activities/Softphone/StartedTest.php\n create mode 100644 tests/Unit/Http/Transformers/PartnerTransformerTest.php\n create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php\n create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php\n create mode 100644 tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php\n create mode 100644 tests/Unit/Listeners/Users/SyncIntercomTest.php\n create mode 100644 tests/Unit/Mail/Reports/ReportNotGeneratedTest.php\n create mode 100644 tests/Unit/Models/PartnerTest.php\n create mode 100644 tests/Unit/Services/ActivityServiceTest.php\n create mode 100644 tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php\n create mode 100644 tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull \nremote: Enumerating objects: 628, done.\nremote: Counting objects: 100% (331/331), done.\nremote: Compressing objects: 100% (63/63), done.\nremote: Total 628 (delta 280), reused 274 (delta 266), pack-reused 297 (from 1)\nReceiving objects: 100% (628/628), 186.75 KiB | 1.23 MiB/s, done.\nResolving deltas: 100% (391/391), completed with 57 local objects.\nFrom github.com:jiminny/app\n ad2ce76737..12295204cf master -> origin/master\n 14f54b5be2..5e7646e5f9 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3\n b167b19973..acba55cf38 JY-20289-api-tests -> origin/JY-20289-api-tests\n f23cfee7c3..e5a3ec5dba JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null\n af59d60926..766efba1c5 JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import\n * [new branch] JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering\n 1737b7c528..c57e71e763 JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall\n * [new branch] JY-20671-anyvan-twilio-s3-recordings-ftech -> origin/JY-20671-anyvan-twilio-s3-recordings-ftech\n + ba181441c6...20a74137b0 JY-20742-mcp-poc -> origin/JY-20742-mcp-poc (forced update)\n * [new branch] JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue\n * [new branch] JY-20816-calendar-events-diplication -> origin/JY-20816-calendar-events-diplication\n * [new branch] desktop-app -> origin/desktop-app\n 4c4c974e46..185442c26e make-claude-great-again -> origin/make-claude-great-again\n * [new branch] mcp-tools-schemas -> origin/mcp-tools-schemas\nUpdating ad2ce76737..12295204cf\nFast-forward\n app/Component/Encoding/Job/AnalyzeTrackChannelsJob.php | 2 +-\n app/Component/Transcription/TranscriptionProcessor/AssemblyAI/Services/SubmitAudioFileService.php | 66 ++----------------------------------------------------------------\n app/Console/Commands/Tracks/CleanupActivityTracksCommand.php | 24 +++++++++++++++++-------\n tests/Unit/Console/Commands/Tracks/CleanupActivityTracksCommandTest.php | 40 +++++++++++++++++++++++++++++-----------\n tests/Unit/fixtures/assembly_ai_transcript_response.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_channel_diarization.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language_error.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language_not_ready.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language_post.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_without_utterances.json | 1 -\n 11 files changed, 49 insertions(+), 90 deletions(-)\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20818-move-AJ-reports-to-separated-datadog-metric\nSwitched to a new branch 'JY-20818-move-AJ-reports-to-separated-datadog-metric'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5663 files in 83.615 seconds, 67.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ ;xd\ndocker exec -it docker_lamp_1 bash -c \"mv /usr/local/etc/php/conf.d/xdebug.ini ~/xdebug.ini\"\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 supervisorctl restart all\njiminny-worker-processing-2:jiminny-worker-processing-2_00: stopped\njiminny-worker-processing-3:jiminny-worker-processing-3_00: stopped\njiminny-worker-processing-4:jiminny-worker-processing-4_00: stopped\njiminny-worker-processing-5:jiminny-worker-processing-5_00: stopped\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: stopped\nworker-analytics:worker-analytics_00: stopped\nworker-crm-update:worker-crm-update_00: stopped\nworker-download:worker-download_00: stopped\nworker-nudges:worker-nudges_00: stopped\nartisan-schedule:artisan-schedule_00: stopped\nworker-calendar:worker-calendar_00: stopped\nworker-crm-sync:worker-crm-sync_00: stopped\njiminny-worker-processing-1:jiminny-worker-processing-1_00: stopped\nworker:worker_00: stopped\nworker-emails:worker-emails_00: stopped\nworker-audio:worker-audio_00: stopped\nworker-conferences:worker-conferences_00: stopped\nworker-es-update:worker-es-update_00: stopped\nartisan-schedule:artisan-schedule_00: started\njiminny-worker-processing-1:jiminny-worker-processing-1_00: started\njiminny-worker-processing-2:jiminny-worker-processing-2_00: started\njiminny-worker-processing-3:jiminny-worker-processing-3_00: started\njiminny-worker-processing-4:jiminny-worker-processing-4_00: started\njiminny-worker-processing-5:jiminny-worker-processing-5_00: started\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: started\nworker:worker_00: started\nworker-analytics:worker-analytics_00: started\nworker-audio:worker-audio_00: started\nworker-calendar:worker-calendar_00: started\nworker-conferences:worker-conferences_00: started\nworker-crm-sync:worker-crm-sync_00: started\nworker-crm-update:worker-crm-update_00: started\nworker-download:worker-download_00: started\nworker-emails:worker-emails_00: started\nworker-es-update:worker-es-update_00: started\nworker-nudges:worker-nudges_00: started\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 php -v\nPHP 8.3.30 (cli) (built: Mar 16 2026 22:32:32) (NTS)\nCopyright (c) The PHP Group\nZend Engine v4.3.30, Copyright (c) Zend Technologies\n with Zend OPcache v8.3.30, Copyright (c), by Zend Technologies\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5663 files in 42.875 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ git status\nOn branch master\nYour branch is up to date with 'origin/master'.\n\nChanges not staged for commit:\n (use \"git add <file>...\" to update what will be committed)\n (use \"git restore <file>...\" to discard changes in working directory)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: .env.local\n\nUntracked files:\n (use \"git add <file>...\" to include in what will be committed)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.nikilocal\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.other\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tWEBHOOK_FILTERING_IMPLEMENTATION.md\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Crm/Hubspot/SimulateWebhooksCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Reports/CreateMockAskJiminnyReportResultCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tids.txt\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tpublic/favicon.ico\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\traw_sql_query.sql\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\ttests/Unit/Policies/CanAccessAiReportsTest.php\n\nno changes added to commit (use \"git add\" and/or \"git commit -a\")\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nremote: Enumerating objects: 15, done.\nremote: Counting objects: 100% (15/15), done.\nremote: Compressing objects: 100% (2/2), done.\nremote: Total 15 (delta 13), reused 15 (delta 13), pack-reused 0 (from 0)\nUnpacking objects: 100% (15/15), 1.28 KiB | 72.00 KiB/s, done.\nFrom github.com:jiminny/app\n c57e71e763..8743fea32e JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall\n * [new branch] JY-20819-increase-download-transctip-rate-limit -> origin/JY-20819-increase-download-transctip-rate-limit\nAlready up to date.\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull \nremote: Enumerating objects: 180, done.\nremote: Counting objects: 100% (179/179), done.\nremote: Compressing objects: 100% (55/55), done.\nremote: Total 180 (delta 127), reused 165 (delta 119), pack-reused 1 (from 1)\nReceiving objects: 100% (180/180), 57.50 KiB | 2.74 MiB/s, done.\nResolving deltas: 100% (127/127), completed with 47 local objects.\nFrom github.com:jiminny/app\n 12295204cf..35f036ace6 master -> origin/master\n * [new branch] JY-18091-upgrade-to-php-8-5 -> origin/JY-18091-upgrade-to-php-8-5\n 5f21965da8..497fbc85c2 JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering\n f029263118..6ed9e2bb13 JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue\n * [new branch] JY-20817-fix-deleting-s3-directories -> origin/JY-20817-fix-deleting-s3-directories\n * [new branch] JY-20820-es-reindex-stream-model-hydration -> origin/JY-20820-es-reindex-stream-model-hydration\n + ca92730ec5...2c8a1d0856 desktop-app -> origin/desktop-app (forced update)\n 8425d4e0de..89b45ec8b0 mcp-tools-schemas -> origin/mcp-tools-schemas\nUpdating 12295204cf..35f036ace6\nFast-forward\n app/Component/Datadog/Constants.php | 1 +\n app/Providers/RouteServiceProvider.php | 2 +-\n app/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackService.php | 13 +++++++++++++\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackServiceTest.php | 54 +++++++++++++++++++++++++++++++++++++++++++++++-------\n 4 files changed, 62 insertions(+), 8 deletions(-)\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ gbr \n* master\n JY-20818-move-AJ-reports-to-separated-datadog-metric\n JY-20773-fix-automated-reports-user-pilot-tracking\n JY-20157-AJ-report-not-send-notification\n JY-20508-notify-before-AJ-report-expiration\n JY-20372-ai-reports-promotion-pages\n JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null\n JY-20738-debug-AJ-tracking-UP\n a\n JY-18909-automated-reports-ask-jiminny\n JY-20692-fix-integration-app-token-auth-response-change\n JY-20553-debug-crm-sync-delays\n JY-20698-fix-SF-activity-types-on-new-playbook\n JY-20543-AJ-report-tracking\n JY-20384-handle-auto-sync-with-no-access-to-event-type\n JY-20458-ask-jiminny-user-definitions\n JY-19666-fix-import-contacts-account-association\n JY-19666-HS-import-contacts-and-accounts-batch-job\n JY-20458-Ask-Jiminny-Reports\n JY-20200-batch-update-CRM-objects-Salesforce\n JY-19666-HS-webhooks-add-contact-and-company\n JY-20348-trigger-setup-DI-layout-on-team-creation\n JY-20326-refactor-info-message-in-command\n JY-20317-fix-auto-log-delay-issue-on-all-channels-disabled\n JY-20312-remove-on-update-change-last-synced-at-crm-configurations\n JY-20306-SF-skip-auto-sync-for-task-based-playbook\n JY-20192-remove-deleted-team-from-saved-search-filters\n JY-20197-import-opportunity-batch-job\n JY-20293-enable-status-field-for-pipedrive-deals\n JY-20191-remove-commands-interactive-prompts\n JY-20118-change-default-sync-strategy\n JY-20183-add-cache-on-auto-log-delay\n JY-20197-add-import-opportunity-batch-job\n 20118-hs-opportunity-make-webhook-strategy-default\n JY-20118-make-default-hs-opportunity-sync-strategy-webhook-based\n JY-20196-handle-opportunity-without-note\n JY-20118-improve-opportunity-import\n JY-20189-handle-activity-search-on-deleted-groups\n JY-20160\n JY-20145-filter-out-converted-leads-when-matching\n JY-20150-skip-push-summary-on-summary-ready-if-autolog\n JY-20132-fix-note-encoding\n JY-19792-clean-logs\n JY-20117-fix-sync-profile-fields-on-empty-fields\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20725-handle-HS-search-rate-limit \nSwitched to a new branch 'JY-20725-handle-HS-search-rate-limit'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ ;xd\ndocker exec -it docker_lamp_1 bash -c \"mv /usr/local/etc/php/conf.d/xdebug.ini ~/xdebug.ini\"\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 supervisorctl restart all\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: stopped\njiminny-worker-processing-2:jiminny-worker-processing-2_00: stopped\njiminny-worker-processing-3:jiminny-worker-processing-3_00: stopped\njiminny-worker-processing-4:jiminny-worker-processing-4_00: stopped\njiminny-worker-processing-5:jiminny-worker-processing-5_00: stopped\nworker-analytics:worker-analytics_00: stopped\nworker-crm-update:worker-crm-update_00: stopped\nworker-download:worker-download_00: stopped\nworker-nudges:worker-nudges_00: stopped\nartisan-schedule:artisan-schedule_00: stopped\nworker-emails:worker-emails_00: stopped\nworker:worker_00: stopped\nworker-calendar:worker-calendar_00: stopped\njiminny-worker-processing-1:jiminny-worker-processing-1_00: stopped\nworker-crm-sync:worker-crm-sync_00: stopped\nworker-audio:worker-audio_00: stopped\nworker-conferences:worker-conferences_00: stopped\nworker-es-update:worker-es-update_00: stopped\nartisan-schedule:artisan-schedule_00: started\njiminny-worker-processing-1:jiminny-worker-processing-1_00: started\njiminny-worker-processing-2:jiminny-worker-processing-2_00: started\njiminny-worker-processing-3:jiminny-worker-processing-3_00: started\njiminny-worker-processing-4:jiminny-worker-processing-4_00: started\njiminny-worker-processing-5:jiminny-worker-processing-5_00: started\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: started\nworker:worker_00: started\nworker-analytics:worker-analytics_00: started\nworker-audio:worker-audio_00: started\nworker-calendar:worker-calendar_00: started\nworker-conferences:worker-conferences_00: started\nworker-crm-sync:worker-crm-sync_00: started\nworker-crm-update:worker-crm-update_00: started\nworker-download:worker-download_00: started\nworker-emails:worker-emails_00: started\nworker-es-update:worker-es-update_00: started\nworker-nudges:worker-nudges_00: started\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 php -v\nPHP 8.3.30 (cli) (built: Mar 16 2026 22:32:32) (NTS)\nCopyright (c) The PHP Group\nZend Engine v4.3.30, Copyright (c) Zend Technologies\n with Zend OPcache v8.3.30, Copyright (c), by Zend Technologies\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5666/5666 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n 1) app/Jobs/Crm/MatchActivityCrmData.php (ordered_class_elements)\n ---------- begin diff ----------\n--- /home/jiminny/app/Jobs/Crm/MatchActivityCrmData.php\n+++ /home/jiminny/app/Jobs/Crm/MatchActivityCrmData.php\n@@ -29,24 +29,14 @@\n use InteractsWithQueue;\n use SerializesModels;\n \n+ private const int RETRY_WINDOW_MINUTES = 120;\n+\n public int $maxExceptions = 3;\n \n- private const int RETRY_WINDOW_MINUTES = 120;\n-\n private int $activityId;\n private ?Configuration $fromConfiguration;\n private bool $remoteSearch;\n \n- public function middleware(): array\n- {\n- return [new HandleHubspotRateLimit()];\n- }\n-\n- public function retryUntil(): \\DateTimeInterface\n- {\n- return now()->addMinutes(self::RETRY_WINDOW_MINUTES);\n- }\n-\n public function __construct(\n int $activityId,\n ?Configuration $fromConfiguration = null,\n@@ -57,6 +47,16 @@\n $this->remoteSearch = $remoteSearch;\n \n $this->onQueue(Constants::QUEUE_ANALYTICS_LOW);\n+ }\n+\n+ public function middleware(): array\n+ {\n+ return [new HandleHubspotRateLimit()];\n+ }\n+\n+ public function retryUntil(): \\DateTimeInterface\n+ {\n+ return now()->addMinutes(self::RETRY_WINDOW_MINUTES);\n }\n \n public function uniqueId(): string\n\n ----------- end diff -----------\n\n 2) app/Services/Crm/Hubspot/HubspotClientInterface.php (phpdoc_order, phpdoc_separation)\n ---------- begin diff ----------\n--- /home/jiminny/app/Services/Crm/Hubspot/HubspotClientInterface.php\n+++ /home/jiminny/app/Services/Crm/Hubspot/HubspotClientInterface.php\n@@ -46,9 +46,11 @@\n *\n * @param string $objectType The object type ('deals', 'companies', 'contacts', 'calls')\n * @param array<string, mixed> $payload The search payload with filters, sorts, properties, etc.\n- * @return array The search response with 'results', 'total', 'paging' keys\n+ *\n * @throws RateLimitException When rate limit is hit\n * @throws HubspotException On API errors\n+ *\n+ * @return array The search response with 'results', 'total', 'paging' keys\n */\n public function search(string $objectType, array $payload): array;\n }\n\n ----------- end diff -----------\n\n 3) app/Services/Crm/Hubspot/Client.php (phpdoc_order, phpdoc_separation, blank_line_before_statement)\n ---------- begin diff ----------\n--- /home/jiminny/app/Services/Crm/Hubspot/Client.php\n+++ /home/jiminny/app/Services/Crm/Hubspot/Client.php\n@@ -69,10 +69,12 @@\n * the cache near expiry are not delayed longer than necessary.\n *\n * @template T\n+ *\n * @param callable(): T $apiCall The API call to execute\n- * @return T The result of the API call\n *\n * @throws RateLimitException When rate limit is hit or cached rate limit is active\n+ *\n+ * @return T The result of the API call\n */\n private function executeRequest(callable $apiCall)\n {\n@@ -81,6 +83,7 @@\n $cachedExpiresAt = Redis::get($cacheKey);\n if (is_string($cachedExpiresAt) && is_numeric($cachedExpiresAt)) {\n $remaining = max(1, (int) $cachedExpiresAt - time());\n+\n throw new RateLimitException(\n 'Hubspot rate limit (cached circuit-breaker)',\n $remaining,\n@@ -232,9 +235,11 @@\n *\n * @param string $objectType The object type ('deals', 'companies', 'contacts', 'calls')\n * @param array<string, mixed> $payload The search payload with filters, sorts, properties, etc.\n- * @return array The search response with 'results', 'total', 'paging' keys\n+ *\n * @throws RateLimitException When rate limit is hit\n * @throws HubspotException On API errors\n+ *\n+ * @return array The search response with 'results', 'total', 'paging' keys\n */\n public function search(string $objectType, array $payload): array\n {\n\n ----------- end diff -----------\n\n 4) app/Console/Commands/JiminnyDebugCommand.php (statement_indentation)\n ---------- begin diff ----------\n--- /home/jiminny/app/Console/Commands/JiminnyDebugCommand.php\n+++ /home/jiminny/app/Console/Commands/JiminnyDebugCommand.php\n@@ -359,11 +359,11 @@\n $crmService = $crmResolver->prepareCrmService();\n \n for ($i = 0 ; $i < 3; $i++) {\n-// if ($i % 25 === 0) {\n-// $this->info(\"Syncing opportunity {$i}\");\n- $this->info(\"Matching contact {$i}\");\n-// }\n-// $crmService->syncOpportunity('374720564');\n+ // if ($i % 25 === 0) {\n+ // $this->info(\"Syncing opportunity {$i}\");\n+ $this->info(\"Matching contact {$i}\");\n+ // }\n+ // $crmService->syncOpportunity('374720564');\n $crmService->matchByName('Robot');\n }\n }\n\n ----------- end diff -----------\n\n\nFixed 4 of 5666 files in 146.870 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ csfix \ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5666/5666 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5666 files in 106.192 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5666/5666 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5666 files in 66.457 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $","depth":4,"on_screen":true,"value":"Last login: Thu May 7 09:44:56 on ttys007\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\n\nPoetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ git status\nOn branch master\nYour branch is up to date with 'origin/master'.\n\nChanges not staged for commit:\n (use \"git add <file>...\" to update what will be committed)\n (use \"git restore <file>...\" to discard changes in working directory)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: .env.local\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: app/Console/Commands/JiminnyDebugCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: app/Jobs/Team/SyncToIntercom.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: app/Services/PlaybackService.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: config/logging.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: resources/views/partials/crm/push-summary/html-assembly.blade.php\n\nUntracked files:\n (use \"git add <file>...\" to include in what will be committed)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.nikilocal\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.other\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tWEBHOOK_FILTERING_IMPLEMENTATION.md\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Crm/Hubspot/SimulateWebhooksCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Reports/CreateMockAskJiminnyReportResultCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tids.txt\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tpublic/favicon.ico\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\traw_sql_query.sql\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\ttests/Unit/Policies/CanAccessAiReportsTest.php\n\nno changes added to commit (use \"git add\" and/or \"git commit -a\")\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nremote: Enumerating objects: 1482, done.\nremote: Counting objects: 100% (481/481), done.\nremote: Compressing objects: 100% (191/191), done.\nremote: Total 1482 (delta 349), reused 305 (delta 289), pack-reused 1001 (from 4)\nReceiving objects: 100% (1482/1482), 1017.97 KiB | 1.44 MiB/s, done.\nResolving deltas: 100% (877/877), completed with 96 local objects.\nFrom github.com:jiminny/app\n 83b628967a..ad2ce76737 master -> origin/master\n 1ee8cbcb7b..14f54b5be2 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3\n 5662c3b32f..b167b19973 JY-20289-api-tests -> origin/JY-20289-api-tests\n b40408cfad..f23cfee7c3 JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null\n * [new branch] JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import\n * [new branch] JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall\n * [new branch] JY-20662-remove-word-boost -> origin/JY-20662-remove-word-boost\n * [new branch] JY-20742-mcp-poc -> origin/JY-20742-mcp-poc\n * [new branch] make-claude-great-again -> origin/make-claude-great-again\n * [new branch] secfix/composer-20260507 -> origin/secfix/composer-20260507\n * [new branch] secfix/npm-20260507 -> origin/secfix/npm-20260507\nUpdating 83b628967a..ad2ce76737\nerror: Your local changes to the following files would be overwritten by merge:\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Jobs/Team/SyncToIntercom.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tresources/views/partials/crm/push-summary/html-assembly.blade.php\nPlease commit your changes or stash them before you merge.\nAborting\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nUpdating 83b628967a..ad2ce76737\nerror: Your local changes to the following files would be overwritten by merge:\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Jobs/Team/SyncToIntercom.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tresources/views/partials/crm/push-summary/html-assembly.blade.php\nPlease commit your changes or stash them before you merge.\nAborting\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nUpdating 83b628967a..ad2ce76737\nerror: Your local changes to the following files would be overwritten by merge:\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Jobs/Team/SyncToIntercom.php\nPlease commit your changes or stash them before you merge.\nAborting\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nUpdating 83b628967a..ad2ce76737\nFast-forward\n .cursor/rules/frontend-conventions.mdc | 23 ++\n .env.production-eu | 2 +-\n .env.staging | 2 +-\n Makefile | 10 +\n app/Component/ActivityAnalytics/Service/ActivityAnalyticsService.php | 6 +-\n app/Component/AiAutomation/Repositories/AiTemplateFieldsRepository.php | 32 +-\n app/Component/AiCallScoring/Repositories/AiScorecardRepository.php | 56 ++--\n app/Component/AskAnything/AskAnythingPromptService.php | 3 +\n app/Component/Transcription/Job/FinishTranscriptionJob.php | 37 ++-\n app/Component/Transcription/TranscriptionProcessor/Gong/Gong.php | 18 +-\n app/Component/Twilio/Conference/ConferenceManager/SoftPhoneManager.php | 4 +-\n app/Component/Twilio/Service/SoftPhoneService.php | 124 ++++---\n app/Component/Twilio/TwilioRepository.php | 27 ++\n app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php | 59 ----\n app/Console/Commands/Reports/AutomatedReportsCommand.php | 122 +++++--\n app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php | 200 ++++++++++++\n app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php | 60 ----\n app/Console/Commands/Users/SyncToIntercom.php | 4 +-\n app/Console/Kernel.php | 3 +-\n app/Contracts/ES/Events/UpdateMultipleEntities.php | 4 -\n app/Contracts/ES/Events/UpdateSingleEntity.php | 4 -\n app/Contracts/Repositories/TeamRepository.php | 3 +-\n app/Events/Activities/ActivityUpdated.php | 10 +-\n app/Events/Activities/Audio/RecordingEvent.php | 6 +-\n app/Events/Activities/Softphone/Ended.php | 8 +-\n app/Events/Activities/Softphone/SoftphoneEvent.php | 24 +-\n app/Events/Activities/Softphone/Started.php | 8 +-\n app/Http/Controllers/API/ActivityController.php | 17 +-\n app/Http/Controllers/API/SoftphoneController.php | 9 +-\n app/Http/Controllers/API/UserAutomatedReports/UserAutomatedReportsController.php | 19 +-\n app/Http/Controllers/API/V2/AskAnythingController.php | 2 +-\n app/Http/Controllers/Auth/SocialController.php | 6 +-\n app/Http/Controllers/Kiosk/AutomatedReportsController.php | 38 ++-\n app/Http/Controllers/Kiosk/OrganizationsController.php | 8 +-\n app/Http/Controllers/Kiosk/PartnersController.php | 46 +++\n app/Http/Controllers/Kiosk/SearchController.php | 8 +\n app/Http/Controllers/Kiosk/Teams/OnboardController.php | 24 +-\n app/Http/Controllers/Settings/Teams/IntegrationController.php | 6 +-\n app/Http/Controllers/TeamSetupController.php | 4 +-\n app/Http/Controllers/Telephony/TextMessaging/MessageController.php | 12 +-\n app/Http/Controllers/Telephony/TextMessaging/WebhookController.php | 18 +-\n app/Http/Requests/Settings/Teams/CreateTeamRequest.php | 1 +\n app/Http/Requests/Settings/Teams/EditTeamRequest.php | 1 +\n app/Http/Transformers/ActivityTransformer.php | 4 +-\n app/Http/Transformers/OnDemandActivitiesTransformer.php | 2 +-\n app/Http/Transformers/PartnerTransformer.php | 1 +\n app/Http/Transformers/StageTransformer.php | 6 +-\n app/Http/Transformers/UserTransformer.php | 11 +-\n app/Interactions/Settings/Teams/CreateTeam.php | 3 +\n app/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJob.php | 80 ++++-\n app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php | 119 +++++++\n app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php | 89 +++++\n app/Jobs/Crm/Hubspot/ImportBatchJobTrait.php | 12 +-\n app/Jobs/Crm/UpdateStage.php | 3 +\n app/Jobs/Team/SyncToIntercom.php | 7 +-\n app/Listeners/Teams/SyncIntercomCompany.php | 5 +-\n app/Listeners/Teams/UpdateSalesforceAccount.php | 8 +-\n app/Listeners/Users/SyncIntercom.php | 5 +-\n app/Mail/Reports/AskJiminnyReportExpiringMail.php | 40 +++\n app/Mail/Reports/ReportNotGenerated.php | 41 +++\n app/Models/Activity.php | 25 +-\n app/Models/Activity/Question.php | 14 +-\n app/Models/Activity/Search.php | 7 +\n app/Models/AskAnything/AskAnythingPrompt.php | 6 +\n app/Models/AutomatedReport.php | 10 +\n app/Models/CoachingFeedback.php | 44 ++-\n app/Models/ElasticSearch/ActivityElasticSearchTrait.php | 86 +----\n app/Models/ElasticSearch/OpportunityElasticSearchTrait.php | 71 ----\n app/Models/ElasticSearch/SharedDocumentDeleteTrait.php | 27 --\n app/Models/Partner.php | 13 +\n app/Models/Playlist/Activity.php | 14 +-\n app/Notifications/OwnerInvitedToTrial.php | 14 +-\n app/Policies/UserPolicy.php | 16 +-\n app/Queue/Worker/Worker.php | 3 +-\n app/Repositories/ActivityRepository.php | 13 +-\n app/Repositories/AutomatedReportsRepository.php | 42 ++-\n app/Repositories/TeamRepository.php | 21 +-\n app/Repositories/UserRepository.php | 2 +-\n app/Services/Activity/MeetingBotService.php | 8 +-\n app/Services/ActivityService.php | 111 ++-----\n app/Services/Crm/Hubspot/Service.php | 36 +-\n app/Services/Crm/Hubspot/ServiceTraits/OpportunitySyncTrait.php | 2 +-\n app/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityService.php | 5 +-\n app/Services/Kiosk/AutomatedReports/AutomatedReportsService.php | 49 +--\n app/Services/Kiosk/KioskService.php | 7 +-\n app/Services/Webhook/Triggers/AiScorecardCompletedTrigger.php | 13 +-\n app/UseCases/TeamInsights/ConversationRowMapper.php | 78 +++++\n app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php | 68 ++++\n app/UseCases/TeamInsights/StrictConsentColumnResolver.php | 45 +++\n app/UseCases/TeamInsights/TeamConversationsExport.php | 154 ++++-----\n composer.json | 1 -\n composer.lock | 95 +-----\n config/secure-headers.php | 5 +-\n database/mappings/mapping_activities.json | 16 +\n database/migrations/2026_04_14_000000_add_rockeed_partner.php | 51 +++\n database/migrations/2026_04_22_000000_add_success_email_to_partners.php | 26 ++\n database/migrations/2026_04_27_000000_add_label_to_partners.php | 28 ++\n database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php | 79 +++++\n front-end/package.json | 5 +-\n front-end/src/__mocks__/jiminny.js | 4 +-\n front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js | 9 +\n front-end/src/__mocks__/setup.js | 1 +\n front-end/src/apps/ai-reports-promo.js | 22 ++\n front-end/src/components/AiReports/AiReportsPromo.vue | 22 ++\n front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue | 190 +++++++++++\n front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue | 111 +++++++\n front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue | 103 ++++++\n front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js | 98 ++++++\n .../src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html | 283 ++++++++++++++++\n front-end/src/components/AiReports/Manage/ManageAiReports.vue | 8 +-\n front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue | 228 +++++++++++++\n front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js | 71 ++++\n .../src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html | 217 ++++++++++++\n front-end/src/components/AiReports/constants.js | 7 +\n front-end/src/components/Settings/Kiosk/OrganizationSearch/Organizations.vue | 1 +\n front-end/src/components/Settings/Kiosk/__mocks__/Jiminny.js | 1 +\n front-end/src/components/Settings/Kiosk/modals/EditTeamModal/EditTeamModal.vue | 43 ++-\n front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js | 203 ++++++++++++\n front-end/src/components/Settings/Kiosk/shared/Navigation/Navigation.vue | 3 +\n front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js | 67 ++++\n front-end/src/components/TeamInsights/CoachingFrameworks/AICallScoring/aiCallScoringOverTime.ts | 4 +-\n front-end/src/components/TeamInsights/CoachingFrameworks/UsersList.vue | 2 +-\n front-end/src/components/layout/Sidebar/HelpMenu.vue | 25 +-\n front-end/src/components/layout/Sidebar/Sidebar.vue | 27 +-\n front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js | 94 ++++++\n front-end/src/components/layout/Sidebar/__tests__/__snapshots__/Sidebar.spec.js.snap | 4 +-\n front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js | 204 ++++++++++++\n front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js | 49 +++\n front-end/src/main.js | 1 +\n front-end/src/store/modules/TeamInsights/util.js | 1 +\n front-end/src/store/modules/platform/__tests__/getters.spec.js | 22 ++\n front-end/src/store/modules/platform/getters.js | 3 +\n front-end/src/utils/index.js | 11 +\n front-end/yarn.lock | 21 +-\n phpstan-baseline.neon | 60 ----\n public/pdf/exec-reports/com/coaching-profiles.pdf | Bin 0 -> 1531178 bytes\n public/pdf/exec-reports/com/exec-summary.pdf | Bin 0 -> 2237381 bytes\n public/pdf/exec-reports/com/loss-report.pdf | Bin 0 -> 1955343 bytes\n public/pdf/exec-reports/com/product-feedback.pdf | Bin 0 -> 2184417 bytes\n public/pdf/exec-reports/eu/coaching-profiles.pdf | Bin 0 -> 1528704 bytes\n public/pdf/exec-reports/eu/exec-summary.pdf | Bin 0 -> 2296741 bytes\n public/pdf/exec-reports/eu/loss-report.pdf | Bin 0 -> 1955808 bytes\n public/pdf/exec-reports/eu/product-feedback.pdf | Bin 0 -> 2184083 bytes\n resources/views/emails/reports/ask-jiminny-report-expiring.blade.php | 22 ++\n resources/views/emails/reports/report-not-generated.blade.php | 24 ++\n resources/views/partials/crm/push-summary/html-assembly.blade.php | 2 +-\n routes/api.php | 6 +\n routes/web.php | 4 +\n tests/Feature/Policies/UserPolicyTest.php | 90 ++++-\n tests/Unit/Component/ActivityAnalytics/Service/ActivityAnalyticsServiceTest.php | 40 +++\n tests/Unit/Component/AskAnything/AskAnythingPromptServiceTest.php | 26 ++\n tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php | 276 ++++++++++++++++\n tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php | 375 +++++++++++++++++++++\n tests/Unit/Component/Twilio/Service/SoftPhoneServiceTest.php | 1014 +++++++++++++++++++++++++++++++++++++++++++++++++++++++--\n tests/Unit/Console/Commands/Reports/AutomatedReportsCommandTest.php | 157 ++++++++-\n tests/Unit/Events/Activities/Audio/RecordingEventTest.php | 72 ++++\n tests/Unit/Events/Activities/Softphone/EndedTest.php | 86 +++++\n tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php | 88 +++++\n tests/Unit/Events/Activities/Softphone/StartedTest.php | 86 +++++\n tests/Unit/Http/Controllers/Kiosk/AutomatedReportsControllerTest.php | 99 ++++++\n tests/Unit/Http/Transformers/ActivityTransformerTest.php | 5 +-\n tests/Unit/Http/Transformers/PartnerTransformerTest.php | 34 ++\n tests/Unit/Interactions/Settings/Teams/CreateTeamTest.php | 49 +++\n tests/Unit/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJobTest.php | 106 +++++-\n tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php | 205 ++++++++++++\n tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php | 188 +++++++++++\n tests/Unit/Jobs/Crm/ImportOpportunityBatchTest.php | 2 +-\n tests/Unit/Jobs/Team/SyncToIntercomTest.php | 6 +\n tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php | 59 ++++\n tests/Unit/Listeners/Teams/UpdateSalesforceAccountTest.php | 11 +-\n tests/Unit/Listeners/Users/SyncIntercomTest.php | 59 ++++\n tests/Unit/Mail/Reports/ReportNotGeneratedTest.php | 166 ++++++++++\n tests/Unit/Models/PartnerTest.php | 28 ++\n tests/Unit/Repositories/AutomatedReportsRepositoryTest.php | 68 ++++\n tests/Unit/Services/Activity/MeetingBotServiceRequestRecordingToStopTest.php | 14 +-\n tests/Unit/Services/ActivityServiceTest.php | 391 ++++++++++++++++++++++\n tests/Unit/Services/Crm/Hubspot/ServiceResponseNormalizeTest.php | 68 ++--\n tests/Unit/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityServiceTest.php | 48 +--\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceActivitiesCountTest.php | 16 +-\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceReportGenerationTest.php | 24 +-\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceTest.php | 130 ++++++++\n tests/Unit/Services/KioskServiceTest.php | 8 +\n tests/Unit/Services/Webhook/Triggers/AiScorecardCompletedTriggerTest.php | 6 +-\n tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php | 119 +++++++\n tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php | 108 ++++++\n tests/Unit/UseCases/TeamInsights/TeamConversationsExportTest.php | 342 ++++++++++++++-----\n 186 files changed, 8538 insertions(+), 1233 deletions(-)\n create mode 100644 app/Component/Twilio/TwilioRepository.php\n delete mode 100644 app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php\n create mode 100644 app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php\n delete mode 100644 app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php\n create mode 100644 app/Http/Controllers/Kiosk/PartnersController.php\n create mode 100644 app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php\n create mode 100644 app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php\n create mode 100644 app/Mail/Reports/AskJiminnyReportExpiringMail.php\n create mode 100644 app/Mail/Reports/ReportNotGenerated.php\n delete mode 100644 app/Models/ElasticSearch/SharedDocumentDeleteTrait.php\n create mode 100644 app/UseCases/TeamInsights/ConversationRowMapper.php\n create mode 100644 app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php\n create mode 100644 app/UseCases/TeamInsights/StrictConsentColumnResolver.php\n create mode 100644 database/migrations/2026_04_14_000000_add_rockeed_partner.php\n create mode 100644 database/migrations/2026_04_22_000000_add_success_email_to_partners.php\n create mode 100644 database/migrations/2026_04_27_000000_add_label_to_partners.php\n create mode 100644 database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php\n create mode 100644 front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js\n create mode 100644 front-end/src/apps/ai-reports-promo.js\n create mode 100644 front-end/src/components/AiReports/AiReportsPromo.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js\n create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html\n create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue\n create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js\n create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html\n create mode 100644 front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js\n create mode 100644 front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js\n create mode 100644 front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js\n create mode 100644 front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js\n create mode 100644 front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js\n create mode 100644 front-end/src/store/modules/platform/__tests__/getters.spec.js\n create mode 100644 public/pdf/exec-reports/com/coaching-profiles.pdf\n create mode 100644 public/pdf/exec-reports/com/exec-summary.pdf\n create mode 100644 public/pdf/exec-reports/com/loss-report.pdf\n create mode 100644 public/pdf/exec-reports/com/product-feedback.pdf\n create mode 100644 public/pdf/exec-reports/eu/coaching-profiles.pdf\n create mode 100644 public/pdf/exec-reports/eu/exec-summary.pdf\n create mode 100644 public/pdf/exec-reports/eu/loss-report.pdf\n create mode 100644 public/pdf/exec-reports/eu/product-feedback.pdf\n create mode 100644 resources/views/emails/reports/ask-jiminny-report-expiring.blade.php\n create mode 100644 resources/views/emails/reports/report-not-generated.blade.php\n create mode 100644 tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php\n create mode 100644 tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php\n create mode 100644 tests/Unit/Events/Activities/Audio/RecordingEventTest.php\n create mode 100644 tests/Unit/Events/Activities/Softphone/EndedTest.php\n create mode 100644 tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php\n create mode 100644 tests/Unit/Events/Activities/Softphone/StartedTest.php\n create mode 100644 tests/Unit/Http/Transformers/PartnerTransformerTest.php\n create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php\n create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php\n create mode 100644 tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php\n create mode 100644 tests/Unit/Listeners/Users/SyncIntercomTest.php\n create mode 100644 tests/Unit/Mail/Reports/ReportNotGeneratedTest.php\n create mode 100644 tests/Unit/Models/PartnerTest.php\n create mode 100644 tests/Unit/Services/ActivityServiceTest.php\n create mode 100644 tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php\n create mode 100644 tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull \nremote: Enumerating objects: 628, done.\nremote: Counting objects: 100% (331/331), done.\nremote: Compressing objects: 100% (63/63), done.\nremote: Total 628 (delta 280), reused 274 (delta 266), pack-reused 297 (from 1)\nReceiving objects: 100% (628/628), 186.75 KiB | 1.23 MiB/s, done.\nResolving deltas: 100% (391/391), completed with 57 local objects.\nFrom github.com:jiminny/app\n ad2ce76737..12295204cf master -> origin/master\n 14f54b5be2..5e7646e5f9 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3\n b167b19973..acba55cf38 JY-20289-api-tests -> origin/JY-20289-api-tests\n f23cfee7c3..e5a3ec5dba JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null\n af59d60926..766efba1c5 JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import\n * [new branch] JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering\n 1737b7c528..c57e71e763 JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall\n * [new branch] JY-20671-anyvan-twilio-s3-recordings-ftech -> origin/JY-20671-anyvan-twilio-s3-recordings-ftech\n + ba181441c6...20a74137b0 JY-20742-mcp-poc -> origin/JY-20742-mcp-poc (forced update)\n * [new branch] JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue\n * [new branch] JY-20816-calendar-events-diplication -> origin/JY-20816-calendar-events-diplication\n * [new branch] desktop-app -> origin/desktop-app\n 4c4c974e46..185442c26e make-claude-great-again -> origin/make-claude-great-again\n * [new branch] mcp-tools-schemas -> origin/mcp-tools-schemas\nUpdating ad2ce76737..12295204cf\nFast-forward\n app/Component/Encoding/Job/AnalyzeTrackChannelsJob.php | 2 +-\n app/Component/Transcription/TranscriptionProcessor/AssemblyAI/Services/SubmitAudioFileService.php | 66 ++----------------------------------------------------------------\n app/Console/Commands/Tracks/CleanupActivityTracksCommand.php | 24 +++++++++++++++++-------\n tests/Unit/Console/Commands/Tracks/CleanupActivityTracksCommandTest.php | 40 +++++++++++++++++++++++++++++-----------\n tests/Unit/fixtures/assembly_ai_transcript_response.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_channel_diarization.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language_error.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language_not_ready.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_language_post.json | 1 -\n tests/Unit/fixtures/assembly_ai_transcript_response_without_utterances.json | 1 -\n 11 files changed, 49 insertions(+), 90 deletions(-)\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20818-move-AJ-reports-to-separated-datadog-metric\nSwitched to a new branch 'JY-20818-move-AJ-reports-to-separated-datadog-metric'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5663 files in 83.615 seconds, 67.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ ;xd\ndocker exec -it docker_lamp_1 bash -c \"mv /usr/local/etc/php/conf.d/xdebug.ini ~/xdebug.ini\"\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 supervisorctl restart all\njiminny-worker-processing-2:jiminny-worker-processing-2_00: stopped\njiminny-worker-processing-3:jiminny-worker-processing-3_00: stopped\njiminny-worker-processing-4:jiminny-worker-processing-4_00: stopped\njiminny-worker-processing-5:jiminny-worker-processing-5_00: stopped\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: stopped\nworker-analytics:worker-analytics_00: stopped\nworker-crm-update:worker-crm-update_00: stopped\nworker-download:worker-download_00: stopped\nworker-nudges:worker-nudges_00: stopped\nartisan-schedule:artisan-schedule_00: stopped\nworker-calendar:worker-calendar_00: stopped\nworker-crm-sync:worker-crm-sync_00: stopped\njiminny-worker-processing-1:jiminny-worker-processing-1_00: stopped\nworker:worker_00: stopped\nworker-emails:worker-emails_00: stopped\nworker-audio:worker-audio_00: stopped\nworker-conferences:worker-conferences_00: stopped\nworker-es-update:worker-es-update_00: stopped\nartisan-schedule:artisan-schedule_00: started\njiminny-worker-processing-1:jiminny-worker-processing-1_00: started\njiminny-worker-processing-2:jiminny-worker-processing-2_00: started\njiminny-worker-processing-3:jiminny-worker-processing-3_00: started\njiminny-worker-processing-4:jiminny-worker-processing-4_00: started\njiminny-worker-processing-5:jiminny-worker-processing-5_00: started\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: started\nworker:worker_00: started\nworker-analytics:worker-analytics_00: started\nworker-audio:worker-audio_00: started\nworker-calendar:worker-calendar_00: started\nworker-conferences:worker-conferences_00: started\nworker-crm-sync:worker-crm-sync_00: started\nworker-crm-update:worker-crm-update_00: started\nworker-download:worker-download_00: started\nworker-emails:worker-emails_00: started\nworker-es-update:worker-es-update_00: started\nworker-nudges:worker-nudges_00: started\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 php -v\nPHP 8.3.30 (cli) (built: Mar 16 2026 22:32:32) (NTS)\nCopyright (c) The PHP Group\nZend Engine v4.3.30, Copyright (c) Zend Technologies\n with Zend OPcache v8.3.30, Copyright (c), by Zend Technologies\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5663 files in 42.875 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ git status\nOn branch master\nYour branch is up to date with 'origin/master'.\n\nChanges not staged for commit:\n (use \"git add <file>...\" to update what will be committed)\n (use \"git restore <file>...\" to discard changes in working directory)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tmodified: .env.local\n\nUntracked files:\n (use \"git add <file>...\" to include in what will be committed)\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.nikilocal\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\t.env.other\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tWEBHOOK_FILTERING_IMPLEMENTATION.md\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Crm/Hubspot/SimulateWebhooksCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tapp/Console/Commands/Reports/CreateMockAskJiminnyReportResultCommand.php\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tids.txt\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\tpublic/favicon.ico\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\traw_sql_query.sql\n\u0000\u0000\u0000\u0000\u0000\u0000\u0000\ttests/Unit/Policies/CanAccessAiReportsTest.php\n\nno changes added to commit (use \"git add\" and/or \"git commit -a\")\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull\nremote: Enumerating objects: 15, done.\nremote: Counting objects: 100% (15/15), done.\nremote: Compressing objects: 100% (2/2), done.\nremote: Total 15 (delta 13), reused 15 (delta 13), pack-reused 0 (from 0)\nUnpacking objects: 100% (15/15), 1.28 KiB | 72.00 KiB/s, done.\nFrom github.com:jiminny/app\n c57e71e763..8743fea32e JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall\n * [new branch] JY-20819-increase-download-transctip-rate-limit -> origin/JY-20819-increase-download-transctip-rate-limit\nAlready up to date.\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull \nremote: Enumerating objects: 180, done.\nremote: Counting objects: 100% (179/179), done.\nremote: Compressing objects: 100% (55/55), done.\nremote: Total 180 (delta 127), reused 165 (delta 119), pack-reused 1 (from 1)\nReceiving objects: 100% (180/180), 57.50 KiB | 2.74 MiB/s, done.\nResolving deltas: 100% (127/127), completed with 47 local objects.\nFrom github.com:jiminny/app\n 12295204cf..35f036ace6 master -> origin/master\n * [new branch] JY-18091-upgrade-to-php-8-5 -> origin/JY-18091-upgrade-to-php-8-5\n 5f21965da8..497fbc85c2 JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering\n f029263118..6ed9e2bb13 JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue\n * [new branch] JY-20817-fix-deleting-s3-directories -> origin/JY-20817-fix-deleting-s3-directories\n * [new branch] JY-20820-es-reindex-stream-model-hydration -> origin/JY-20820-es-reindex-stream-model-hydration\n + ca92730ec5...2c8a1d0856 desktop-app -> origin/desktop-app (forced update)\n 8425d4e0de..89b45ec8b0 mcp-tools-schemas -> origin/mcp-tools-schemas\nUpdating 12295204cf..35f036ace6\nFast-forward\n app/Component/Datadog/Constants.php | 1 +\n app/Providers/RouteServiceProvider.php | 2 +-\n app/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackService.php | 13 +++++++++++++\n tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackServiceTest.php | 54 +++++++++++++++++++++++++++++++++++++++++++++++-------\n 4 files changed, 62 insertions(+), 8 deletions(-)\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ gbr \n* master\n JY-20818-move-AJ-reports-to-separated-datadog-metric\n JY-20773-fix-automated-reports-user-pilot-tracking\n JY-20157-AJ-report-not-send-notification\n JY-20508-notify-before-AJ-report-expiration\n JY-20372-ai-reports-promotion-pages\n JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null\n JY-20738-debug-AJ-tracking-UP\n a\n JY-18909-automated-reports-ask-jiminny\n JY-20692-fix-integration-app-token-auth-response-change\n JY-20553-debug-crm-sync-delays\n JY-20698-fix-SF-activity-types-on-new-playbook\n JY-20543-AJ-report-tracking\n JY-20384-handle-auto-sync-with-no-access-to-event-type\n JY-20458-ask-jiminny-user-definitions\n JY-19666-fix-import-contacts-account-association\n JY-19666-HS-import-contacts-and-accounts-batch-job\n JY-20458-Ask-Jiminny-Reports\n JY-20200-batch-update-CRM-objects-Salesforce\n JY-19666-HS-webhooks-add-contact-and-company\n JY-20348-trigger-setup-DI-layout-on-team-creation\n JY-20326-refactor-info-message-in-command\n JY-20317-fix-auto-log-delay-issue-on-all-channels-disabled\n JY-20312-remove-on-update-change-last-synced-at-crm-configurations\n JY-20306-SF-skip-auto-sync-for-task-based-playbook\n JY-20192-remove-deleted-team-from-saved-search-filters\n JY-20197-import-opportunity-batch-job\n JY-20293-enable-status-field-for-pipedrive-deals\n JY-20191-remove-commands-interactive-prompts\n JY-20118-change-default-sync-strategy\n JY-20183-add-cache-on-auto-log-delay\n JY-20197-add-import-opportunity-batch-job\n 20118-hs-opportunity-make-webhook-strategy-default\n JY-20118-make-default-hs-opportunity-sync-strategy-webhook-based\n JY-20196-handle-opportunity-without-note\n JY-20118-improve-opportunity-import\n JY-20189-handle-activity-search-on-deleted-groups\n JY-20160\n JY-20145-filter-out-converted-leads-when-matching\n JY-20150-skip-push-summary-on-summary-ready-if-autolog\n JY-20132-fix-note-encoding\n JY-19792-clean-logs\n JY-20117-fix-sync-profile-fields-on-empty-fields\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20725-handle-HS-search-rate-limit \nSwitched to a new branch 'JY-20725-handle-HS-search-rate-limit'\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ ;xd\ndocker exec -it docker_lamp_1 bash -c \"mv /usr/local/etc/php/conf.d/xdebug.ini ~/xdebug.ini\"\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 supervisorctl restart all\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: stopped\njiminny-worker-processing-2:jiminny-worker-processing-2_00: stopped\njiminny-worker-processing-3:jiminny-worker-processing-3_00: stopped\njiminny-worker-processing-4:jiminny-worker-processing-4_00: stopped\njiminny-worker-processing-5:jiminny-worker-processing-5_00: stopped\nworker-analytics:worker-analytics_00: stopped\nworker-crm-update:worker-crm-update_00: stopped\nworker-download:worker-download_00: stopped\nworker-nudges:worker-nudges_00: stopped\nartisan-schedule:artisan-schedule_00: stopped\nworker-emails:worker-emails_00: stopped\nworker:worker_00: stopped\nworker-calendar:worker-calendar_00: stopped\njiminny-worker-processing-1:jiminny-worker-processing-1_00: stopped\nworker-crm-sync:worker-crm-sync_00: stopped\nworker-audio:worker-audio_00: stopped\nworker-conferences:worker-conferences_00: stopped\nworker-es-update:worker-es-update_00: stopped\nartisan-schedule:artisan-schedule_00: started\njiminny-worker-processing-1:jiminny-worker-processing-1_00: started\njiminny-worker-processing-2:jiminny-worker-processing-2_00: started\njiminny-worker-processing-3:jiminny-worker-processing-3_00: started\njiminny-worker-processing-4:jiminny-worker-processing-4_00: started\njiminny-worker-processing-5:jiminny-worker-processing-5_00: started\njiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: started\nworker:worker_00: started\nworker-analytics:worker-analytics_00: started\nworker-audio:worker-audio_00: started\nworker-calendar:worker-calendar_00: started\nworker-conferences:worker-conferences_00: started\nworker-crm-sync:worker-crm-sync_00: started\nworker-crm-update:worker-crm-update_00: started\nworker-download:worker-download_00: started\nworker-emails:worker-emails_00: started\nworker-es-update:worker-es-update_00: started\nworker-nudges:worker-nudges_00: started\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\ndocker exec -it docker_lamp_1 php -v\nPHP 8.3.30 (cli) (built: Mar 16 2026 22:32:32) (NTS)\nCopyright (c) The PHP Group\nZend Engine v4.3.30, Copyright (c) Zend Technologies\n with Zend OPcache v8.3.30, Copyright (c), by Zend Technologies\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5666/5666 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n 1) app/Jobs/Crm/MatchActivityCrmData.php (ordered_class_elements)\n ---------- begin diff ----------\n--- /home/jiminny/app/Jobs/Crm/MatchActivityCrmData.php\n+++ /home/jiminny/app/Jobs/Crm/MatchActivityCrmData.php\n@@ -29,24 +29,14 @@\n use InteractsWithQueue;\n use SerializesModels;\n \n+ private const int RETRY_WINDOW_MINUTES = 120;\n+\n public int $maxExceptions = 3;\n \n- private const int RETRY_WINDOW_MINUTES = 120;\n-\n private int $activityId;\n private ?Configuration $fromConfiguration;\n private bool $remoteSearch;\n \n- public function middleware(): array\n- {\n- return [new HandleHubspotRateLimit()];\n- }\n-\n- public function retryUntil(): \\DateTimeInterface\n- {\n- return now()->addMinutes(self::RETRY_WINDOW_MINUTES);\n- }\n-\n public function __construct(\n int $activityId,\n ?Configuration $fromConfiguration = null,\n@@ -57,6 +47,16 @@\n $this->remoteSearch = $remoteSearch;\n \n $this->onQueue(Constants::QUEUE_ANALYTICS_LOW);\n+ }\n+\n+ public function middleware(): array\n+ {\n+ return [new HandleHubspotRateLimit()];\n+ }\n+\n+ public function retryUntil(): \\DateTimeInterface\n+ {\n+ return now()->addMinutes(self::RETRY_WINDOW_MINUTES);\n }\n \n public function uniqueId(): string\n\n ----------- end diff -----------\n\n 2) app/Services/Crm/Hubspot/HubspotClientInterface.php (phpdoc_order, phpdoc_separation)\n ---------- begin diff ----------\n--- /home/jiminny/app/Services/Crm/Hubspot/HubspotClientInterface.php\n+++ /home/jiminny/app/Services/Crm/Hubspot/HubspotClientInterface.php\n@@ -46,9 +46,11 @@\n *\n * @param string $objectType The object type ('deals', 'companies', 'contacts', 'calls')\n * @param array<string, mixed> $payload The search payload with filters, sorts, properties, etc.\n- * @return array The search response with 'results', 'total', 'paging' keys\n+ *\n * @throws RateLimitException When rate limit is hit\n * @throws HubspotException On API errors\n+ *\n+ * @return array The search response with 'results', 'total', 'paging' keys\n */\n public function search(string $objectType, array $payload): array;\n }\n\n ----------- end diff -----------\n\n 3) app/Services/Crm/Hubspot/Client.php (phpdoc_order, phpdoc_separation, blank_line_before_statement)\n ---------- begin diff ----------\n--- /home/jiminny/app/Services/Crm/Hubspot/Client.php\n+++ /home/jiminny/app/Services/Crm/Hubspot/Client.php\n@@ -69,10 +69,12 @@\n * the cache near expiry are not delayed longer than necessary.\n *\n * @template T\n+ *\n * @param callable(): T $apiCall The API call to execute\n- * @return T The result of the API call\n *\n * @throws RateLimitException When rate limit is hit or cached rate limit is active\n+ *\n+ * @return T The result of the API call\n */\n private function executeRequest(callable $apiCall)\n {\n@@ -81,6 +83,7 @@\n $cachedExpiresAt = Redis::get($cacheKey);\n if (is_string($cachedExpiresAt) && is_numeric($cachedExpiresAt)) {\n $remaining = max(1, (int) $cachedExpiresAt - time());\n+\n throw new RateLimitException(\n 'Hubspot rate limit (cached circuit-breaker)',\n $remaining,\n@@ -232,9 +235,11 @@\n *\n * @param string $objectType The object type ('deals', 'companies', 'contacts', 'calls')\n * @param array<string, mixed> $payload The search payload with filters, sorts, properties, etc.\n- * @return array The search response with 'results', 'total', 'paging' keys\n+ *\n * @throws RateLimitException When rate limit is hit\n * @throws HubspotException On API errors\n+ *\n+ * @return array The search response with 'results', 'total', 'paging' keys\n */\n public function search(string $objectType, array $payload): array\n {\n\n ----------- end diff -----------\n\n 4) app/Console/Commands/JiminnyDebugCommand.php (statement_indentation)\n ---------- begin diff ----------\n--- /home/jiminny/app/Console/Commands/JiminnyDebugCommand.php\n+++ /home/jiminny/app/Console/Commands/JiminnyDebugCommand.php\n@@ -359,11 +359,11 @@\n $crmService = $crmResolver->prepareCrmService();\n \n for ($i = 0 ; $i < 3; $i++) {\n-// if ($i % 25 === 0) {\n-// $this->info(\"Syncing opportunity {$i}\");\n- $this->info(\"Matching contact {$i}\");\n-// }\n-// $crmService->syncOpportunity('374720564');\n+ // if ($i % 25 === 0) {\n+ // $this->info(\"Syncing opportunity {$i}\");\n+ $this->info(\"Matching contact {$i}\");\n+ // }\n+ // $crmService->syncOpportunity('374720564');\n $crmService->matchByName('Robot');\n }\n }\n\n ----------- end diff -----------\n\n\nFixed 4 of 5666 files in 146.870 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ csfix \ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5666/5666 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5666 files in 106.192 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ csfix\ndocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff \nPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.\nPHP runtime: 8.3.30\nRunning analysis on 7 cores with 10 files per process.\nParallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!\nLoaded config default from \".php-cs-fixer.dist.php\".\n 5666/5666 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%\n\n\nFixed 0 of 5666 files in 66.457 seconds, 60.00 MB memory used\n\nWhat's next:\n Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1\n Learn more at https://docs.docker.com/go/debug-cli/\nlukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $","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":"APP (-zsh)","depth":1,"bounds":{"left":0.47430557,"top":0.033333335,"width":0.05138889,"height":0.017777778},"on_screen":true,"role_description":"text"}]...
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Last login: Thu May 7 09:44:56 on ttys007
Poetry Last login: Thu May 7 09:44:56 on ttys007
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
Poetry could not find a pyproject.toml file in /Users/lukas/jiminny/app or its parents
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20773-fix-automated-reports-user-pilot-tracking) $ git status
On branch master
Your branch is up to date with 'origin/master'.
Changes not staged for commit:
(use "git add <file>..." to update what will be committed)
(use "git restore <file>..." to discard changes in working directory)
modified: .env.local
modified: app/Console/Commands/JiminnyDebugCommand.php
modified: app/Jobs/Team/SyncToIntercom.php
modified: app/Services/PlaybackService.php
modified: config/logging.php
modified: resources/views/partials/crm/push-summary/html-assembly.blade.php
Untracked files:
(use "git add <file>..." to include in what will be committed)
.env.nikilocal
.env.other
WEBHOOK_FILTERING_IMPLEMENTATION.md
app/Console/Commands/Crm/Hubspot/SimulateWebhooksCommand.php
app/Console/Commands/Reports/CreateMockAskJiminnyReportResultCommand.php
ids.txt
public/favicon.ico
raw_sql_query.sql
tests/Unit/Policies/CanAccessAiReportsTest.php
no changes added to commit (use "git add" and/or "git commit -a")
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 1482, done.
remote: Counting objects: 100% (481/481), done.
remote: Compressing objects: 100% (191/191), done.
remote: Total 1482 (delta 349), reused 305 (delta 289), pack-reused 1001 (from 4)
Receiving objects: 100% (1482/1482), 1017.97 KiB | 1.44 MiB/s, done.
Resolving deltas: 100% (877/877), completed with 96 local objects.
From github.com:jiminny/app
83b628967a..ad2ce76737 master -> origin/master
1ee8cbcb7b..14f54b5be2 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3
5662c3b32f..b167b19973 JY-20289-api-tests -> origin/JY-20289-api-tests
b40408cfad..f23cfee7c3 JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null
* [new branch] JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import
* [new branch] JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall
* [new branch] JY-20662-remove-word-boost -> origin/JY-20662-remove-word-boost
* [new branch] JY-20742-mcp-poc -> origin/JY-20742-mcp-poc
* [new branch] make-claude-great-again -> origin/make-claude-great-again
* [new branch] secfix/composer-20260507 -> origin/secfix/composer-20260507
* [new branch] secfix/npm-20260507 -> origin/secfix/npm-20260507
Updating 83b628967a..ad2ce76737
error: Your local changes to the following files would be overwritten by merge:
app/Jobs/Team/SyncToIntercom.php
resources/views/partials/crm/push-summary/html-assembly.blade.php
Please commit your changes or stash them before you merge.
Aborting
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
Updating 83b628967a..ad2ce76737
error: Your local changes to the following files would be overwritten by merge:
app/Jobs/Team/SyncToIntercom.php
resources/views/partials/crm/push-summary/html-assembly.blade.php
Please commit your changes or stash them before you merge.
Aborting
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
Updating 83b628967a..ad2ce76737
error: Your local changes to the following files would be overwritten by merge:
app/Jobs/Team/SyncToIntercom.php
Please commit your changes or stash them before you merge.
Aborting
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
Updating 83b628967a..ad2ce76737
Fast-forward
.cursor/rules/frontend-conventions.mdc | 23 ++
.env.production-eu | 2 +-
.env.staging | 2 +-
Makefile | 10 +
app/Component/ActivityAnalytics/Service/ActivityAnalyticsService.php | 6 +-
app/Component/AiAutomation/Repositories/AiTemplateFieldsRepository.php | 32 +-
app/Component/AiCallScoring/Repositories/AiScorecardRepository.php | 56 ++--
app/Component/AskAnything/AskAnythingPromptService.php | 3 +
app/Component/Transcription/Job/FinishTranscriptionJob.php | 37 ++-
app/Component/Transcription/TranscriptionProcessor/Gong/Gong.php | 18 +-
app/Component/Twilio/Conference/ConferenceManager/SoftPhoneManager.php | 4 +-
app/Component/Twilio/Service/SoftPhoneService.php | 124 ++++---
app/Component/Twilio/TwilioRepository.php | 27 ++
app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php | 59 ----
app/Console/Commands/Reports/AutomatedReportsCommand.php | 122 +++++--
app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php | 200 ++++++++++++
app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php | 60 ----
app/Console/Commands/Users/SyncToIntercom.php | 4 +-
app/Console/Kernel.php | 3 +-
app/Contracts/ES/Events/UpdateMultipleEntities.php | 4 -
app/Contracts/ES/Events/UpdateSingleEntity.php | 4 -
app/Contracts/Repositories/TeamRepository.php | 3 +-
app/Events/Activities/ActivityUpdated.php | 10 +-
app/Events/Activities/Audio/RecordingEvent.php | 6 +-
app/Events/Activities/Softphone/Ended.php | 8 +-
app/Events/Activities/Softphone/SoftphoneEvent.php | 24 +-
app/Events/Activities/Softphone/Started.php | 8 +-
app/Http/Controllers/API/ActivityController.php | 17 +-
app/Http/Controllers/API/SoftphoneController.php | 9 +-
app/Http/Controllers/API/UserAutomatedReports/UserAutomatedReportsController.php | 19 +-
app/Http/Controllers/API/V2/AskAnythingController.php | 2 +-
app/Http/Controllers/Auth/SocialController.php | 6 +-
app/Http/Controllers/Kiosk/AutomatedReportsController.php | 38 ++-
app/Http/Controllers/Kiosk/OrganizationsController.php | 8 +-
app/Http/Controllers/Kiosk/PartnersController.php | 46 +++
app/Http/Controllers/Kiosk/SearchController.php | 8 +
app/Http/Controllers/Kiosk/Teams/OnboardController.php | 24 +-
app/Http/Controllers/Settings/Teams/IntegrationController.php | 6 +-
app/Http/Controllers/TeamSetupController.php | 4 +-
app/Http/Controllers/Telephony/TextMessaging/MessageController.php | 12 +-
app/Http/Controllers/Telephony/TextMessaging/WebhookController.php | 18 +-
app/Http/Requests/Settings/Teams/CreateTeamRequest.php | 1 +
app/Http/Requests/Settings/Teams/EditTeamRequest.php | 1 +
app/Http/Transformers/ActivityTransformer.php | 4 +-
app/Http/Transformers/OnDemandActivitiesTransformer.php | 2 +-
app/Http/Transformers/PartnerTransformer.php | 1 +
app/Http/Transformers/StageTransformer.php | 6 +-
app/Http/Transformers/UserTransformer.php | 11 +-
app/Interactions/Settings/Teams/CreateTeam.php | 3 +
app/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJob.php | 80 ++++-
app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php | 119 +++++++
app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php | 89 +++++
app/Jobs/Crm/Hubspot/ImportBatchJobTrait.php | 12 +-
app/Jobs/Crm/UpdateStage.php | 3 +
app/Jobs/Team/SyncToIntercom.php | 7 +-
app/Listeners/Teams/SyncIntercomCompany.php | 5 +-
app/Listeners/Teams/UpdateSalesforceAccount.php | 8 +-
app/Listeners/Users/SyncIntercom.php | 5 +-
app/Mail/Reports/AskJiminnyReportExpiringMail.php | 40 +++
app/Mail/Reports/ReportNotGenerated.php | 41 +++
app/Models/Activity.php | 25 +-
app/Models/Activity/Question.php | 14 +-
app/Models/Activity/Search.php | 7 +
app/Models/AskAnything/AskAnythingPrompt.php | 6 +
app/Models/AutomatedReport.php | 10 +
app/Models/CoachingFeedback.php | 44 ++-
app/Models/ElasticSearch/ActivityElasticSearchTrait.php | 86 +----
app/Models/ElasticSearch/OpportunityElasticSearchTrait.php | 71 ----
app/Models/ElasticSearch/SharedDocumentDeleteTrait.php | 27 --
app/Models/Partner.php | 13 +
app/Models/Playlist/Activity.php | 14 +-
app/Notifications/OwnerInvitedToTrial.php | 14 +-
app/Policies/UserPolicy.php | 16 +-
app/Queue/Worker/Worker.php | 3 +-
app/Repositories/ActivityRepository.php | 13 +-
app/Repositories/AutomatedReportsRepository.php | 42 ++-
app/Repositories/TeamRepository.php | 21 +-
app/Repositories/UserRepository.php | 2 +-
app/Services/Activity/MeetingBotService.php | 8 +-
app/Services/ActivityService.php | 111 ++-----
app/Services/Crm/Hubspot/Service.php | 36 +-
app/Services/Crm/Hubspot/ServiceTraits/OpportunitySyncTrait.php | 2 +-
app/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityService.php | 5 +-
app/Services/Kiosk/AutomatedReports/AutomatedReportsService.php | 49 +--
app/Services/Kiosk/KioskService.php | 7 +-
app/Services/Webhook/Triggers/AiScorecardCompletedTrigger.php | 13 +-
app/UseCases/TeamInsights/ConversationRowMapper.php | 78 +++++
app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php | 68 ++++
app/UseCases/TeamInsights/StrictConsentColumnResolver.php | 45 +++
app/UseCases/TeamInsights/TeamConversationsExport.php | 154 ++++-----
composer.json | 1 -
composer.lock | 95 +-----
config/secure-headers.php | 5 +-
database/mappings/mapping_activities.json | 16 +
database/migrations/2026_04_14_000000_add_rockeed_partner.php | 51 +++
database/migrations/2026_04_22_000000_add_success_email_to_partners.php | 26 ++
database/migrations/2026_04_27_000000_add_label_to_partners.php | 28 ++
database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php | 79 +++++
front-end/package.json | 5 +-
front-end/src/__mocks__/jiminny.js | 4 +-
front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js | 9 +
front-end/src/__mocks__/setup.js | 1 +
front-end/src/apps/ai-reports-promo.js | 22 ++
front-end/src/components/AiReports/AiReportsPromo.vue | 22 ++
front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue | 190 +++++++++++
front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue | 111 +++++++
front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue | 103 ++++++
front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js | 98 ++++++
.../src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html | 283 ++++++++++++++++
front-end/src/components/AiReports/Manage/ManageAiReports.vue | 8 +-
front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue | 228 +++++++++++++
front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js | 71 ++++
.../src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html | 217 ++++++++++++
front-end/src/components/AiReports/constants.js | 7 +
front-end/src/components/Settings/Kiosk/OrganizationSearch/Organizations.vue | 1 +
front-end/src/components/Settings/Kiosk/__mocks__/Jiminny.js | 1 +
front-end/src/components/Settings/Kiosk/modals/EditTeamModal/EditTeamModal.vue | 43 ++-
front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js | 203 ++++++++++++
front-end/src/components/Settings/Kiosk/shared/Navigation/Navigation.vue | 3 +
front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js | 67 ++++
front-end/src/components/TeamInsights/CoachingFrameworks/AICallScoring/aiCallScoringOverTime.ts | 4 +-
front-end/src/components/TeamInsights/CoachingFrameworks/UsersList.vue | 2 +-
front-end/src/components/layout/Sidebar/HelpMenu.vue | 25 +-
front-end/src/components/layout/Sidebar/Sidebar.vue | 27 +-
front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js | 94 ++++++
front-end/src/components/layout/Sidebar/__tests__/__snapshots__/Sidebar.spec.js.snap | 4 +-
front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js | 204 ++++++++++++
front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js | 49 +++
front-end/src/main.js | 1 +
front-end/src/store/modules/TeamInsights/util.js | 1 +
front-end/src/store/modules/platform/__tests__/getters.spec.js | 22 ++
front-end/src/store/modules/platform/getters.js | 3 +
front-end/src/utils/index.js | 11 +
front-end/yarn.lock | 21 +-
phpstan-baseline.neon | 60 ----
public/pdf/exec-reports/com/coaching-profiles.pdf | Bin 0 -> 1531178 bytes
public/pdf/exec-reports/com/exec-summary.pdf | Bin 0 -> 2237381 bytes
public/pdf/exec-reports/com/loss-report.pdf | Bin 0 -> 1955343 bytes
public/pdf/exec-reports/com/product-feedback.pdf | Bin 0 -> 2184417 bytes
public/pdf/exec-reports/eu/coaching-profiles.pdf | Bin 0 -> 1528704 bytes
public/pdf/exec-reports/eu/exec-summary.pdf | Bin 0 -> 2296741 bytes
public/pdf/exec-reports/eu/loss-report.pdf | Bin 0 -> 1955808 bytes
public/pdf/exec-reports/eu/product-feedback.pdf | Bin 0 -> 2184083 bytes
resources/views/emails/reports/ask-jiminny-report-expiring.blade.php | 22 ++
resources/views/emails/reports/report-not-generated.blade.php | 24 ++
resources/views/partials/crm/push-summary/html-assembly.blade.php | 2 +-
routes/api.php | 6 +
routes/web.php | 4 +
tests/Feature/Policies/UserPolicyTest.php | 90 ++++-
tests/Unit/Component/ActivityAnalytics/Service/ActivityAnalyticsServiceTest.php | 40 +++
tests/Unit/Component/AskAnything/AskAnythingPromptServiceTest.php | 26 ++
tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php | 276 ++++++++++++++++
tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php | 375 +++++++++++++++++++++
tests/Unit/Component/Twilio/Service/SoftPhoneServiceTest.php | 1014 +++++++++++++++++++++++++++++++++++++++++++++++++++++++--
tests/Unit/Console/Commands/Reports/AutomatedReportsCommandTest.php | 157 ++++++++-
tests/Unit/Events/Activities/Audio/RecordingEventTest.php | 72 ++++
tests/Unit/Events/Activities/Softphone/EndedTest.php | 86 +++++
tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php | 88 +++++
tests/Unit/Events/Activities/Softphone/StartedTest.php | 86 +++++
tests/Unit/Http/Controllers/Kiosk/AutomatedReportsControllerTest.php | 99 ++++++
tests/Unit/Http/Transformers/ActivityTransformerTest.php | 5 +-
tests/Unit/Http/Transformers/PartnerTransformerTest.php | 34 ++
tests/Unit/Interactions/Settings/Teams/CreateTeamTest.php | 49 +++
tests/Unit/Jobs/AutomatedReports/RequestGenerateAskJiminnyReportJobTest.php | 106 +++++-
tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php | 205 ++++++++++++
tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php | 188 +++++++++++
tests/Unit/Jobs/Crm/ImportOpportunityBatchTest.php | 2 +-
tests/Unit/Jobs/Team/SyncToIntercomTest.php | 6 +
tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php | 59 ++++
tests/Unit/Listeners/Teams/UpdateSalesforceAccountTest.php | 11 +-
tests/Unit/Listeners/Users/SyncIntercomTest.php | 59 ++++
tests/Unit/Mail/Reports/ReportNotGeneratedTest.php | 166 ++++++++++
tests/Unit/Models/PartnerTest.php | 28 ++
tests/Unit/Repositories/AutomatedReportsRepositoryTest.php | 68 ++++
tests/Unit/Services/Activity/MeetingBotServiceRequestRecordingToStopTest.php | 14 +-
tests/Unit/Services/ActivityServiceTest.php | 391 ++++++++++++++++++++++
tests/Unit/Services/Crm/Hubspot/ServiceResponseNormalizeTest.php | 68 ++--
tests/Unit/Services/Kiosk/AutomatedReports/AskJiminnyReportActivityServiceTest.php | 48 +--
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceActivitiesCountTest.php | 16 +-
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceReportGenerationTest.php | 24 +-
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsServiceTest.php | 130 ++++++++
tests/Unit/Services/KioskServiceTest.php | 8 +
tests/Unit/Services/Webhook/Triggers/AiScorecardCompletedTriggerTest.php | 6 +-
tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php | 119 +++++++
tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php | 108 ++++++
tests/Unit/UseCases/TeamInsights/TeamConversationsExportTest.php | 342 ++++++++++++++-----
186 files changed, 8538 insertions(+), 1233 deletions(-)
create mode 100644 app/Component/Twilio/TwilioRepository.php
delete mode 100644 app/Console/Commands/CoachingFeedbacksUpdateEsActivities.php
create mode 100644 app/Console/Commands/RunAiCallScoringForUntypedActivitiesCommand.php
delete mode 100644 app/Console/Commands/UpdateActivitiesAverageScoreExcludingFeedbacksNotSetVisibleToAll.php
create mode 100644 app/Http/Controllers/Kiosk/PartnersController.php
create mode 100644 app/Jobs/AutomatedReports/SendReportExpiringSoonMailJob.php
create mode 100644 app/Jobs/AutomatedReports/SendReportNotGeneratedMailJob.php
create mode 100644 app/Mail/Reports/AskJiminnyReportExpiringMail.php
create mode 100644 app/Mail/Reports/ReportNotGenerated.php
delete mode 100644 app/Models/ElasticSearch/SharedDocumentDeleteTrait.php
create mode 100644 app/UseCases/TeamInsights/ConversationRowMapper.php
create mode 100644 app/UseCases/TeamInsights/RecordingOutcomeTextResolver.php
create mode 100644 app/UseCases/TeamInsights/StrictConsentColumnResolver.php
create mode 100644 database/migrations/2026_04_14_000000_add_rockeed_partner.php
create mode 100644 database/migrations/2026_04_22_000000_add_success_email_to_partners.php
create mode 100644 database/migrations/2026_04_27_000000_add_label_to_partners.php
create mode 100644 database/migrations/2026_04_29_105053_move_ask_jiminny_reports_to_grow_tier.php
create mode 100644 front-end/src/__mocks__/kit/endpoints/automated-reports-promo.js
create mode 100644 front-end/src/apps/ai-reports-promo.js
create mode 100644 front-end/src/components/AiReports/AiReportsPromo.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/AutomatedReportsPromo.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/PromoCard.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/WhyItMattersCard.vue
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/AutomatedReportsPromo.spec.js
create mode 100644 front-end/src/components/AiReports/AutomatedReportsPromo/__tests__/__snapshots__/automated-reports-promo.output.html
create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/PanoramaReportsPromo.vue
create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/PanoramaReportsPromo.spec.js
create mode 100644 front-end/src/components/AiReports/PanoramaReportsPromo/__tests__/__snapshots__/panorama-reports-promo.output.html
create mode 100644 front-end/src/components/Settings/Kiosk/modals/EditTeamModal/__tests__/EditTeamModal.spec.js
create mode 100644 front-end/src/components/Settings/Kiosk/shared/Navigation/__tests__/Navigation.spec.js
create mode 100644 front-end/src/components/layout/Sidebar/__tests__/HelpMenu.spec.js
create mode 100644 front-end/src/components/layout/Sidebar/__tests__/useAiReportsSidebarButton.spec.js
create mode 100644 front-end/src/components/layout/Sidebar/useAiReportsSidebarButton.js
create mode 100644 front-end/src/store/modules/platform/__tests__/getters.spec.js
create mode 100644 public/pdf/exec-reports/com/coaching-profiles.pdf
create mode 100644 public/pdf/exec-reports/com/exec-summary.pdf
create mode 100644 public/pdf/exec-reports/com/loss-report.pdf
create mode 100644 public/pdf/exec-reports/com/product-feedback.pdf
create mode 100644 public/pdf/exec-reports/eu/coaching-profiles.pdf
create mode 100644 public/pdf/exec-reports/eu/exec-summary.pdf
create mode 100644 public/pdf/exec-reports/eu/loss-report.pdf
create mode 100644 public/pdf/exec-reports/eu/product-feedback.pdf
create mode 100644 resources/views/emails/reports/ask-jiminny-report-expiring.blade.php
create mode 100644 resources/views/emails/reports/report-not-generated.blade.php
create mode 100644 tests/Unit/Component/Transcription/Job/FinishTranscriptionJobTest.php
create mode 100644 tests/Unit/Component/Transcription/TranscriptionProcessor/Gong/GongTest.php
create mode 100644 tests/Unit/Events/Activities/Audio/RecordingEventTest.php
create mode 100644 tests/Unit/Events/Activities/Softphone/EndedTest.php
create mode 100644 tests/Unit/Events/Activities/Softphone/SoftphoneEventTest.php
create mode 100644 tests/Unit/Events/Activities/Softphone/StartedTest.php
create mode 100644 tests/Unit/Http/Transformers/PartnerTransformerTest.php
create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportExpiringSoonMailJobTest.php
create mode 100644 tests/Unit/Jobs/AutomatedReports/SendReportNotGeneratedMailJobTest.php
create mode 100644 tests/Unit/Listeners/Teams/SyncIntercomCompanyTest.php
create mode 100644 tests/Unit/Listeners/Users/SyncIntercomTest.php
create mode 100644 tests/Unit/Mail/Reports/ReportNotGeneratedTest.php
create mode 100644 tests/Unit/Models/PartnerTest.php
create mode 100644 tests/Unit/Services/ActivityServiceTest.php
create mode 100644 tests/Unit/UseCases/TeamInsights/RecordingOutcomeTextResolverTest.php
create mode 100644 tests/Unit/UseCases/TeamInsights/StrictConsentColumnResolverTest.php
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 628, done.
remote: Counting objects: 100% (331/331), done.
remote: Compressing objects: 100% (63/63), done.
remote: Total 628 (delta 280), reused 274 (delta 266), pack-reused 297 (from 1)
Receiving objects: 100% (628/628), 186.75 KiB | 1.23 MiB/s, done.
Resolving deltas: 100% (391/391), completed with 57 local objects.
From github.com:jiminny/app
ad2ce76737..12295204cf master -> origin/master
14f54b5be2..5e7646e5f9 JY-17836-participant-speeches-in-s3 -> origin/JY-17836-participant-speeches-in-s3
b167b19973..acba55cf38 JY-20289-api-tests -> origin/JY-20289-api-tests
f23cfee7c3..e5a3ec5dba JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null -> origin/JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null
af59d60926..766efba1c5 JY-20395-fix-memory-issue-with-mail-import -> origin/JY-20395-fix-memory-issue-with-mail-import
* [new branch] JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering
1737b7c528..c57e71e763 JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall
* [new branch] JY-20671-anyvan-twilio-s3-recordings-ftech -> origin/JY-20671-anyvan-twilio-s3-recordings-ftech
+ ba181441c6...20a74137b0 JY-20742-mcp-poc -> origin/JY-20742-mcp-poc (forced update)
* [new branch] JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue
* [new branch] JY-20816-calendar-events-diplication -> origin/JY-20816-calendar-events-diplication
* [new branch] desktop-app -> origin/desktop-app
4c4c974e46..185442c26e make-claude-great-again -> origin/make-claude-great-again
* [new branch] mcp-tools-schemas -> origin/mcp-tools-schemas
Updating ad2ce76737..12295204cf
Fast-forward
app/Component/Encoding/Job/AnalyzeTrackChannelsJob.php | 2 +-
app/Component/Transcription/TranscriptionProcessor/AssemblyAI/Services/SubmitAudioFileService.php | 66 ++----------------------------------------------------------------
app/Console/Commands/Tracks/CleanupActivityTracksCommand.php | 24 +++++++++++++++++-------
tests/Unit/Console/Commands/Tracks/CleanupActivityTracksCommandTest.php | 40 +++++++++++++++++++++++++++++-----------
tests/Unit/fixtures/assembly_ai_transcript_response.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_channel_diarization.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language_error.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language_not_ready.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_language_post.json | 1 -
tests/Unit/fixtures/assembly_ai_transcript_response_without_utterances.json | 1 -
11 files changed, 49 insertions(+), 90 deletions(-)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20818-move-AJ-reports-to-separated-datadog-metric
Switched to a new branch 'JY-20818-move-AJ-reports-to-separated-datadog-metric'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix
docker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff
PHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.
PHP runtime: 8.3.30
Running analysis on 7 cores with 10 files per process.
Parallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!
Loaded config default from ".php-cs-fixer.dist.php".
5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%
Fixed 0 of 5663 files in 83.615 seconds, 67.00 MB memory used
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at [URL_WITH_CREDENTIALS] ~/jiminny/app (JY-20818-move-AJ-reports-to-separated-datadog-metric) $ csfix
docker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diff
PHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.
PHP runtime: 8.3.30
Running analysis on 7 cores with 10 files per process.
Parallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!
Loaded config default from ".php-cs-fixer.dist.php".
5663/5663 [▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓▓] 100%
Fixed 0 of 5663 files in 42.875 seconds, 60.00 MB memory used
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at [URL_WITH_CREDENTIALS] ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 15, done.
remote: Counting objects: 100% (15/15), done.
remote: Compressing objects: 100% (2/2), done.
remote: Total 15 (delta 13), reused 15 (delta 13), pack-reused 0 (from 0)
Unpacking objects: 100% (15/15), 1.28 KiB | 72.00 KiB/s, done.
From github.com:jiminny/app
c57e71e763..8743fea32e JY-20606-desktop-app-recall -> origin/JY-20606-desktop-app-recall
* [new branch] JY-20819-increase-download-transctip-rate-limit -> origin/JY-20819-increase-download-transctip-rate-limit
Already up to date.
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ git pull
remote: Enumerating objects: 180, done.
remote: Counting objects: 100% (179/179), done.
remote: Compressing objects: 100% (55/55), done.
remote: Total 180 (delta 127), reused 165 (delta 119), pack-reused 1 (from 1)
Receiving objects: 100% (180/180), 57.50 KiB | 2.74 MiB/s, done.
Resolving deltas: 100% (127/127), completed with 47 local objects.
From github.com:jiminny/app
12295204cf..35f036ace6 master -> origin/master
* [new branch] JY-18091-upgrade-to-php-8-5 -> origin/JY-18091-upgrade-to-php-8-5
5f21965da8..497fbc85c2 JY-20493-smart-instant-nudge-pre-filtering -> origin/JY-20493-smart-instant-nudge-pre-filtering
f029263118..6ed9e2bb13 JY-20808-low-priority-indexing-queue -> origin/JY-20808-low-priority-indexing-queue
* [new branch] JY-20817-fix-deleting-s3-directories -> origin/JY-20817-fix-deleting-s3-directories
* [new branch] JY-20820-es-reindex-stream-model-hydration -> origin/JY-20820-es-reindex-stream-model-hydration
+ ca92730ec5...2c8a1d0856 desktop-app -> origin/desktop-app (forced update)
8425d4e0de..89b45ec8b0 mcp-tools-schemas -> origin/mcp-tools-schemas
Updating 12295204cf..35f036ace6
Fast-forward
app/Component/Datadog/Constants.php | 1 +
app/Providers/RouteServiceProvider.php | 2 +-
app/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackService.php | 13 +++++++++++++
tests/Unit/Services/Kiosk/AutomatedReports/AutomatedReportsCallbackServiceTest.php | 54 +++++++++++++++++++++++++++++++++++++++++++++++-------
4 files changed, 62 insertions(+), 8 deletions(-)
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ gbr
* master
JY-20818-move-AJ-reports-to-separated-datadog-metric
JY-20773-fix-automated-reports-user-pilot-tracking
JY-20157-AJ-report-not-send-notification
JY-20508-notify-before-AJ-report-expiration
JY-20372-ai-reports-promotion-pages
JY-20352-sync-opportunities-without-a-local-owner-user-id-is-null
JY-20738-debug-AJ-tracking-UP
a
JY-18909-automated-reports-ask-jiminny
JY-20692-fix-integration-app-[API_KEY]
JY-20553-debug-crm-sync-delays
JY-20698-fix-SF-activity-types-on-new-playbook
JY-20543-AJ-report-tracking
JY-20384-handle-auto-sync-with-no-access-to-event-type
JY-20458-ask-jiminny-user-definitions
JY-19666-fix-import-contacts-account-association
JY-19666-HS-import-contacts-and-accounts-batch-job
JY-20458-Ask-Jiminny-Reports
JY-20200-batch-update-CRM-objects-Salesforce
JY-19666-HS-webhooks-add-contact-and-company
JY-20348-trigger-setup-DI-layout-on-team-creation
JY-20326-refactor-info-message-in-command
JY-20317-fix-auto-log-delay-issue-on-all-channels-disabled
JY-20312-remove-on-update-change-last-synced-at-crm-configurations
JY-20306-SF-skip-auto-sync-for-task-based-playbook
JY-20192-remove-deleted-team-from-saved-search-filters
JY-20197-import-opportunity-batch-job
JY-20293-enable-status-field-for-pipedrive-deals
JY-20191-remove-commands-interactive-prompts
JY-20118-change-default-sync-strategy
JY-20183-add-cache-on-auto-log-delay
JY-20197-add-import-opportunity-batch-job
20118-hs-opportunity-make-webhook-strategy-default
JY-20118-make-default-hs-opportunity-sync-strategy-webhook-based
JY-20196-handle-opportunity-without-note
JY-20118-improve-opportunity-import
JY-20189-handle-activity-search-on-deleted-groups
JY-20160
JY-20145-filter-out-converted-leads-when-matching
JY-20150-skip-push-summary-on-summary-ready-if-autolog
JY-20132-fix-note-encoding
JY-19792-clean-logs
JY-20117-fix-sync-profile-fields-on-empty-fields
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (master) $ co -b JY-20725-handle-HS-search-rate-limit
Switched to a new branch 'JY-20725-handle-HS-search-rate-limit'
lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ ;xd
docker exec -it docker_lamp_1 bash -c "mv /usr/local/etc/php/conf.d/xdebug.ini ~/xdebug.ini"
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at https://docs.docker.com/go/debug-cli/
docker exec -it docker_lamp_1 supervisorctl restart all
jiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: stopped
jiminny-worker-processing-2:jiminny-worker-processing-2_00: stopped
jiminny-worker-processing-3:jiminny-worker-processing-3_00: stopped
jiminny-worker-processing-4:jiminny-worker-processing-4_00: stopped
jiminny-worker-processing-5:jiminny-worker-processing-5_00: stopped
worker-analytics:worker-analytics_00: stopped
worker-crm-update:worker-crm-update_00: stopped
worker-download:worker-download_00: stopped
worker-nudges:worker-nudges_00: stopped
artisan-schedule:artisan-schedule_00: stopped
worker-emails:worker-emails_00: stopped
worker:worker_00: stopped
worker-calendar:worker-calendar_00: stopped
jiminny-worker-processing-1:jiminny-worker-processing-1_00: stopped
worker-crm-sync:worker-crm-sync_00: stopped
worker-audio:worker-audio_00: stopped
worker-conferences:worker-conferences_00: stopped
worker-es-update:worker-es-update_00: stopped
artisan-schedule:artisan-schedule_00: started
jiminny-worker-processing-1:jiminny-worker-processing-1_00: started
jiminny-worker-processing-2:jiminny-worker-processing-2_00: started
jiminny-worker-processing-3:jiminny-worker-processing-3_00: started
jiminny-worker-processing-4:jiminny-worker-processing-4_00: started
jiminny-worker-processing-5:jiminny-worker-processing-5_00: started
jiminny-worker-processing-delayed:jiminny-worker-processing-delayed_00: started
worker:worker_00: started
worker-analytics:worker-analytics_00: started
worker-audio:worker-audio_00: started
worker-calendar:worker-calendar_00: started
worker-conferences:worker-conferences_00: started
worker-crm-sync:worker-crm-sync_00: started
worker-crm-update:worker-crm-update_00: started
worker-download:worker-download_00: started
worker-emails:worker-emails_00: started
worker-es-update:worker-es-update_00: started
worker-nudges:worker-nudges_00: started
What's next:
Try Docker Debug for seamless, persistent debugging tools in any container or image → docker debug docker_lamp_1
Learn more at https://docs.docker.com/go/debug-cli/
docker exec -it docker_lamp_1 php -v
PHP 8.3.30 (cli) (built: Mar 16 2026 22:32:32) (NTS)
Copyright (c) The PHP Group
Zend En...
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2026-05-11T17:11:08.411418+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519468411_m1.jpg...
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Code
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screenpipe_sync.sh — screenpipe [SSH: nas]
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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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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
...
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-8829654875386564147
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-5551997238571740788
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click
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accessibility
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NULL
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
...
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/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519468410_m2.jpg...
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screenpipe_sync.sh — screenpipe [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) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle...
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996310670335807839
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-5588377913675525752
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click
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accessibility
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NULL
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle...
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screenpipe_sync.sh — screenpipe [SSH: nas]
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True
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NULL
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NULL
|
NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
screenpipe_sync.sh, Editor Group 1
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Shell Script
Editor Language Status: $(copilot) No inline suggestion available, Inline suggestions
LF
UTF-8
Spaces: 2
Ln 30, Col 2
git-commit Lukas Kovalik (2 weeks ago)
Lukas Kovalik (2 weeks ago)
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST "http://localhost:8766/api/pipes/day-recap/run"
curl -X POST "http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25"
Rebuild and restart
to pick up the changes:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
How it works:
Each
pipe.md
file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The "Read screenpipe skill first" line is stripped automatically.
The pipes directory inside Docker is
/data/pipes
(since
/volume1/screenpipe
→
/data
). You can override it with a
PIPES_DIR
env var if needed.
Message actions
pipe.md
pipe.md
where to place api key and can I use different keys
Thinking
Thinking
Bash
Read .env file
IN
cat /volume1/screenpipe/app/.env
Copy code to clipboard
OUT
[ENV_SECRET]...
|
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Problems","depth":16,"bounds":{"left":0.06416223,"top":0.98244214,"width":0.022606382,"height":0.01755786},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"","depth":17,"bounds":{"left":0.06582447,"top":0.9848364,"width":0.005319149,"height":0.012769354},"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"0","depth":17,"bounds":{"left":0.07114362,"top":0.9856345,"width":0.004986702,"height":0.011173184},"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"","depth":17,"bounds":{"left":0.07579787,"top":0.9848364,"width":0.0056515955,"height":0.012769354},"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"0","depth":17,"bounds":{"left":0.08111702,"top":0.9856345,"width":0.0039893617,"height":0.011173184},"on_screen":true,"role_description":"text"},{"role":"AXButton","text":"Forwarded Ports: 8766","depth":16,"bounds":{"left":0.08843085,"top":0.98244214,"width":0.012632979,"height":0.01755786},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"","depth":17,"bounds":{"left":0.09009308,"top":0.9848364,"width":0.0056515955,"height":0.012769354},"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":17,"bounds":{"left":0.09541223,"top":0.9856345,"width":0.0039893617,"height":0.011173184},"on_screen":true,"role_description":"text"},{"role":"AXButton","text":"Notifications","depth":16,"bounds":{"left":0.9886968,"top":0.98244214,"width":0.010638298,"height":0.01755786},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Sign In","depth":16,"bounds":{"left":0.9650931,"top":0.98244214,"width":0.022606382,"height":0.01755786},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"","depth":17,"bounds":{"left":0.96675533,"top":0.9848364,"width":0.0056515955,"height":0.012769354},"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"Sign In","depth":17,"bounds":{"left":0.97207445,"top":0.9856345,"width":0.013962766,"height":0.011173184},"on_screen":true,"lines":[{"char_start":0,"char_count":1,"bounds":{"left":0.97207445,"top":0.9856345,"width":0.0013297872,"height":0.011173184}},{"char_start":1,"char_count":6,"bounds":{"left":0.9734042,"top":0.9856345,"width":0.010638298,"height":0.011173184}}],"role_description":"text"},{"role":"AXButton","text":"Shell Script","depth":16,"bounds":{"left":0.93916225,"top":0.98244214,"width":0.023603724,"height":0.01755786},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Editor Language Status: $(copilot) No inline suggestion available, Inline suggestions","depth":16,"bounds":{"left":0.9318484,"top":0.98244214,"width":0.00731383,"height":0.01755786},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"LF","depth":16,"bounds":{"left":0.9212101,"top":0.98244214,"width":0.007978723,"height":0.01755786},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"UTF-8","depth":16,"bounds":{"left":0.90359044,"top":0.98244214,"width":0.015625,"height":0.01755786},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Spaces: 2","depth":16,"bounds":{"left":0.8796542,"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 30, Col 2","depth":16,"bounds":{"left":0.85139626,"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":"AXButton","text":"git-commit Lukas Kovalik (2 weeks ago)","depth":16,"bounds":{"left":0.7869016,"top":0.98244214,"width":0.062832445,"height":0.01755786},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"","depth":17,"bounds":{"left":0.78856385,"top":0.9848364,"width":0.005319149,"height":0.012769354},"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"Lukas Kovalik (2 weeks ago)","depth":17,"bounds":{"left":0.79388297,"top":0.9856345,"width":0.05418883,"height":0.011173184},"on_screen":true,"lines":[{"char_start":0,"char_count":1,"bounds":{"left":0.79388297,"top":0.9856345,"width":0.0013297872,"height":0.011173184}},{"char_start":1,"char_count":26,"bounds":{"left":0.79488033,"top":0.9856345,"width":0.051529255,"height":0.011173184}}],"role_description":"text"},{"role":"AXStaticText","text":"Info: Setting up SSH Host nas: Setting up SSH tunnel","depth":12,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Implement and run pipe logic","depth":19,"bounds":{"left":0.56017286,"top":0.08060654,"width":0.07114362,"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 history","depth":19,"bounds":{"left":0.9780585,"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":0.9886968,"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":"main.py","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lets implement logic with pipes. how can I run 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":"Let me look at the current project structure to understand what's already in place.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"List project files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"find /volume1/screenpipe -type f | head -50 && echo \"---\" && ls /volume1/screenpipe","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":"/volume1/screenpipe/.DS_Store\n/volume1/screenpipe/screenpipe.db\n/volume1/screenpipe/screenpipe_sync.sh\n/volume1/screenpipe/app_settings.json\n/volume1/screenpipe/.gitignore\n/volume1/screenpipe/archive.db\n/volume1/screenpipe/db.sqlite\n/volume1/screenpipe/db.sqlite-wal\n/volume1/screenpipe/db.sqlite-shm\n/volume1/screenpipe/#recycle/desktop.ini\n/volume1/screenpipe/#recycle/db.sqlite\n/volume1/screenpipe/#recycle/Copy #1 of db.sqlite\n/volume1/screenpipe/#recycle/.DS_Store\n/volume1/screenpipe/#recycle/Copy #2 of db.sqlite\n/volume1/screenpipe/#recycle/archive.db\n/volume1/screenpipe/#recycle/Copy #1 of archive.db\n/volume1/screenpipe/#recycle/Copy #2 of archive.db\n/volume1/screenpipe/#recycle/Copy #3 of archive.db\n/volume1/screenpipe/#recycle/Copy #4 of archive.db\n/volume1/screenpipe/#recycle/Copy #5 of archive.db\n/volume1/screenpipe/#recycle/Copy #3 of db.sqlite\n/volume1/screenpipe/#recycle/Copy #4 of db.sqlite\n/volume1/screenpipe/#recycle/Copy #6 of archive.db\n/volume1/screenpipe/#recycle/test.txt\n/volume1/screenpipe/#recycle/Copy #7 of archive.db\n/volume1/screenpipe/#recycle/Copy #8 of archive.db\n/volume1/screenpipe/#recycle/archive.db-journal\n/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #5 of db.sqlite\n/volume1/screenpipe/pipes/.DS_Store\n/volume1/screenpipe/app/.env\n/volume1/screenpipe/app/cli.py\n/volume1/screenpipe/app/.DS_Store\n/volume1/screenpipe/app/db.py\n/volume1/screenpipe/app/docker-compose.yml\n/volume1/screenpipe/app/main.py\n/volume1/screenpipe/app/requirements.txt\n/volume1/screenpipe/app/Dockerfile\n/volume1/screenpipe/data/.DS_Store\n/volume1/screenpipe/.git/description\n/volume1/screenpipe/.git/HEAD\n/volume1/screenpipe/.git/index\n/volume1/screenpipe/.git/COMMIT_EDITMSG\n/volume1/screenpipe/#recycle/data/.DS_Store\n---\napp\napp_settings.json\narchive.db\ndata\ndb.sqlite\ndb.sqlite-shm\ndb.sqlite-wal\npipes\n#recycle\nscreenpipe.db\nscreenpipe_sync.sh","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check pipes directory and docker-compose","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml","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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\ncli.py\nconsumers\ndb.py\ndocker-compose.yml\nDockerfile\nmain.py\n__pycache__\nrequirements.txt\nstatic\nservices:\n screenpipe-app:\n build: .\n container_name: screenpipe-app\n restart: unless-stopped\n ports:\n - \"8766:8000\"\n volumes:\n - /volume1/screenpipe:/data\n env_file:\n - .env\n environment:\n TZ: Europe/Sofia\n DB_PATH: /data/db.sqlite\n\n sqlite-web-archive:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-archive\n restart: unless-stopped\n ports:\n - \"8767:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/archive.db\"]\n\n sqlite-web-live:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-live\n restart: unless-stopped\n ports:\n - \"8768:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/db.sqlite\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"requirements.txt","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"requirements.txt","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Inspect a pipe directory","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/","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":"pipe.md\npipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"List all pipes and their contents","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo \"=== $d ===\"; ls \"$d\"; 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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\n=== /volume1/screenpipe/pipes/ai-habits/ ===\npipe.md\n=== /volume1/screenpipe/pipes/day-recap/ ===\npipe.md\n=== /volume1/screenpipe/pipes/meeting-summary/ ===\npipe.md\n=== /volume1/screenpipe/pipes/standup-update/ ===\npipe.md\n=== /volume1/screenpipe/pipes/time-breakdown/ ===\npipe.md\n=== /volume1/screenpipe/pipes/video-export/ ===\npipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read pipe markdown files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo \"===\" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50","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":"---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.","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":"Read summary consumer","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py","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":"activity.py\naudio.py\nelements.py\n__init__.py\ninteractions.py\nocr.py\n__pycache__\nreport.py\nsummary.py\n\"\"\"AI summary generator using Claude.\"\"\"\nimport os\nfrom datetime import date\nfrom typing import Any\n\nfrom consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary\nfrom consumers.ocr import deduplicated_text\nfrom consumers.audio import formatted_transcript\n\n\nSUMMARY_TYPES = {\n \"day_recap\": {\n \"title\": \"Day Recap\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a concise day recap using EXACTLY this format:\n\n## Summary\nOne sentence: what I mainly worked on today.\n\n## Accomplishments\n- Top 3 things I finished, with approximate times\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things seen or heard, with timestamps\n\n## Unfinished Work\n- What to continue tomorrow\n\n## Patterns\n- Apps used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with:\n**Next step:** [most important thing to continue]\"\"\",\n },\n \"standup\": {\n \"title\": \"Standup Update\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a brief standup update:\n\n**Yesterday:** What I worked on (2-3 bullets)\n**Today:** What I plan to continue (1-2 bullets)\n**Blockers:** Any issues observed (or \"None\")\n\nKeep it under 150 words. Only report what's verifiable from the data.\"\"\",\n },\n \"focus_time\": {\n \"title\": \"Focus & Distraction Analysis\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\nAnalyze focus vs distraction patterns:\n\n## Deep Work Periods\n- When and how long were sustained focus sessions?\n- What was being worked on?\n\n## Distractions\n- Which apps/sites were used recreationally?\n- How much time was lost to context switching?\n\n## Recommendations\n- 2-3 concrete suggestions to improve focus tomorrow\n\nBe specific with times and app names.\"\"\",\n },\n}\n\n\ndef _build_context(for_date: date) -> dict[str, str]:\n apps = app_time(for_date)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(for_date, limit=20)\n url_lines = \"\\n\".join(\n f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls\n )\n\n ui_rows = ui_event_summary(for_date)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(for_date, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(for_date)\n\n return {\n \"app_time\": app_lines or \"(no app data)\",\n \"browser_urls\": url_lines or \"(no browser data)\",\n \"ui_events\": ui_lines or \"(no UI event data)\",\n \"ocr_text\": ocr_lines or \"(no screen data)\",\n \"audio\": audio[:3000] if len(audio) > 3000 else audio,\n }\n\n\ndef generate(\n summary_type: str = \"day_recap\",\n for_date: date | None = None,\n api_key: str | None = None,\n) -> dict[str, Any]:\n \"\"\"Generate an AI summary. Returns dict with 'title', 'content', 'date'.\"\"\"\n import anthropic\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\n \"title\": \"Error\",\n \"content\": \"ANTHROPIC_API_KEY not set. Add it to your .env file.\",\n \"date\": str(d),\n }\n\n spec = SUMMARY_TYPES.get(summary_type)\n if not spec:\n return {\"title\": \"Error\", \"content\": f\"Unknown summary type: {summary_type}\", \"date\": str(d)}\n\n stats = summary_stats(d)\n if stats[\"total_frames\"] == 0:\n return {\n \"title\": spec[\"title\"],\n \"content\": f\"No screen data found for {d}.\",\n \"date\": str(d),\n }\n\n ctx = _build_context(d)\n prompt = spec[\"prompt\"].format(**ctx)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": prompt}],\n )\n\n return {\n \"title\": spec[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","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":"Read all pipe.md files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"for f in /volume1/screenpipe/pipes/*/pipe.md; do echo \"=== $f ===\"; cat \"$f\"; 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":"=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: AI Habits\ndescription: \"How you use AI tools — patterns and insights\"\nicon: \"🤖\"\nfeatured: true\n---\n\nSearch my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## AI Tools Used\n- List each tool with approximate time spent (e.g. \"Claude: ~45min\")\n\n## What I Used Them For\n- For each tool: coding, writing, research, or brainstorming\n\n## Usage Patterns\n- Do I switch between tools? Use them in bursts or steadily?\n\n## Effectiveness\n- Which tool appeared alongside completed work vs. abandoned attempts\n\nIf no AI usage is found, say so clearly. End with: \"**Tip:** [one suggestion to use AI tools more effectively]\"\n\n=== /volume1/screenpipe/pipes/day-recap/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n\n=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.\n\n=== /volume1/screenpipe/pipes/standup-update/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Standup Update\ndescription: \"What you did, what's next, and any blockers\"\nicon: \"🏢\"\nfeatured: true\n---\n\nBased on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Yesterday\n- What I worked on (name specific projects, files, tools, PRs)\n\n## Today\n- What I will work on next (based on unfinished tasks and recent activity)\n\n## Blockers\n- Issues I hit — errors, slow builds, waiting on someone\n- If no blockers, write \"None\"\n\nKeep it under 150 words. Copy-paste ready for a team standup.\n\n=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Time Breakdown\ndescription: \"Where your time went — by app, project, and category\"\nicon: \"⏱\"\nfeatured: false\n---\n\nAnalyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.\n\nRead screenpipe skill first.\n\nUse this exact format with durations and percentages:\n\n## By Application\n- List each app with duration and percentage, sorted by time (e.g. \"VS Code: 2h 15min (28%)\")\n\n## By Category\n- Group into: coding, meetings, browsing, writing, communication, other\n- Show hours and percentage per category\n\n## By Project\n- Group related activities by project/topic. Name specific repos or tasks.\n\n## Productivity Score\n- Calculate: focused_work_hours / total_hours as a percentage\n- Focused = coding + writing. Unfocused = browsing + switching.\n\nEnd with: \"**Suggestion:** [one specific change to improve tomorrow's productivity]\"\n\n=== /volume1/screenpipe/pipes/video-export/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Export Video Clip\ndescription: \"Create a video of your recent screen activity\"\nicon: \"🎬\"\nfeatured: false\n---\n\nExport a video of my screen activity from the last 5 minutes.\n\nRead screenpipe skill first.\n\nUse the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.\n\nIf the export is large, suggest a lower fps or shorter time range.","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 clear picture. The pipes are markdown prompt templates in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe/pipes/","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but there's no code to actually load and run them —","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"has its own hardcoded prompts instead.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Here's what I'll implement:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/pipes.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— two new endpoints:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"GET /api/pipes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /api/pipes/{pipe_id}/run","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cli.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— a","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"command to run pipes from the terminal","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Let me build it:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check browser_urls signature","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/consumers/activity.py | grep \"def browser_urls\" -A 5","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":"def browser_urls(\n for_date: date | None = None,\n app_name: str | None = None,\n ts_from: str | None = None,\n ts_to: str | None = None,\n limit: int = 30,","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":"pipes.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipes.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"143 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"\"\"\"Dynamic pipe loader and runner.\"\"\"\nimport os\nimport re\nfrom datetime import date\nfrom pathlib import Path\nfrom typing import Any\n\n\ndef _parse_frontmatter(text: str) -> tuple[dict, str]:\n if not text.startswith(\"---\"):\n return {}, text\n try:\n end = text.index(\"---\", 3)\n except ValueError:\n return {}, text\n fm_text = text[3:end].strip()\n body = text[end + 3:].strip()\n meta: dict = {}\n for line in fm_text.splitlines():\n if \":\" in line:\n k, _, v = line.partition(\":\")\n meta[k.strip()] = v.strip().strip('\"')\n return meta, body\n\n\ndef load_pipes(pipes_dir: Path) -> list[dict]:\n if not pipes_dir.exists():\n return []\n pipes = []\n for pipe_dir in sorted(pipes_dir.iterdir()):\n if not pipe_dir.is_dir() or pipe_dir.name.startswith(\".\"):\n continue\n pipe_md = pipe_dir / \"pipe.md\"\n if not pipe_md.exists():\n continue\n text = pipe_md.read_text(encoding=\"utf-8\")\n meta, body = _parse_frontmatter(text)\n if meta.get(\"enabled\", \"true\").lower() == \"false\":\n continue\n body = re.sub(r\"Read screenpipe skill first\\.?\\n?\", \"\", body).strip()\n pipes.append({\n \"id\": pipe_dir.name,\n \"title\": meta.get(\"title\", pipe_dir.name),\n \"description\": meta.get(\"description\", \"\"),\n \"icon\": meta.get(\"icon\", \"\"),\n \"schedule\": meta.get(\"schedule\", \"manual\"),\n \"featured\": meta.get(\"featured\", \"false\").lower() == \"true\",\n \"prompt\": body,\n })\n return pipes\n\n\ndef _build_system(d: date, stats: dict) -> str:\n from consumers.activity import app_time, browser_urls, ui_event_summary\n from consumers.ocr import deduplicated_text\n from consumers.audio import formatted_transcript\n\n apps = app_time(d)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(d, limit=20)\n url_lines = \"\\n\".join(f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls)\n\n ui_rows = ui_event_summary(d)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(d, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(d)\n if len(audio) > 3000:\n audio = audio[:3000]\n\n return f\"\"\"You are analyzing screenpipe data — recordings of a person's computer activity.\n\n## App usage (minutes per app):\n{app_lines or '(no app data)'}\n\n## Browser URLs visited:\n{url_lines or '(no browser data)'}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_lines or '(no UI event data)'}\n\n## Screen content (sampled every 5 minutes):\n{ocr_lines or '(no screen data)'}\n\n## Audio / speech:\n{audio or '(no audio data)'}\n\nDate: {d}\nTotal frames recorded: {stats['total_frames']}\"\"\"\n\n\ndef run_pipe(\n pipe_id: str,\n for_date: date | None = None,\n api_key: str | None = None,\n pipes_dir: Path | None = None,\n) -> dict[str, Any]:\n import anthropic\n from consumers.activity import summary_stats\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\"title\": \"Error\", \"content\": \"ANTHROPIC_API_KEY not set.\", \"date\": str(d)}\n\n _pipes_dir = pipes_dir or Path(os.environ.get(\"PIPES_DIR\", \"/data/pipes\"))\n all_pipes = {p[\"id\"]: p for p in load_pipes(_pipes_dir)}\n\n if pipe_id not in all_pipes:\n return {\"title\": \"Error\", \"content\": f\"Pipe not found: {pipe_id}\", \"date\": str(d)}\n\n pipe = all_pipes[pipe_id]\n stats = summary_stats(d)\n\n if stats[\"total_frames\"] == 0:\n return {\"title\": pipe[\"title\"], \"content\": f\"No screen data found for {d}.\", \"date\": str(d)}\n\n system = _build_system(d, stats)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n system=system,\n messages=[{\"role\": \"user\", \"content\": pipe[\"prompt\"]}],\n )\n\n return {\n \"title\": pipe[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the API endpoints to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the pipe endpoints at the end of main.py, before the closing summary section:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 14 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the CLI command to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 40 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Done. Here's how to run pipes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to run pipes","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to run pipes","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via Docker (inside the running container):","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"docker exec -it screenpipe-app python cli.py pipe --list\ndocker exec -it screenpipe-app python cli.py pipe day-recap\ndocker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via the API","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(once the container is running on port 8766):","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# List pipes\ncurl http://localhost:8766/api/pipes\n\n# Run a pipe\ncurl -X POST \"http://localhost:8766/api/pipes/day-recap/run\"\ncurl -X POST \"http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rebuild and restart","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to pick up the changes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"cd /volume1/screenpipe/app\ndocker compose up --build -d","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"How it works:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Each","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The \"Read screenpipe skill first\" line is stripped automatically.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The pipes directory inside Docker is","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data/pipes","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(since","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"→","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). You can override it with a","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"PIPES_DIR","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"env var if needed.","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":"AXButton","text":"pipe.md","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"where to place api key and can I use different keys","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":"Read .env file","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/.env","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":"ANTHROPIC_API_KEY=your_key_here","depth":24,"on_screen":false,"role_description":"text"}]...
|
-3576203112056561664
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-8691438911294027668
|
visual_change
|
accessibility
|
NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
screenpipe_sync.sh, Editor Group 1
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Shell Script
Editor Language Status: $(copilot) No inline suggestion available, Inline suggestions
LF
UTF-8
Spaces: 2
Ln 30, Col 2
git-commit Lukas Kovalik (2 weeks ago)
Lukas Kovalik (2 weeks ago)
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST "http://localhost:8766/api/pipes/day-recap/run"
curl -X POST "http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25"
Rebuild and restart
to pick up the changes:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
How it works:
Each
pipe.md
file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The "Read screenpipe skill first" line is stripped automatically.
The pipes directory inside Docker is
/data/pipes
(since
/volume1/screenpipe
→
/data
). You can override it with a
PIPES_DIR
env var if needed.
Message actions
pipe.md
pipe.md
where to place api key and can I use different keys
Thinking
Thinking
Bash
Read .env file
IN
cat /volume1/screenpipe/app/.env
Copy code to clipboard
OUT
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Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
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app_settings.json
archive.db
archive.db-bak
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db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
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OUTLINE
Timeline Section
TIMELINE
TIMELINE
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screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
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Source Control (⌃⇧G) - 10 pending changes
10
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Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
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pipes
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app_settings.json
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screenpipe_sync_updated.sh
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screenpipe_sync.sh
screenpipe.db
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Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
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screenpipe_sync.sh
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Section","depth":21,"bounds":{"left":0.015957447,"top":0.9473264,"width":0.09940159,"height":0.017557861},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false}]...
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accessibility
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section...
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Code
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Implement and run pipe l… — screenpipe [SSH: nas]
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True
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monitor_1
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
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PROBLEMS
Output (⇧⌘U)
OUTPUT
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DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
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Forwarded Ports: 8766
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Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST "http://localhost:8766/api/pipes/day-recap/run"
curl -X POST "http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25"
Rebuild and restart
to pick up the changes:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
How it works:
Each
pipe.md
file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The "Read screenpipe skill first" line is stripped automatically.
The pipes directory inside Docker is
/data/pipes
(since
/volume1/screenpipe
→
/data
). You can override it with a
PIPES_DIR
env var if needed.
Message actions
pipe.md
pipe.md
where to place api key and can I use different keys
Thinking
Thinking
Bash
Read .env file
IN
cat /volume1/screenpipe/app/.env
Copy code to clipboard
OUT
[ENV_SECRET]
Where to place the key:
app/.env
app/.env
— replace
your_key_here
with your actual key:
Copy code to clipboard
[ENV_SECRET]
That file is loaded by
load_dotenv()
at startup and is excluded from git via
.gitignore
.
Can you use different keys per pipe?
Not currently — all pipes share the one key from
.env
. But you can add per-pipe key support by adding an
api_key
field to the pipe's frontmatter:
Copy code to clipboard
---
title: Meeting Summary
api_key_env: ANTHROPIC_KEY_MEETINGS
---
Then in
consumers/pipes.py
consumers/pipes.py
, read it in
_parse_frontmatter
and pass it through
run_pipe
. Want me to add that?
Message actions
pipe.md
pipe.md
can I use mistral or other llm? or is is build for antrophic only
Thinking
Thinking
Currently it's Anthropic-only — the code calls the
anthropic
SDK directly in both...
|
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unless-stopped\n ports:\n - \"8766:8000\"\n volumes:\n - /volume1/screenpipe:/data\n env_file:\n - .env\n environment:\n TZ: Europe/Sofia\n DB_PATH: /data/db.sqlite\n\n sqlite-web-archive:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-archive\n restart: unless-stopped\n ports:\n - \"8767:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/archive.db\"]\n\n sqlite-web-live:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-live\n restart: unless-stopped\n ports:\n - \"8768:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", 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their contents","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo \"=== $d ===\"; ls \"$d\"; 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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\n=== /volume1/screenpipe/pipes/ai-habits/ ===\npipe.md\n=== /volume1/screenpipe/pipes/day-recap/ ===\npipe.md\n=== /volume1/screenpipe/pipes/meeting-summary/ ===\npipe.md\n=== /volume1/screenpipe/pipes/standup-update/ ===\npipe.md\n=== /volume1/screenpipe/pipes/time-breakdown/ ===\npipe.md\n=== /volume1/screenpipe/pipes/video-export/ ===\npipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read pipe markdown files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo \"===\" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50","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":"---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.","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":"Read summary consumer","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py","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":"activity.py\naudio.py\nelements.py\n__init__.py\ninteractions.py\nocr.py\n__pycache__\nreport.py\nsummary.py\n\"\"\"AI summary generator using Claude.\"\"\"\nimport os\nfrom datetime import date\nfrom typing import Any\n\nfrom consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary\nfrom consumers.ocr import deduplicated_text\nfrom consumers.audio import formatted_transcript\n\n\nSUMMARY_TYPES = {\n \"day_recap\": {\n \"title\": \"Day Recap\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a concise day recap using EXACTLY this format:\n\n## Summary\nOne sentence: what I mainly worked on today.\n\n## Accomplishments\n- Top 3 things I finished, with approximate times\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things seen or heard, with timestamps\n\n## Unfinished Work\n- What to continue tomorrow\n\n## Patterns\n- Apps used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with:\n**Next step:** [most important thing to continue]\"\"\",\n },\n \"standup\": {\n \"title\": \"Standup Update\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a brief standup update:\n\n**Yesterday:** What I worked on (2-3 bullets)\n**Today:** What I plan to continue (1-2 bullets)\n**Blockers:** Any issues observed (or \"None\")\n\nKeep it under 150 words. Only report what's verifiable from the data.\"\"\",\n },\n \"focus_time\": {\n \"title\": \"Focus & Distraction Analysis\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\nAnalyze focus vs distraction patterns:\n\n## Deep Work Periods\n- When and how long were sustained focus sessions?\n- What was being worked on?\n\n## Distractions\n- Which apps/sites were used recreationally?\n- How much time was lost to context switching?\n\n## Recommendations\n- 2-3 concrete suggestions to improve focus tomorrow\n\nBe specific with times and app names.\"\"\",\n },\n}\n\n\ndef _build_context(for_date: date) -> dict[str, str]:\n apps = app_time(for_date)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(for_date, limit=20)\n url_lines = \"\\n\".join(\n f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls\n )\n\n ui_rows = ui_event_summary(for_date)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(for_date, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(for_date)\n\n return {\n \"app_time\": app_lines or \"(no app data)\",\n \"browser_urls\": url_lines or \"(no browser data)\",\n \"ui_events\": ui_lines or \"(no UI event data)\",\n \"ocr_text\": ocr_lines or \"(no screen data)\",\n \"audio\": audio[:3000] if len(audio) > 3000 else audio,\n }\n\n\ndef generate(\n summary_type: str = \"day_recap\",\n for_date: date | None = None,\n api_key: str | None = None,\n) -> dict[str, Any]:\n \"\"\"Generate an AI summary. Returns dict with 'title', 'content', 'date'.\"\"\"\n import anthropic\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\n \"title\": \"Error\",\n \"content\": \"ANTHROPIC_API_KEY not set. Add it to your .env file.\",\n \"date\": str(d),\n }\n\n spec = SUMMARY_TYPES.get(summary_type)\n if not spec:\n return {\"title\": \"Error\", \"content\": f\"Unknown summary type: {summary_type}\", \"date\": str(d)}\n\n stats = summary_stats(d)\n if stats[\"total_frames\"] == 0:\n return {\n \"title\": spec[\"title\"],\n \"content\": f\"No screen data found for {d}.\",\n \"date\": str(d),\n }\n\n ctx = _build_context(d)\n prompt = spec[\"prompt\"].format(**ctx)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": prompt}],\n )\n\n return {\n \"title\": spec[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","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":"Read all pipe.md files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"for f in /volume1/screenpipe/pipes/*/pipe.md; do echo \"=== $f ===\"; cat \"$f\"; 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":"=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: AI Habits\ndescription: \"How you use AI tools — patterns and insights\"\nicon: \"🤖\"\nfeatured: true\n---\n\nSearch my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## AI Tools Used\n- List each tool with approximate time spent (e.g. \"Claude: ~45min\")\n\n## What I Used Them For\n- For each tool: coding, writing, research, or brainstorming\n\n## Usage Patterns\n- Do I switch between tools? Use them in bursts or steadily?\n\n## Effectiveness\n- Which tool appeared alongside completed work vs. abandoned attempts\n\nIf no AI usage is found, say so clearly. End with: \"**Tip:** [one suggestion to use AI tools more effectively]\"\n\n=== /volume1/screenpipe/pipes/day-recap/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n\n=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.\n\n=== /volume1/screenpipe/pipes/standup-update/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Standup Update\ndescription: \"What you did, what's next, and any blockers\"\nicon: \"🏢\"\nfeatured: true\n---\n\nBased on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Yesterday\n- What I worked on (name specific projects, files, tools, PRs)\n\n## Today\n- What I will work on next (based on unfinished tasks and recent activity)\n\n## Blockers\n- Issues I hit — errors, slow builds, waiting on someone\n- If no blockers, write \"None\"\n\nKeep it under 150 words. Copy-paste ready for a team standup.\n\n=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Time Breakdown\ndescription: \"Where your time went — by app, project, and category\"\nicon: \"⏱\"\nfeatured: false\n---\n\nAnalyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.\n\nRead screenpipe skill first.\n\nUse this exact format with durations and percentages:\n\n## By Application\n- List each app with duration and percentage, sorted by time (e.g. \"VS Code: 2h 15min (28%)\")\n\n## By Category\n- Group into: coding, meetings, browsing, writing, communication, other\n- Show hours and percentage per category\n\n## By Project\n- Group related activities by project/topic. Name specific repos or tasks.\n\n## Productivity Score\n- Calculate: focused_work_hours / total_hours as a percentage\n- Focused = coding + writing. Unfocused = browsing + switching.\n\nEnd with: \"**Suggestion:** [one specific change to improve tomorrow's productivity]\"\n\n=== /volume1/screenpipe/pipes/video-export/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Export Video Clip\ndescription: \"Create a video of your recent screen activity\"\nicon: \"🎬\"\nfeatured: false\n---\n\nExport a video of my screen activity from the last 5 minutes.\n\nRead screenpipe skill first.\n\nUse the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.\n\nIf the export is large, suggest a lower fps or shorter time range.","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 clear picture. The pipes are markdown prompt templates in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe/pipes/","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but there's no code to actually load and run them —","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"has its own hardcoded prompts instead.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Here's what I'll implement:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/pipes.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— two new endpoints:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"GET /api/pipes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /api/pipes/{pipe_id}/run","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cli.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— a","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"command to run pipes from the terminal","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Let me build it:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check browser_urls signature","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/consumers/activity.py | grep \"def browser_urls\" -A 5","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":"def browser_urls(\n for_date: date | None = None,\n app_name: str | None = None,\n ts_from: str | None = None,\n ts_to: str | None = None,\n limit: int = 30,","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":"pipes.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipes.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"143 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"\"\"\"Dynamic pipe loader and runner.\"\"\"\nimport os\nimport re\nfrom datetime import date\nfrom pathlib import Path\nfrom typing import Any\n\n\ndef _parse_frontmatter(text: str) -> tuple[dict, str]:\n if not text.startswith(\"---\"):\n return {}, text\n try:\n end = text.index(\"---\", 3)\n except ValueError:\n return {}, text\n fm_text = text[3:end].strip()\n body = text[end + 3:].strip()\n meta: dict = {}\n for line in fm_text.splitlines():\n if \":\" in line:\n k, _, v = line.partition(\":\")\n meta[k.strip()] = v.strip().strip('\"')\n return meta, body\n\n\ndef load_pipes(pipes_dir: Path) -> list[dict]:\n if not pipes_dir.exists():\n return []\n pipes = []\n for pipe_dir in sorted(pipes_dir.iterdir()):\n if not pipe_dir.is_dir() or pipe_dir.name.startswith(\".\"):\n continue\n pipe_md = pipe_dir / \"pipe.md\"\n if not pipe_md.exists():\n continue\n text = pipe_md.read_text(encoding=\"utf-8\")\n meta, body = _parse_frontmatter(text)\n if meta.get(\"enabled\", \"true\").lower() == \"false\":\n continue\n body = re.sub(r\"Read screenpipe skill first\\.?\\n?\", \"\", body).strip()\n pipes.append({\n \"id\": pipe_dir.name,\n \"title\": meta.get(\"title\", pipe_dir.name),\n \"description\": meta.get(\"description\", \"\"),\n \"icon\": meta.get(\"icon\", \"\"),\n \"schedule\": meta.get(\"schedule\", \"manual\"),\n \"featured\": meta.get(\"featured\", \"false\").lower() == \"true\",\n \"prompt\": body,\n })\n return pipes\n\n\ndef _build_system(d: date, stats: dict) -> str:\n from consumers.activity import app_time, browser_urls, ui_event_summary\n from consumers.ocr import deduplicated_text\n from consumers.audio import formatted_transcript\n\n apps = app_time(d)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(d, limit=20)\n url_lines = \"\\n\".join(f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls)\n\n ui_rows = ui_event_summary(d)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(d, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(d)\n if len(audio) > 3000:\n audio = audio[:3000]\n\n return f\"\"\"You are analyzing screenpipe data — recordings of a person's computer activity.\n\n## App usage (minutes per app):\n{app_lines or '(no app data)'}\n\n## Browser URLs visited:\n{url_lines or '(no browser data)'}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_lines or '(no UI event data)'}\n\n## Screen content (sampled every 5 minutes):\n{ocr_lines or '(no screen data)'}\n\n## Audio / speech:\n{audio or '(no audio data)'}\n\nDate: {d}\nTotal frames recorded: {stats['total_frames']}\"\"\"\n\n\ndef run_pipe(\n pipe_id: str,\n for_date: date | None = None,\n api_key: str | None = None,\n pipes_dir: Path | None = None,\n) -> dict[str, Any]:\n import anthropic\n from consumers.activity import summary_stats\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\"title\": \"Error\", \"content\": \"ANTHROPIC_API_KEY not set.\", \"date\": str(d)}\n\n _pipes_dir = pipes_dir or Path(os.environ.get(\"PIPES_DIR\", \"/data/pipes\"))\n all_pipes = {p[\"id\"]: p for p in load_pipes(_pipes_dir)}\n\n if pipe_id not in all_pipes:\n return {\"title\": \"Error\", \"content\": f\"Pipe not found: {pipe_id}\", \"date\": str(d)}\n\n pipe = all_pipes[pipe_id]\n stats = summary_stats(d)\n\n if stats[\"total_frames\"] == 0:\n return {\"title\": pipe[\"title\"], \"content\": f\"No screen data found for {d}.\", \"date\": str(d)}\n\n system = _build_system(d, stats)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n system=system,\n messages=[{\"role\": \"user\", \"content\": pipe[\"prompt\"]}],\n )\n\n return {\n \"title\": pipe[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the API endpoints to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the pipe endpoints at the end of main.py, before the closing summary section:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 14 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the CLI command to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 40 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Done. Here's how to run pipes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to run pipes","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to run pipes","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via Docker (inside the running container):","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"docker exec -it screenpipe-app python cli.py pipe --list\ndocker exec -it screenpipe-app python cli.py pipe day-recap\ndocker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via the API","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(once the container is running on port 8766):","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# List pipes\ncurl http://localhost:8766/api/pipes\n\n# Run a pipe\ncurl -X POST \"http://localhost:8766/api/pipes/day-recap/run\"\ncurl -X POST \"http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rebuild and restart","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to pick up the changes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"cd /volume1/screenpipe/app\ndocker compose up --build -d","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"How it works:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Each","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The \"Read screenpipe skill first\" line is stripped automatically.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The pipes directory inside Docker is","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data/pipes","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(since","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"→","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). You can override it with a","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"PIPES_DIR","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"env var if needed.","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":"AXButton","text":"pipe.md","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"where to place api key and can I use different keys","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":"Read .env file","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/.env","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":"ANTHROPIC_API_KEY=your_key_here","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Where to place the key:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"app/.env","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"app/.env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— replace","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"your_key_here","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with your actual key:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"ANTHROPIC_API_KEY=sk-ant-...","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"That file is loaded by","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"load_dotenv()","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"at startup and is excluded from git via","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".gitignore","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Can you use different keys per pipe?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Not currently — all pipes share the one key from","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". But you can add per-pipe key support by adding an","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"api_key","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"field to the pipe's frontmatter:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"---\ntitle: Meeting Summary\napi_key_env: ANTHROPIC_KEY_MEETINGS\n---","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Then in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/pipes.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/pipes.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", read it in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"_parse_frontmatter","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and pass it through","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"run_pipe","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". Want me to add that?","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":"AXButton","text":"pipe.md","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"can I use mistral or other llm? or is is build for antrophic only","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":"Currently it's Anthropic-only — the code calls the","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"anthropic","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SDK directly in both","depth":23,"on_screen":false,"role_description":"text"}]...
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556607221063026044
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-8763776880662820760
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idle
|
accessibility
|
NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST "http://localhost:8766/api/pipes/day-recap/run"
curl -X POST "http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25"
Rebuild and restart
to pick up the changes:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
How it works:
Each
pipe.md
file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The "Read screenpipe skill first" line is stripped automatically.
The pipes directory inside Docker is
/data/pipes
(since
/volume1/screenpipe
→
/data
). You can override it with a
PIPES_DIR
env var if needed.
Message actions
pipe.md
pipe.md
where to place api key and can I use different keys
Thinking
Thinking
Bash
Read .env file
IN
cat /volume1/screenpipe/app/.env
Copy code to clipboard
OUT
[ENV_SECRET]
Where to place the key:
app/.env
app/.env
— replace
your_key_here
with your actual key:
Copy code to clipboard
[ENV_SECRET]
That file is loaded by
load_dotenv()
at startup and is excluded from git via
.gitignore
.
Can you use different keys per pipe?
Not currently — all pipes share the one key from
.env
. But you can add per-pipe key support by adding an
api_key
field to the pipe's frontmatter:
Copy code to clipboard
---
title: Meeting Summary
api_key_env: ANTHROPIC_KEY_MEETINGS
---
Then in
consumers/pipes.py
consumers/pipes.py
, read it in
_parse_frontmatter
and pass it through
run_pipe
. Want me to add that?
Message actions
pipe.md
pipe.md
can I use mistral or other llm? or is is build for antrophic only
Thinking
Thinking
Currently it's Anthropic-only — the code calls the
anthropic
SDK directly in both...
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
...
|
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idle
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accessibility
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NULL
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
...
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/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519419434_m1.jpg...
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Code
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Implement and run pipe l… — screenpipe [SSH: nas]
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True
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monitor_1
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST "http://localhost:8766/api/pipes/day-recap/run"
curl -X POST "http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25"
Rebuild and restart
to pick up the changes:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
How it works:
Each
pipe.md
file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The "Read screenpipe skill first" line is stripped automatically.
The pipes directory inside Docker is
/data/pipes
(since
/volume1/screenpipe
→
/data
). You can override it with a
PIPES_DIR
env var if needed.
Message actions
pipe.md
pipe.md
where to place api key and can I use different keys
Thinking
Thinking
Bash
Read .env file
IN
cat /volume1/screenpipe/app/.env
Copy code to clipboard
OUT
[ENV_SECRET]
Where to place the key:
app/.env
app/.env
— replace
your_key_here
with your actual key:
Copy code to clipboard
[ENV_SECRET]
That file is loaded by
load_dotenv()
at startup and is excluded from git via
.gitignore
.
Can you use different keys per pipe?
Not currently — all pipes share the one key from
.env
. But you can add per-pipe key support by adding an
api_key
field to the pipe's frontmatter:
Copy code to clipboard
---
title: Meeting Summary
api_key_env: ANTHROPIC_KEY_MEETINGS
---
Then in
consumers/pipes.py
consumers/pipes.py
, read it in
_parse_frontmatter
and pass it through
run_pipe
. Want me to add that?
Message actions
pipe.md
pipe.md
can I use mistral or other llm? or is is build for antrophic only
Thinking
Thinking
Currently it's Anthropic-only — the code calls the
anthropic
SDK directly in both
consumers/pipes.py
consumers/pipes.py
and
consumers/summary.py
consumers/summary.py
.
Adding other providers is straightforward since Mistral, Ollama, OpenRouter, Groq, and most modern LLMs expose an OpenAI-compatible API. The cleanest approach: add the
openai
package and let you configure the provider via
.env
:
Copy code to clipboard
# Anthropic (default)
[ENV_SECRET]
# OR: any OpenAI-compatible provider
LLM_PROVIDER=openai-compatible
LLM_BASE_URL=https://api.mistral.ai/v1
[ENV_SECRET]
LLM_MODEL=mistral-small-latest
This would cover Mistral, Ollama (
http://localhost:11434/v1
), OpenRouter, Groq, etc. with one code path.
Want me to implement that? It's a small change — a
_call_llm(system, user_prompt)
helper in
pipes.py
that branches on
LLM_PROVIDER
, and
openai
added to
requirements.txt
.
Message actions
lets test it with anthropic first, how to run pipe
Thinking
Thinking
Bash
Check if container is running
IN
cd /volume1/screenpipe/app && docker compose ps 2>/dev/null || docker ps --filter name=screenpipe
Copy code to clipboard
OUT
Exit code 1
permission denied while trying to connect to the Docker daemon socket at unix:///var/run/docker.sock: Get "http://%2Fvar%2Frun%2Fdocker.sock/v1.45/containers/json?filters=%7B%22name%22%3A%7B%22screenpipe%22%3Atrue%7D%7D": dial unix /var/run/docker.sock: connect: permission denied
I don't have Docker socket access, so you'll need to run these yourself. Here are your options:
Option A — via Docker (if container is already running):
Copy code to clipboard
# List available pipes
docker exec -it screenpipe-app python cli.py pipe --list
# Run a specific pipe
docker exec -it screenpipe-app python cli.py pipe day-recap
Option B — rebuild first (since we added new files), then run:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
docker exec -it screenpipe-app python cli.py pipe day-recap
Option C — via the API
(if container is up on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST http://localhost:8766/api/pipes/day-recap/run
The...
|
[{"role":"AXRadioButton","text [{"role":"AXRadioButton","text":"Explorer (⇧⌘E)","depth":19,"on_screen":true,"role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":true,"is_expanded":true},{"role":"AXStaticText","text":"","depth":22,"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Search (⇧⌘F)","depth":19,"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,"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Source Control (⌃⇧G) - 10 pending changes","depth":19,"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,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"10","depth":22,"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Run and Debug (⇧⌘D)","depth":19,"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,"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Remote Explorer","depth":19,"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,"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Extensions (⇧⌘X) - 2 require 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unless-stopped\n ports:\n - \"8766:8000\"\n volumes:\n - /volume1/screenpipe:/data\n env_file:\n - .env\n environment:\n TZ: Europe/Sofia\n DB_PATH: /data/db.sqlite\n\n sqlite-web-archive:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-archive\n restart: unless-stopped\n ports:\n - \"8767:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/archive.db\"]\n\n sqlite-web-live:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-live\n restart: unless-stopped\n ports:\n - \"8768:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", 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their contents","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo \"=== $d ===\"; ls \"$d\"; 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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\n=== /volume1/screenpipe/pipes/ai-habits/ ===\npipe.md\n=== /volume1/screenpipe/pipes/day-recap/ ===\npipe.md\n=== /volume1/screenpipe/pipes/meeting-summary/ ===\npipe.md\n=== /volume1/screenpipe/pipes/standup-update/ ===\npipe.md\n=== /volume1/screenpipe/pipes/time-breakdown/ ===\npipe.md\n=== /volume1/screenpipe/pipes/video-export/ ===\npipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read pipe markdown files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo \"===\" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50","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":"---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.","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":"Read summary consumer","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py","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":"activity.py\naudio.py\nelements.py\n__init__.py\ninteractions.py\nocr.py\n__pycache__\nreport.py\nsummary.py\n\"\"\"AI summary generator using Claude.\"\"\"\nimport os\nfrom datetime import date\nfrom typing import Any\n\nfrom consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary\nfrom consumers.ocr import deduplicated_text\nfrom consumers.audio import formatted_transcript\n\n\nSUMMARY_TYPES = {\n \"day_recap\": {\n \"title\": \"Day Recap\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a concise day recap using EXACTLY this format:\n\n## Summary\nOne sentence: what I mainly worked on today.\n\n## Accomplishments\n- Top 3 things I finished, with approximate times\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things seen or heard, with timestamps\n\n## Unfinished Work\n- What to continue tomorrow\n\n## Patterns\n- Apps used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with:\n**Next step:** [most important thing to continue]\"\"\",\n },\n \"standup\": {\n \"title\": \"Standup Update\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a brief standup update:\n\n**Yesterday:** What I worked on (2-3 bullets)\n**Today:** What I plan to continue (1-2 bullets)\n**Blockers:** Any issues observed (or \"None\")\n\nKeep it under 150 words. Only report what's verifiable from the data.\"\"\",\n },\n \"focus_time\": {\n \"title\": \"Focus & Distraction Analysis\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\nAnalyze focus vs distraction patterns:\n\n## Deep Work Periods\n- When and how long were sustained focus sessions?\n- What was being worked on?\n\n## Distractions\n- Which apps/sites were used recreationally?\n- How much time was lost to context switching?\n\n## Recommendations\n- 2-3 concrete suggestions to improve focus tomorrow\n\nBe specific with times and app names.\"\"\",\n },\n}\n\n\ndef _build_context(for_date: date) -> dict[str, str]:\n apps = app_time(for_date)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(for_date, limit=20)\n url_lines = \"\\n\".join(\n f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls\n )\n\n ui_rows = ui_event_summary(for_date)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(for_date, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(for_date)\n\n return {\n \"app_time\": app_lines or \"(no app data)\",\n \"browser_urls\": url_lines or \"(no browser data)\",\n \"ui_events\": ui_lines or \"(no UI event data)\",\n \"ocr_text\": ocr_lines or \"(no screen data)\",\n \"audio\": audio[:3000] if len(audio) > 3000 else audio,\n }\n\n\ndef generate(\n summary_type: str = \"day_recap\",\n for_date: date | None = None,\n api_key: str | None = None,\n) -> dict[str, Any]:\n \"\"\"Generate an AI summary. Returns dict with 'title', 'content', 'date'.\"\"\"\n import anthropic\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\n \"title\": \"Error\",\n \"content\": \"ANTHROPIC_API_KEY not set. Add it to your .env file.\",\n \"date\": str(d),\n }\n\n spec = SUMMARY_TYPES.get(summary_type)\n if not spec:\n return {\"title\": \"Error\", \"content\": f\"Unknown summary type: {summary_type}\", \"date\": str(d)}\n\n stats = summary_stats(d)\n if stats[\"total_frames\"] == 0:\n return {\n \"title\": spec[\"title\"],\n \"content\": f\"No screen data found for {d}.\",\n \"date\": str(d),\n }\n\n ctx = _build_context(d)\n prompt = spec[\"prompt\"].format(**ctx)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": prompt}],\n )\n\n return {\n \"title\": spec[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","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":"Read all pipe.md files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"for f in /volume1/screenpipe/pipes/*/pipe.md; do echo \"=== $f ===\"; cat \"$f\"; 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":"=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: AI Habits\ndescription: \"How you use AI tools — patterns and insights\"\nicon: \"🤖\"\nfeatured: true\n---\n\nSearch my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## AI Tools Used\n- List each tool with approximate time spent (e.g. \"Claude: ~45min\")\n\n## What I Used Them For\n- For each tool: coding, writing, research, or brainstorming\n\n## Usage Patterns\n- Do I switch between tools? Use them in bursts or steadily?\n\n## Effectiveness\n- Which tool appeared alongside completed work vs. abandoned attempts\n\nIf no AI usage is found, say so clearly. End with: \"**Tip:** [one suggestion to use AI tools more effectively]\"\n\n=== /volume1/screenpipe/pipes/day-recap/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n\n=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.\n\n=== /volume1/screenpipe/pipes/standup-update/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Standup Update\ndescription: \"What you did, what's next, and any blockers\"\nicon: \"🏢\"\nfeatured: true\n---\n\nBased on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Yesterday\n- What I worked on (name specific projects, files, tools, PRs)\n\n## Today\n- What I will work on next (based on unfinished tasks and recent activity)\n\n## Blockers\n- Issues I hit — errors, slow builds, waiting on someone\n- If no blockers, write \"None\"\n\nKeep it under 150 words. Copy-paste ready for a team standup.\n\n=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Time Breakdown\ndescription: \"Where your time went — by app, project, and category\"\nicon: \"⏱\"\nfeatured: false\n---\n\nAnalyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.\n\nRead screenpipe skill first.\n\nUse this exact format with durations and percentages:\n\n## By Application\n- List each app with duration and percentage, sorted by time (e.g. \"VS Code: 2h 15min (28%)\")\n\n## By Category\n- Group into: coding, meetings, browsing, writing, communication, other\n- Show hours and percentage per category\n\n## By Project\n- Group related activities by project/topic. Name specific repos or tasks.\n\n## Productivity Score\n- Calculate: focused_work_hours / total_hours as a percentage\n- Focused = coding + writing. Unfocused = browsing + switching.\n\nEnd with: \"**Suggestion:** [one specific change to improve tomorrow's productivity]\"\n\n=== /volume1/screenpipe/pipes/video-export/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Export Video Clip\ndescription: \"Create a video of your recent screen activity\"\nicon: \"🎬\"\nfeatured: false\n---\n\nExport a video of my screen activity from the last 5 minutes.\n\nRead screenpipe skill first.\n\nUse the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.\n\nIf the export is large, suggest a lower fps or shorter time range.","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 clear picture. The pipes are markdown prompt templates in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe/pipes/","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but there's no code to actually load and run them —","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"has its own hardcoded prompts instead.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Here's what I'll implement:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/pipes.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— two new endpoints:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"GET /api/pipes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /api/pipes/{pipe_id}/run","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cli.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— a","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"command to run pipes from the terminal","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Let me build it:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check browser_urls signature","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/consumers/activity.py | grep \"def browser_urls\" -A 5","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":"def browser_urls(\n for_date: date | None = None,\n app_name: str | None = None,\n ts_from: str | None = None,\n ts_to: str | None = None,\n limit: int = 30,","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":"pipes.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipes.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"143 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"\"\"\"Dynamic pipe loader and runner.\"\"\"\nimport os\nimport re\nfrom datetime import date\nfrom pathlib import Path\nfrom typing import Any\n\n\ndef _parse_frontmatter(text: str) -> tuple[dict, str]:\n if not text.startswith(\"---\"):\n return {}, text\n try:\n end = text.index(\"---\", 3)\n except ValueError:\n return {}, text\n fm_text = text[3:end].strip()\n body = text[end + 3:].strip()\n meta: dict = {}\n for line in fm_text.splitlines():\n if \":\" in line:\n k, _, v = line.partition(\":\")\n meta[k.strip()] = v.strip().strip('\"')\n return meta, body\n\n\ndef load_pipes(pipes_dir: Path) -> list[dict]:\n if not pipes_dir.exists():\n return []\n pipes = []\n for pipe_dir in sorted(pipes_dir.iterdir()):\n if not pipe_dir.is_dir() or pipe_dir.name.startswith(\".\"):\n continue\n pipe_md = pipe_dir / \"pipe.md\"\n if not pipe_md.exists():\n continue\n text = pipe_md.read_text(encoding=\"utf-8\")\n meta, body = _parse_frontmatter(text)\n if meta.get(\"enabled\", \"true\").lower() == \"false\":\n continue\n body = re.sub(r\"Read screenpipe skill first\\.?\\n?\", \"\", body).strip()\n pipes.append({\n \"id\": pipe_dir.name,\n \"title\": meta.get(\"title\", pipe_dir.name),\n \"description\": meta.get(\"description\", \"\"),\n \"icon\": meta.get(\"icon\", \"\"),\n \"schedule\": meta.get(\"schedule\", \"manual\"),\n \"featured\": meta.get(\"featured\", \"false\").lower() == \"true\",\n \"prompt\": body,\n })\n return pipes\n\n\ndef _build_system(d: date, stats: dict) -> str:\n from consumers.activity import app_time, browser_urls, ui_event_summary\n from consumers.ocr import deduplicated_text\n from consumers.audio import formatted_transcript\n\n apps = app_time(d)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(d, limit=20)\n url_lines = \"\\n\".join(f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls)\n\n ui_rows = ui_event_summary(d)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(d, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(d)\n if len(audio) > 3000:\n audio = audio[:3000]\n\n return f\"\"\"You are analyzing screenpipe data — recordings of a person's computer activity.\n\n## App usage (minutes per app):\n{app_lines or '(no app data)'}\n\n## Browser URLs visited:\n{url_lines or '(no browser data)'}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_lines or '(no UI event data)'}\n\n## Screen content (sampled every 5 minutes):\n{ocr_lines or '(no screen data)'}\n\n## Audio / speech:\n{audio or '(no audio data)'}\n\nDate: {d}\nTotal frames recorded: {stats['total_frames']}\"\"\"\n\n\ndef run_pipe(\n pipe_id: str,\n for_date: date | None = None,\n api_key: str | None = None,\n pipes_dir: Path | None = None,\n) -> dict[str, Any]:\n import anthropic\n from consumers.activity import summary_stats\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\"title\": \"Error\", \"content\": \"ANTHROPIC_API_KEY not set.\", \"date\": str(d)}\n\n _pipes_dir = pipes_dir or Path(os.environ.get(\"PIPES_DIR\", \"/data/pipes\"))\n all_pipes = {p[\"id\"]: p for p in load_pipes(_pipes_dir)}\n\n if pipe_id not in all_pipes:\n return {\"title\": \"Error\", \"content\": f\"Pipe not found: {pipe_id}\", \"date\": str(d)}\n\n pipe = all_pipes[pipe_id]\n stats = summary_stats(d)\n\n if stats[\"total_frames\"] == 0:\n return {\"title\": pipe[\"title\"], \"content\": f\"No screen data found for {d}.\", \"date\": str(d)}\n\n system = _build_system(d, stats)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n system=system,\n messages=[{\"role\": \"user\", \"content\": pipe[\"prompt\"]}],\n )\n\n return {\n \"title\": pipe[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the API endpoints to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the pipe endpoints at the end of main.py, before the closing summary section:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 14 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the CLI command to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 40 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Done. Here's how to run pipes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to run pipes","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to run pipes","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via Docker (inside the running container):","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"docker exec -it screenpipe-app python cli.py pipe --list\ndocker exec -it screenpipe-app python cli.py pipe day-recap\ndocker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via the API","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(once the container is running on port 8766):","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# List pipes\ncurl http://localhost:8766/api/pipes\n\n# Run a pipe\ncurl -X POST \"http://localhost:8766/api/pipes/day-recap/run\"\ncurl -X POST \"http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rebuild and restart","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to pick up the changes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"cd /volume1/screenpipe/app\ndocker compose up --build -d","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"How it works:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Each","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The \"Read screenpipe skill first\" line is stripped automatically.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The pipes directory inside Docker is","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data/pipes","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(since","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"→","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). You can override it with a","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"PIPES_DIR","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"env var if needed.","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":"AXButton","text":"pipe.md","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"where to place api key and can I use different keys","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":"Read .env file","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/.env","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":"ANTHROPIC_API_KEY=your_key_here","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Where to place the key:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"app/.env","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"app/.env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— replace","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"your_key_here","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with your actual key:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"ANTHROPIC_API_KEY=sk-ant-...","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"That file is loaded by","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"load_dotenv()","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"at startup and is excluded from git via","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".gitignore","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Can you use different keys per pipe?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Not currently — all pipes share the one key from","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". But you can add per-pipe key support by adding an","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"api_key","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"field to the pipe's frontmatter:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"---\ntitle: Meeting Summary\napi_key_env: ANTHROPIC_KEY_MEETINGS\n---","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Then in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/pipes.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/pipes.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", read it in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"_parse_frontmatter","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and pass it through","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"run_pipe","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". Want me to add that?","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":"AXButton","text":"pipe.md","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"can I use mistral or other llm? or is is build for antrophic only","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":"Currently it's Anthropic-only — the code calls the","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"anthropic","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SDK directly in both","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/pipes.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/pipes.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/summary.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Adding other providers is straightforward since Mistral, Ollama, OpenRouter, Groq, and most modern LLMs expose an OpenAI-compatible API. The cleanest approach: add the","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"openai","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"package and let you configure the provider via","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# Anthropic (default)\nANTHROPIC_API_KEY=sk-ant-...\n\n# OR: any OpenAI-compatible provider\nLLM_PROVIDER=openai-compatible\nLLM_BASE_URL=https://api.mistral.ai/v1\nLLM_API_KEY=your-mistral-key\nLLM_MODEL=mistral-small-latest","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"This would cover Mistral, Ollama (","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"http://localhost:11434/v1","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"), OpenRouter, Groq, etc. with one code path.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Want me to implement that? It's a small change — a","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"_call_llm(system, user_prompt)","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"helper in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipes.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"that branches on","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"LLM_PROVIDER","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", and","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"openai","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"added to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"requirements.txt","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","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":"lets test it with anthropic first, how to run pipe","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":"Check if container is running","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cd /volume1/screenpipe/app && docker compose ps 2>/dev/null || docker ps --filter name=screenpipe","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\npermission denied while trying to connect to the Docker daemon socket at unix:///var/run/docker.sock: Get \"http://%2Fvar%2Frun%2Fdocker.sock/v1.45/containers/json?filters=%7B%22name%22%3A%7B%22screenpipe%22%3Atrue%7D%7D\": dial unix /var/run/docker.sock: connect: permission denied","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"I don't have Docker socket access, so you'll need to run these yourself. Here are your options:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option A — via Docker (if container is already running):","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# List available pipes\ndocker exec -it screenpipe-app python cli.py pipe --list\n\n# Run a specific pipe\ndocker exec -it screenpipe-app python cli.py pipe day-recap","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option B — rebuild first (since we added new files), then run:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"cd /volume1/screenpipe/app\ndocker compose up --build -d\ndocker exec -it screenpipe-app python cli.py pipe day-recap","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option C — via the API","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(if container is up on port 8766):","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# List pipes\ncurl http://localhost:8766/api/pipes\n\n# Run a pipe\ncurl -X POST http://localhost:8766/api/pipes/day-recap/run","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The","depth":23,"on_screen":false,"role_description":"text"}]...
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idle
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accessibility
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST "http://localhost:8766/api/pipes/day-recap/run"
curl -X POST "http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25"
Rebuild and restart
to pick up the changes:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
How it works:
Each
pipe.md
file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The "Read screenpipe skill first" line is stripped automatically.
The pipes directory inside Docker is
/data/pipes
(since
/volume1/screenpipe
→
/data
). You can override it with a
PIPES_DIR
env var if needed.
Message actions
pipe.md
pipe.md
where to place api key and can I use different keys
Thinking
Thinking
Bash
Read .env file
IN
cat /volume1/screenpipe/app/.env
Copy code to clipboard
OUT
[ENV_SECRET]
Where to place the key:
app/.env
app/.env
— replace
your_key_here
with your actual key:
Copy code to clipboard
[ENV_SECRET]
That file is loaded by
load_dotenv()
at startup and is excluded from git via
.gitignore
.
Can you use different keys per pipe?
Not currently — all pipes share the one key from
.env
. But you can add per-pipe key support by adding an
api_key
field to the pipe's frontmatter:
Copy code to clipboard
---
title: Meeting Summary
api_key_env: ANTHROPIC_KEY_MEETINGS
---
Then in
consumers/pipes.py
consumers/pipes.py
, read it in
_parse_frontmatter
and pass it through
run_pipe
. Want me to add that?
Message actions
pipe.md
pipe.md
can I use mistral or other llm? or is is build for antrophic only
Thinking
Thinking
Currently it's Anthropic-only — the code calls the
anthropic
SDK directly in both
consumers/pipes.py
consumers/pipes.py
and
consumers/summary.py
consumers/summary.py
.
Adding other providers is straightforward since Mistral, Ollama, OpenRouter, Groq, and most modern LLMs expose an OpenAI-compatible API. The cleanest approach: add the
openai
package and let you configure the provider via
.env
:
Copy code to clipboard
# Anthropic (default)
[ENV_SECRET]
# OR: any OpenAI-compatible provider
LLM_PROVIDER=openai-compatible
LLM_BASE_URL=https://api.mistral.ai/v1
[ENV_SECRET]
LLM_MODEL=mistral-small-latest
This would cover Mistral, Ollama (
http://localhost:11434/v1
), OpenRouter, Groq, etc. with one code path.
Want me to implement that? It's a small change — a
_call_llm(system, user_prompt)
helper in
pipes.py
that branches on
LLM_PROVIDER
, and
openai
added to
requirements.txt
.
Message actions
lets test it with anthropic first, how to run pipe
Thinking
Thinking
Bash
Check if container is running
IN
cd /volume1/screenpipe/app && docker compose ps 2>/dev/null || docker ps --filter name=screenpipe
Copy code to clipboard
OUT
Exit code 1
permission denied while trying to connect to the Docker daemon socket at unix:///var/run/docker.sock: Get "http://%2Fvar%2Frun%2Fdocker.sock/v1.45/containers/json?filters=%7B%22name%22%3A%7B%22screenpipe%22%3Atrue%7D%7D": dial unix /var/run/docker.sock: connect: permission denied
I don't have Docker socket access, so you'll need to run these yourself. Here are your options:
Option A — via Docker (if container is already running):
Copy code to clipboard
# List available pipes
docker exec -it screenpipe-app python cli.py pipe --list
# Run a specific pipe
docker exec -it screenpipe-app python cli.py pipe day-recap
Option B — rebuild first (since we added new files), then run:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
docker exec -it screenpipe-app python cli.py pipe day-recap
Option C — via the API
(if container is up on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST http://localhost:8766/api/pipes/day-recap/run
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2026-05-11T17:10:07.803191+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519407803_m2.jpg...
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Code
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Implement and run pipe l… — screenpipe [SSH: nas]
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True
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NULL
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monitor_2
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section...
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Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
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Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section...
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21074
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920
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2026-05-11T17:09:49.076795+00:00
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Code
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Implement and run pipe l… — screenpipe [SSH: nas]
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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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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
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TERMINAL
Ports - 1 forwarded port
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remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
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Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
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OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST "http://localhost:8766/api/pipes/day-recap/run"
curl -X POST "http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25"
Rebuild and restart
to pick up the changes:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
How it works:
Each
pipe.md
file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The "Read screenpipe skill first" line is stripped automatically.
The pipes directory inside Docker is
/data/pipes
(since
/volume1/screenpipe
→
/data
). You can override it with a
PIPES_DIR
env var if needed.
Message actions
pipe.md
pipe.md
where to place api key and can I use different keys
Thinking
Thinking
Bash
Read .env file
IN
cat /volume1/screenpipe/app/.env
Copy code to clipboard
OUT
[ENV_SECRET]
Where to place the key:
app/.env
app/.env
— replace
your_key_here
with your actual key:
Copy code to clipboard
[ENV_SECRET]
That file is loaded by
load_dotenv()
at startup and is excluded from git via
.gitignore
.
Can you use different keys per pipe?
Not currently — all pipes share the one key from
.env
. But you can add per-pipe key support by adding an
api_key
field to the pipe's frontmatter:
Copy code to clipboard
---
title: Meeting Summary
api_key_env: ANTHROPIC_KEY_MEETINGS
---
Then in
consumers/pipes.py
consumers/pipes.py
, read it in...
|
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\"/data/db.sqlite\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"requirements.txt","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"requirements.txt","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Inspect a pipe directory","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/","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":"pipe.md\npipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"List all pipes and their contents","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo \"=== $d ===\"; ls \"$d\"; 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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\n=== /volume1/screenpipe/pipes/ai-habits/ ===\npipe.md\n=== /volume1/screenpipe/pipes/day-recap/ ===\npipe.md\n=== /volume1/screenpipe/pipes/meeting-summary/ ===\npipe.md\n=== /volume1/screenpipe/pipes/standup-update/ ===\npipe.md\n=== /volume1/screenpipe/pipes/time-breakdown/ ===\npipe.md\n=== /volume1/screenpipe/pipes/video-export/ ===\npipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read pipe markdown files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo \"===\" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50","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":"---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.","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":"Read summary consumer","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py","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":"activity.py\naudio.py\nelements.py\n__init__.py\ninteractions.py\nocr.py\n__pycache__\nreport.py\nsummary.py\n\"\"\"AI summary generator using Claude.\"\"\"\nimport os\nfrom datetime import date\nfrom typing import Any\n\nfrom consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary\nfrom consumers.ocr import deduplicated_text\nfrom consumers.audio import formatted_transcript\n\n\nSUMMARY_TYPES = {\n \"day_recap\": {\n \"title\": \"Day Recap\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a concise day recap using EXACTLY this format:\n\n## Summary\nOne sentence: what I mainly worked on today.\n\n## Accomplishments\n- Top 3 things I finished, with approximate times\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things seen or heard, with timestamps\n\n## Unfinished Work\n- What to continue tomorrow\n\n## Patterns\n- Apps used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with:\n**Next step:** [most important thing to continue]\"\"\",\n },\n \"standup\": {\n \"title\": \"Standup Update\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a brief standup update:\n\n**Yesterday:** What I worked on (2-3 bullets)\n**Today:** What I plan to continue (1-2 bullets)\n**Blockers:** Any issues observed (or \"None\")\n\nKeep it under 150 words. Only report what's verifiable from the data.\"\"\",\n },\n \"focus_time\": {\n \"title\": \"Focus & Distraction Analysis\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\nAnalyze focus vs distraction patterns:\n\n## Deep Work Periods\n- When and how long were sustained focus sessions?\n- What was being worked on?\n\n## Distractions\n- Which apps/sites were used recreationally?\n- How much time was lost to context switching?\n\n## Recommendations\n- 2-3 concrete suggestions to improve focus tomorrow\n\nBe specific with times and app names.\"\"\",\n },\n}\n\n\ndef _build_context(for_date: date) -> dict[str, str]:\n apps = app_time(for_date)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(for_date, limit=20)\n url_lines = \"\\n\".join(\n f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls\n )\n\n ui_rows = ui_event_summary(for_date)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(for_date, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(for_date)\n\n return {\n \"app_time\": app_lines or \"(no app data)\",\n \"browser_urls\": url_lines or \"(no browser data)\",\n \"ui_events\": ui_lines or \"(no UI event data)\",\n \"ocr_text\": ocr_lines or \"(no screen data)\",\n \"audio\": audio[:3000] if len(audio) > 3000 else audio,\n }\n\n\ndef generate(\n summary_type: str = \"day_recap\",\n for_date: date | None = None,\n api_key: str | None = None,\n) -> dict[str, Any]:\n \"\"\"Generate an AI summary. Returns dict with 'title', 'content', 'date'.\"\"\"\n import anthropic\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\n \"title\": \"Error\",\n \"content\": \"ANTHROPIC_API_KEY not set. Add it to your .env file.\",\n \"date\": str(d),\n }\n\n spec = SUMMARY_TYPES.get(summary_type)\n if not spec:\n return {\"title\": \"Error\", \"content\": f\"Unknown summary type: {summary_type}\", \"date\": str(d)}\n\n stats = summary_stats(d)\n if stats[\"total_frames\"] == 0:\n return {\n \"title\": spec[\"title\"],\n \"content\": f\"No screen data found for {d}.\",\n \"date\": str(d),\n }\n\n ctx = _build_context(d)\n prompt = spec[\"prompt\"].format(**ctx)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": prompt}],\n )\n\n return {\n \"title\": spec[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","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":"Read all pipe.md files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"for f in /volume1/screenpipe/pipes/*/pipe.md; do echo \"=== $f ===\"; cat \"$f\"; 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":"=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: AI Habits\ndescription: \"How you use AI tools — patterns and insights\"\nicon: \"🤖\"\nfeatured: true\n---\n\nSearch my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## AI Tools Used\n- List each tool with approximate time spent (e.g. \"Claude: ~45min\")\n\n## What I Used Them For\n- For each tool: coding, writing, research, or brainstorming\n\n## Usage Patterns\n- Do I switch between tools? Use them in bursts or steadily?\n\n## Effectiveness\n- Which tool appeared alongside completed work vs. abandoned attempts\n\nIf no AI usage is found, say so clearly. End with: \"**Tip:** [one suggestion to use AI tools more effectively]\"\n\n=== /volume1/screenpipe/pipes/day-recap/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n\n=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.\n\n=== /volume1/screenpipe/pipes/standup-update/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Standup Update\ndescription: \"What you did, what's next, and any blockers\"\nicon: \"🏢\"\nfeatured: true\n---\n\nBased on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Yesterday\n- What I worked on (name specific projects, files, tools, PRs)\n\n## Today\n- What I will work on next (based on unfinished tasks and recent activity)\n\n## Blockers\n- Issues I hit — errors, slow builds, waiting on someone\n- If no blockers, write \"None\"\n\nKeep it under 150 words. Copy-paste ready for a team standup.\n\n=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Time Breakdown\ndescription: \"Where your time went — by app, project, and category\"\nicon: \"⏱\"\nfeatured: false\n---\n\nAnalyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.\n\nRead screenpipe skill first.\n\nUse this exact format with durations and percentages:\n\n## By Application\n- List each app with duration and percentage, sorted by time (e.g. \"VS Code: 2h 15min (28%)\")\n\n## By Category\n- Group into: coding, meetings, browsing, writing, communication, other\n- Show hours and percentage per category\n\n## By Project\n- Group related activities by project/topic. Name specific repos or tasks.\n\n## Productivity Score\n- Calculate: focused_work_hours / total_hours as a percentage\n- Focused = coding + writing. Unfocused = browsing + switching.\n\nEnd with: \"**Suggestion:** [one specific change to improve tomorrow's productivity]\"\n\n=== /volume1/screenpipe/pipes/video-export/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Export Video Clip\ndescription: \"Create a video of your recent screen activity\"\nicon: \"🎬\"\nfeatured: false\n---\n\nExport a video of my screen activity from the last 5 minutes.\n\nRead screenpipe skill first.\n\nUse the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.\n\nIf the export is large, suggest a lower fps or shorter time range.","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 clear picture. The pipes are markdown prompt templates in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe/pipes/","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but there's no code to actually load and run them —","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"has its own hardcoded prompts instead.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Here's what I'll implement:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/pipes.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— two new endpoints:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"GET /api/pipes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /api/pipes/{pipe_id}/run","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cli.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— a","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"command to run pipes from the terminal","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Let me build it:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check browser_urls signature","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/consumers/activity.py | grep \"def browser_urls\" -A 5","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":"def browser_urls(\n for_date: date | None = None,\n app_name: str | None = None,\n ts_from: str | None = None,\n ts_to: str | None = None,\n limit: int = 30,","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":"pipes.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipes.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"143 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"\"\"\"Dynamic pipe loader and runner.\"\"\"\nimport os\nimport re\nfrom datetime import date\nfrom pathlib import Path\nfrom typing import Any\n\n\ndef _parse_frontmatter(text: str) -> tuple[dict, str]:\n if not text.startswith(\"---\"):\n return {}, text\n try:\n end = text.index(\"---\", 3)\n except ValueError:\n return {}, text\n fm_text = text[3:end].strip()\n body = text[end + 3:].strip()\n meta: dict = {}\n for line in fm_text.splitlines():\n if \":\" in line:\n k, _, v = line.partition(\":\")\n meta[k.strip()] = v.strip().strip('\"')\n return meta, body\n\n\ndef load_pipes(pipes_dir: Path) -> list[dict]:\n if not pipes_dir.exists():\n return []\n pipes = []\n for pipe_dir in sorted(pipes_dir.iterdir()):\n if not pipe_dir.is_dir() or pipe_dir.name.startswith(\".\"):\n continue\n pipe_md = pipe_dir / \"pipe.md\"\n if not pipe_md.exists():\n continue\n text = pipe_md.read_text(encoding=\"utf-8\")\n meta, body = _parse_frontmatter(text)\n if meta.get(\"enabled\", \"true\").lower() == \"false\":\n continue\n body = re.sub(r\"Read screenpipe skill first\\.?\\n?\", \"\", body).strip()\n pipes.append({\n \"id\": pipe_dir.name,\n \"title\": meta.get(\"title\", pipe_dir.name),\n \"description\": meta.get(\"description\", \"\"),\n \"icon\": meta.get(\"icon\", \"\"),\n \"schedule\": meta.get(\"schedule\", \"manual\"),\n \"featured\": meta.get(\"featured\", \"false\").lower() == \"true\",\n \"prompt\": body,\n })\n return pipes\n\n\ndef _build_system(d: date, stats: dict) -> str:\n from consumers.activity import app_time, browser_urls, ui_event_summary\n from consumers.ocr import deduplicated_text\n from consumers.audio import formatted_transcript\n\n apps = app_time(d)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(d, limit=20)\n url_lines = \"\\n\".join(f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls)\n\n ui_rows = ui_event_summary(d)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(d, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(d)\n if len(audio) > 3000:\n audio = audio[:3000]\n\n return f\"\"\"You are analyzing screenpipe data — recordings of a person's computer activity.\n\n## App usage (minutes per app):\n{app_lines or '(no app data)'}\n\n## Browser URLs visited:\n{url_lines or '(no browser data)'}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_lines or '(no UI event data)'}\n\n## Screen content (sampled every 5 minutes):\n{ocr_lines or '(no screen data)'}\n\n## Audio / speech:\n{audio or '(no audio data)'}\n\nDate: {d}\nTotal frames recorded: {stats['total_frames']}\"\"\"\n\n\ndef run_pipe(\n pipe_id: str,\n for_date: date | None = None,\n api_key: str | None = None,\n pipes_dir: Path | None = None,\n) -> dict[str, Any]:\n import anthropic\n from consumers.activity import summary_stats\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\"title\": \"Error\", \"content\": \"ANTHROPIC_API_KEY not set.\", \"date\": str(d)}\n\n _pipes_dir = pipes_dir or Path(os.environ.get(\"PIPES_DIR\", \"/data/pipes\"))\n all_pipes = {p[\"id\"]: p for p in load_pipes(_pipes_dir)}\n\n if pipe_id not in all_pipes:\n return {\"title\": \"Error\", \"content\": f\"Pipe not found: {pipe_id}\", \"date\": str(d)}\n\n pipe = all_pipes[pipe_id]\n stats = summary_stats(d)\n\n if stats[\"total_frames\"] == 0:\n return {\"title\": pipe[\"title\"], \"content\": f\"No screen data found for {d}.\", \"date\": str(d)}\n\n system = _build_system(d, stats)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n system=system,\n messages=[{\"role\": \"user\", \"content\": pipe[\"prompt\"]}],\n )\n\n return {\n \"title\": pipe[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the API endpoints to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the pipe endpoints at the end of main.py, before the closing summary section:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 14 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the CLI command to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 40 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Done. Here's how to run pipes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to run pipes","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to run pipes","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via Docker (inside the running container):","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"docker exec -it screenpipe-app python cli.py pipe --list\ndocker exec -it screenpipe-app python cli.py pipe day-recap\ndocker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via the API","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(once the container is running on port 8766):","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# List pipes\ncurl http://localhost:8766/api/pipes\n\n# Run a pipe\ncurl -X POST \"http://localhost:8766/api/pipes/day-recap/run\"\ncurl -X POST \"http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rebuild and restart","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to pick up the changes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"cd /volume1/screenpipe/app\ndocker compose up --build -d","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"How it works:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Each","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The \"Read screenpipe skill first\" line is stripped automatically.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The pipes directory inside Docker is","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data/pipes","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(since","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"→","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). You can override it with a","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"PIPES_DIR","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"env var if needed.","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":"AXButton","text":"pipe.md","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"where to place api key and can I use different keys","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":"Read .env file","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/.env","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":"ANTHROPIC_API_KEY=your_key_here","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Where to place the key:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"app/.env","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"app/.env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— replace","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"your_key_here","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with your actual key:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"ANTHROPIC_API_KEY=sk-ant-...","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"That file is loaded by","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"load_dotenv()","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"at startup and is excluded from git via","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".gitignore","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Can you use different keys per pipe?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Not currently — all pipes share the one key from","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". But you can add per-pipe key support by adding an","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"api_key","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"field to the pipe's frontmatter:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"---\ntitle: Meeting Summary\napi_key_env: ANTHROPIC_KEY_MEETINGS\n---","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Then in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/pipes.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/pipes.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", read it in","depth":23,"on_screen":false,"role_description":"text"}]...
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-8763496496607803156
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idle
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accessibility
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NULL
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST "http://localhost:8766/api/pipes/day-recap/run"
curl -X POST "http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25"
Rebuild and restart
to pick up the changes:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
How it works:
Each
pipe.md
file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The "Read screenpipe skill first" line is stripped automatically.
The pipes directory inside Docker is
/data/pipes
(since
/volume1/screenpipe
→
/data
). You can override it with a
PIPES_DIR
env var if needed.
Message actions
pipe.md
pipe.md
where to place api key and can I use different keys
Thinking
Thinking
Bash
Read .env file
IN
cat /volume1/screenpipe/app/.env
Copy code to clipboard
OUT
[ENV_SECRET]
Where to place the key:
app/.env
app/.env
— replace
your_key_here
with your actual key:
Copy code to clipboard
[ENV_SECRET]
That file is loaded by
load_dotenv()
at startup and is excluded from git via
.gitignore
.
Can you use different keys per pipe?
Not currently — all pipes share the one key from
.env
. But you can add per-pipe key support by adding an
api_key
field to the pipe's frontmatter:
Copy code to clipboard
---
title: Meeting Summary
api_key_env: ANTHROPIC_KEY_MEETINGS
---
Then in
consumers/pipes.py
consumers/pipes.py
, read it in...
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NULL
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NULL
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NULL
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NULL
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21073
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921
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7
|
2026-05-11T17:09:37.404118+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519377404_m2.jpg...
|
Code
|
Implement and run pipe l… — screenpipe [SSH: nas]
|
True
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NULL
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monitor_2
|
NULL
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NULL
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NULL
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NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST "http://localhost:8766/api/pipes/day-recap/run"
curl -X POST "http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25"
Rebuild and restart
to pick up the changes:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
How it works:
Each
pipe.md
file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The "Read screenpipe skill first" line is stripped automatically.
The pipes directory inside Docker is
/data/pipes
(since
/volume1/screenpipe
→
/data
). You can override it with a
PIPES_DIR
env var if needed.
Message actions
pipe.md
pipe.md
where to place api key and can I use different keys
Thinking
Thinking
Bash
Read .env file
IN
cat /volume1/screenpipe/app/.env
Copy code to clipboard
OUT
[ENV_SECRET]
Where to place the key:
app/.env
app/.env
— replace
your_key_here
with your actual key:
Copy code to clipboard
[ENV_SECRET]
That file is loaded by
load_dotenv()
at startup and is excluded from git via
.gitignore
.
Can you use different keys per pipe?
Not currently — all pipes share the one key from
.env
. But you can add per-pipe key support by adding an
api_key
field to the pipe's frontmatter:
Copy code to clipboard
---
title: Meeting Summary
api_key_env: ANTHROPIC_KEY_MEETINGS
---
Then in
consumers/pipes.py
consumers/pipes.py
, read it in
_parse_frontmatter
and pass it through
run_pipe
. Want me to add that?
Message actions
pipe.md
pipe.md
can I use mistral or other llm? or is is build for antrophic only
Thinking
Thinking
Currently it's Anthropic-only — the code calls the
anthropic
SDK directly in both
consumers/pipes.py
consumers/pipes.py
and
consumers/summary.py
consumers/summary.py
.
Adding other providers is straightforward since Mistral, Ollama, OpenRouter, Groq, and most modern LLMs expose an OpenAI-compatible API. The cleanest approach: add the
openai
package and let you configure the provider via
.env
:
Copy code to clipboard
# Anthropic (default)
[ENV_SECRET]
# OR: any OpenAI-compatible provider
LLM_PROVIDER=openai-compatible
LLM_BASE_URL=https://api.mistral.ai/v1
[ENV_SECRET]
LLM_MODEL=mistral-small-latest
This would cover Mistral, Ollama (
http://localhost:11434/v1
), OpenRouter, Groq, etc. with one code path.
Want me to implement that? It's a small change — a
_call_llm(system, user_prompt)
helper in
pipes.py
that branches on
LLM_PROVIDER...
|
[{"role":"AXRadioButton","text [{"role":"AXRadioButton","text":"Explorer (⇧⌘E)","depth":19,"bounds":{"left":0.0,"top":0.047885075,"width":0.015957447,"height":0.03830806},"on_screen":true,"role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":true,"is_expanded":true},{"role":"AXStaticText","text":"","depth":22,"bounds":{"left":0.0039893617,"top":0.057462092,"width":0.007978723,"height":0.01915403},"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Search (⇧⌘F)","depth":19,"bounds":{"left":0.0,"top":0.08619314,"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":0.09577015,"width":0.007978723,"height":0.01915403},"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Source Control (⌃⇧G) - 10 pending changes","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":"AXStaticText","text":"10","depth":22,"bounds":{"left":0.00831117,"top":0.1452514,"width":0.003656915,"height":0.008778931},"on_screen":true,"lines":[{"char_start":0,"char_count":1,"bounds":{"left":0.00831117,"top":0.14604948,"width":0.0016622341,"height":0.007980846}},{"char_start":1,"char_count":1,"bounds":{"left":0.009973404,"top":0.14604948,"width":0.0023271276,"height":0.007980846}}],"role_description":"text"},{"role":"AXRadioButton","text":"Run and Debug 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place.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"List project files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"find /volume1/screenpipe -type f | head -50 && echo \"---\" && ls /volume1/screenpipe","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":"/volume1/screenpipe/.DS_Store\n/volume1/screenpipe/screenpipe.db\n/volume1/screenpipe/screenpipe_sync.sh\n/volume1/screenpipe/app_settings.json\n/volume1/screenpipe/.gitignore\n/volume1/screenpipe/archive.db\n/volume1/screenpipe/db.sqlite\n/volume1/screenpipe/db.sqlite-wal\n/volume1/screenpipe/db.sqlite-shm\n/volume1/screenpipe/#recycle/desktop.ini\n/volume1/screenpipe/#recycle/db.sqlite\n/volume1/screenpipe/#recycle/Copy #1 of db.sqlite\n/volume1/screenpipe/#recycle/.DS_Store\n/volume1/screenpipe/#recycle/Copy #2 of db.sqlite\n/volume1/screenpipe/#recycle/archive.db\n/volume1/screenpipe/#recycle/Copy #1 of archive.db\n/volume1/screenpipe/#recycle/Copy #2 of archive.db\n/volume1/screenpipe/#recycle/Copy #3 of archive.db\n/volume1/screenpipe/#recycle/Copy #4 of archive.db\n/volume1/screenpipe/#recycle/Copy #5 of archive.db\n/volume1/screenpipe/#recycle/Copy #3 of db.sqlite\n/volume1/screenpipe/#recycle/Copy #4 of db.sqlite\n/volume1/screenpipe/#recycle/Copy #6 of archive.db\n/volume1/screenpipe/#recycle/test.txt\n/volume1/screenpipe/#recycle/Copy #7 of archive.db\n/volume1/screenpipe/#recycle/Copy #8 of archive.db\n/volume1/screenpipe/#recycle/archive.db-journal\n/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #5 of db.sqlite\n/volume1/screenpipe/pipes/.DS_Store\n/volume1/screenpipe/app/.env\n/volume1/screenpipe/app/cli.py\n/volume1/screenpipe/app/.DS_Store\n/volume1/screenpipe/app/db.py\n/volume1/screenpipe/app/docker-compose.yml\n/volume1/screenpipe/app/main.py\n/volume1/screenpipe/app/requirements.txt\n/volume1/screenpipe/app/Dockerfile\n/volume1/screenpipe/data/.DS_Store\n/volume1/screenpipe/.git/description\n/volume1/screenpipe/.git/HEAD\n/volume1/screenpipe/.git/index\n/volume1/screenpipe/.git/COMMIT_EDITMSG\n/volume1/screenpipe/#recycle/data/.DS_Store\n---\napp\napp_settings.json\narchive.db\ndata\ndb.sqlite\ndb.sqlite-shm\ndb.sqlite-wal\npipes\n#recycle\nscreenpipe.db\nscreenpipe_sync.sh","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check pipes directory and docker-compose","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml","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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\ncli.py\nconsumers\ndb.py\ndocker-compose.yml\nDockerfile\nmain.py\n__pycache__\nrequirements.txt\nstatic\nservices:\n screenpipe-app:\n build: .\n container_name: screenpipe-app\n restart: unless-stopped\n ports:\n - \"8766:8000\"\n volumes:\n - /volume1/screenpipe:/data\n env_file:\n - .env\n environment:\n TZ: Europe/Sofia\n DB_PATH: /data/db.sqlite\n\n sqlite-web-archive:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-archive\n restart: unless-stopped\n ports:\n - \"8767:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/archive.db\"]\n\n sqlite-web-live:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-live\n restart: unless-stopped\n ports:\n - \"8768:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/db.sqlite\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"requirements.txt","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"requirements.txt","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Inspect a pipe directory","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/","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":"pipe.md\npipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"List all pipes and their contents","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo \"=== $d ===\"; ls \"$d\"; 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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\n=== /volume1/screenpipe/pipes/ai-habits/ ===\npipe.md\n=== /volume1/screenpipe/pipes/day-recap/ ===\npipe.md\n=== /volume1/screenpipe/pipes/meeting-summary/ ===\npipe.md\n=== /volume1/screenpipe/pipes/standup-update/ ===\npipe.md\n=== /volume1/screenpipe/pipes/time-breakdown/ ===\npipe.md\n=== /volume1/screenpipe/pipes/video-export/ ===\npipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read pipe markdown files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo \"===\" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50","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":"---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.","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":"Read summary consumer","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py","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":"activity.py\naudio.py\nelements.py\n__init__.py\ninteractions.py\nocr.py\n__pycache__\nreport.py\nsummary.py\n\"\"\"AI summary generator using Claude.\"\"\"\nimport os\nfrom datetime import date\nfrom typing import Any\n\nfrom consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary\nfrom consumers.ocr import deduplicated_text\nfrom consumers.audio import formatted_transcript\n\n\nSUMMARY_TYPES = {\n \"day_recap\": {\n \"title\": \"Day Recap\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a concise day recap using EXACTLY this format:\n\n## Summary\nOne sentence: what I mainly worked on today.\n\n## Accomplishments\n- Top 3 things I finished, with approximate times\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things seen or heard, with timestamps\n\n## Unfinished Work\n- What to continue tomorrow\n\n## Patterns\n- Apps used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with:\n**Next step:** [most important thing to continue]\"\"\",\n },\n \"standup\": {\n \"title\": \"Standup Update\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a brief standup update:\n\n**Yesterday:** What I worked on (2-3 bullets)\n**Today:** What I plan to continue (1-2 bullets)\n**Blockers:** Any issues observed (or \"None\")\n\nKeep it under 150 words. Only report what's verifiable from the data.\"\"\",\n },\n \"focus_time\": {\n \"title\": \"Focus & Distraction Analysis\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\nAnalyze focus vs distraction patterns:\n\n## Deep Work Periods\n- When and how long were sustained focus sessions?\n- What was being worked on?\n\n## Distractions\n- Which apps/sites were used recreationally?\n- How much time was lost to context switching?\n\n## Recommendations\n- 2-3 concrete suggestions to improve focus tomorrow\n\nBe specific with times and app names.\"\"\",\n },\n}\n\n\ndef _build_context(for_date: date) -> dict[str, str]:\n apps = app_time(for_date)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(for_date, limit=20)\n url_lines = \"\\n\".join(\n f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls\n )\n\n ui_rows = ui_event_summary(for_date)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(for_date, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(for_date)\n\n return {\n \"app_time\": app_lines or \"(no app data)\",\n \"browser_urls\": url_lines or \"(no browser data)\",\n \"ui_events\": ui_lines or \"(no UI event data)\",\n \"ocr_text\": ocr_lines or \"(no screen data)\",\n \"audio\": audio[:3000] if len(audio) > 3000 else audio,\n }\n\n\ndef generate(\n summary_type: str = \"day_recap\",\n for_date: date | None = None,\n api_key: str | None = None,\n) -> dict[str, Any]:\n \"\"\"Generate an AI summary. Returns dict with 'title', 'content', 'date'.\"\"\"\n import anthropic\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\n \"title\": \"Error\",\n \"content\": \"ANTHROPIC_API_KEY not set. Add it to your .env file.\",\n \"date\": str(d),\n }\n\n spec = SUMMARY_TYPES.get(summary_type)\n if not spec:\n return {\"title\": \"Error\", \"content\": f\"Unknown summary type: {summary_type}\", \"date\": str(d)}\n\n stats = summary_stats(d)\n if stats[\"total_frames\"] == 0:\n return {\n \"title\": spec[\"title\"],\n \"content\": f\"No screen data found for {d}.\",\n \"date\": str(d),\n }\n\n ctx = _build_context(d)\n prompt = spec[\"prompt\"].format(**ctx)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": prompt}],\n )\n\n return {\n \"title\": spec[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","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":"Read all pipe.md files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"for f in /volume1/screenpipe/pipes/*/pipe.md; do echo \"=== $f ===\"; cat \"$f\"; 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":"=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: AI Habits\ndescription: \"How you use AI tools — patterns and insights\"\nicon: \"🤖\"\nfeatured: true\n---\n\nSearch my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## AI Tools Used\n- List each tool with approximate time spent (e.g. \"Claude: ~45min\")\n\n## What I Used Them For\n- For each tool: coding, writing, research, or brainstorming\n\n## Usage Patterns\n- Do I switch between tools? Use them in bursts or steadily?\n\n## Effectiveness\n- Which tool appeared alongside completed work vs. abandoned attempts\n\nIf no AI usage is found, say so clearly. End with: \"**Tip:** [one suggestion to use AI tools more effectively]\"\n\n=== /volume1/screenpipe/pipes/day-recap/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n\n=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.\n\n=== /volume1/screenpipe/pipes/standup-update/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Standup Update\ndescription: \"What you did, what's next, and any blockers\"\nicon: \"🏢\"\nfeatured: true\n---\n\nBased on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Yesterday\n- What I worked on (name specific projects, files, tools, PRs)\n\n## Today\n- What I will work on next (based on unfinished tasks and recent activity)\n\n## Blockers\n- Issues I hit — errors, slow builds, waiting on someone\n- If no blockers, write \"None\"\n\nKeep it under 150 words. Copy-paste ready for a team standup.\n\n=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Time Breakdown\ndescription: \"Where your time went — by app, project, and category\"\nicon: \"⏱\"\nfeatured: false\n---\n\nAnalyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.\n\nRead screenpipe skill first.\n\nUse this exact format with durations and percentages:\n\n## By Application\n- List each app with duration and percentage, sorted by time (e.g. \"VS Code: 2h 15min (28%)\")\n\n## By Category\n- Group into: coding, meetings, browsing, writing, communication, other\n- Show hours and percentage per category\n\n## By Project\n- Group related activities by project/topic. Name specific repos or tasks.\n\n## Productivity Score\n- Calculate: focused_work_hours / total_hours as a percentage\n- Focused = coding + writing. Unfocused = browsing + switching.\n\nEnd with: \"**Suggestion:** [one specific change to improve tomorrow's productivity]\"\n\n=== /volume1/screenpipe/pipes/video-export/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Export Video Clip\ndescription: \"Create a video of your recent screen activity\"\nicon: \"🎬\"\nfeatured: false\n---\n\nExport a video of my screen activity from the last 5 minutes.\n\nRead screenpipe skill first.\n\nUse the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.\n\nIf the export is large, suggest a lower fps or shorter time range.","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 clear picture. The pipes are markdown prompt templates in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe/pipes/","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but there's no code to actually load and run them —","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"has its own hardcoded prompts instead.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Here's what I'll implement:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/pipes.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— two new endpoints:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"GET /api/pipes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /api/pipes/{pipe_id}/run","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cli.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— a","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"command to run pipes from the terminal","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Let me build it:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check browser_urls signature","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/consumers/activity.py | grep \"def browser_urls\" -A 5","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":"def browser_urls(\n for_date: date | None = None,\n app_name: str | None = None,\n ts_from: str | None = None,\n ts_to: str | None = None,\n limit: int = 30,","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":"pipes.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipes.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"143 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"\"\"\"Dynamic pipe loader and runner.\"\"\"\nimport os\nimport re\nfrom datetime import date\nfrom pathlib import Path\nfrom typing import Any\n\n\ndef _parse_frontmatter(text: str) -> tuple[dict, str]:\n if not text.startswith(\"---\"):\n return {}, text\n try:\n end = text.index(\"---\", 3)\n except ValueError:\n return {}, text\n fm_text = text[3:end].strip()\n body = text[end + 3:].strip()\n meta: dict = {}\n for line in fm_text.splitlines():\n if \":\" in line:\n k, _, v = line.partition(\":\")\n meta[k.strip()] = v.strip().strip('\"')\n return meta, body\n\n\ndef load_pipes(pipes_dir: Path) -> list[dict]:\n if not pipes_dir.exists():\n return []\n pipes = []\n for pipe_dir in sorted(pipes_dir.iterdir()):\n if not pipe_dir.is_dir() or pipe_dir.name.startswith(\".\"):\n continue\n pipe_md = pipe_dir / \"pipe.md\"\n if not pipe_md.exists():\n continue\n text = pipe_md.read_text(encoding=\"utf-8\")\n meta, body = _parse_frontmatter(text)\n if meta.get(\"enabled\", \"true\").lower() == \"false\":\n continue\n body = re.sub(r\"Read screenpipe skill first\\.?\\n?\", \"\", body).strip()\n pipes.append({\n \"id\": pipe_dir.name,\n \"title\": meta.get(\"title\", pipe_dir.name),\n \"description\": meta.get(\"description\", \"\"),\n \"icon\": meta.get(\"icon\", \"\"),\n \"schedule\": meta.get(\"schedule\", \"manual\"),\n \"featured\": meta.get(\"featured\", \"false\").lower() == \"true\",\n \"prompt\": body,\n })\n return pipes\n\n\ndef _build_system(d: date, stats: dict) -> str:\n from consumers.activity import app_time, browser_urls, ui_event_summary\n from consumers.ocr import deduplicated_text\n from consumers.audio import formatted_transcript\n\n apps = app_time(d)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(d, limit=20)\n url_lines = \"\\n\".join(f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls)\n\n ui_rows = ui_event_summary(d)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(d, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(d)\n if len(audio) > 3000:\n audio = audio[:3000]\n\n return f\"\"\"You are analyzing screenpipe data — recordings of a person's computer activity.\n\n## App usage (minutes per app):\n{app_lines or '(no app data)'}\n\n## Browser URLs visited:\n{url_lines or '(no browser data)'}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_lines or '(no UI event data)'}\n\n## Screen content (sampled every 5 minutes):\n{ocr_lines or '(no screen data)'}\n\n## Audio / speech:\n{audio or '(no audio data)'}\n\nDate: {d}\nTotal frames recorded: {stats['total_frames']}\"\"\"\n\n\ndef run_pipe(\n pipe_id: str,\n for_date: date | None = None,\n api_key: str | None = None,\n pipes_dir: Path | None = None,\n) -> dict[str, Any]:\n import anthropic\n from consumers.activity import summary_stats\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\"title\": \"Error\", \"content\": \"ANTHROPIC_API_KEY not set.\", \"date\": str(d)}\n\n _pipes_dir = pipes_dir or Path(os.environ.get(\"PIPES_DIR\", \"/data/pipes\"))\n all_pipes = {p[\"id\"]: p for p in load_pipes(_pipes_dir)}\n\n if pipe_id not in all_pipes:\n return {\"title\": \"Error\", \"content\": f\"Pipe not found: {pipe_id}\", \"date\": str(d)}\n\n pipe = all_pipes[pipe_id]\n stats = summary_stats(d)\n\n if stats[\"total_frames\"] == 0:\n return {\"title\": pipe[\"title\"], \"content\": f\"No screen data found for {d}.\", \"date\": str(d)}\n\n system = _build_system(d, stats)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n system=system,\n messages=[{\"role\": \"user\", \"content\": pipe[\"prompt\"]}],\n )\n\n return {\n \"title\": pipe[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the API endpoints to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the pipe endpoints at the end of main.py, before the closing summary section:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 14 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the CLI command to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 40 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Done. Here's how to run pipes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to run pipes","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to run pipes","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via Docker (inside the running container):","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"docker exec -it screenpipe-app python cli.py pipe --list\ndocker exec -it screenpipe-app python cli.py pipe day-recap\ndocker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via the API","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(once the container is running on port 8766):","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# List pipes\ncurl http://localhost:8766/api/pipes\n\n# Run a pipe\ncurl -X POST \"http://localhost:8766/api/pipes/day-recap/run\"\ncurl -X POST \"http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rebuild and restart","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to pick up the changes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"cd /volume1/screenpipe/app\ndocker compose up --build -d","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"How it works:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Each","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The \"Read screenpipe skill first\" line is stripped automatically.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The pipes directory inside Docker is","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data/pipes","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(since","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"→","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). You can override it with a","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"PIPES_DIR","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"env var if needed.","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":"AXButton","text":"pipe.md","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"where to place api key and can I use different keys","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":"Read .env file","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/.env","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":"ANTHROPIC_API_KEY=your_key_here","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Where to place the key:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"app/.env","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"app/.env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— replace","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"your_key_here","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with your actual key:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"ANTHROPIC_API_KEY=sk-ant-...","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"That file is loaded by","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"load_dotenv()","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"at startup and is excluded from git via","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".gitignore","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Can you use different keys per pipe?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Not currently — all pipes share the one key from","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". But you can add per-pipe key support by adding an","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"api_key","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"field to the pipe's frontmatter:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"---\ntitle: Meeting Summary\napi_key_env: ANTHROPIC_KEY_MEETINGS\n---","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Then in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/pipes.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/pipes.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", read it in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"_parse_frontmatter","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and pass it through","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"run_pipe","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". Want me to add that?","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":"AXButton","text":"pipe.md","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"can I use mistral or other llm? or is is build for antrophic only","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":"Currently it's Anthropic-only — the code calls the","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"anthropic","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SDK directly in both","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/pipes.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/pipes.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/summary.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Adding other providers is straightforward since Mistral, Ollama, OpenRouter, Groq, and most modern LLMs expose an OpenAI-compatible API. The cleanest approach: add the","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"openai","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"package and let you configure the provider via","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# Anthropic (default)\nANTHROPIC_API_KEY=sk-ant-...\n\n# OR: any OpenAI-compatible provider\nLLM_PROVIDER=openai-compatible\nLLM_BASE_URL=https://api.mistral.ai/v1\nLLM_API_KEY=your-mistral-key\nLLM_MODEL=mistral-small-latest","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"This would cover Mistral, Ollama (","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"http://localhost:11434/v1","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"), OpenRouter, Groq, etc. with one code path.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Want me to implement that? It's a small change — a","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"_call_llm(system, user_prompt)","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"helper in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipes.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"that branches on","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"LLM_PROVIDER","depth":24,"on_screen":false,"role_description":"text"}]...
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Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST "http://localhost:8766/api/pipes/day-recap/run"
curl -X POST "http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25"
Rebuild and restart
to pick up the changes:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
How it works:
Each
pipe.md
file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The "Read screenpipe skill first" line is stripped automatically.
The pipes directory inside Docker is
/data/pipes
(since
/volume1/screenpipe
→
/data
). You can override it with a
PIPES_DIR
env var if needed.
Message actions
pipe.md
pipe.md
where to place api key and can I use different keys
Thinking
Thinking
Bash
Read .env file
IN
cat /volume1/screenpipe/app/.env
Copy code to clipboard
OUT
[ENV_SECRET]
Where to place the key:
app/.env
app/.env
— replace
your_key_here
with your actual key:
Copy code to clipboard
[ENV_SECRET]
That file is loaded by
load_dotenv()
at startup and is excluded from git via
.gitignore
.
Can you use different keys per pipe?
Not currently — all pipes share the one key from
.env
. But you can add per-pipe key support by adding an
api_key
field to the pipe's frontmatter:
Copy code to clipboard
---
title: Meeting Summary
api_key_env: ANTHROPIC_KEY_MEETINGS
---
Then in
consumers/pipes.py
consumers/pipes.py
, read it in
_parse_frontmatter
and pass it through
run_pipe
. Want me to add that?
Message actions
pipe.md
pipe.md
can I use mistral or other llm? or is is build for antrophic only
Thinking
Thinking
Currently it's Anthropic-only — the code calls the
anthropic
SDK directly in both
consumers/pipes.py
consumers/pipes.py
and
consumers/summary.py
consumers/summary.py
.
Adding other providers is straightforward since Mistral, Ollama, OpenRouter, Groq, and most modern LLMs expose an OpenAI-compatible API. The cleanest approach: add the
openai
package and let you configure the provider via
.env
:
Copy code to clipboard
# Anthropic (default)
[ENV_SECRET]
# OR: any OpenAI-compatible provider
LLM_PROVIDER=openai-compatible
LLM_BASE_URL=https://api.mistral.ai/v1
[ENV_SECRET]
LLM_MODEL=mistral-small-latest
This would cover Mistral, Ollama (
http://localhost:11434/v1
), OpenRouter, Groq, etc. with one code path.
Want me to implement that? It's a small change — a
_call_llm(system, user_prompt)
helper in
pipes.py
that branches on
LLM_PROVIDER...
|
21071
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NULL
|
NULL
|
NULL
|
|
21072
|
920
|
6
|
2026-05-11T17:09:18.712171+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519358712_m1.jpg...
|
Code
|
Implement and run pipe l… — screenpipe [SSH: nas]
|
True
|
NULL
|
monitor_1
|
NULL
|
NULL
|
NULL
|
NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST "http://localhost:8766/api/pipes/day-recap/run"
curl -X POST "http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25"
Rebuild and restart
to pick up the changes:
Copy code to clipboard...
|
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#4 of archive.db\n/volume1/screenpipe/#recycle/Copy #5 of archive.db\n/volume1/screenpipe/#recycle/Copy #3 of db.sqlite\n/volume1/screenpipe/#recycle/Copy #4 of db.sqlite\n/volume1/screenpipe/#recycle/Copy #6 of archive.db\n/volume1/screenpipe/#recycle/test.txt\n/volume1/screenpipe/#recycle/Copy #7 of archive.db\n/volume1/screenpipe/#recycle/Copy #8 of archive.db\n/volume1/screenpipe/#recycle/archive.db-journal\n/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #5 of db.sqlite\n/volume1/screenpipe/pipes/.DS_Store\n/volume1/screenpipe/app/.env\n/volume1/screenpipe/app/cli.py\n/volume1/screenpipe/app/.DS_Store\n/volume1/screenpipe/app/db.py\n/volume1/screenpipe/app/docker-compose.yml\n/volume1/screenpipe/app/main.py\n/volume1/screenpipe/app/requirements.txt\n/volume1/screenpipe/app/Dockerfile\n/volume1/screenpipe/data/.DS_Store\n/volume1/screenpipe/.git/description\n/volume1/screenpipe/.git/HEAD\n/volume1/screenpipe/.git/index\n/volume1/screenpipe/.git/COMMIT_EDITMSG\n/volume1/screenpipe/#recycle/data/.DS_Store\n---\napp\napp_settings.json\narchive.db\ndata\ndb.sqlite\ndb.sqlite-shm\ndb.sqlite-wal\npipes\n#recycle\nscreenpipe.db\nscreenpipe_sync.sh","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check pipes directory and docker-compose","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml","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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\ncli.py\nconsumers\ndb.py\ndocker-compose.yml\nDockerfile\nmain.py\n__pycache__\nrequirements.txt\nstatic\nservices:\n screenpipe-app:\n build: .\n container_name: screenpipe-app\n restart: unless-stopped\n ports:\n - \"8766:8000\"\n volumes:\n - /volume1/screenpipe:/data\n env_file:\n - .env\n environment:\n TZ: Europe/Sofia\n DB_PATH: /data/db.sqlite\n\n sqlite-web-archive:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-archive\n restart: unless-stopped\n ports:\n - \"8767:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/archive.db\"]\n\n sqlite-web-live:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-live\n restart: unless-stopped\n ports:\n - \"8768:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/db.sqlite\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"requirements.txt","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"requirements.txt","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Inspect a pipe directory","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/","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":"pipe.md\npipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"List all pipes and their contents","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo \"=== $d ===\"; ls \"$d\"; 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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\n=== /volume1/screenpipe/pipes/ai-habits/ ===\npipe.md\n=== /volume1/screenpipe/pipes/day-recap/ ===\npipe.md\n=== /volume1/screenpipe/pipes/meeting-summary/ ===\npipe.md\n=== /volume1/screenpipe/pipes/standup-update/ ===\npipe.md\n=== /volume1/screenpipe/pipes/time-breakdown/ ===\npipe.md\n=== /volume1/screenpipe/pipes/video-export/ ===\npipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read pipe markdown files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo \"===\" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50","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":"---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.","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":"Read summary consumer","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py","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":"activity.py\naudio.py\nelements.py\n__init__.py\ninteractions.py\nocr.py\n__pycache__\nreport.py\nsummary.py\n\"\"\"AI summary generator using Claude.\"\"\"\nimport os\nfrom datetime import date\nfrom typing import Any\n\nfrom consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary\nfrom consumers.ocr import deduplicated_text\nfrom consumers.audio import formatted_transcript\n\n\nSUMMARY_TYPES = {\n \"day_recap\": {\n \"title\": \"Day Recap\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a concise day recap using EXACTLY this format:\n\n## Summary\nOne sentence: what I mainly worked on today.\n\n## Accomplishments\n- Top 3 things I finished, with approximate times\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things seen or heard, with timestamps\n\n## Unfinished Work\n- What to continue tomorrow\n\n## Patterns\n- Apps used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with:\n**Next step:** [most important thing to continue]\"\"\",\n },\n \"standup\": {\n \"title\": \"Standup Update\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a brief standup update:\n\n**Yesterday:** What I worked on (2-3 bullets)\n**Today:** What I plan to continue (1-2 bullets)\n**Blockers:** Any issues observed (or \"None\")\n\nKeep it under 150 words. Only report what's verifiable from the data.\"\"\",\n },\n \"focus_time\": {\n \"title\": \"Focus & Distraction Analysis\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\nAnalyze focus vs distraction patterns:\n\n## Deep Work Periods\n- When and how long were sustained focus sessions?\n- What was being worked on?\n\n## Distractions\n- Which apps/sites were used recreationally?\n- How much time was lost to context switching?\n\n## Recommendations\n- 2-3 concrete suggestions to improve focus tomorrow\n\nBe specific with times and app names.\"\"\",\n },\n}\n\n\ndef _build_context(for_date: date) -> dict[str, str]:\n apps = app_time(for_date)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(for_date, limit=20)\n url_lines = \"\\n\".join(\n f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls\n )\n\n ui_rows = ui_event_summary(for_date)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(for_date, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(for_date)\n\n return {\n \"app_time\": app_lines or \"(no app data)\",\n \"browser_urls\": url_lines or \"(no browser data)\",\n \"ui_events\": ui_lines or \"(no UI event data)\",\n \"ocr_text\": ocr_lines or \"(no screen data)\",\n \"audio\": audio[:3000] if len(audio) > 3000 else audio,\n }\n\n\ndef generate(\n summary_type: str = \"day_recap\",\n for_date: date | None = None,\n api_key: str | None = None,\n) -> dict[str, Any]:\n \"\"\"Generate an AI summary. Returns dict with 'title', 'content', 'date'.\"\"\"\n import anthropic\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\n \"title\": \"Error\",\n \"content\": \"ANTHROPIC_API_KEY not set. Add it to your .env file.\",\n \"date\": str(d),\n }\n\n spec = SUMMARY_TYPES.get(summary_type)\n if not spec:\n return {\"title\": \"Error\", \"content\": f\"Unknown summary type: {summary_type}\", \"date\": str(d)}\n\n stats = summary_stats(d)\n if stats[\"total_frames\"] == 0:\n return {\n \"title\": spec[\"title\"],\n \"content\": f\"No screen data found for {d}.\",\n \"date\": str(d),\n }\n\n ctx = _build_context(d)\n prompt = spec[\"prompt\"].format(**ctx)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": prompt}],\n )\n\n return {\n \"title\": spec[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","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":"Read all pipe.md files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"for f in /volume1/screenpipe/pipes/*/pipe.md; do echo \"=== $f ===\"; cat \"$f\"; 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":"=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: AI Habits\ndescription: \"How you use AI tools — patterns and insights\"\nicon: \"🤖\"\nfeatured: true\n---\n\nSearch my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## AI Tools Used\n- List each tool with approximate time spent (e.g. \"Claude: ~45min\")\n\n## What I Used Them For\n- For each tool: coding, writing, research, or brainstorming\n\n## Usage Patterns\n- Do I switch between tools? Use them in bursts or steadily?\n\n## Effectiveness\n- Which tool appeared alongside completed work vs. abandoned attempts\n\nIf no AI usage is found, say so clearly. End with: \"**Tip:** [one suggestion to use AI tools more effectively]\"\n\n=== /volume1/screenpipe/pipes/day-recap/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n\n=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.\n\n=== /volume1/screenpipe/pipes/standup-update/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Standup Update\ndescription: \"What you did, what's next, and any blockers\"\nicon: \"🏢\"\nfeatured: true\n---\n\nBased on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Yesterday\n- What I worked on (name specific projects, files, tools, PRs)\n\n## Today\n- What I will work on next (based on unfinished tasks and recent activity)\n\n## Blockers\n- Issues I hit — errors, slow builds, waiting on someone\n- If no blockers, write \"None\"\n\nKeep it under 150 words. Copy-paste ready for a team standup.\n\n=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Time Breakdown\ndescription: \"Where your time went — by app, project, and category\"\nicon: \"⏱\"\nfeatured: false\n---\n\nAnalyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.\n\nRead screenpipe skill first.\n\nUse this exact format with durations and percentages:\n\n## By Application\n- List each app with duration and percentage, sorted by time (e.g. \"VS Code: 2h 15min (28%)\")\n\n## By Category\n- Group into: coding, meetings, browsing, writing, communication, other\n- Show hours and percentage per category\n\n## By Project\n- Group related activities by project/topic. Name specific repos or tasks.\n\n## Productivity Score\n- Calculate: focused_work_hours / total_hours as a percentage\n- Focused = coding + writing. Unfocused = browsing + switching.\n\nEnd with: \"**Suggestion:** [one specific change to improve tomorrow's productivity]\"\n\n=== /volume1/screenpipe/pipes/video-export/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Export Video Clip\ndescription: \"Create a video of your recent screen activity\"\nicon: \"🎬\"\nfeatured: false\n---\n\nExport a video of my screen activity from the last 5 minutes.\n\nRead screenpipe skill first.\n\nUse the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.\n\nIf the export is large, suggest a lower fps or shorter time range.","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 clear picture. The pipes are markdown prompt templates in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe/pipes/","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but there's no code to actually load and run them —","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"has its own hardcoded prompts instead.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Here's what I'll implement:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/pipes.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— two new endpoints:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"GET /api/pipes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /api/pipes/{pipe_id}/run","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cli.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— a","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"command to run pipes from the terminal","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Let me build it:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check browser_urls signature","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/consumers/activity.py | grep \"def browser_urls\" -A 5","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":"def browser_urls(\n for_date: date | None = None,\n app_name: str | None = None,\n ts_from: str | None = None,\n ts_to: str | None = None,\n limit: int = 30,","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":"pipes.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipes.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"143 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"\"\"\"Dynamic pipe loader and runner.\"\"\"\nimport os\nimport re\nfrom datetime import date\nfrom pathlib import Path\nfrom typing import Any\n\n\ndef _parse_frontmatter(text: str) -> tuple[dict, str]:\n if not text.startswith(\"---\"):\n return {}, text\n try:\n end = text.index(\"---\", 3)\n except ValueError:\n return {}, text\n fm_text = text[3:end].strip()\n body = text[end + 3:].strip()\n meta: dict = {}\n for line in fm_text.splitlines():\n if \":\" in line:\n k, _, v = line.partition(\":\")\n meta[k.strip()] = v.strip().strip('\"')\n return meta, body\n\n\ndef load_pipes(pipes_dir: Path) -> list[dict]:\n if not pipes_dir.exists():\n return []\n pipes = []\n for pipe_dir in sorted(pipes_dir.iterdir()):\n if not pipe_dir.is_dir() or pipe_dir.name.startswith(\".\"):\n continue\n pipe_md = pipe_dir / \"pipe.md\"\n if not pipe_md.exists():\n continue\n text = pipe_md.read_text(encoding=\"utf-8\")\n meta, body = _parse_frontmatter(text)\n if meta.get(\"enabled\", \"true\").lower() == \"false\":\n continue\n body = re.sub(r\"Read screenpipe skill first\\.?\\n?\", \"\", body).strip()\n pipes.append({\n \"id\": pipe_dir.name,\n \"title\": meta.get(\"title\", pipe_dir.name),\n \"description\": meta.get(\"description\", \"\"),\n \"icon\": meta.get(\"icon\", \"\"),\n \"schedule\": meta.get(\"schedule\", \"manual\"),\n \"featured\": meta.get(\"featured\", \"false\").lower() == \"true\",\n \"prompt\": body,\n })\n return pipes\n\n\ndef _build_system(d: date, stats: dict) -> str:\n from consumers.activity import app_time, browser_urls, ui_event_summary\n from consumers.ocr import deduplicated_text\n from consumers.audio import formatted_transcript\n\n apps = app_time(d)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(d, limit=20)\n url_lines = \"\\n\".join(f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls)\n\n ui_rows = ui_event_summary(d)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(d, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(d)\n if len(audio) > 3000:\n audio = audio[:3000]\n\n return f\"\"\"You are analyzing screenpipe data — recordings of a person's computer activity.\n\n## App usage (minutes per app):\n{app_lines or '(no app data)'}\n\n## Browser URLs visited:\n{url_lines or '(no browser data)'}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_lines or '(no UI event data)'}\n\n## Screen content (sampled every 5 minutes):\n{ocr_lines or '(no screen data)'}\n\n## Audio / speech:\n{audio or '(no audio data)'}\n\nDate: {d}\nTotal frames recorded: {stats['total_frames']}\"\"\"\n\n\ndef run_pipe(\n pipe_id: str,\n for_date: date | None = None,\n api_key: str | None = None,\n pipes_dir: Path | None = None,\n) -> dict[str, Any]:\n import anthropic\n from consumers.activity import summary_stats\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\"title\": \"Error\", \"content\": \"ANTHROPIC_API_KEY not set.\", \"date\": str(d)}\n\n _pipes_dir = pipes_dir or Path(os.environ.get(\"PIPES_DIR\", \"/data/pipes\"))\n all_pipes = {p[\"id\"]: p for p in load_pipes(_pipes_dir)}\n\n if pipe_id not in all_pipes:\n return {\"title\": \"Error\", \"content\": f\"Pipe not found: {pipe_id}\", \"date\": str(d)}\n\n pipe = all_pipes[pipe_id]\n stats = summary_stats(d)\n\n if stats[\"total_frames\"] == 0:\n return {\"title\": pipe[\"title\"], \"content\": f\"No screen data found for {d}.\", \"date\": str(d)}\n\n system = _build_system(d, stats)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n system=system,\n messages=[{\"role\": \"user\", \"content\": pipe[\"prompt\"]}],\n )\n\n return {\n \"title\": pipe[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the API endpoints to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the pipe endpoints at the end of main.py, before the closing summary section:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 14 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the CLI command to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 40 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Done. Here's how to run pipes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to run pipes","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to run pipes","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via Docker (inside the running container):","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"docker exec -it screenpipe-app python cli.py pipe --list\ndocker exec -it screenpipe-app python cli.py pipe day-recap\ndocker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via the API","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(once the container is running on port 8766):","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# List pipes\ncurl http://localhost:8766/api/pipes\n\n# Run a pipe\ncurl -X POST \"http://localhost:8766/api/pipes/day-recap/run\"\ncurl -X POST \"http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rebuild and restart","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to pick up the changes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"on_screen":false,"help_text":"Copy code","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false}]...
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3052796390275798323
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-8691439186037733140
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idle
|
accessibility
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NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST "http://localhost:8766/api/pipes/day-recap/run"
curl -X POST "http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25"
Rebuild and restart
to pick up the changes:
Copy code to clipboard...
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6
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2026-05-11T17:09:07.011215+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519347011_m2.jpg...
|
Code
|
Implement and run pipe l… — screenpipe [SSH: nas]
|
True
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NULL
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monitor_2
|
NULL
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NULL
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NULL
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NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST "http://localhost:8766/api/pipes/day-recap/run"
curl -X POST "http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25"
Rebuild and restart
to pick up the changes:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
How it works:
Each
pipe.md
file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The "Read screenpipe skill first" line is stripped automatically.
The pipes directory inside Docker is
/data/pipes
(since
/volume1/screenpipe
→
/data
). You can override it with a
PIPES_DIR
env var if needed.
Message actions
pipe.md
pipe.md
where to place api key and can I use different keys
Thinking
Thinking
Bash
Read .env file
IN
cat /volume1/screenpipe/app/.env
Copy code to clipboard
OUT
[ENV_SECRET]
Where to place the key:
app/.env
app/.env
— replace
your_key_here
with your actual key:
Copy code to clipboard
[ENV_SECRET]
That file is loaded by
load_dotenv()
at startup and is excluded from git via
.gitignore
.
Can you use different keys per pipe?
Not currently — all pipes share the one key from
.env
. But you can add per-pipe key support by adding an
api_key
field to the pipe's frontmatter:
Copy code to clipboard
---
title: Meeting Summary
api_key_env: ANTHROPIC_KEY_MEETINGS
---
Then in
consumers/pipes.py
consumers/pipes.py
, read it in
_parse_frontmatter
and pass it through
run_pipe
. Want me to add that?
Message actions
pipe.md
pipe.md
can I use mistral or other llm? or is is build for antrophic only
Thinking
Thinking
Currently it's Anthropic-only — the code calls the
anthropic
SDK directly in both
consumers/pipes.py
consumers/pipes.py
and
consumers/summary.py
consumers/summary.py
.
Adding other providers is straightforward since Mistral, Ollama, OpenRouter, Groq, and most modern LLMs expose an OpenAI-compatible API. The cleanest approach: add the...
|
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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":"/volume1/screenpipe/.DS_Store\n/volume1/screenpipe/screenpipe.db\n/volume1/screenpipe/screenpipe_sync.sh\n/volume1/screenpipe/app_settings.json\n/volume1/screenpipe/.gitignore\n/volume1/screenpipe/archive.db\n/volume1/screenpipe/db.sqlite\n/volume1/screenpipe/db.sqlite-wal\n/volume1/screenpipe/db.sqlite-shm\n/volume1/screenpipe/#recycle/desktop.ini\n/volume1/screenpipe/#recycle/db.sqlite\n/volume1/screenpipe/#recycle/Copy #1 of db.sqlite\n/volume1/screenpipe/#recycle/.DS_Store\n/volume1/screenpipe/#recycle/Copy #2 of db.sqlite\n/volume1/screenpipe/#recycle/archive.db\n/volume1/screenpipe/#recycle/Copy #1 of archive.db\n/volume1/screenpipe/#recycle/Copy #2 of archive.db\n/volume1/screenpipe/#recycle/Copy #3 of archive.db\n/volume1/screenpipe/#recycle/Copy #4 of archive.db\n/volume1/screenpipe/#recycle/Copy #5 of archive.db\n/volume1/screenpipe/#recycle/Copy #3 of db.sqlite\n/volume1/screenpipe/#recycle/Copy #4 of db.sqlite\n/volume1/screenpipe/#recycle/Copy #6 of archive.db\n/volume1/screenpipe/#recycle/test.txt\n/volume1/screenpipe/#recycle/Copy #7 of archive.db\n/volume1/screenpipe/#recycle/Copy #8 of archive.db\n/volume1/screenpipe/#recycle/archive.db-journal\n/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #5 of db.sqlite\n/volume1/screenpipe/pipes/.DS_Store\n/volume1/screenpipe/app/.env\n/volume1/screenpipe/app/cli.py\n/volume1/screenpipe/app/.DS_Store\n/volume1/screenpipe/app/db.py\n/volume1/screenpipe/app/docker-compose.yml\n/volume1/screenpipe/app/main.py\n/volume1/screenpipe/app/requirements.txt\n/volume1/screenpipe/app/Dockerfile\n/volume1/screenpipe/data/.DS_Store\n/volume1/screenpipe/.git/description\n/volume1/screenpipe/.git/HEAD\n/volume1/screenpipe/.git/index\n/volume1/screenpipe/.git/COMMIT_EDITMSG\n/volume1/screenpipe/#recycle/data/.DS_Store\n---\napp\napp_settings.json\narchive.db\ndata\ndb.sqlite\ndb.sqlite-shm\ndb.sqlite-wal\npipes\n#recycle\nscreenpipe.db\nscreenpipe_sync.sh","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check pipes directory and docker-compose","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml","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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\ncli.py\nconsumers\ndb.py\ndocker-compose.yml\nDockerfile\nmain.py\n__pycache__\nrequirements.txt\nstatic\nservices:\n screenpipe-app:\n build: .\n container_name: screenpipe-app\n restart: unless-stopped\n ports:\n - \"8766:8000\"\n volumes:\n - /volume1/screenpipe:/data\n env_file:\n - .env\n environment:\n TZ: Europe/Sofia\n DB_PATH: /data/db.sqlite\n\n sqlite-web-archive:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-archive\n restart: unless-stopped\n ports:\n - \"8767:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/archive.db\"]\n\n sqlite-web-live:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-live\n restart: unless-stopped\n ports:\n - \"8768:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/db.sqlite\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"requirements.txt","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"requirements.txt","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Inspect a pipe directory","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/","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":"pipe.md\npipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"List all pipes and their contents","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo \"=== $d ===\"; ls \"$d\"; 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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\n=== /volume1/screenpipe/pipes/ai-habits/ ===\npipe.md\n=== /volume1/screenpipe/pipes/day-recap/ ===\npipe.md\n=== /volume1/screenpipe/pipes/meeting-summary/ ===\npipe.md\n=== /volume1/screenpipe/pipes/standup-update/ ===\npipe.md\n=== /volume1/screenpipe/pipes/time-breakdown/ ===\npipe.md\n=== /volume1/screenpipe/pipes/video-export/ ===\npipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read pipe markdown files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo \"===\" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50","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":"---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.","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":"Read summary consumer","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py","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":"activity.py\naudio.py\nelements.py\n__init__.py\ninteractions.py\nocr.py\n__pycache__\nreport.py\nsummary.py\n\"\"\"AI summary generator using Claude.\"\"\"\nimport os\nfrom datetime import date\nfrom typing import Any\n\nfrom consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary\nfrom consumers.ocr import deduplicated_text\nfrom consumers.audio import formatted_transcript\n\n\nSUMMARY_TYPES = {\n \"day_recap\": {\n \"title\": \"Day Recap\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a concise day recap using EXACTLY this format:\n\n## Summary\nOne sentence: what I mainly worked on today.\n\n## Accomplishments\n- Top 3 things I finished, with approximate times\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things seen or heard, with timestamps\n\n## Unfinished Work\n- What to continue tomorrow\n\n## Patterns\n- Apps used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with:\n**Next step:** [most important thing to continue]\"\"\",\n },\n \"standup\": {\n \"title\": \"Standup Update\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a brief standup update:\n\n**Yesterday:** What I worked on (2-3 bullets)\n**Today:** What I plan to continue (1-2 bullets)\n**Blockers:** Any issues observed (or \"None\")\n\nKeep it under 150 words. Only report what's verifiable from the data.\"\"\",\n },\n \"focus_time\": {\n \"title\": \"Focus & Distraction Analysis\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\nAnalyze focus vs distraction patterns:\n\n## Deep Work Periods\n- When and how long were sustained focus sessions?\n- What was being worked on?\n\n## Distractions\n- Which apps/sites were used recreationally?\n- How much time was lost to context switching?\n\n## Recommendations\n- 2-3 concrete suggestions to improve focus tomorrow\n\nBe specific with times and app names.\"\"\",\n },\n}\n\n\ndef _build_context(for_date: date) -> dict[str, str]:\n apps = app_time(for_date)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(for_date, limit=20)\n url_lines = \"\\n\".join(\n f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls\n )\n\n ui_rows = ui_event_summary(for_date)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(for_date, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(for_date)\n\n return {\n \"app_time\": app_lines or \"(no app data)\",\n \"browser_urls\": url_lines or \"(no browser data)\",\n \"ui_events\": ui_lines or \"(no UI event data)\",\n \"ocr_text\": ocr_lines or \"(no screen data)\",\n \"audio\": audio[:3000] if len(audio) > 3000 else audio,\n }\n\n\ndef generate(\n summary_type: str = \"day_recap\",\n for_date: date | None = None,\n api_key: str | None = None,\n) -> dict[str, Any]:\n \"\"\"Generate an AI summary. Returns dict with 'title', 'content', 'date'.\"\"\"\n import anthropic\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\n \"title\": \"Error\",\n \"content\": \"ANTHROPIC_API_KEY not set. Add it to your .env file.\",\n \"date\": str(d),\n }\n\n spec = SUMMARY_TYPES.get(summary_type)\n if not spec:\n return {\"title\": \"Error\", \"content\": f\"Unknown summary type: {summary_type}\", \"date\": str(d)}\n\n stats = summary_stats(d)\n if stats[\"total_frames\"] == 0:\n return {\n \"title\": spec[\"title\"],\n \"content\": f\"No screen data found for {d}.\",\n \"date\": str(d),\n }\n\n ctx = _build_context(d)\n prompt = spec[\"prompt\"].format(**ctx)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": prompt}],\n )\n\n return {\n \"title\": spec[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","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":"Read all pipe.md files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"for f in /volume1/screenpipe/pipes/*/pipe.md; do echo \"=== $f ===\"; cat \"$f\"; 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":"=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: AI Habits\ndescription: \"How you use AI tools — patterns and insights\"\nicon: \"🤖\"\nfeatured: true\n---\n\nSearch my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## AI Tools Used\n- List each tool with approximate time spent (e.g. \"Claude: ~45min\")\n\n## What I Used Them For\n- For each tool: coding, writing, research, or brainstorming\n\n## Usage Patterns\n- Do I switch between tools? Use them in bursts or steadily?\n\n## Effectiveness\n- Which tool appeared alongside completed work vs. abandoned attempts\n\nIf no AI usage is found, say so clearly. End with: \"**Tip:** [one suggestion to use AI tools more effectively]\"\n\n=== /volume1/screenpipe/pipes/day-recap/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n\n=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.\n\n=== /volume1/screenpipe/pipes/standup-update/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Standup Update\ndescription: \"What you did, what's next, and any blockers\"\nicon: \"🏢\"\nfeatured: true\n---\n\nBased on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Yesterday\n- What I worked on (name specific projects, files, tools, PRs)\n\n## Today\n- What I will work on next (based on unfinished tasks and recent activity)\n\n## Blockers\n- Issues I hit — errors, slow builds, waiting on someone\n- If no blockers, write \"None\"\n\nKeep it under 150 words. Copy-paste ready for a team standup.\n\n=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Time Breakdown\ndescription: \"Where your time went — by app, project, and category\"\nicon: \"⏱\"\nfeatured: false\n---\n\nAnalyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.\n\nRead screenpipe skill first.\n\nUse this exact format with durations and percentages:\n\n## By Application\n- List each app with duration and percentage, sorted by time (e.g. \"VS Code: 2h 15min (28%)\")\n\n## By Category\n- Group into: coding, meetings, browsing, writing, communication, other\n- Show hours and percentage per category\n\n## By Project\n- Group related activities by project/topic. Name specific repos or tasks.\n\n## Productivity Score\n- Calculate: focused_work_hours / total_hours as a percentage\n- Focused = coding + writing. Unfocused = browsing + switching.\n\nEnd with: \"**Suggestion:** [one specific change to improve tomorrow's productivity]\"\n\n=== /volume1/screenpipe/pipes/video-export/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Export Video Clip\ndescription: \"Create a video of your recent screen activity\"\nicon: \"🎬\"\nfeatured: false\n---\n\nExport a video of my screen activity from the last 5 minutes.\n\nRead screenpipe skill first.\n\nUse the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.\n\nIf the export is large, suggest a lower fps or shorter time range.","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 clear picture. The pipes are markdown prompt templates in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe/pipes/","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but there's no code to actually load and run them —","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"has its own hardcoded prompts instead.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Here's what I'll implement:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/pipes.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— two new endpoints:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"GET /api/pipes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /api/pipes/{pipe_id}/run","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cli.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— a","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"command to run pipes from the terminal","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Let me build it:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check browser_urls signature","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/consumers/activity.py | grep \"def browser_urls\" -A 5","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":"def browser_urls(\n for_date: date | None = None,\n app_name: str | None = None,\n ts_from: str | None = None,\n ts_to: str | None = None,\n limit: int = 30,","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":"pipes.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipes.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"143 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"\"\"\"Dynamic pipe loader and runner.\"\"\"\nimport os\nimport re\nfrom datetime import date\nfrom pathlib import Path\nfrom typing import Any\n\n\ndef _parse_frontmatter(text: str) -> tuple[dict, str]:\n if not text.startswith(\"---\"):\n return {}, text\n try:\n end = text.index(\"---\", 3)\n except ValueError:\n return {}, text\n fm_text = text[3:end].strip()\n body = text[end + 3:].strip()\n meta: dict = {}\n for line in fm_text.splitlines():\n if \":\" in line:\n k, _, v = line.partition(\":\")\n meta[k.strip()] = v.strip().strip('\"')\n return meta, body\n\n\ndef load_pipes(pipes_dir: Path) -> list[dict]:\n if not pipes_dir.exists():\n return []\n pipes = []\n for pipe_dir in sorted(pipes_dir.iterdir()):\n if not pipe_dir.is_dir() or pipe_dir.name.startswith(\".\"):\n continue\n pipe_md = pipe_dir / \"pipe.md\"\n if not pipe_md.exists():\n continue\n text = pipe_md.read_text(encoding=\"utf-8\")\n meta, body = _parse_frontmatter(text)\n if meta.get(\"enabled\", \"true\").lower() == \"false\":\n continue\n body = re.sub(r\"Read screenpipe skill first\\.?\\n?\", \"\", body).strip()\n pipes.append({\n \"id\": pipe_dir.name,\n \"title\": meta.get(\"title\", pipe_dir.name),\n \"description\": meta.get(\"description\", \"\"),\n \"icon\": meta.get(\"icon\", \"\"),\n \"schedule\": meta.get(\"schedule\", \"manual\"),\n \"featured\": meta.get(\"featured\", \"false\").lower() == \"true\",\n \"prompt\": body,\n })\n return pipes\n\n\ndef _build_system(d: date, stats: dict) -> str:\n from consumers.activity import app_time, browser_urls, ui_event_summary\n from consumers.ocr import deduplicated_text\n from consumers.audio import formatted_transcript\n\n apps = app_time(d)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(d, limit=20)\n url_lines = \"\\n\".join(f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls)\n\n ui_rows = ui_event_summary(d)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(d, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(d)\n if len(audio) > 3000:\n audio = audio[:3000]\n\n return f\"\"\"You are analyzing screenpipe data — recordings of a person's computer activity.\n\n## App usage (minutes per app):\n{app_lines or '(no app data)'}\n\n## Browser URLs visited:\n{url_lines or '(no browser data)'}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_lines or '(no UI event data)'}\n\n## Screen content (sampled every 5 minutes):\n{ocr_lines or '(no screen data)'}\n\n## Audio / speech:\n{audio or '(no audio data)'}\n\nDate: {d}\nTotal frames recorded: {stats['total_frames']}\"\"\"\n\n\ndef run_pipe(\n pipe_id: str,\n for_date: date | None = None,\n api_key: str | None = None,\n pipes_dir: Path | None = None,\n) -> dict[str, Any]:\n import anthropic\n from consumers.activity import summary_stats\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\"title\": \"Error\", \"content\": \"ANTHROPIC_API_KEY not set.\", \"date\": str(d)}\n\n _pipes_dir = pipes_dir or Path(os.environ.get(\"PIPES_DIR\", \"/data/pipes\"))\n all_pipes = {p[\"id\"]: p for p in load_pipes(_pipes_dir)}\n\n if pipe_id not in all_pipes:\n return {\"title\": \"Error\", \"content\": f\"Pipe not found: {pipe_id}\", \"date\": str(d)}\n\n pipe = all_pipes[pipe_id]\n stats = summary_stats(d)\n\n if stats[\"total_frames\"] == 0:\n return {\"title\": pipe[\"title\"], \"content\": f\"No screen data found for {d}.\", \"date\": str(d)}\n\n system = _build_system(d, stats)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n system=system,\n messages=[{\"role\": \"user\", \"content\": pipe[\"prompt\"]}],\n )\n\n return {\n \"title\": pipe[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the API endpoints to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the pipe endpoints at the end of main.py, before the closing summary section:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 14 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the CLI command to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 40 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Done. Here's how to run pipes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to run pipes","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to run pipes","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via Docker (inside the running container):","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"docker exec -it screenpipe-app python cli.py pipe --list\ndocker exec -it screenpipe-app python cli.py pipe day-recap\ndocker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via the API","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(once the container is running on port 8766):","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# List pipes\ncurl http://localhost:8766/api/pipes\n\n# Run a pipe\ncurl -X POST \"http://localhost:8766/api/pipes/day-recap/run\"\ncurl -X POST \"http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rebuild and restart","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to pick up the changes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"cd /volume1/screenpipe/app\ndocker compose up --build -d","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"How it works:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Each","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The \"Read screenpipe skill first\" line is stripped automatically.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The pipes directory inside Docker is","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data/pipes","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(since","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"→","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). You can override it with a","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"PIPES_DIR","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"env var if needed.","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":"AXButton","text":"pipe.md","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"where to place api key and can I use different keys","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":"Read .env file","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/.env","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":"ANTHROPIC_API_KEY=your_key_here","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Where to place the key:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"app/.env","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"app/.env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— replace","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"your_key_here","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with your actual key:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"ANTHROPIC_API_KEY=sk-ant-...","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"That file is loaded by","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"load_dotenv()","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"at startup and is excluded from git via","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".gitignore","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Can you use different keys per pipe?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Not currently — all pipes share the one key from","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". But you can add per-pipe key support by adding an","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"api_key","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"field to the pipe's frontmatter:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"---\ntitle: Meeting Summary\napi_key_env: ANTHROPIC_KEY_MEETINGS\n---","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Then in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/pipes.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/pipes.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", read it in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"_parse_frontmatter","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and pass it through","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"run_pipe","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". Want me to add that?","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":"AXButton","text":"pipe.md","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"can I use mistral or other llm? or is is build for antrophic only","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":"Currently it's Anthropic-only — the code calls the","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"anthropic","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SDK directly in both","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/pipes.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/pipes.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/summary.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Adding other providers is straightforward since Mistral, Ollama, OpenRouter, Groq, and most modern LLMs expose an OpenAI-compatible API. The cleanest approach: add the","depth":23,"on_screen":false,"role_description":"text"}]...
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2382478734108606323
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-8763776880662820632
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idle
|
accessibility
|
NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST "http://localhost:8766/api/pipes/day-recap/run"
curl -X POST "http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25"
Rebuild and restart
to pick up the changes:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
How it works:
Each
pipe.md
file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The "Read screenpipe skill first" line is stripped automatically.
The pipes directory inside Docker is
/data/pipes
(since
/volume1/screenpipe
→
/data
). You can override it with a
PIPES_DIR
env var if needed.
Message actions
pipe.md
pipe.md
where to place api key and can I use different keys
Thinking
Thinking
Bash
Read .env file
IN
cat /volume1/screenpipe/app/.env
Copy code to clipboard
OUT
[ENV_SECRET]
Where to place the key:
app/.env
app/.env
— replace
your_key_here
with your actual key:
Copy code to clipboard
[ENV_SECRET]
That file is loaded by
load_dotenv()
at startup and is excluded from git via
.gitignore
.
Can you use different keys per pipe?
Not currently — all pipes share the one key from
.env
. But you can add per-pipe key support by adding an
api_key
field to the pipe's frontmatter:
Copy code to clipboard
---
title: Meeting Summary
api_key_env: ANTHROPIC_KEY_MEETINGS
---
Then in
consumers/pipes.py
consumers/pipes.py
, read it in
_parse_frontmatter
and pass it through
run_pipe
. Want me to add that?
Message actions
pipe.md
pipe.md
can I use mistral or other llm? or is is build for antrophic only
Thinking
Thinking
Currently it's Anthropic-only — the code calls the
anthropic
SDK directly in both
consumers/pipes.py
consumers/pipes.py
and
consumers/summary.py
consumers/summary.py
.
Adding other providers is straightforward since Mistral, Ollama, OpenRouter, Groq, and most modern LLMs expose an OpenAI-compatible API. The cleanest approach: add the...
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Implement and run pipe l… — screenpipe [SSH: nas]
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash...
|
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unless-stopped\n ports:\n - \"8766:8000\"\n volumes:\n - /volume1/screenpipe:/data\n env_file:\n - .env\n environment:\n TZ: Europe/Sofia\n DB_PATH: /data/db.sqlite\n\n sqlite-web-archive:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-archive\n restart: unless-stopped\n ports:\n - \"8767:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/archive.db\"]\n\n sqlite-web-live:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-live\n restart: unless-stopped\n ports:\n - \"8768:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/db.sqlite\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"requirements.txt","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"requirements.txt","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Inspect a pipe directory","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/","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":"pipe.md\npipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"List all pipes and their contents","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo \"=== $d ===\"; ls \"$d\"; 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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\n=== /volume1/screenpipe/pipes/ai-habits/ ===\npipe.md\n=== /volume1/screenpipe/pipes/day-recap/ ===\npipe.md\n=== /volume1/screenpipe/pipes/meeting-summary/ ===\npipe.md\n=== /volume1/screenpipe/pipes/standup-update/ ===\npipe.md\n=== /volume1/screenpipe/pipes/time-breakdown/ ===\npipe.md\n=== /volume1/screenpipe/pipes/video-export/ ===\npipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"}]...
|
-8437136971691210160
|
2643949388798334725
|
idle
|
accessibility
|
NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash...
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21069
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921
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5
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2026-05-11T17:08:36.559641+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519316559_m2.jpg...
|
Code
|
Implement and run pipe l… — screenpipe [SSH: nas]
|
True
|
NULL
|
monitor_2
|
NULL
|
NULL
|
NULL
|
NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt...
|
[{"role":"AXRadioButton","text [{"role":"AXRadioButton","text":"Explorer (⇧⌘E)","depth":19,"bounds":{"left":0.0,"top":0.047885075,"width":0.015957447,"height":0.03830806},"on_screen":true,"role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":true,"is_expanded":true},{"role":"AXStaticText","text":"","depth":22,"bounds":{"left":0.0039893617,"top":0.057462092,"width":0.007978723,"height":0.01915403},"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Search (⇧⌘F)","depth":19,"bounds":{"left":0.0,"top":0.08619314,"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":0.09577015,"width":0.007978723,"height":0.01915403},"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Source Control (⌃⇧G) - 10 pending changes","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":"AXStaticText","text":"10","depth":22,"bounds":{"left":0.00831117,"top":0.1452514,"width":0.003656915,"height":0.008778931},"on_screen":true,"lines":[{"char_start":0,"char_count":1,"bounds":{"left":0.00831117,"top":0.14604948,"width":0.0016622341,"height":0.007980846}},{"char_start":1,"char_count":1,"bounds":{"left":0.009973404,"top":0.14604948,"width":0.0023271276,"height":0.007980846}}],"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 update","depth":19,"bounds":{"left":0.0,"top":0.23942538,"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":0.2490024,"width":0.007978723,"height":0.01915403},"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"2","depth":22,"bounds":{"left":0.009640957,"top":0.2601756,"width":0.0019946808,"height":0.008778931},"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Claude 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8766","depth":16,"bounds":{"left":0.08843085,"top":0.98244214,"width":0.012632979,"height":0.01755786},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"","depth":17,"bounds":{"left":0.09009308,"top":0.9848364,"width":0.0056515955,"height":0.012769354},"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"1","depth":17,"bounds":{"left":0.09541223,"top":0.9856345,"width":0.0039893617,"height":0.011173184},"on_screen":true,"role_description":"text"},{"role":"AXButton","text":"Notifications","depth":16,"bounds":{"left":0.9886968,"top":0.98244214,"width":0.010638298,"height":0.01755786},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Sign In","depth":16,"bounds":{"left":0.9650931,"top":0.98244214,"width":0.022606382,"height":0.01755786},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"","depth":17,"bounds":{"left":0.96675533,"top":0.9848364,"width":0.0056515955,"height":0.012769354},"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"Sign In","depth":17,"bounds":{"left":0.97207445,"top":0.9856345,"width":0.013962766,"height":0.011173184},"on_screen":true,"lines":[{"char_start":0,"char_count":1,"bounds":{"left":0.97207445,"top":0.9856345,"width":0.0013297872,"height":0.011173184}},{"char_start":1,"char_count":6,"bounds":{"left":0.9734042,"top":0.9856345,"width":0.010638298,"height":0.011173184}}],"role_description":"text"},{"role":"AXStaticText","text":"Info: Setting up SSH Host nas: Setting up SSH tunnel","depth":12,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Implement and run pipe logic","depth":19,"bounds":{"left":0.56017286,"top":0.08060654,"width":0.07114362,"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 history","depth":19,"bounds":{"left":0.9780585,"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":0.9886968,"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":"main.py","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lets implement logic with pipes. how can I run 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":"Let me look at the current project structure to understand what's already in place.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"List project files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"find /volume1/screenpipe -type f | head -50 && echo \"---\" && ls /volume1/screenpipe","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":"/volume1/screenpipe/.DS_Store\n/volume1/screenpipe/screenpipe.db\n/volume1/screenpipe/screenpipe_sync.sh\n/volume1/screenpipe/app_settings.json\n/volume1/screenpipe/.gitignore\n/volume1/screenpipe/archive.db\n/volume1/screenpipe/db.sqlite\n/volume1/screenpipe/db.sqlite-wal\n/volume1/screenpipe/db.sqlite-shm\n/volume1/screenpipe/#recycle/desktop.ini\n/volume1/screenpipe/#recycle/db.sqlite\n/volume1/screenpipe/#recycle/Copy #1 of db.sqlite\n/volume1/screenpipe/#recycle/.DS_Store\n/volume1/screenpipe/#recycle/Copy #2 of db.sqlite\n/volume1/screenpipe/#recycle/archive.db\n/volume1/screenpipe/#recycle/Copy #1 of archive.db\n/volume1/screenpipe/#recycle/Copy #2 of archive.db\n/volume1/screenpipe/#recycle/Copy #3 of archive.db\n/volume1/screenpipe/#recycle/Copy #4 of archive.db\n/volume1/screenpipe/#recycle/Copy #5 of archive.db\n/volume1/screenpipe/#recycle/Copy #3 of db.sqlite\n/volume1/screenpipe/#recycle/Copy #4 of db.sqlite\n/volume1/screenpipe/#recycle/Copy #6 of archive.db\n/volume1/screenpipe/#recycle/test.txt\n/volume1/screenpipe/#recycle/Copy #7 of archive.db\n/volume1/screenpipe/#recycle/Copy #8 of archive.db\n/volume1/screenpipe/#recycle/archive.db-journal\n/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #5 of db.sqlite\n/volume1/screenpipe/pipes/.DS_Store\n/volume1/screenpipe/app/.env\n/volume1/screenpipe/app/cli.py\n/volume1/screenpipe/app/.DS_Store\n/volume1/screenpipe/app/db.py\n/volume1/screenpipe/app/docker-compose.yml\n/volume1/screenpipe/app/main.py\n/volume1/screenpipe/app/requirements.txt\n/volume1/screenpipe/app/Dockerfile\n/volume1/screenpipe/data/.DS_Store\n/volume1/screenpipe/.git/description\n/volume1/screenpipe/.git/HEAD\n/volume1/screenpipe/.git/index\n/volume1/screenpipe/.git/COMMIT_EDITMSG\n/volume1/screenpipe/#recycle/data/.DS_Store\n---\napp\napp_settings.json\narchive.db\ndata\ndb.sqlite\ndb.sqlite-shm\ndb.sqlite-wal\npipes\n#recycle\nscreenpipe.db\nscreenpipe_sync.sh","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check pipes directory and docker-compose","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml","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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\ncli.py\nconsumers\ndb.py\ndocker-compose.yml\nDockerfile\nmain.py\n__pycache__\nrequirements.txt\nstatic\nservices:\n screenpipe-app:\n build: .\n container_name: screenpipe-app\n restart: unless-stopped\n ports:\n - \"8766:8000\"\n volumes:\n - /volume1/screenpipe:/data\n env_file:\n - .env\n environment:\n TZ: Europe/Sofia\n DB_PATH: /data/db.sqlite\n\n sqlite-web-archive:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-archive\n restart: unless-stopped\n ports:\n - \"8767:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/archive.db\"]\n\n sqlite-web-live:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-live\n restart: unless-stopped\n ports:\n - \"8768:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/db.sqlite\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"requirements.txt","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false}]...
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2774729678109247237
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idle
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accessibility
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NULL
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt...
|
21067
|
NULL
|
NULL
|
NULL
|
|
21068
|
920
|
4
|
2026-05-11T17:08:17.995607+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519297995_m1.jpg...
|
Code
|
Implement and run pipe l… — screenpipe [SSH: nas]
|
True
|
NULL
|
monitor_1
|
NULL
|
NULL
|
NULL
|
NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:...
|
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/volume1/screenpipe/pipes/day-recap/","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":"pipe.md\npipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"List all pipes and their contents","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo \"=== $d ===\"; ls \"$d\"; 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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\n=== /volume1/screenpipe/pipes/ai-habits/ ===\npipe.md\n=== /volume1/screenpipe/pipes/day-recap/ ===\npipe.md\n=== /volume1/screenpipe/pipes/meeting-summary/ ===\npipe.md\n=== /volume1/screenpipe/pipes/standup-update/ ===\npipe.md\n=== /volume1/screenpipe/pipes/time-breakdown/ ===\npipe.md\n=== /volume1/screenpipe/pipes/video-export/ ===\npipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read pipe markdown files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo \"===\" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50","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":"---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.","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":"Read summary consumer","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py","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":"activity.py\naudio.py\nelements.py\n__init__.py\ninteractions.py\nocr.py\n__pycache__\nreport.py\nsummary.py\n\"\"\"AI summary generator using Claude.\"\"\"\nimport os\nfrom datetime import date\nfrom typing import Any\n\nfrom consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary\nfrom consumers.ocr import deduplicated_text\nfrom consumers.audio import formatted_transcript\n\n\nSUMMARY_TYPES = {\n \"day_recap\": {\n \"title\": \"Day Recap\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a concise day recap using EXACTLY this format:\n\n## Summary\nOne sentence: what I mainly worked on today.\n\n## Accomplishments\n- Top 3 things I finished, with approximate times\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things seen or heard, with timestamps\n\n## Unfinished Work\n- What to continue tomorrow\n\n## Patterns\n- Apps used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with:\n**Next step:** [most important thing to continue]\"\"\",\n },\n \"standup\": {\n \"title\": \"Standup Update\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a brief standup update:\n\n**Yesterday:** What I worked on (2-3 bullets)\n**Today:** What I plan to continue (1-2 bullets)\n**Blockers:** Any issues observed (or \"None\")\n\nKeep it under 150 words. Only report what's verifiable from the data.\"\"\",\n },\n \"focus_time\": {\n \"title\": \"Focus & Distraction Analysis\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\nAnalyze focus vs distraction patterns:\n\n## Deep Work Periods\n- When and how long were sustained focus sessions?\n- What was being worked on?\n\n## Distractions\n- Which apps/sites were used recreationally?\n- How much time was lost to context switching?\n\n## Recommendations\n- 2-3 concrete suggestions to improve focus tomorrow\n\nBe specific with times and app names.\"\"\",\n },\n}\n\n\ndef _build_context(for_date: date) -> dict[str, str]:\n apps = app_time(for_date)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(for_date, limit=20)\n url_lines = \"\\n\".join(\n f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls\n )\n\n ui_rows = ui_event_summary(for_date)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(for_date, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(for_date)\n\n return {\n \"app_time\": app_lines or \"(no app data)\",\n \"browser_urls\": url_lines or \"(no browser data)\",\n \"ui_events\": ui_lines or \"(no UI event data)\",\n \"ocr_text\": ocr_lines or \"(no screen data)\",\n \"audio\": audio[:3000] if len(audio) > 3000 else audio,\n }\n\n\ndef generate(\n summary_type: str = \"day_recap\",\n for_date: date | None = None,\n api_key: str | None = None,\n) -> dict[str, Any]:\n \"\"\"Generate an AI summary. Returns dict with 'title', 'content', 'date'.\"\"\"\n import anthropic\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\n \"title\": \"Error\",\n \"content\": \"ANTHROPIC_API_KEY not set. Add it to your .env file.\",\n \"date\": str(d),\n }\n\n spec = SUMMARY_TYPES.get(summary_type)\n if not spec:\n return {\"title\": \"Error\", \"content\": f\"Unknown summary type: {summary_type}\", \"date\": str(d)}\n\n stats = summary_stats(d)\n if stats[\"total_frames\"] == 0:\n return {\n \"title\": spec[\"title\"],\n \"content\": f\"No screen data found for {d}.\",\n \"date\": str(d),\n }\n\n ctx = _build_context(d)\n prompt = spec[\"prompt\"].format(**ctx)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": prompt}],\n )\n\n return {\n \"title\": spec[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","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":"Read all pipe.md files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"for f in /volume1/screenpipe/pipes/*/pipe.md; do echo \"=== $f ===\"; cat \"$f\"; 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":"=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: AI Habits\ndescription: \"How you use AI tools — patterns and insights\"\nicon: \"🤖\"\nfeatured: true\n---\n\nSearch my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## AI Tools Used\n- List each tool with approximate time spent (e.g. \"Claude: ~45min\")\n\n## What I Used Them For\n- For each tool: coding, writing, research, or brainstorming\n\n## Usage Patterns\n- Do I switch between tools? Use them in bursts or steadily?\n\n## Effectiveness\n- Which tool appeared alongside completed work vs. abandoned attempts\n\nIf no AI usage is found, say so clearly. End with: \"**Tip:** [one suggestion to use AI tools more effectively]\"\n\n=== /volume1/screenpipe/pipes/day-recap/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n\n=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.\n\n=== /volume1/screenpipe/pipes/standup-update/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Standup Update\ndescription: \"What you did, what's next, and any blockers\"\nicon: \"🏢\"\nfeatured: true\n---\n\nBased on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Yesterday\n- What I worked on (name specific projects, files, tools, PRs)\n\n## Today\n- What I will work on next (based on unfinished tasks and recent activity)\n\n## Blockers\n- Issues I hit — errors, slow builds, waiting on someone\n- If no blockers, write \"None\"\n\nKeep it under 150 words. Copy-paste ready for a team standup.\n\n=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Time Breakdown\ndescription: \"Where your time went — by app, project, and category\"\nicon: \"⏱\"\nfeatured: false\n---\n\nAnalyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.\n\nRead screenpipe skill first.\n\nUse this exact format with durations and percentages:\n\n## By Application\n- List each app with duration and percentage, sorted by time (e.g. \"VS Code: 2h 15min (28%)\")\n\n## By Category\n- Group into: coding, meetings, browsing, writing, communication, other\n- Show hours and percentage per category\n\n## By Project\n- Group related activities by project/topic. Name specific repos or tasks.\n\n## Productivity Score\n- Calculate: focused_work_hours / total_hours as a percentage\n- Focused = coding + writing. Unfocused = browsing + switching.\n\nEnd with: \"**Suggestion:** [one specific change to improve tomorrow's productivity]\"\n\n=== /volume1/screenpipe/pipes/video-export/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Export Video Clip\ndescription: \"Create a video of your recent screen activity\"\nicon: \"🎬\"\nfeatured: false\n---\n\nExport a video of my screen activity from the last 5 minutes.\n\nRead screenpipe skill first.\n\nUse the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.\n\nIf the export is large, suggest a lower fps or shorter time range.","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 clear picture. The pipes are markdown prompt templates in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe/pipes/","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but there's no code to actually load and run them —","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"has its own hardcoded prompts instead.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Here's what I'll implement:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/pipes.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— two new endpoints:","depth":24,"on_screen":false,"role_description":"text"}]...
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-8907047231489583008
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idle
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accessibility
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NULL
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:...
|
21066
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NULL
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21067
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921
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4
|
2026-05-11T17:08:06.091583+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519286091_m2.jpg...
|
Code
|
Implement and run pipe l… — screenpipe [SSH: nas]
|
True
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NULL
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monitor_2
|
NULL
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NULL
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NULL
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NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST "http://localhost:8766/api/pipes/day-recap/run"
curl -X POST "http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25"
Rebuild and restart
to pick up the changes:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
How it works:
Each
pipe.md
file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The "Read screenpipe skill first" line is stripped automatically.
The pipes directory inside Docker is
/data/pipes
(since
/volume1/screenpipe
→
/data
). You can override it with a
PIPES_DIR
env var if needed.
Message actions
pipe.md
pipe.md
where to place api key and can I use different keys
Thinking
Thinking
Bash
Read .env file
IN
cat /volume1/screenpipe/app/.env
Copy code to clipboard
OUT
[ENV_SECRET]
Where to place the key:
app/.env
app/.env
— replace
your_key_here
with your actual key:
Copy code to clipboard
[ENV_SECRET]
That file is loaded by
load_dotenv()
at startup and is excluded from git via
.gitignore
.
Can you use different keys per pipe?
Not currently — all pipes share the one key from
.env
. But you can add per-pipe key support by adding an
api_key
field to the pipe's frontmatter:
Copy code to clipboard
---
title: Meeting Summary
api_key_env: ANTHROPIC_KEY_MEETINGS
---
Then in
consumers/pipes.py
consumers/pipes.py
, read it in
_parse_frontmatter
and pass it through
run_pipe
. Want me to add that?
Message actions
pipe.md
pipe.md
can I use mistral or other llm? or is is build for antrophic only
Thinking
Thinking
Currently it's Anthropic-only — the code calls the
anthropic
SDK directly in both
consumers/pipes.py
consumers/pipes.py
and
consumers/summary.py
consumers/summary.py
.
Adding other providers is straightforward since Mistral, Ollama, OpenRouter, Groq, and most modern LLMs expose an OpenAI-compatible API. The cleanest approach: add the
openai
package and let you configure the provider via
.env
:...
|
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(⇧⌘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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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":"/volume1/screenpipe/.DS_Store\n/volume1/screenpipe/screenpipe.db\n/volume1/screenpipe/screenpipe_sync.sh\n/volume1/screenpipe/app_settings.json\n/volume1/screenpipe/.gitignore\n/volume1/screenpipe/archive.db\n/volume1/screenpipe/db.sqlite\n/volume1/screenpipe/db.sqlite-wal\n/volume1/screenpipe/db.sqlite-shm\n/volume1/screenpipe/#recycle/desktop.ini\n/volume1/screenpipe/#recycle/db.sqlite\n/volume1/screenpipe/#recycle/Copy #1 of db.sqlite\n/volume1/screenpipe/#recycle/.DS_Store\n/volume1/screenpipe/#recycle/Copy #2 of db.sqlite\n/volume1/screenpipe/#recycle/archive.db\n/volume1/screenpipe/#recycle/Copy #1 of archive.db\n/volume1/screenpipe/#recycle/Copy #2 of archive.db\n/volume1/screenpipe/#recycle/Copy #3 of archive.db\n/volume1/screenpipe/#recycle/Copy #4 of archive.db\n/volume1/screenpipe/#recycle/Copy #5 of archive.db\n/volume1/screenpipe/#recycle/Copy #3 of db.sqlite\n/volume1/screenpipe/#recycle/Copy #4 of db.sqlite\n/volume1/screenpipe/#recycle/Copy #6 of archive.db\n/volume1/screenpipe/#recycle/test.txt\n/volume1/screenpipe/#recycle/Copy #7 of archive.db\n/volume1/screenpipe/#recycle/Copy #8 of archive.db\n/volume1/screenpipe/#recycle/archive.db-journal\n/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #5 of db.sqlite\n/volume1/screenpipe/pipes/.DS_Store\n/volume1/screenpipe/app/.env\n/volume1/screenpipe/app/cli.py\n/volume1/screenpipe/app/.DS_Store\n/volume1/screenpipe/app/db.py\n/volume1/screenpipe/app/docker-compose.yml\n/volume1/screenpipe/app/main.py\n/volume1/screenpipe/app/requirements.txt\n/volume1/screenpipe/app/Dockerfile\n/volume1/screenpipe/data/.DS_Store\n/volume1/screenpipe/.git/description\n/volume1/screenpipe/.git/HEAD\n/volume1/screenpipe/.git/index\n/volume1/screenpipe/.git/COMMIT_EDITMSG\n/volume1/screenpipe/#recycle/data/.DS_Store\n---\napp\napp_settings.json\narchive.db\ndata\ndb.sqlite\ndb.sqlite-shm\ndb.sqlite-wal\npipes\n#recycle\nscreenpipe.db\nscreenpipe_sync.sh","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check pipes directory and docker-compose","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml","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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\ncli.py\nconsumers\ndb.py\ndocker-compose.yml\nDockerfile\nmain.py\n__pycache__\nrequirements.txt\nstatic\nservices:\n screenpipe-app:\n build: .\n container_name: screenpipe-app\n restart: unless-stopped\n ports:\n - \"8766:8000\"\n volumes:\n - /volume1/screenpipe:/data\n env_file:\n - .env\n environment:\n TZ: Europe/Sofia\n DB_PATH: /data/db.sqlite\n\n sqlite-web-archive:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-archive\n restart: unless-stopped\n ports:\n - \"8767:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/archive.db\"]\n\n sqlite-web-live:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-live\n restart: unless-stopped\n ports:\n - \"8768:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/db.sqlite\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"requirements.txt","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"requirements.txt","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Inspect a pipe directory","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/","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":"pipe.md\npipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"List all pipes and their contents","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo \"=== $d ===\"; ls \"$d\"; 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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\n=== /volume1/screenpipe/pipes/ai-habits/ ===\npipe.md\n=== /volume1/screenpipe/pipes/day-recap/ ===\npipe.md\n=== /volume1/screenpipe/pipes/meeting-summary/ ===\npipe.md\n=== /volume1/screenpipe/pipes/standup-update/ ===\npipe.md\n=== /volume1/screenpipe/pipes/time-breakdown/ ===\npipe.md\n=== /volume1/screenpipe/pipes/video-export/ ===\npipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read pipe markdown files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo \"===\" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50","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":"---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.","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":"Read summary consumer","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py","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":"activity.py\naudio.py\nelements.py\n__init__.py\ninteractions.py\nocr.py\n__pycache__\nreport.py\nsummary.py\n\"\"\"AI summary generator using Claude.\"\"\"\nimport os\nfrom datetime import date\nfrom typing import Any\n\nfrom consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary\nfrom consumers.ocr import deduplicated_text\nfrom consumers.audio import formatted_transcript\n\n\nSUMMARY_TYPES = {\n \"day_recap\": {\n \"title\": \"Day Recap\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a concise day recap using EXACTLY this format:\n\n## Summary\nOne sentence: what I mainly worked on today.\n\n## Accomplishments\n- Top 3 things I finished, with approximate times\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things seen or heard, with timestamps\n\n## Unfinished Work\n- What to continue tomorrow\n\n## Patterns\n- Apps used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with:\n**Next step:** [most important thing to continue]\"\"\",\n },\n \"standup\": {\n \"title\": \"Standup Update\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a brief standup update:\n\n**Yesterday:** What I worked on (2-3 bullets)\n**Today:** What I plan to continue (1-2 bullets)\n**Blockers:** Any issues observed (or \"None\")\n\nKeep it under 150 words. Only report what's verifiable from the data.\"\"\",\n },\n \"focus_time\": {\n \"title\": \"Focus & Distraction Analysis\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\nAnalyze focus vs distraction patterns:\n\n## Deep Work Periods\n- When and how long were sustained focus sessions?\n- What was being worked on?\n\n## Distractions\n- Which apps/sites were used recreationally?\n- How much time was lost to context switching?\n\n## Recommendations\n- 2-3 concrete suggestions to improve focus tomorrow\n\nBe specific with times and app names.\"\"\",\n },\n}\n\n\ndef _build_context(for_date: date) -> dict[str, str]:\n apps = app_time(for_date)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(for_date, limit=20)\n url_lines = \"\\n\".join(\n f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls\n )\n\n ui_rows = ui_event_summary(for_date)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(for_date, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(for_date)\n\n return {\n \"app_time\": app_lines or \"(no app data)\",\n \"browser_urls\": url_lines or \"(no browser data)\",\n \"ui_events\": ui_lines or \"(no UI event data)\",\n \"ocr_text\": ocr_lines or \"(no screen data)\",\n \"audio\": audio[:3000] if len(audio) > 3000 else audio,\n }\n\n\ndef generate(\n summary_type: str = \"day_recap\",\n for_date: date | None = None,\n api_key: str | None = None,\n) -> dict[str, Any]:\n \"\"\"Generate an AI summary. Returns dict with 'title', 'content', 'date'.\"\"\"\n import anthropic\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\n \"title\": \"Error\",\n \"content\": \"ANTHROPIC_API_KEY not set. Add it to your .env file.\",\n \"date\": str(d),\n }\n\n spec = SUMMARY_TYPES.get(summary_type)\n if not spec:\n return {\"title\": \"Error\", \"content\": f\"Unknown summary type: {summary_type}\", \"date\": str(d)}\n\n stats = summary_stats(d)\n if stats[\"total_frames\"] == 0:\n return {\n \"title\": spec[\"title\"],\n \"content\": f\"No screen data found for {d}.\",\n \"date\": str(d),\n }\n\n ctx = _build_context(d)\n prompt = spec[\"prompt\"].format(**ctx)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": prompt}],\n )\n\n return {\n \"title\": spec[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","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":"Read all pipe.md files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"for f in /volume1/screenpipe/pipes/*/pipe.md; do echo \"=== $f ===\"; cat \"$f\"; 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":"=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: AI Habits\ndescription: \"How you use AI tools — patterns and insights\"\nicon: \"🤖\"\nfeatured: true\n---\n\nSearch my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## AI Tools Used\n- List each tool with approximate time spent (e.g. \"Claude: ~45min\")\n\n## What I Used Them For\n- For each tool: coding, writing, research, or brainstorming\n\n## Usage Patterns\n- Do I switch between tools? Use them in bursts or steadily?\n\n## Effectiveness\n- Which tool appeared alongside completed work vs. abandoned attempts\n\nIf no AI usage is found, say so clearly. End with: \"**Tip:** [one suggestion to use AI tools more effectively]\"\n\n=== /volume1/screenpipe/pipes/day-recap/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n\n=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.\n\n=== /volume1/screenpipe/pipes/standup-update/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Standup Update\ndescription: \"What you did, what's next, and any blockers\"\nicon: \"🏢\"\nfeatured: true\n---\n\nBased on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Yesterday\n- What I worked on (name specific projects, files, tools, PRs)\n\n## Today\n- What I will work on next (based on unfinished tasks and recent activity)\n\n## Blockers\n- Issues I hit — errors, slow builds, waiting on someone\n- If no blockers, write \"None\"\n\nKeep it under 150 words. Copy-paste ready for a team standup.\n\n=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Time Breakdown\ndescription: \"Where your time went — by app, project, and category\"\nicon: \"⏱\"\nfeatured: false\n---\n\nAnalyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.\n\nRead screenpipe skill first.\n\nUse this exact format with durations and percentages:\n\n## By Application\n- List each app with duration and percentage, sorted by time (e.g. \"VS Code: 2h 15min (28%)\")\n\n## By Category\n- Group into: coding, meetings, browsing, writing, communication, other\n- Show hours and percentage per category\n\n## By Project\n- Group related activities by project/topic. Name specific repos or tasks.\n\n## Productivity Score\n- Calculate: focused_work_hours / total_hours as a percentage\n- Focused = coding + writing. Unfocused = browsing + switching.\n\nEnd with: \"**Suggestion:** [one specific change to improve tomorrow's productivity]\"\n\n=== /volume1/screenpipe/pipes/video-export/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Export Video Clip\ndescription: \"Create a video of your recent screen activity\"\nicon: \"🎬\"\nfeatured: false\n---\n\nExport a video of my screen activity from the last 5 minutes.\n\nRead screenpipe skill first.\n\nUse the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.\n\nIf the export is large, suggest a lower fps or shorter time range.","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 clear picture. The pipes are markdown prompt templates in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe/pipes/","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but there's no code to actually load and run them —","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"has its own hardcoded prompts instead.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Here's what I'll implement:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/pipes.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— two new endpoints:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"GET /api/pipes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /api/pipes/{pipe_id}/run","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cli.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— a","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"command to run pipes from the terminal","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Let me build it:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check browser_urls signature","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/consumers/activity.py | grep \"def browser_urls\" -A 5","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":"def browser_urls(\n for_date: date | None = None,\n app_name: str | None = None,\n ts_from: str | None = None,\n ts_to: str | None = None,\n limit: int = 30,","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":"pipes.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipes.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"143 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"\"\"\"Dynamic pipe loader and runner.\"\"\"\nimport os\nimport re\nfrom datetime import date\nfrom pathlib import Path\nfrom typing import Any\n\n\ndef _parse_frontmatter(text: str) -> tuple[dict, str]:\n if not text.startswith(\"---\"):\n return {}, text\n try:\n end = text.index(\"---\", 3)\n except ValueError:\n return {}, text\n fm_text = text[3:end].strip()\n body = text[end + 3:].strip()\n meta: dict = {}\n for line in fm_text.splitlines():\n if \":\" in line:\n k, _, v = line.partition(\":\")\n meta[k.strip()] = v.strip().strip('\"')\n return meta, body\n\n\ndef load_pipes(pipes_dir: Path) -> list[dict]:\n if not pipes_dir.exists():\n return []\n pipes = []\n for pipe_dir in sorted(pipes_dir.iterdir()):\n if not pipe_dir.is_dir() or pipe_dir.name.startswith(\".\"):\n continue\n pipe_md = pipe_dir / \"pipe.md\"\n if not pipe_md.exists():\n continue\n text = pipe_md.read_text(encoding=\"utf-8\")\n meta, body = _parse_frontmatter(text)\n if meta.get(\"enabled\", \"true\").lower() == \"false\":\n continue\n body = re.sub(r\"Read screenpipe skill first\\.?\\n?\", \"\", body).strip()\n pipes.append({\n \"id\": pipe_dir.name,\n \"title\": meta.get(\"title\", pipe_dir.name),\n \"description\": meta.get(\"description\", \"\"),\n \"icon\": meta.get(\"icon\", \"\"),\n \"schedule\": meta.get(\"schedule\", \"manual\"),\n \"featured\": meta.get(\"featured\", \"false\").lower() == \"true\",\n \"prompt\": body,\n })\n return pipes\n\n\ndef _build_system(d: date, stats: dict) -> str:\n from consumers.activity import app_time, browser_urls, ui_event_summary\n from consumers.ocr import deduplicated_text\n from consumers.audio import formatted_transcript\n\n apps = app_time(d)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(d, limit=20)\n url_lines = \"\\n\".join(f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls)\n\n ui_rows = ui_event_summary(d)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(d, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(d)\n if len(audio) > 3000:\n audio = audio[:3000]\n\n return f\"\"\"You are analyzing screenpipe data — recordings of a person's computer activity.\n\n## App usage (minutes per app):\n{app_lines or '(no app data)'}\n\n## Browser URLs visited:\n{url_lines or '(no browser data)'}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_lines or '(no UI event data)'}\n\n## Screen content (sampled every 5 minutes):\n{ocr_lines or '(no screen data)'}\n\n## Audio / speech:\n{audio or '(no audio data)'}\n\nDate: {d}\nTotal frames recorded: {stats['total_frames']}\"\"\"\n\n\ndef run_pipe(\n pipe_id: str,\n for_date: date | None = None,\n api_key: str | None = None,\n pipes_dir: Path | None = None,\n) -> dict[str, Any]:\n import anthropic\n from consumers.activity import summary_stats\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\"title\": \"Error\", \"content\": \"ANTHROPIC_API_KEY not set.\", \"date\": str(d)}\n\n _pipes_dir = pipes_dir or Path(os.environ.get(\"PIPES_DIR\", \"/data/pipes\"))\n all_pipes = {p[\"id\"]: p for p in load_pipes(_pipes_dir)}\n\n if pipe_id not in all_pipes:\n return {\"title\": \"Error\", \"content\": f\"Pipe not found: {pipe_id}\", \"date\": str(d)}\n\n pipe = all_pipes[pipe_id]\n stats = summary_stats(d)\n\n if stats[\"total_frames\"] == 0:\n return {\"title\": pipe[\"title\"], \"content\": f\"No screen data found for {d}.\", \"date\": str(d)}\n\n system = _build_system(d, stats)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n system=system,\n messages=[{\"role\": \"user\", \"content\": pipe[\"prompt\"]}],\n )\n\n return {\n \"title\": pipe[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the API endpoints to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the pipe endpoints at the end of main.py, before the closing summary section:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 14 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the CLI command to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 40 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Done. Here's how to run pipes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to run pipes","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to run pipes","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via Docker (inside the running container):","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"docker exec -it screenpipe-app python cli.py pipe --list\ndocker exec -it screenpipe-app python cli.py pipe day-recap\ndocker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via the API","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(once the container is running on port 8766):","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# List pipes\ncurl http://localhost:8766/api/pipes\n\n# Run a pipe\ncurl -X POST \"http://localhost:8766/api/pipes/day-recap/run\"\ncurl -X POST \"http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rebuild and restart","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to pick up the changes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"cd /volume1/screenpipe/app\ndocker compose up --build -d","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"How it works:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Each","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The \"Read screenpipe skill first\" line is stripped automatically.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The pipes directory inside Docker is","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data/pipes","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(since","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"→","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). You can override it with a","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"PIPES_DIR","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"env var if needed.","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":"AXButton","text":"pipe.md","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"where to place api key and can I use different keys","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":"Read .env file","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/.env","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":"ANTHROPIC_API_KEY=your_key_here","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Where to place the key:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"app/.env","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"app/.env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— replace","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"your_key_here","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with your actual key:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"ANTHROPIC_API_KEY=sk-ant-...","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"That file is loaded by","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"load_dotenv()","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"at startup and is excluded from git via","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".gitignore","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Can you use different keys per pipe?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Not currently — all pipes share the one key from","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". But you can add per-pipe key support by adding an","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"api_key","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"field to the pipe's frontmatter:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"---\ntitle: Meeting Summary\napi_key_env: ANTHROPIC_KEY_MEETINGS\n---","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Then in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/pipes.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/pipes.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", read it in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"_parse_frontmatter","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and pass it through","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"run_pipe","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". Want me to add that?","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":"AXButton","text":"pipe.md","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"can I use mistral or other llm? or is is build for antrophic only","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":"Currently it's Anthropic-only — the code calls the","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"anthropic","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SDK directly in both","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/pipes.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/pipes.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/summary.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Adding other providers is straightforward since Mistral, Ollama, OpenRouter, Groq, and most modern LLMs expose an OpenAI-compatible API. The cleanest approach: add the","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"openai","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"package and let you configure the provider via","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"}]...
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idle
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accessibility
|
NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
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OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
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OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST "http://localhost:8766/api/pipes/day-recap/run"
curl -X POST "http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25"
Rebuild and restart
to pick up the changes:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
How it works:
Each
pipe.md
file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The "Read screenpipe skill first" line is stripped automatically.
The pipes directory inside Docker is
/data/pipes
(since
/volume1/screenpipe
→
/data
). You can override it with a
PIPES_DIR
env var if needed.
Message actions
pipe.md
pipe.md
where to place api key and can I use different keys
Thinking
Thinking
Bash
Read .env file
IN
cat /volume1/screenpipe/app/.env
Copy code to clipboard
OUT
[ENV_SECRET]
Where to place the key:
app/.env
app/.env
— replace
your_key_here
with your actual key:
Copy code to clipboard
[ENV_SECRET]
That file is loaded by
load_dotenv()
at startup and is excluded from git via
.gitignore
.
Can you use different keys per pipe?
Not currently — all pipes share the one key from
.env
. But you can add per-pipe key support by adding an
api_key
field to the pipe's frontmatter:
Copy code to clipboard
---
title: Meeting Summary
api_key_env: ANTHROPIC_KEY_MEETINGS
---
Then in
consumers/pipes.py
consumers/pipes.py
, read it in
_parse_frontmatter
and pass it through
run_pipe
. Want me to add that?
Message actions
pipe.md
pipe.md
can I use mistral or other llm? or is is build for antrophic only
Thinking
Thinking
Currently it's Anthropic-only — the code calls the
anthropic
SDK directly in both
consumers/pipes.py
consumers/pipes.py
and
consumers/summary.py
consumers/summary.py
.
Adding other providers is straightforward since Mistral, Ollama, OpenRouter, Groq, and most modern LLMs expose an OpenAI-compatible API. The cleanest approach: add the
openai
package and let you configure the provider via
.env
:...
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Implement and run pipe l… — screenpipe [SSH: nas]
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard...
|
[{"role":"AXRadioButton","text [{"role":"AXRadioButton","text":"Explorer (⇧⌘E)","depth":19,"on_screen":true,"role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":true,"is_expanded":true},{"role":"AXStaticText","text":"","depth":22,"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Search (⇧⌘F)","depth":19,"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,"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Source Control (⌃⇧G) - 10 pending changes","depth":19,"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,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"10","depth":22,"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Run and Debug (⇧⌘D)","depth":19,"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,"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Remote Explorer","depth":19,"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,"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Extensions (⇧⌘X) - 2 require 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unless-stopped\n ports:\n - \"8766:8000\"\n volumes:\n - /volume1/screenpipe:/data\n env_file:\n - .env\n environment:\n TZ: Europe/Sofia\n DB_PATH: /data/db.sqlite\n\n sqlite-web-archive:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-archive\n restart: unless-stopped\n ports:\n - \"8767:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/archive.db\"]\n\n sqlite-web-live:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-live\n restart: unless-stopped\n ports:\n - \"8768:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", 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their contents","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo \"=== $d ===\"; ls \"$d\"; 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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\n=== /volume1/screenpipe/pipes/ai-habits/ ===\npipe.md\n=== /volume1/screenpipe/pipes/day-recap/ ===\npipe.md\n=== /volume1/screenpipe/pipes/meeting-summary/ ===\npipe.md\n=== /volume1/screenpipe/pipes/standup-update/ ===\npipe.md\n=== /volume1/screenpipe/pipes/time-breakdown/ ===\npipe.md\n=== /volume1/screenpipe/pipes/video-export/ ===\npipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read pipe markdown files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo \"===\" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50","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":"---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.","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":"Read summary consumer","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py","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":"activity.py\naudio.py\nelements.py\n__init__.py\ninteractions.py\nocr.py\n__pycache__\nreport.py\nsummary.py\n\"\"\"AI summary generator using Claude.\"\"\"\nimport os\nfrom datetime import date\nfrom typing import Any\n\nfrom consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary\nfrom consumers.ocr import deduplicated_text\nfrom consumers.audio import formatted_transcript\n\n\nSUMMARY_TYPES = {\n \"day_recap\": {\n \"title\": \"Day Recap\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a concise day recap using EXACTLY this format:\n\n## Summary\nOne sentence: what I mainly worked on today.\n\n## Accomplishments\n- Top 3 things I finished, with approximate times\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things seen or heard, with timestamps\n\n## Unfinished Work\n- What to continue tomorrow\n\n## Patterns\n- Apps used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with:\n**Next step:** [most important thing to continue]\"\"\",\n },\n \"standup\": {\n \"title\": \"Standup Update\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a brief standup update:\n\n**Yesterday:** What I worked on (2-3 bullets)\n**Today:** What I plan to continue (1-2 bullets)\n**Blockers:** Any issues observed (or \"None\")\n\nKeep it under 150 words. Only report what's verifiable from the data.\"\"\",\n },\n \"focus_time\": {\n \"title\": \"Focus & Distraction Analysis\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\nAnalyze focus vs distraction patterns:\n\n## Deep Work Periods\n- When and how long were sustained focus sessions?\n- What was being worked on?\n\n## Distractions\n- Which apps/sites were used recreationally?\n- How much time was lost to context switching?\n\n## Recommendations\n- 2-3 concrete suggestions to improve focus tomorrow\n\nBe specific with times and app names.\"\"\",\n },\n}\n\n\ndef _build_context(for_date: date) -> dict[str, str]:\n apps = app_time(for_date)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(for_date, limit=20)\n url_lines = \"\\n\".join(\n f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls\n )\n\n ui_rows = ui_event_summary(for_date)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(for_date, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(for_date)\n\n return {\n \"app_time\": app_lines or \"(no app data)\",\n \"browser_urls\": url_lines or \"(no browser data)\",\n \"ui_events\": ui_lines or \"(no UI event data)\",\n \"ocr_text\": ocr_lines or \"(no screen data)\",\n \"audio\": audio[:3000] if len(audio) > 3000 else audio,\n }\n\n\ndef generate(\n summary_type: str = \"day_recap\",\n for_date: date | None = None,\n api_key: str | None = None,\n) -> dict[str, Any]:\n \"\"\"Generate an AI summary. Returns dict with 'title', 'content', 'date'.\"\"\"\n import anthropic\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\n \"title\": \"Error\",\n \"content\": \"ANTHROPIC_API_KEY not set. Add it to your .env file.\",\n \"date\": str(d),\n }\n\n spec = SUMMARY_TYPES.get(summary_type)\n if not spec:\n return {\"title\": \"Error\", \"content\": f\"Unknown summary type: {summary_type}\", \"date\": str(d)}\n\n stats = summary_stats(d)\n if stats[\"total_frames\"] == 0:\n return {\n \"title\": spec[\"title\"],\n \"content\": f\"No screen data found for {d}.\",\n \"date\": str(d),\n }\n\n ctx = _build_context(d)\n prompt = spec[\"prompt\"].format(**ctx)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": prompt}],\n )\n\n return {\n \"title\": spec[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","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":"Read all pipe.md files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"for f in /volume1/screenpipe/pipes/*/pipe.md; do echo \"=== $f ===\"; cat \"$f\"; 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":"=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: AI Habits\ndescription: \"How you use AI tools — patterns and insights\"\nicon: \"🤖\"\nfeatured: true\n---\n\nSearch my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## AI Tools Used\n- List each tool with approximate time spent (e.g. \"Claude: ~45min\")\n\n## What I Used Them For\n- For each tool: coding, writing, research, or brainstorming\n\n## Usage Patterns\n- Do I switch between tools? Use them in bursts or steadily?\n\n## Effectiveness\n- Which tool appeared alongside completed work vs. abandoned attempts\n\nIf no AI usage is found, say so clearly. End with: \"**Tip:** [one suggestion to use AI tools more effectively]\"\n\n=== /volume1/screenpipe/pipes/day-recap/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n\n=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.\n\n=== /volume1/screenpipe/pipes/standup-update/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Standup Update\ndescription: \"What you did, what's next, and any blockers\"\nicon: \"🏢\"\nfeatured: true\n---\n\nBased on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Yesterday\n- What I worked on (name specific projects, files, tools, PRs)\n\n## Today\n- What I will work on next (based on unfinished tasks and recent activity)\n\n## Blockers\n- Issues I hit — errors, slow builds, waiting on someone\n- If no blockers, write \"None\"\n\nKeep it under 150 words. Copy-paste ready for a team standup.\n\n=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Time Breakdown\ndescription: \"Where your time went — by app, project, and category\"\nicon: \"⏱\"\nfeatured: false\n---\n\nAnalyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.\n\nRead screenpipe skill first.\n\nUse this exact format with durations and percentages:\n\n## By Application\n- List each app with duration and percentage, sorted by time (e.g. \"VS Code: 2h 15min (28%)\")\n\n## By Category\n- Group into: coding, meetings, browsing, writing, communication, other\n- Show hours and percentage per category\n\n## By Project\n- Group related activities by project/topic. Name specific repos or tasks.\n\n## Productivity Score\n- Calculate: focused_work_hours / total_hours as a percentage\n- Focused = coding + writing. Unfocused = browsing + switching.\n\nEnd with: \"**Suggestion:** [one specific change to improve tomorrow's productivity]\"\n\n=== /volume1/screenpipe/pipes/video-export/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Export Video Clip\ndescription: \"Create a video of your recent screen activity\"\nicon: \"🎬\"\nfeatured: false\n---\n\nExport a video of my screen activity from the last 5 minutes.\n\nRead screenpipe skill first.\n\nUse the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.\n\nIf the export is large, suggest a lower fps or shorter time range.","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 clear picture. The pipes are markdown prompt templates in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe/pipes/","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but there's no code to actually load and run them —","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"has its own hardcoded prompts instead.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Here's what I'll implement:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/pipes.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— two new endpoints:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"GET /api/pipes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /api/pipes/{pipe_id}/run","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cli.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— a","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"command to run pipes from the terminal","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Let me build it:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check browser_urls signature","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/consumers/activity.py | grep \"def browser_urls\" -A 5","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":"def browser_urls(\n for_date: date | None = None,\n app_name: str | None = None,\n ts_from: str | None = None,\n ts_to: str | None = None,\n limit: int = 30,","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":"pipes.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipes.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"143 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"\"\"\"Dynamic pipe loader and runner.\"\"\"\nimport os\nimport re\nfrom datetime import date\nfrom pathlib import Path\nfrom typing import Any\n\n\ndef _parse_frontmatter(text: str) -> tuple[dict, str]:\n if not text.startswith(\"---\"):\n return {}, text\n try:\n end = text.index(\"---\", 3)\n except ValueError:\n return {}, text\n fm_text = text[3:end].strip()\n body = text[end + 3:].strip()\n meta: dict = {}\n for line in fm_text.splitlines():\n if \":\" in line:\n k, _, v = line.partition(\":\")\n meta[k.strip()] = v.strip().strip('\"')\n return meta, body\n\n\ndef load_pipes(pipes_dir: Path) -> list[dict]:\n if not pipes_dir.exists():\n return []\n pipes = []\n for pipe_dir in sorted(pipes_dir.iterdir()):\n if not pipe_dir.is_dir() or pipe_dir.name.startswith(\".\"):\n continue\n pipe_md = pipe_dir / \"pipe.md\"\n if not pipe_md.exists():\n continue\n text = pipe_md.read_text(encoding=\"utf-8\")\n meta, body = _parse_frontmatter(text)\n if meta.get(\"enabled\", \"true\").lower() == \"false\":\n continue\n body = re.sub(r\"Read screenpipe skill first\\.?\\n?\", \"\", body).strip()\n pipes.append({\n \"id\": pipe_dir.name,\n \"title\": meta.get(\"title\", pipe_dir.name),\n \"description\": meta.get(\"description\", \"\"),\n \"icon\": meta.get(\"icon\", \"\"),\n \"schedule\": meta.get(\"schedule\", \"manual\"),\n \"featured\": meta.get(\"featured\", \"false\").lower() == \"true\",\n \"prompt\": body,\n })\n return pipes\n\n\ndef _build_system(d: date, stats: dict) -> str:\n from consumers.activity import app_time, browser_urls, ui_event_summary\n from consumers.ocr import deduplicated_text\n from consumers.audio import formatted_transcript\n\n apps = app_time(d)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(d, limit=20)\n url_lines = \"\\n\".join(f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls)\n\n ui_rows = ui_event_summary(d)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(d, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(d)\n if len(audio) > 3000:\n audio = audio[:3000]\n\n return f\"\"\"You are analyzing screenpipe data — recordings of a person's computer activity.\n\n## App usage (minutes per app):\n{app_lines or '(no app data)'}\n\n## Browser URLs visited:\n{url_lines or '(no browser data)'}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_lines or '(no UI event data)'}\n\n## Screen content (sampled every 5 minutes):\n{ocr_lines or '(no screen data)'}\n\n## Audio / speech:\n{audio or '(no audio data)'}\n\nDate: {d}\nTotal frames recorded: {stats['total_frames']}\"\"\"\n\n\ndef run_pipe(\n pipe_id: str,\n for_date: date | None = None,\n api_key: str | None = None,\n pipes_dir: Path | None = None,\n) -> dict[str, Any]:\n import anthropic\n from consumers.activity import summary_stats\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\"title\": \"Error\", \"content\": \"ANTHROPIC_API_KEY not set.\", \"date\": str(d)}\n\n _pipes_dir = pipes_dir or Path(os.environ.get(\"PIPES_DIR\", \"/data/pipes\"))\n all_pipes = {p[\"id\"]: p for p in load_pipes(_pipes_dir)}\n\n if pipe_id not in all_pipes:\n return {\"title\": \"Error\", \"content\": f\"Pipe not found: {pipe_id}\", \"date\": str(d)}\n\n pipe = all_pipes[pipe_id]\n stats = summary_stats(d)\n\n if stats[\"total_frames\"] == 0:\n return {\"title\": pipe[\"title\"], \"content\": f\"No screen data found for {d}.\", \"date\": str(d)}\n\n system = _build_system(d, stats)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n system=system,\n messages=[{\"role\": \"user\", \"content\": pipe[\"prompt\"]}],\n )\n\n return {\n \"title\": pipe[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the API endpoints to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the pipe endpoints at the end of main.py, before the closing summary section:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 14 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the CLI command to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 40 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Done. Here's how to run pipes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to run pipes","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to run pipes","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via Docker (inside the running container):","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"docker exec -it screenpipe-app python cli.py pipe --list\ndocker exec -it screenpipe-app python cli.py pipe day-recap\ndocker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via the API","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(once the container is running on port 8766):","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"on_screen":false,"help_text":"Copy code","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false}]...
|
-8963375894614035486
|
-8691439177447798548
|
idle
|
accessibility
|
NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard...
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21065
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921
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3
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2026-05-11T17:07:35.584854+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519255584_m2.jpg...
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Code
|
Implement and run pipe l… — screenpipe [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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NULL
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines...
|
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tunnel","depth":12,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Implement and run pipe logic","depth":19,"bounds":{"left":0.56017286,"top":0.08060654,"width":0.07114362,"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 history","depth":19,"bounds":{"left":0.9780585,"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":0.9886968,"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 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place.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"List project files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"find /volume1/screenpipe -type f | head -50 && echo \"---\" && ls /volume1/screenpipe","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":"/volume1/screenpipe/.DS_Store\n/volume1/screenpipe/screenpipe.db\n/volume1/screenpipe/screenpipe_sync.sh\n/volume1/screenpipe/app_settings.json\n/volume1/screenpipe/.gitignore\n/volume1/screenpipe/archive.db\n/volume1/screenpipe/db.sqlite\n/volume1/screenpipe/db.sqlite-wal\n/volume1/screenpipe/db.sqlite-shm\n/volume1/screenpipe/#recycle/desktop.ini\n/volume1/screenpipe/#recycle/db.sqlite\n/volume1/screenpipe/#recycle/Copy #1 of db.sqlite\n/volume1/screenpipe/#recycle/.DS_Store\n/volume1/screenpipe/#recycle/Copy #2 of db.sqlite\n/volume1/screenpipe/#recycle/archive.db\n/volume1/screenpipe/#recycle/Copy #1 of archive.db\n/volume1/screenpipe/#recycle/Copy #2 of archive.db\n/volume1/screenpipe/#recycle/Copy #3 of archive.db\n/volume1/screenpipe/#recycle/Copy #4 of archive.db\n/volume1/screenpipe/#recycle/Copy #5 of archive.db\n/volume1/screenpipe/#recycle/Copy #3 of db.sqlite\n/volume1/screenpipe/#recycle/Copy #4 of db.sqlite\n/volume1/screenpipe/#recycle/Copy #6 of archive.db\n/volume1/screenpipe/#recycle/test.txt\n/volume1/screenpipe/#recycle/Copy #7 of archive.db\n/volume1/screenpipe/#recycle/Copy #8 of archive.db\n/volume1/screenpipe/#recycle/archive.db-journal\n/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #5 of db.sqlite\n/volume1/screenpipe/pipes/.DS_Store\n/volume1/screenpipe/app/.env\n/volume1/screenpipe/app/cli.py\n/volume1/screenpipe/app/.DS_Store\n/volume1/screenpipe/app/db.py\n/volume1/screenpipe/app/docker-compose.yml\n/volume1/screenpipe/app/main.py\n/volume1/screenpipe/app/requirements.txt\n/volume1/screenpipe/app/Dockerfile\n/volume1/screenpipe/data/.DS_Store\n/volume1/screenpipe/.git/description\n/volume1/screenpipe/.git/HEAD\n/volume1/screenpipe/.git/index\n/volume1/screenpipe/.git/COMMIT_EDITMSG\n/volume1/screenpipe/#recycle/data/.DS_Store\n---\napp\napp_settings.json\narchive.db\ndata\ndb.sqlite\ndb.sqlite-shm\ndb.sqlite-wal\npipes\n#recycle\nscreenpipe.db\nscreenpipe_sync.sh","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check pipes directory and docker-compose","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml","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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\ncli.py\nconsumers\ndb.py\ndocker-compose.yml\nDockerfile\nmain.py\n__pycache__\nrequirements.txt\nstatic\nservices:\n screenpipe-app:\n build: .\n container_name: screenpipe-app\n restart: unless-stopped\n ports:\n - \"8766:8000\"\n volumes:\n - /volume1/screenpipe:/data\n env_file:\n - .env\n environment:\n TZ: Europe/Sofia\n DB_PATH: /data/db.sqlite\n\n sqlite-web-archive:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-archive\n restart: unless-stopped\n ports:\n - \"8767:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/archive.db\"]\n\n sqlite-web-live:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-live\n restart: unless-stopped\n ports:\n - \"8768:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/db.sqlite\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"requirements.txt","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"requirements.txt","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Inspect a pipe directory","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/","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":"pipe.md\npipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"List all pipes and their contents","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo \"=== $d ===\"; ls \"$d\"; 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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\n=== /volume1/screenpipe/pipes/ai-habits/ ===\npipe.md\n=== /volume1/screenpipe/pipes/day-recap/ ===\npipe.md\n=== /volume1/screenpipe/pipes/meeting-summary/ ===\npipe.md\n=== /volume1/screenpipe/pipes/standup-update/ ===\npipe.md\n=== /volume1/screenpipe/pipes/time-breakdown/ ===\npipe.md\n=== /volume1/screenpipe/pipes/video-export/ ===\npipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read pipe markdown files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo \"===\" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50","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":"---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.","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":"Read summary consumer","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py","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":"activity.py\naudio.py\nelements.py\n__init__.py\ninteractions.py\nocr.py\n__pycache__\nreport.py\nsummary.py\n\"\"\"AI summary generator using Claude.\"\"\"\nimport os\nfrom datetime import date\nfrom typing import Any\n\nfrom consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary\nfrom consumers.ocr import deduplicated_text\nfrom consumers.audio import formatted_transcript\n\n\nSUMMARY_TYPES = {\n \"day_recap\": {\n \"title\": \"Day Recap\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a concise day recap using EXACTLY this format:\n\n## Summary\nOne sentence: what I mainly worked on today.\n\n## Accomplishments\n- Top 3 things I finished, with approximate times\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things seen or heard, with timestamps\n\n## Unfinished Work\n- What to continue tomorrow\n\n## Patterns\n- Apps used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with:\n**Next step:** [most important thing to continue]\"\"\",\n },\n \"standup\": {\n \"title\": \"Standup Update\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a brief standup update:\n\n**Yesterday:** What I worked on (2-3 bullets)\n**Today:** What I plan to continue (1-2 bullets)\n**Blockers:** Any issues observed (or \"None\")\n\nKeep it under 150 words. Only report what's verifiable from the data.\"\"\",\n },\n \"focus_time\": {\n \"title\": \"Focus & Distraction Analysis\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\nAnalyze focus vs distraction patterns:\n\n## Deep Work Periods\n- When and how long were sustained focus sessions?\n- What was being worked on?\n\n## Distractions\n- Which apps/sites were used recreationally?\n- How much time was lost to context switching?\n\n## Recommendations\n- 2-3 concrete suggestions to improve focus tomorrow\n\nBe specific with times and app names.\"\"\",\n },\n}\n\n\ndef _build_context(for_date: date) -> dict[str, str]:\n apps = app_time(for_date)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(for_date, limit=20)\n url_lines = \"\\n\".join(\n f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls\n )\n\n ui_rows = ui_event_summary(for_date)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(for_date, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(for_date)\n\n return {\n \"app_time\": app_lines or \"(no app data)\",\n \"browser_urls\": url_lines or \"(no browser data)\",\n \"ui_events\": ui_lines or \"(no UI event data)\",\n \"ocr_text\": ocr_lines or \"(no screen data)\",\n \"audio\": audio[:3000] if len(audio) > 3000 else audio,\n }\n\n\ndef generate(\n summary_type: str = \"day_recap\",\n for_date: date | None = None,\n api_key: str | None = None,\n) -> dict[str, Any]:\n \"\"\"Generate an AI summary. Returns dict with 'title', 'content', 'date'.\"\"\"\n import anthropic\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\n \"title\": \"Error\",\n \"content\": \"ANTHROPIC_API_KEY not set. Add it to your .env file.\",\n \"date\": str(d),\n }\n\n spec = SUMMARY_TYPES.get(summary_type)\n if not spec:\n return {\"title\": \"Error\", \"content\": f\"Unknown summary type: {summary_type}\", \"date\": str(d)}\n\n stats = summary_stats(d)\n if stats[\"total_frames\"] == 0:\n return {\n \"title\": spec[\"title\"],\n \"content\": f\"No screen data found for {d}.\",\n \"date\": str(d),\n }\n\n ctx = _build_context(d)\n prompt = spec[\"prompt\"].format(**ctx)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": prompt}],\n )\n\n return {\n \"title\": spec[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","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":"Read all pipe.md files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"for f in /volume1/screenpipe/pipes/*/pipe.md; do echo \"=== $f ===\"; cat \"$f\"; 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":"=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: AI Habits\ndescription: \"How you use AI tools — patterns and insights\"\nicon: \"🤖\"\nfeatured: true\n---\n\nSearch my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## AI Tools Used\n- List each tool with approximate time spent (e.g. \"Claude: ~45min\")\n\n## What I Used Them For\n- For each tool: coding, writing, research, or brainstorming\n\n## Usage Patterns\n- Do I switch between tools? Use them in bursts or steadily?\n\n## Effectiveness\n- Which tool appeared alongside completed work vs. abandoned attempts\n\nIf no AI usage is found, say so clearly. End with: \"**Tip:** [one suggestion to use AI tools more effectively]\"\n\n=== /volume1/screenpipe/pipes/day-recap/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n\n=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.\n\n=== /volume1/screenpipe/pipes/standup-update/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Standup Update\ndescription: \"What you did, what's next, and any blockers\"\nicon: \"🏢\"\nfeatured: true\n---\n\nBased on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Yesterday\n- What I worked on (name specific projects, files, tools, PRs)\n\n## Today\n- What I will work on next (based on unfinished tasks and recent activity)\n\n## Blockers\n- Issues I hit — errors, slow builds, waiting on someone\n- If no blockers, write \"None\"\n\nKeep it under 150 words. Copy-paste ready for a team standup.\n\n=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Time Breakdown\ndescription: \"Where your time went — by app, project, and category\"\nicon: \"⏱\"\nfeatured: false\n---\n\nAnalyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.\n\nRead screenpipe skill first.\n\nUse this exact format with durations and percentages:\n\n## By Application\n- List each app with duration and percentage, sorted by time (e.g. \"VS Code: 2h 15min (28%)\")\n\n## By Category\n- Group into: coding, meetings, browsing, writing, communication, other\n- Show hours and percentage per category\n\n## By Project\n- Group related activities by project/topic. Name specific repos or tasks.\n\n## Productivity Score\n- Calculate: focused_work_hours / total_hours as a percentage\n- Focused = coding + writing. Unfocused = browsing + switching.\n\nEnd with: \"**Suggestion:** [one specific change to improve tomorrow's productivity]\"\n\n=== /volume1/screenpipe/pipes/video-export/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Export Video Clip\ndescription: \"Create a video of your recent screen activity\"\nicon: \"🎬\"\nfeatured: false\n---\n\nExport a video of my screen activity from the last 5 minutes.\n\nRead screenpipe skill first.\n\nUse the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.\n\nIf the export is large, suggest a lower fps or shorter time range.","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 clear picture. The pipes are markdown prompt templates in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe/pipes/","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but there's no code to actually load and run them —","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"has its own hardcoded prompts instead.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Here's what I'll implement:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/pipes.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— two new endpoints:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"GET /api/pipes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /api/pipes/{pipe_id}/run","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cli.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— a","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"command to run pipes from the terminal","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Let me build it:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check browser_urls signature","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/consumers/activity.py | grep \"def browser_urls\" -A 5","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":"def browser_urls(\n for_date: date | None = None,\n app_name: str | None = None,\n ts_from: str | None = None,\n ts_to: str | None = None,\n limit: int = 30,","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":"pipes.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipes.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"143 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"\"\"\"Dynamic pipe loader and runner.\"\"\"\nimport os\nimport re\nfrom datetime import date\nfrom pathlib import Path\nfrom typing import Any\n\n\ndef _parse_frontmatter(text: str) -> tuple[dict, str]:\n if not text.startswith(\"---\"):\n return {}, text\n try:\n end = text.index(\"---\", 3)\n except ValueError:\n return {}, text\n fm_text = text[3:end].strip()\n body = text[end + 3:].strip()\n meta: dict = {}\n for line in fm_text.splitlines():\n if \":\" in line:\n k, _, v = line.partition(\":\")\n meta[k.strip()] = v.strip().strip('\"')\n return meta, body\n\n\ndef load_pipes(pipes_dir: Path) -> list[dict]:\n if not pipes_dir.exists():\n return []\n pipes = []\n for pipe_dir in sorted(pipes_dir.iterdir()):\n if not pipe_dir.is_dir() or pipe_dir.name.startswith(\".\"):\n continue\n pipe_md = pipe_dir / \"pipe.md\"\n if not pipe_md.exists():\n continue\n text = pipe_md.read_text(encoding=\"utf-8\")\n meta, body = _parse_frontmatter(text)\n if meta.get(\"enabled\", \"true\").lower() == \"false\":\n continue\n body = re.sub(r\"Read screenpipe skill first\\.?\\n?\", \"\", body).strip()\n pipes.append({\n \"id\": pipe_dir.name,\n \"title\": meta.get(\"title\", pipe_dir.name),\n \"description\": meta.get(\"description\", \"\"),\n \"icon\": meta.get(\"icon\", \"\"),\n \"schedule\": meta.get(\"schedule\", \"manual\"),\n \"featured\": meta.get(\"featured\", \"false\").lower() == \"true\",\n \"prompt\": body,\n })\n return pipes\n\n\ndef _build_system(d: date, stats: dict) -> str:\n from consumers.activity import app_time, browser_urls, ui_event_summary\n from consumers.ocr import deduplicated_text\n from consumers.audio import formatted_transcript\n\n apps = app_time(d)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(d, limit=20)\n url_lines = \"\\n\".join(f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls)\n\n ui_rows = ui_event_summary(d)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(d, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(d)\n if len(audio) > 3000:\n audio = audio[:3000]\n\n return f\"\"\"You are analyzing screenpipe data — recordings of a person's computer activity.\n\n## App usage (minutes per app):\n{app_lines or '(no app data)'}\n\n## Browser URLs visited:\n{url_lines or '(no browser data)'}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_lines or '(no UI event data)'}\n\n## Screen content (sampled every 5 minutes):\n{ocr_lines or '(no screen data)'}\n\n## Audio / speech:\n{audio or '(no audio data)'}\n\nDate: {d}\nTotal frames recorded: {stats['total_frames']}\"\"\"\n\n\ndef run_pipe(\n pipe_id: str,\n for_date: date | None = None,\n api_key: str | None = None,\n pipes_dir: Path | None = None,\n) -> dict[str, Any]:\n import anthropic\n from consumers.activity import summary_stats\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\"title\": \"Error\", \"content\": \"ANTHROPIC_API_KEY not set.\", \"date\": str(d)}\n\n _pipes_dir = pipes_dir or Path(os.environ.get(\"PIPES_DIR\", \"/data/pipes\"))\n all_pipes = {p[\"id\"]: p for p in load_pipes(_pipes_dir)}\n\n if pipe_id not in all_pipes:\n return {\"title\": \"Error\", \"content\": f\"Pipe not found: {pipe_id}\", \"date\": str(d)}\n\n pipe = all_pipes[pipe_id]\n stats = summary_stats(d)\n\n if stats[\"total_frames\"] == 0:\n return {\"title\": pipe[\"title\"], \"content\": f\"No screen data found for {d}.\", \"date\": str(d)}\n\n system = _build_system(d, stats)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n system=system,\n messages=[{\"role\": \"user\", \"content\": pipe[\"prompt\"]}],\n )\n\n return {\n \"title\": pipe[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the API endpoints to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the pipe endpoints at the end of main.py, before the closing summary section:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 14 lines","depth":24,"on_screen":false,"role_description":"text"}]...
|
-5020969173427241853
|
-8187034928260855700
|
idle
|
accessibility
|
NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines...
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/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519237284_m1.jpg...
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Code
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Implement and run pipe l… — screenpipe [SSH: nas]
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl [URL_WITH_CREDENTIALS] sudo docker exec -it screenpipe-app python cli.py pipe day-recap --date 2026-04-20
Running pipe 'day-recap' for 2026-04-20...
Traceback (most recent call last):
File "/app/cli.py", line 245, in <module>
cli()
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1161, in __call__
return self.main(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1082, in main
rv = self.invoke(ctx)
^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1697, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1443, in invoke
return ctx.invoke(self.callback, **ctx.params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 788, in invoke
return __callback(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/app/cli.py", line 225, in pipe
result = run_pipe(pipe_id, target, pipes_dir=pipes_dir)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/app/consumers/pipes.py", line 130, in run_pipe
message = client.messages.create(
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_utils/_utils.py", line 275, in wrapper
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/resources/messages/messages.py", line 953, in create
return self._post(
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py", line 1336, in post
return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py", line 1013, in request
return self._request(
^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py", line 1117, in _request
raise self._make_status_error_from_response(err.response) from None
anthropic.AuthenticationError: Error code: 401 - {'type': 'error', 'error': {'type': 'authentication_error', 'message': 'invalid x-api-key'}, 'request_id': 'req_011CaSoR75WgV8fTcHTYJMDY'}
Adm1n@DXP4800PLUS-B5F8:/volume1/screenpipe/app$
Thinking
Thinking...
|
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#4 of archive.db\n/volume1/screenpipe/#recycle/Copy #5 of archive.db\n/volume1/screenpipe/#recycle/Copy #3 of db.sqlite\n/volume1/screenpipe/#recycle/Copy #4 of db.sqlite\n/volume1/screenpipe/#recycle/Copy #6 of archive.db\n/volume1/screenpipe/#recycle/test.txt\n/volume1/screenpipe/#recycle/Copy #7 of archive.db\n/volume1/screenpipe/#recycle/Copy #8 of archive.db\n/volume1/screenpipe/#recycle/archive.db-journal\n/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #5 of db.sqlite\n/volume1/screenpipe/pipes/.DS_Store\n/volume1/screenpipe/app/.env\n/volume1/screenpipe/app/cli.py\n/volume1/screenpipe/app/.DS_Store\n/volume1/screenpipe/app/db.py\n/volume1/screenpipe/app/docker-compose.yml\n/volume1/screenpipe/app/main.py\n/volume1/screenpipe/app/requirements.txt\n/volume1/screenpipe/app/Dockerfile\n/volume1/screenpipe/data/.DS_Store\n/volume1/screenpipe/.git/description\n/volume1/screenpipe/.git/HEAD\n/volume1/screenpipe/.git/index\n/volume1/screenpipe/.git/COMMIT_EDITMSG\n/volume1/screenpipe/#recycle/data/.DS_Store\n---\napp\napp_settings.json\narchive.db\ndata\ndb.sqlite\ndb.sqlite-shm\ndb.sqlite-wal\npipes\n#recycle\nscreenpipe.db\nscreenpipe_sync.sh","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check pipes directory and docker-compose","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml","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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\ncli.py\nconsumers\ndb.py\ndocker-compose.yml\nDockerfile\nmain.py\n__pycache__\nrequirements.txt\nstatic\nservices:\n screenpipe-app:\n build: .\n container_name: screenpipe-app\n restart: unless-stopped\n ports:\n - \"8766:8000\"\n volumes:\n - /volume1/screenpipe:/data\n env_file:\n - .env\n environment:\n TZ: Europe/Sofia\n DB_PATH: /data/db.sqlite\n\n sqlite-web-archive:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-archive\n restart: unless-stopped\n ports:\n - \"8767:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/archive.db\"]\n\n sqlite-web-live:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-live\n restart: unless-stopped\n ports:\n - \"8768:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/db.sqlite\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"requirements.txt","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"requirements.txt","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Inspect a pipe directory","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/","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":"pipe.md\npipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"List all pipes and their contents","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo \"=== $d ===\"; ls \"$d\"; 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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\n=== /volume1/screenpipe/pipes/ai-habits/ ===\npipe.md\n=== /volume1/screenpipe/pipes/day-recap/ ===\npipe.md\n=== /volume1/screenpipe/pipes/meeting-summary/ ===\npipe.md\n=== /volume1/screenpipe/pipes/standup-update/ ===\npipe.md\n=== /volume1/screenpipe/pipes/time-breakdown/ ===\npipe.md\n=== /volume1/screenpipe/pipes/video-export/ ===\npipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read pipe markdown files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo \"===\" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50","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":"---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.","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":"Read summary consumer","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py","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":"activity.py\naudio.py\nelements.py\n__init__.py\ninteractions.py\nocr.py\n__pycache__\nreport.py\nsummary.py\n\"\"\"AI summary generator using Claude.\"\"\"\nimport os\nfrom datetime import date\nfrom typing import Any\n\nfrom consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary\nfrom consumers.ocr import deduplicated_text\nfrom consumers.audio import formatted_transcript\n\n\nSUMMARY_TYPES = {\n \"day_recap\": {\n \"title\": \"Day Recap\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a concise day recap using EXACTLY this format:\n\n## Summary\nOne sentence: what I mainly worked on today.\n\n## Accomplishments\n- Top 3 things I finished, with approximate times\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things seen or heard, with timestamps\n\n## Unfinished Work\n- What to continue tomorrow\n\n## Patterns\n- Apps used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with:\n**Next step:** [most important thing to continue]\"\"\",\n },\n \"standup\": {\n \"title\": \"Standup Update\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a brief standup update:\n\n**Yesterday:** What I worked on (2-3 bullets)\n**Today:** What I plan to continue (1-2 bullets)\n**Blockers:** Any issues observed (or \"None\")\n\nKeep it under 150 words. Only report what's verifiable from the data.\"\"\",\n },\n \"focus_time\": {\n \"title\": \"Focus & Distraction Analysis\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\nAnalyze focus vs distraction patterns:\n\n## Deep Work Periods\n- When and how long were sustained focus sessions?\n- What was being worked on?\n\n## Distractions\n- Which apps/sites were used recreationally?\n- How much time was lost to context switching?\n\n## Recommendations\n- 2-3 concrete suggestions to improve focus tomorrow\n\nBe specific with times and app names.\"\"\",\n },\n}\n\n\ndef _build_context(for_date: date) -> dict[str, str]:\n apps = app_time(for_date)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(for_date, limit=20)\n url_lines = \"\\n\".join(\n f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls\n )\n\n ui_rows = ui_event_summary(for_date)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(for_date, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(for_date)\n\n return {\n \"app_time\": app_lines or \"(no app data)\",\n \"browser_urls\": url_lines or \"(no browser data)\",\n \"ui_events\": ui_lines or \"(no UI event data)\",\n \"ocr_text\": ocr_lines or \"(no screen data)\",\n \"audio\": audio[:3000] if len(audio) > 3000 else audio,\n }\n\n\ndef generate(\n summary_type: str = \"day_recap\",\n for_date: date | None = None,\n api_key: str | None = None,\n) -> dict[str, Any]:\n \"\"\"Generate an AI summary. Returns dict with 'title', 'content', 'date'.\"\"\"\n import anthropic\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\n \"title\": \"Error\",\n \"content\": \"ANTHROPIC_API_KEY not set. Add it to your .env file.\",\n \"date\": str(d),\n }\n\n spec = SUMMARY_TYPES.get(summary_type)\n if not spec:\n return {\"title\": \"Error\", \"content\": f\"Unknown summary type: {summary_type}\", \"date\": str(d)}\n\n stats = summary_stats(d)\n if stats[\"total_frames\"] == 0:\n return {\n \"title\": spec[\"title\"],\n \"content\": f\"No screen data found for {d}.\",\n \"date\": str(d),\n }\n\n ctx = _build_context(d)\n prompt = spec[\"prompt\"].format(**ctx)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": prompt}],\n )\n\n return {\n \"title\": spec[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","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":"Read all pipe.md files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"for f in /volume1/screenpipe/pipes/*/pipe.md; do echo \"=== $f ===\"; cat \"$f\"; 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":"=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: AI Habits\ndescription: \"How you use AI tools — patterns and insights\"\nicon: \"🤖\"\nfeatured: true\n---\n\nSearch my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## AI Tools Used\n- List each tool with approximate time spent (e.g. \"Claude: ~45min\")\n\n## What I Used Them For\n- For each tool: coding, writing, research, or brainstorming\n\n## Usage Patterns\n- Do I switch between tools? Use them in bursts or steadily?\n\n## Effectiveness\n- Which tool appeared alongside completed work vs. abandoned attempts\n\nIf no AI usage is found, say so clearly. End with: \"**Tip:** [one suggestion to use AI tools more effectively]\"\n\n=== /volume1/screenpipe/pipes/day-recap/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n\n=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.\n\n=== /volume1/screenpipe/pipes/standup-update/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Standup Update\ndescription: \"What you did, what's next, and any blockers\"\nicon: \"🏢\"\nfeatured: true\n---\n\nBased on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Yesterday\n- What I worked on (name specific projects, files, tools, PRs)\n\n## Today\n- What I will work on next (based on unfinished tasks and recent activity)\n\n## Blockers\n- Issues I hit — errors, slow builds, waiting on someone\n- If no blockers, write \"None\"\n\nKeep it under 150 words. Copy-paste ready for a team standup.\n\n=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Time Breakdown\ndescription: \"Where your time went — by app, project, and category\"\nicon: \"⏱\"\nfeatured: false\n---\n\nAnalyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.\n\nRead screenpipe skill first.\n\nUse this exact format with durations and percentages:\n\n## By Application\n- List each app with duration and percentage, sorted by time (e.g. \"VS Code: 2h 15min (28%)\")\n\n## By Category\n- Group into: coding, meetings, browsing, writing, communication, other\n- Show hours and percentage per category\n\n## By Project\n- Group related activities by project/topic. Name specific repos or tasks.\n\n## Productivity Score\n- Calculate: focused_work_hours / total_hours as a percentage\n- Focused = coding + writing. Unfocused = browsing + switching.\n\nEnd with: \"**Suggestion:** [one specific change to improve tomorrow's productivity]\"\n\n=== /volume1/screenpipe/pipes/video-export/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Export Video Clip\ndescription: \"Create a video of your recent screen activity\"\nicon: \"🎬\"\nfeatured: false\n---\n\nExport a video of my screen activity from the last 5 minutes.\n\nRead screenpipe skill first.\n\nUse the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.\n\nIf the export is large, suggest a lower fps or shorter time range.","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 clear picture. The pipes are markdown prompt templates in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe/pipes/","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but there's no code to actually load and run them —","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"has its own hardcoded prompts instead.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Here's what I'll implement:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/pipes.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— two new endpoints:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"GET /api/pipes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /api/pipes/{pipe_id}/run","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cli.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— a","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"command to run pipes from the terminal","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Let me build it:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check browser_urls signature","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/consumers/activity.py | grep \"def browser_urls\" -A 5","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":"def browser_urls(\n for_date: date | None = None,\n app_name: str | None = None,\n ts_from: str | None = None,\n ts_to: str | None = None,\n limit: int = 30,","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":"pipes.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipes.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"143 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"\"\"\"Dynamic pipe loader and runner.\"\"\"\nimport os\nimport re\nfrom datetime import date\nfrom pathlib import Path\nfrom typing import Any\n\n\ndef _parse_frontmatter(text: str) -> tuple[dict, str]:\n if not text.startswith(\"---\"):\n return {}, text\n try:\n end = text.index(\"---\", 3)\n except ValueError:\n return {}, text\n fm_text = text[3:end].strip()\n body = text[end + 3:].strip()\n meta: dict = {}\n for line in fm_text.splitlines():\n if \":\" in line:\n k, _, v = line.partition(\":\")\n meta[k.strip()] = v.strip().strip('\"')\n return meta, body\n\n\ndef load_pipes(pipes_dir: Path) -> list[dict]:\n if not pipes_dir.exists():\n return []\n pipes = []\n for pipe_dir in sorted(pipes_dir.iterdir()):\n if not pipe_dir.is_dir() or pipe_dir.name.startswith(\".\"):\n continue\n pipe_md = pipe_dir / \"pipe.md\"\n if not pipe_md.exists():\n continue\n text = pipe_md.read_text(encoding=\"utf-8\")\n meta, body = _parse_frontmatter(text)\n if meta.get(\"enabled\", \"true\").lower() == \"false\":\n continue\n body = re.sub(r\"Read screenpipe skill first\\.?\\n?\", \"\", body).strip()\n pipes.append({\n \"id\": pipe_dir.name,\n \"title\": meta.get(\"title\", pipe_dir.name),\n \"description\": meta.get(\"description\", \"\"),\n \"icon\": meta.get(\"icon\", \"\"),\n \"schedule\": meta.get(\"schedule\", \"manual\"),\n \"featured\": meta.get(\"featured\", \"false\").lower() == \"true\",\n \"prompt\": body,\n })\n return pipes\n\n\ndef _build_system(d: date, stats: dict) -> str:\n from consumers.activity import app_time, browser_urls, ui_event_summary\n from consumers.ocr import deduplicated_text\n from consumers.audio import formatted_transcript\n\n apps = app_time(d)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(d, limit=20)\n url_lines = \"\\n\".join(f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls)\n\n ui_rows = ui_event_summary(d)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(d, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(d)\n if len(audio) > 3000:\n audio = audio[:3000]\n\n return f\"\"\"You are analyzing screenpipe data — recordings of a person's computer activity.\n\n## App usage (minutes per app):\n{app_lines or '(no app data)'}\n\n## Browser URLs visited:\n{url_lines or '(no browser data)'}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_lines or '(no UI event data)'}\n\n## Screen content (sampled every 5 minutes):\n{ocr_lines or '(no screen data)'}\n\n## Audio / speech:\n{audio or '(no audio data)'}\n\nDate: {d}\nTotal frames recorded: {stats['total_frames']}\"\"\"\n\n\ndef run_pipe(\n pipe_id: str,\n for_date: date | None = None,\n api_key: str | None = None,\n pipes_dir: Path | None = None,\n) -> dict[str, Any]:\n import anthropic\n from consumers.activity import summary_stats\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\"title\": \"Error\", \"content\": \"ANTHROPIC_API_KEY not set.\", \"date\": str(d)}\n\n _pipes_dir = pipes_dir or Path(os.environ.get(\"PIPES_DIR\", \"/data/pipes\"))\n all_pipes = {p[\"id\"]: p for p in load_pipes(_pipes_dir)}\n\n if pipe_id not in all_pipes:\n return {\"title\": \"Error\", \"content\": f\"Pipe not found: {pipe_id}\", \"date\": str(d)}\n\n pipe = all_pipes[pipe_id]\n stats = summary_stats(d)\n\n if stats[\"total_frames\"] == 0:\n return {\"title\": pipe[\"title\"], \"content\": f\"No screen data found for {d}.\", \"date\": str(d)}\n\n system = _build_system(d, stats)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n system=system,\n messages=[{\"role\": \"user\", \"content\": pipe[\"prompt\"]}],\n )\n\n return {\n \"title\": pipe[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the API endpoints to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the pipe endpoints at the end of main.py, before the closing summary section:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 14 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the CLI command to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 40 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Done. Here's how to run pipes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to run pipes","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to run pipes","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via Docker (inside the running container):","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"docker exec -it screenpipe-app python cli.py pipe --list\ndocker exec -it screenpipe-app python cli.py pipe day-recap\ndocker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via the API","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(once the container is running on port 8766):","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# List pipes\ncurl http://localhost:8766/api/pipes\n\n# Run a pipe\ncurl -X POST \"http://localhost:8766/api/pipes/day-recap/run\"\ncurl -X POST \"http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rebuild and restart","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to pick up the changes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"cd /volume1/screenpipe/app\ndocker compose up --build -d","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"How it works:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Each","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The \"Read screenpipe skill first\" line is stripped automatically.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The pipes directory inside Docker is","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data/pipes","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(since","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"→","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). You can override it with a","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"PIPES_DIR","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"env var if needed.","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":"AXButton","text":"pipe.md","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"where to place api key and can I use different keys","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":"Read .env file","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/.env","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":"ANTHROPIC_API_KEY=your_key_here","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Where to place the key:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"app/.env","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"app/.env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— replace","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"your_key_here","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with your actual key:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"ANTHROPIC_API_KEY=sk-ant-...","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"That file is loaded by","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"load_dotenv()","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"at startup and is excluded from git via","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".gitignore","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Can you use different keys per pipe?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Not currently — all pipes share the one key from","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". But you can add per-pipe key support by adding an","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"api_key","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"field to the pipe's frontmatter:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"---\ntitle: Meeting Summary\napi_key_env: ANTHROPIC_KEY_MEETINGS\n---","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Then in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/pipes.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/pipes.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", read it in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"_parse_frontmatter","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and pass it through","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"run_pipe","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". Want me to add that?","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":"AXButton","text":"pipe.md","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"can I use mistral or other llm? or is is build for antrophic only","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":"Currently it's Anthropic-only — the code calls the","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"anthropic","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SDK directly in both","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/pipes.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/pipes.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/summary.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Adding other providers is straightforward since Mistral, Ollama, OpenRouter, Groq, and most modern LLMs expose an OpenAI-compatible API. The cleanest approach: add the","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"openai","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"package and let you configure the provider via","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# Anthropic (default)\nANTHROPIC_API_KEY=sk-ant-...\n\n# OR: any OpenAI-compatible provider\nLLM_PROVIDER=openai-compatible\nLLM_BASE_URL=https://api.mistral.ai/v1\nLLM_API_KEY=your-mistral-key\nLLM_MODEL=mistral-small-latest","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"This would cover Mistral, Ollama (","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"http://localhost:11434/v1","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"), OpenRouter, Groq, etc. with one code path.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Want me to implement that? It's a small change — a","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"_call_llm(system, user_prompt)","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"helper in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipes.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"that branches on","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"LLM_PROVIDER","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", and","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"openai","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"added to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"requirements.txt","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","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":"lets test it with anthropic first, how to run pipe","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":"Check if container is running","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cd /volume1/screenpipe/app && docker compose ps 2>/dev/null || docker ps --filter name=screenpipe","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\npermission denied while trying to connect to the Docker daemon socket at unix:///var/run/docker.sock: Get \"http://%2Fvar%2Frun%2Fdocker.sock/v1.45/containers/json?filters=%7B%22name%22%3A%7B%22screenpipe%22%3Atrue%7D%7D\": dial unix /var/run/docker.sock: connect: permission denied","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"I don't have Docker socket access, so you'll need to run these yourself. Here are your options:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option A — via Docker (if container is already running):","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# List available pipes\ndocker exec -it screenpipe-app python cli.py pipe --list\n\n# Run a specific pipe\ndocker exec -it screenpipe-app python cli.py pipe day-recap","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option B — rebuild first (since we added new files), then run:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"cd /volume1/screenpipe/app\ndocker compose up --build -d\ndocker exec -it screenpipe-app python cli.py pipe day-recap","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option C — via the API","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(if container is up on port 8766):","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# List pipes\ncurl http://localhost:8766/api/pipes\n\n# Run a pipe\ncurl -X POST http://localhost:8766/api/pipes/day-recap/run","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"day-recap","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"or","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"standup-update","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipes are the best ones to test first since they use all data sources. Which option works for you?","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":"how ot run for specifiday","depth":25,"on_screen":true,"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":"Docker exec:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"docker exec -it screenpipe-app python cli.py pipe day-recap --date 2026-04-25\n# or shortcuts:\ndocker exec -it screenpipe-app python cli.py pipe day-recap --date yesterday\ndocker exec -it screenpipe-app python cli.py pipe day-recap --date today","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"API:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"on_screen":true,"help_text":"Copy code","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"curl -X POST \"http://localhost:8766/api/pipes/day-recap/run?d=2026-04-25\"","depth":25,"on_screen":true,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Adm1n@DXP4800PLUS-B5F8:/volume1/screenpipe/app$ sudo docker exec -it screenpipe-app python cli.py pipe day-recap --date 2026-04-20\nRunning pipe 'day-recap' for 2026-04-20...\nTraceback (most recent call last):\n File \"/app/cli.py\", line 245, in <module>\n cli()\n File \"/usr/local/lib/python3.12/site-packages/click/core.py\", line 1161, in __call__\n return self.main(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/click/core.py\", line 1082, in main\n rv = self.invoke(ctx)\n ^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/click/core.py\", line 1697, in invoke\n return _process_result(sub_ctx.command.invoke(sub_ctx))\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/click/core.py\", line 1443, in invoke\n return ctx.invoke(self.callback, **ctx.params)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/click/core.py\", line 788, in invoke\n return __callback(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/app/cli.py\", line 225, in pipe\n result = run_pipe(pipe_id, target, pipes_dir=pipes_dir)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/app/consumers/pipes.py\", line 130, in run_pipe\n message = client.messages.create(\n ^^^^^^^^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/anthropic/_utils/_utils.py\", line 275, in wrapper\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/anthropic/resources/messages/messages.py\", line 953, in create\n return self._post(\n ^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py\", line 1336, in post\n return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py\", line 1013, in request\n return self._request(\n ^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py\", line 1117, in _request\n raise self._make_status_error_from_response(err.response) from None\nanthropic.AuthenticationError: Error code: 401 - {'type': 'error', 'error': {'type': 'authentication_error', 'message': 'invalid x-api-key'}, 'request_id': 'req_011CaSoR75WgV8fTcHTYJMDY'}\nAdm1n@DXP4800PLUS-B5F8:/volume1/screenpipe/app$","depth":26,"on_screen":true,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":true,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":true,"role_description":"text"}]...
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2158626665587694396
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-8196324427125781304
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idle
|
accessibility
|
NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl [URL_WITH_CREDENTIALS] sudo docker exec -it screenpipe-app python cli.py pipe day-recap --date 2026-04-20
Running pipe 'day-recap' for 2026-04-20...
Traceback (most recent call last):
File "/app/cli.py", line 245, in <module>
cli()
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1161, in __call__
return self.main(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1082, in main
rv = self.invoke(ctx)
^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1697, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1443, in invoke
return ctx.invoke(self.callback, **ctx.params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 788, in invoke
return __callback(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/app/cli.py", line 225, in pipe
result = run_pipe(pipe_id, target, pipes_dir=pipes_dir)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/app/consumers/pipes.py", line 130, in run_pipe
message = client.messages.create(
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_utils/_utils.py", line 275, in wrapper
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/resources/messages/messages.py", line 953, in create
return self._post(
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py", line 1336, in post
return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py", line 1013, in request
return self._request(
^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py", line 1117, in _request
raise self._make_status_error_from_response(err.response) from None
anthropic.AuthenticationError: Error code: 401 - {'type': 'error', 'error': {'type': 'authentication_error', 'message': 'invalid x-api-key'}, 'request_id': 'req_011CaSoR75WgV8fTcHTYJMDY'}
Adm1n@DXP4800PLUS-B5F8:/volume1/screenpipe/app$
Thinking
Thinking...
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2026-05-11T17:07:05.045986+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519225045_m2.jpg...
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Implement and run pipe l… — screenpipe [SSH: nas]
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U...
|
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idle
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accessibility
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NULL
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U...
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21062
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920
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2026-05-11T17:06:46.927104+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519206927_m1.jpg...
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Code
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Implement and run pipe l… — screenpipe [SSH: nas]
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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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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST "http://localhost:8766/api/pipes/day-recap/run"
curl -X POST "http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25"
Rebuild and restart
to pick up the changes:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
How it works:
Each
pipe.md
file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The "Read screenpipe skill first" line is stripped automatically.
The pipes directory inside Docker is
/data/pipes
(since
/volume1/screenpipe
→
/data
). You can override it with a
PIPES_DIR
env var if needed.
Message actions
pipe.md
pipe.md
where to place api key and can I use different keys
Thinking
Thinking
Bash
Read .env file
IN
cat /volume1/screenpipe/app/.env
Copy code to clipboard
OUT
[ENV_SECRET]
Where to place the key:
app/.env
app/.env
— replace
your_key_here
with your actual key:
Copy code to clipboard
[ENV_SECRET]
That file is loaded by
load_dotenv()
at startup and is excluded from git via
.gitignore
.
Can you use different keys per pipe?
Not currently — all pipes share the one key from
.env
. But you can add per-pipe key support by adding an
api_key
field to the pipe's frontmatter:
Copy code to clipboard
---
title: Meeting Summary
api_key_env: ANTHROPIC_KEY_MEETINGS
---
Then in
consumers/pipes.py
consumers/pipes.py
, read it in
_parse_frontmatter
and pass it through
run_pipe
. Want me to add that?
Message actions
pipe.md
pipe.md
can I use mistral or other llm? or is is build for antrophic only
Thinking
Thinking
Currently it's Anthropic-only — the code calls the
anthropic
SDK directly in both
consumers/pipes.py
consumers/pipes.py
and
consumers/summary.py
consumers/summary.py
.
Adding other providers is straightforward since Mistral, Ollama, OpenRouter, Groq, and most modern LLMs expose an OpenAI-compatible API. The cleanest approach: add the
openai
package and let you configure the provider via
.env
:
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# Anthropic (default)
[ENV_SECRET]
# OR: any OpenAI-compatible provider
LLM_PROVIDER=openai-compatible
LLM_BASE_URL=https://api.mistral.ai/v1
[ENV_SECRET]
LLM_MODEL=mistral-small-latest
This would cover Mistral, Ollama (
http://localhost:11434/v1
), OpenRouter, Groq, etc. with one code path.
Want me to implement that? It's a small change — a
_call_llm(system, user_prompt)
helper in
pipes.py
that branches on
LLM_PROVIDER
, and
openai
added to
requirements.txt
.
Message actions
lets test it with anthropic first, how to run pipe
Thinking
Thinking
Bash
Check if container is running
IN
cd /volume1/screenpipe/app && docker compose ps 2>/dev/null || docker ps --filter name=screenpipe
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OUT
Exit code 1
permission denied while trying to connect to the Docker daemon socket at unix:///var/run/docker.sock: Get "http://%2Fvar%2Frun%2Fdocker.sock/v1.45/containers/json?filters=%7B%22name%22%3A%7B%22screenpipe%22%3Atrue%7D%7D": dial unix /var/run/docker.sock: connect: permission denied
I don't have Docker socket access, so you'll need to run these yourself. Here are your options:
Option A — via Docker (if container is already running):
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# List available pipes
docker exec -it screenpipe-app python cli.py pipe --list
# Run a specific pipe
docker exec -it screenpipe-app python cli.py pipe day-recap
Option B — rebuild first (since we added new files), then run:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
docker exec -it screenpipe-app python cli.py pipe day-recap
Option C — via the API
(if container is up on port 8766):
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# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST http://localhost:8766/api/pipes/day-recap/run
The
day-recap
or
standup-update
pipes are the best ones to test first since they use all data sources. Which option works for you?
Message actions
how ot run for specifiday
Thinking
Thinking
Docker exec:
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe day-recap --date 2026-04-25
# or shortcuts:
docker exec -it screenpipe-app python cli.py pipe day-recap --date yesterday
docker exec -it screenpipe-app python cli.py pipe day-recap --date today
API:
Copy code to clipboard...
|
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db.sqlite\n/volume1/screenpipe/pipes/.DS_Store\n/volume1/screenpipe/app/.env\n/volume1/screenpipe/app/cli.py\n/volume1/screenpipe/app/.DS_Store\n/volume1/screenpipe/app/db.py\n/volume1/screenpipe/app/docker-compose.yml\n/volume1/screenpipe/app/main.py\n/volume1/screenpipe/app/requirements.txt\n/volume1/screenpipe/app/Dockerfile\n/volume1/screenpipe/data/.DS_Store\n/volume1/screenpipe/.git/description\n/volume1/screenpipe/.git/HEAD\n/volume1/screenpipe/.git/index\n/volume1/screenpipe/.git/COMMIT_EDITMSG\n/volume1/screenpipe/#recycle/data/.DS_Store\n---\napp\napp_settings.json\narchive.db\ndata\ndb.sqlite\ndb.sqlite-shm\ndb.sqlite-wal\npipes\n#recycle\nscreenpipe.db\nscreenpipe_sync.sh","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check pipes directory and docker-compose","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml","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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\ncli.py\nconsumers\ndb.py\ndocker-compose.yml\nDockerfile\nmain.py\n__pycache__\nrequirements.txt\nstatic\nservices:\n screenpipe-app:\n build: .\n container_name: screenpipe-app\n restart: unless-stopped\n ports:\n - \"8766:8000\"\n volumes:\n - /volume1/screenpipe:/data\n env_file:\n - .env\n environment:\n TZ: Europe/Sofia\n DB_PATH: /data/db.sqlite\n\n sqlite-web-archive:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-archive\n restart: unless-stopped\n ports:\n - \"8767:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/archive.db\"]\n\n sqlite-web-live:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-live\n restart: unless-stopped\n ports:\n - \"8768:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/db.sqlite\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"requirements.txt","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"requirements.txt","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Inspect a pipe directory","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/","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":"pipe.md\npipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"List all pipes and their contents","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo \"=== $d ===\"; ls \"$d\"; 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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\n=== /volume1/screenpipe/pipes/ai-habits/ ===\npipe.md\n=== /volume1/screenpipe/pipes/day-recap/ ===\npipe.md\n=== /volume1/screenpipe/pipes/meeting-summary/ ===\npipe.md\n=== /volume1/screenpipe/pipes/standup-update/ ===\npipe.md\n=== /volume1/screenpipe/pipes/time-breakdown/ ===\npipe.md\n=== /volume1/screenpipe/pipes/video-export/ ===\npipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read pipe markdown files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo \"===\" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50","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":"---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.","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":"Read summary consumer","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py","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":"activity.py\naudio.py\nelements.py\n__init__.py\ninteractions.py\nocr.py\n__pycache__\nreport.py\nsummary.py\n\"\"\"AI summary generator using Claude.\"\"\"\nimport os\nfrom datetime import date\nfrom typing import Any\n\nfrom consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary\nfrom consumers.ocr import deduplicated_text\nfrom consumers.audio import formatted_transcript\n\n\nSUMMARY_TYPES = {\n \"day_recap\": {\n \"title\": \"Day Recap\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a concise day recap using EXACTLY this format:\n\n## Summary\nOne sentence: what I mainly worked on today.\n\n## Accomplishments\n- Top 3 things I finished, with approximate times\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things seen or heard, with timestamps\n\n## Unfinished Work\n- What to continue tomorrow\n\n## Patterns\n- Apps used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with:\n**Next step:** [most important thing to continue]\"\"\",\n },\n \"standup\": {\n \"title\": \"Standup Update\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a brief standup update:\n\n**Yesterday:** What I worked on (2-3 bullets)\n**Today:** What I plan to continue (1-2 bullets)\n**Blockers:** Any issues observed (or \"None\")\n\nKeep it under 150 words. Only report what's verifiable from the data.\"\"\",\n },\n \"focus_time\": {\n \"title\": \"Focus & Distraction Analysis\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\nAnalyze focus vs distraction patterns:\n\n## Deep Work Periods\n- When and how long were sustained focus sessions?\n- What was being worked on?\n\n## Distractions\n- Which apps/sites were used recreationally?\n- How much time was lost to context switching?\n\n## Recommendations\n- 2-3 concrete suggestions to improve focus tomorrow\n\nBe specific with times and app names.\"\"\",\n },\n}\n\n\ndef _build_context(for_date: date) -> dict[str, str]:\n apps = app_time(for_date)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(for_date, limit=20)\n url_lines = \"\\n\".join(\n f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls\n )\n\n ui_rows = ui_event_summary(for_date)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(for_date, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(for_date)\n\n return {\n \"app_time\": app_lines or \"(no app data)\",\n \"browser_urls\": url_lines or \"(no browser data)\",\n \"ui_events\": ui_lines or \"(no UI event data)\",\n \"ocr_text\": ocr_lines or \"(no screen data)\",\n \"audio\": audio[:3000] if len(audio) > 3000 else audio,\n }\n\n\ndef generate(\n summary_type: str = \"day_recap\",\n for_date: date | None = None,\n api_key: str | None = None,\n) -> dict[str, Any]:\n \"\"\"Generate an AI summary. Returns dict with 'title', 'content', 'date'.\"\"\"\n import anthropic\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\n \"title\": \"Error\",\n \"content\": \"ANTHROPIC_API_KEY not set. Add it to your .env file.\",\n \"date\": str(d),\n }\n\n spec = SUMMARY_TYPES.get(summary_type)\n if not spec:\n return {\"title\": \"Error\", \"content\": f\"Unknown summary type: {summary_type}\", \"date\": str(d)}\n\n stats = summary_stats(d)\n if stats[\"total_frames\"] == 0:\n return {\n \"title\": spec[\"title\"],\n \"content\": f\"No screen data found for {d}.\",\n \"date\": str(d),\n }\n\n ctx = _build_context(d)\n prompt = spec[\"prompt\"].format(**ctx)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": prompt}],\n )\n\n return {\n \"title\": spec[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","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":"Read all pipe.md files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"for f in /volume1/screenpipe/pipes/*/pipe.md; do echo \"=== $f ===\"; cat \"$f\"; 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":"=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: AI Habits\ndescription: \"How you use AI tools — patterns and insights\"\nicon: \"🤖\"\nfeatured: true\n---\n\nSearch my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## AI Tools Used\n- List each tool with approximate time spent (e.g. \"Claude: ~45min\")\n\n## What I Used Them For\n- For each tool: coding, writing, research, or brainstorming\n\n## Usage Patterns\n- Do I switch between tools? Use them in bursts or steadily?\n\n## Effectiveness\n- Which tool appeared alongside completed work vs. abandoned attempts\n\nIf no AI usage is found, say so clearly. End with: \"**Tip:** [one suggestion to use AI tools more effectively]\"\n\n=== /volume1/screenpipe/pipes/day-recap/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n\n=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.\n\n=== /volume1/screenpipe/pipes/standup-update/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Standup Update\ndescription: \"What you did, what's next, and any blockers\"\nicon: \"🏢\"\nfeatured: true\n---\n\nBased on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Yesterday\n- What I worked on (name specific projects, files, tools, PRs)\n\n## Today\n- What I will work on next (based on unfinished tasks and recent activity)\n\n## Blockers\n- Issues I hit — errors, slow builds, waiting on someone\n- If no blockers, write \"None\"\n\nKeep it under 150 words. Copy-paste ready for a team standup.\n\n=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Time Breakdown\ndescription: \"Where your time went — by app, project, and category\"\nicon: \"⏱\"\nfeatured: false\n---\n\nAnalyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.\n\nRead screenpipe skill first.\n\nUse this exact format with durations and percentages:\n\n## By Application\n- List each app with duration and percentage, sorted by time (e.g. \"VS Code: 2h 15min (28%)\")\n\n## By Category\n- Group into: coding, meetings, browsing, writing, communication, other\n- Show hours and percentage per category\n\n## By Project\n- Group related activities by project/topic. Name specific repos or tasks.\n\n## Productivity Score\n- Calculate: focused_work_hours / total_hours as a percentage\n- Focused = coding + writing. Unfocused = browsing + switching.\n\nEnd with: \"**Suggestion:** [one specific change to improve tomorrow's productivity]\"\n\n=== /volume1/screenpipe/pipes/video-export/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Export Video Clip\ndescription: \"Create a video of your recent screen activity\"\nicon: \"🎬\"\nfeatured: false\n---\n\nExport a video of my screen activity from the last 5 minutes.\n\nRead screenpipe skill first.\n\nUse the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.\n\nIf the export is large, suggest a lower fps or shorter time range.","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 clear picture. The pipes are markdown prompt templates in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe/pipes/","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but there's no code to actually load and run them —","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"has its own hardcoded prompts instead.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Here's what I'll implement:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/pipes.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— two new endpoints:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"GET /api/pipes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /api/pipes/{pipe_id}/run","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cli.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— a","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"command to run pipes from the terminal","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Let me build it:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check browser_urls signature","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/consumers/activity.py | grep \"def browser_urls\" -A 5","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":"def browser_urls(\n for_date: date | None = None,\n app_name: str | None = None,\n ts_from: str | None = None,\n ts_to: str | None = None,\n limit: int = 30,","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":"pipes.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipes.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"143 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"\"\"\"Dynamic pipe loader and runner.\"\"\"\nimport os\nimport re\nfrom datetime import date\nfrom pathlib import Path\nfrom typing import Any\n\n\ndef _parse_frontmatter(text: str) -> tuple[dict, str]:\n if not text.startswith(\"---\"):\n return {}, text\n try:\n end = text.index(\"---\", 3)\n except ValueError:\n return {}, text\n fm_text = text[3:end].strip()\n body = text[end + 3:].strip()\n meta: dict = {}\n for line in fm_text.splitlines():\n if \":\" in line:\n k, _, v = line.partition(\":\")\n meta[k.strip()] = v.strip().strip('\"')\n return meta, body\n\n\ndef load_pipes(pipes_dir: Path) -> list[dict]:\n if not pipes_dir.exists():\n return []\n pipes = []\n for pipe_dir in sorted(pipes_dir.iterdir()):\n if not pipe_dir.is_dir() or pipe_dir.name.startswith(\".\"):\n continue\n pipe_md = pipe_dir / \"pipe.md\"\n if not pipe_md.exists():\n continue\n text = pipe_md.read_text(encoding=\"utf-8\")\n meta, body = _parse_frontmatter(text)\n if meta.get(\"enabled\", \"true\").lower() == \"false\":\n continue\n body = re.sub(r\"Read screenpipe skill first\\.?\\n?\", \"\", body).strip()\n pipes.append({\n \"id\": pipe_dir.name,\n \"title\": meta.get(\"title\", pipe_dir.name),\n \"description\": meta.get(\"description\", \"\"),\n \"icon\": meta.get(\"icon\", \"\"),\n \"schedule\": meta.get(\"schedule\", \"manual\"),\n \"featured\": meta.get(\"featured\", \"false\").lower() == \"true\",\n \"prompt\": body,\n })\n return pipes\n\n\ndef _build_system(d: date, stats: dict) -> str:\n from consumers.activity import app_time, browser_urls, ui_event_summary\n from consumers.ocr import deduplicated_text\n from consumers.audio import formatted_transcript\n\n apps = app_time(d)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(d, limit=20)\n url_lines = \"\\n\".join(f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls)\n\n ui_rows = ui_event_summary(d)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(d, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(d)\n if len(audio) > 3000:\n audio = audio[:3000]\n\n return f\"\"\"You are analyzing screenpipe data — recordings of a person's computer activity.\n\n## App usage (minutes per app):\n{app_lines or '(no app data)'}\n\n## Browser URLs visited:\n{url_lines or '(no browser data)'}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_lines or '(no UI event data)'}\n\n## Screen content (sampled every 5 minutes):\n{ocr_lines or '(no screen data)'}\n\n## Audio / speech:\n{audio or '(no audio data)'}\n\nDate: {d}\nTotal frames recorded: {stats['total_frames']}\"\"\"\n\n\ndef run_pipe(\n pipe_id: str,\n for_date: date | None = None,\n api_key: str | None = None,\n pipes_dir: Path | None = None,\n) -> dict[str, Any]:\n import anthropic\n from consumers.activity import summary_stats\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\"title\": \"Error\", \"content\": \"ANTHROPIC_API_KEY not set.\", \"date\": str(d)}\n\n _pipes_dir = pipes_dir or Path(os.environ.get(\"PIPES_DIR\", \"/data/pipes\"))\n all_pipes = {p[\"id\"]: p for p in load_pipes(_pipes_dir)}\n\n if pipe_id not in all_pipes:\n return {\"title\": \"Error\", \"content\": f\"Pipe not found: {pipe_id}\", \"date\": str(d)}\n\n pipe = all_pipes[pipe_id]\n stats = summary_stats(d)\n\n if stats[\"total_frames\"] == 0:\n return {\"title\": pipe[\"title\"], \"content\": f\"No screen data found for {d}.\", \"date\": str(d)}\n\n system = _build_system(d, stats)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n system=system,\n messages=[{\"role\": \"user\", \"content\": pipe[\"prompt\"]}],\n )\n\n return {\n \"title\": pipe[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the API endpoints to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the pipe endpoints at the end of main.py, before the closing summary section:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 14 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the CLI command to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 40 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Done. Here's how to run pipes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to run pipes","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to run pipes","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via Docker (inside the running container):","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"docker exec -it screenpipe-app python cli.py pipe --list\ndocker exec -it screenpipe-app python cli.py pipe day-recap\ndocker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via the API","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(once the container is running on port 8766):","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# List pipes\ncurl http://localhost:8766/api/pipes\n\n# Run a pipe\ncurl -X POST \"http://localhost:8766/api/pipes/day-recap/run\"\ncurl -X POST \"http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rebuild and restart","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to pick up the changes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"cd /volume1/screenpipe/app\ndocker compose up --build -d","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"How it works:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Each","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The \"Read screenpipe skill first\" line is stripped automatically.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The pipes directory inside Docker is","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data/pipes","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(since","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"→","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). You can override it with a","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"PIPES_DIR","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"env var if needed.","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":"AXButton","text":"pipe.md","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"where to place api key and can I use different keys","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":"Read .env file","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/.env","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":"ANTHROPIC_API_KEY=your_key_here","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Where to place the key:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"app/.env","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"app/.env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— replace","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"your_key_here","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with your actual key:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"ANTHROPIC_API_KEY=sk-ant-...","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"That file is loaded by","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"load_dotenv()","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"at startup and is excluded from git via","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".gitignore","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Can you use different keys per pipe?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Not currently — all pipes share the one key from","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". But you can add per-pipe key support by adding an","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"api_key","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"field to the pipe's frontmatter:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"---\ntitle: Meeting Summary\napi_key_env: ANTHROPIC_KEY_MEETINGS\n---","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Then in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/pipes.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/pipes.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", read it in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"_parse_frontmatter","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and pass it through","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"run_pipe","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". Want me to add that?","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":"AXButton","text":"pipe.md","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"can I use mistral or other llm? or is is build for antrophic only","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":"Currently it's Anthropic-only — the code calls the","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"anthropic","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SDK directly in both","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/pipes.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/pipes.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/summary.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Adding other providers is straightforward since Mistral, Ollama, OpenRouter, Groq, and most modern LLMs expose an OpenAI-compatible API. The cleanest approach: add the","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"openai","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"package and let you configure the provider via","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# Anthropic (default)\nANTHROPIC_API_KEY=sk-ant-...\n\n# OR: any OpenAI-compatible provider\nLLM_PROVIDER=openai-compatible\nLLM_BASE_URL=https://api.mistral.ai/v1\nLLM_API_KEY=your-mistral-key\nLLM_MODEL=mistral-small-latest","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"This would cover Mistral, Ollama (","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"http://localhost:11434/v1","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"), OpenRouter, Groq, etc. with one code path.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Want me to implement that? It's a small change — a","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"_call_llm(system, user_prompt)","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"helper in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipes.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"that branches on","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"LLM_PROVIDER","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", and","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"openai","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"added to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"requirements.txt","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","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":"lets test it with anthropic first, how to run pipe","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":"Check if container is running","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cd /volume1/screenpipe/app && docker compose ps 2>/dev/null || docker ps --filter name=screenpipe","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\npermission denied while trying to connect to the Docker daemon socket at unix:///var/run/docker.sock: Get \"http://%2Fvar%2Frun%2Fdocker.sock/v1.45/containers/json?filters=%7B%22name%22%3A%7B%22screenpipe%22%3Atrue%7D%7D\": dial unix /var/run/docker.sock: connect: permission denied","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"I don't have Docker socket access, so you'll need to run these yourself. Here are your options:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option A — via Docker (if container is already running):","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# List available pipes\ndocker exec -it screenpipe-app python cli.py pipe --list\n\n# Run a specific pipe\ndocker exec -it screenpipe-app python cli.py pipe day-recap","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option B — rebuild first (since we added new files), then run:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"cd /volume1/screenpipe/app\ndocker compose up --build -d\ndocker exec -it screenpipe-app python cli.py pipe day-recap","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option C — via the API","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(if container is up on port 8766):","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# List pipes\ncurl http://localhost:8766/api/pipes\n\n# Run a pipe\ncurl -X POST http://localhost:8766/api/pipes/day-recap/run","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"day-recap","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"or","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"standup-update","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipes are the best ones to test first since they use all data sources. Which option works for you?","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":"how ot run for specifiday","depth":25,"on_screen":true,"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":"Docker exec:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"docker exec -it screenpipe-app python cli.py pipe day-recap --date 2026-04-25\n# or shortcuts:\ndocker exec -it screenpipe-app python cli.py pipe day-recap --date yesterday\ndocker exec -it screenpipe-app python cli.py pipe day-recap --date today","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"API:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"on_screen":true,"help_text":"Copy code","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false}]...
|
-4882221530188933818
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-8772785179160752952
|
idle
|
accessibility
|
NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST "http://localhost:8766/api/pipes/day-recap/run"
curl -X POST "http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25"
Rebuild and restart
to pick up the changes:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
How it works:
Each
pipe.md
file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The "Read screenpipe skill first" line is stripped automatically.
The pipes directory inside Docker is
/data/pipes
(since
/volume1/screenpipe
→
/data
). You can override it with a
PIPES_DIR
env var if needed.
Message actions
pipe.md
pipe.md
where to place api key and can I use different keys
Thinking
Thinking
Bash
Read .env file
IN
cat /volume1/screenpipe/app/.env
Copy code to clipboard
OUT
[ENV_SECRET]
Where to place the key:
app/.env
app/.env
— replace
your_key_here
with your actual key:
Copy code to clipboard
[ENV_SECRET]
That file is loaded by
load_dotenv()
at startup and is excluded from git via
.gitignore
.
Can you use different keys per pipe?
Not currently — all pipes share the one key from
.env
. But you can add per-pipe key support by adding an
api_key
field to the pipe's frontmatter:
Copy code to clipboard
---
title: Meeting Summary
api_key_env: ANTHROPIC_KEY_MEETINGS
---
Then in
consumers/pipes.py
consumers/pipes.py
, read it in
_parse_frontmatter
and pass it through
run_pipe
. Want me to add that?
Message actions
pipe.md
pipe.md
can I use mistral or other llm? or is is build for antrophic only
Thinking
Thinking
Currently it's Anthropic-only — the code calls the
anthropic
SDK directly in both
consumers/pipes.py
consumers/pipes.py
and
consumers/summary.py
consumers/summary.py
.
Adding other providers is straightforward since Mistral, Ollama, OpenRouter, Groq, and most modern LLMs expose an OpenAI-compatible API. The cleanest approach: add the
openai
package and let you configure the provider via
.env
:
Copy code to clipboard
# Anthropic (default)
[ENV_SECRET]
# OR: any OpenAI-compatible provider
LLM_PROVIDER=openai-compatible
LLM_BASE_URL=https://api.mistral.ai/v1
[ENV_SECRET]
LLM_MODEL=mistral-small-latest
This would cover Mistral, Ollama (
http://localhost:11434/v1
), OpenRouter, Groq, etc. with one code path.
Want me to implement that? It's a small change — a
_call_llm(system, user_prompt)
helper in
pipes.py
that branches on
LLM_PROVIDER
, and
openai
added to
requirements.txt
.
Message actions
lets test it with anthropic first, how to run pipe
Thinking
Thinking
Bash
Check if container is running
IN
cd /volume1/screenpipe/app && docker compose ps 2>/dev/null || docker ps --filter name=screenpipe
Copy code to clipboard
OUT
Exit code 1
permission denied while trying to connect to the Docker daemon socket at unix:///var/run/docker.sock: Get "http://%2Fvar%2Frun%2Fdocker.sock/v1.45/containers/json?filters=%7B%22name%22%3A%7B%22screenpipe%22%3Atrue%7D%7D": dial unix /var/run/docker.sock: connect: permission denied
I don't have Docker socket access, so you'll need to run these yourself. Here are your options:
Option A — via Docker (if container is already running):
Copy code to clipboard
# List available pipes
docker exec -it screenpipe-app python cli.py pipe --list
# Run a specific pipe
docker exec -it screenpipe-app python cli.py pipe day-recap
Option B — rebuild first (since we added new files), then run:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
docker exec -it screenpipe-app python cli.py pipe day-recap
Option C — via the API
(if container is up on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST http://localhost:8766/api/pipes/day-recap/run
The
day-recap
or
standup-update
pipes are the best ones to test first since they use all data sources. Which option works for you?
Message actions
how ot run for specifiday
Thinking
Thinking
Docker exec:
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe day-recap --date 2026-04-25
# or shortcuts:
docker exec -it screenpipe-app python cli.py pipe day-recap --date yesterday
docker exec -it screenpipe-app python cli.py pipe day-recap --date today
API:
Copy code to clipboard...
|
NULL
|
NULL
|
NULL
|
NULL
|
|
21061
|
921
|
1
|
2026-05-11T17:06:34.547460+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519194547_m2.jpg...
|
Code
|
Implement and run pipe l… — screenpipe [SSH: nas]
|
True
|
NULL
|
monitor_2
|
NULL
|
NULL
|
NULL
|
NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST "http://localhost:8766/api/pipes/day-recap/run"
curl -X POST "http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25"
Rebuild and restart
to pick up the changes:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
How it works:
Each
pipe.md
file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The "Read screenpipe skill first" line is stripped automatically.
The pipes directory inside Docker is
/data/pipes
(since
/volume1/screenpipe
→
/data
). You can override it with a
PIPES_DIR
env var if needed.
Message actions
pipe.md
pipe.md
where to place api key and can I use different keys
Thinking
Thinking
Bash
Read .env file
IN
cat /volume1/screenpipe/app/.env
Copy code to clipboard
OUT
[ENV_SECRET]
Where to place the key:
app/.env
app/.env
— replace
your_key_here
with your actual key:
Copy code to clipboard
[ENV_SECRET]
That file is loaded by
load_dotenv()
at startup and is excluded from git via
.gitignore
.
Can you use different keys per pipe?
Not currently — all pipes share the one key from
.env
. But you can add per-pipe key support by adding an
api_key...
|
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update","depth":19,"bounds":{"left":0.0,"top":0.23942538,"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":0.2490024,"width":0.007978723,"height":0.01915403},"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"2","depth":22,"bounds":{"left":0.009640957,"top":0.2601756,"width":0.0019946808,"height":0.008778931},"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Claude 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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":"/volume1/screenpipe/.DS_Store\n/volume1/screenpipe/screenpipe.db\n/volume1/screenpipe/screenpipe_sync.sh\n/volume1/screenpipe/app_settings.json\n/volume1/screenpipe/.gitignore\n/volume1/screenpipe/archive.db\n/volume1/screenpipe/db.sqlite\n/volume1/screenpipe/db.sqlite-wal\n/volume1/screenpipe/db.sqlite-shm\n/volume1/screenpipe/#recycle/desktop.ini\n/volume1/screenpipe/#recycle/db.sqlite\n/volume1/screenpipe/#recycle/Copy #1 of db.sqlite\n/volume1/screenpipe/#recycle/.DS_Store\n/volume1/screenpipe/#recycle/Copy #2 of db.sqlite\n/volume1/screenpipe/#recycle/archive.db\n/volume1/screenpipe/#recycle/Copy #1 of archive.db\n/volume1/screenpipe/#recycle/Copy #2 of archive.db\n/volume1/screenpipe/#recycle/Copy #3 of archive.db\n/volume1/screenpipe/#recycle/Copy #4 of archive.db\n/volume1/screenpipe/#recycle/Copy #5 of archive.db\n/volume1/screenpipe/#recycle/Copy #3 of db.sqlite\n/volume1/screenpipe/#recycle/Copy #4 of db.sqlite\n/volume1/screenpipe/#recycle/Copy #6 of archive.db\n/volume1/screenpipe/#recycle/test.txt\n/volume1/screenpipe/#recycle/Copy #7 of archive.db\n/volume1/screenpipe/#recycle/Copy #8 of archive.db\n/volume1/screenpipe/#recycle/archive.db-journal\n/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #5 of db.sqlite\n/volume1/screenpipe/pipes/.DS_Store\n/volume1/screenpipe/app/.env\n/volume1/screenpipe/app/cli.py\n/volume1/screenpipe/app/.DS_Store\n/volume1/screenpipe/app/db.py\n/volume1/screenpipe/app/docker-compose.yml\n/volume1/screenpipe/app/main.py\n/volume1/screenpipe/app/requirements.txt\n/volume1/screenpipe/app/Dockerfile\n/volume1/screenpipe/data/.DS_Store\n/volume1/screenpipe/.git/description\n/volume1/screenpipe/.git/HEAD\n/volume1/screenpipe/.git/index\n/volume1/screenpipe/.git/COMMIT_EDITMSG\n/volume1/screenpipe/#recycle/data/.DS_Store\n---\napp\napp_settings.json\narchive.db\ndata\ndb.sqlite\ndb.sqlite-shm\ndb.sqlite-wal\npipes\n#recycle\nscreenpipe.db\nscreenpipe_sync.sh","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check pipes directory and docker-compose","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml","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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\ncli.py\nconsumers\ndb.py\ndocker-compose.yml\nDockerfile\nmain.py\n__pycache__\nrequirements.txt\nstatic\nservices:\n screenpipe-app:\n build: .\n container_name: screenpipe-app\n restart: unless-stopped\n ports:\n - \"8766:8000\"\n volumes:\n - /volume1/screenpipe:/data\n env_file:\n - .env\n environment:\n TZ: Europe/Sofia\n DB_PATH: /data/db.sqlite\n\n sqlite-web-archive:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-archive\n restart: unless-stopped\n ports:\n - \"8767:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/archive.db\"]\n\n sqlite-web-live:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-live\n restart: unless-stopped\n ports:\n - \"8768:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/db.sqlite\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"requirements.txt","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"requirements.txt","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Inspect a pipe directory","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/","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":"pipe.md\npipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"List all pipes and their contents","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo \"=== $d ===\"; ls \"$d\"; 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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\n=== /volume1/screenpipe/pipes/ai-habits/ ===\npipe.md\n=== /volume1/screenpipe/pipes/day-recap/ ===\npipe.md\n=== /volume1/screenpipe/pipes/meeting-summary/ ===\npipe.md\n=== /volume1/screenpipe/pipes/standup-update/ ===\npipe.md\n=== /volume1/screenpipe/pipes/time-breakdown/ ===\npipe.md\n=== /volume1/screenpipe/pipes/video-export/ ===\npipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read pipe markdown files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo \"===\" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50","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":"---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.","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":"Read summary consumer","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py","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":"activity.py\naudio.py\nelements.py\n__init__.py\ninteractions.py\nocr.py\n__pycache__\nreport.py\nsummary.py\n\"\"\"AI summary generator using Claude.\"\"\"\nimport os\nfrom datetime import date\nfrom typing import Any\n\nfrom consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary\nfrom consumers.ocr import deduplicated_text\nfrom consumers.audio import formatted_transcript\n\n\nSUMMARY_TYPES = {\n \"day_recap\": {\n \"title\": \"Day Recap\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a concise day recap using EXACTLY this format:\n\n## Summary\nOne sentence: what I mainly worked on today.\n\n## Accomplishments\n- Top 3 things I finished, with approximate times\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things seen or heard, with timestamps\n\n## Unfinished Work\n- What to continue tomorrow\n\n## Patterns\n- Apps used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with:\n**Next step:** [most important thing to continue]\"\"\",\n },\n \"standup\": {\n \"title\": \"Standup Update\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a brief standup update:\n\n**Yesterday:** What I worked on (2-3 bullets)\n**Today:** What I plan to continue (1-2 bullets)\n**Blockers:** Any issues observed (or \"None\")\n\nKeep it under 150 words. Only report what's verifiable from the data.\"\"\",\n },\n \"focus_time\": {\n \"title\": \"Focus & Distraction Analysis\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\nAnalyze focus vs distraction patterns:\n\n## Deep Work Periods\n- When and how long were sustained focus sessions?\n- What was being worked on?\n\n## Distractions\n- Which apps/sites were used recreationally?\n- How much time was lost to context switching?\n\n## Recommendations\n- 2-3 concrete suggestions to improve focus tomorrow\n\nBe specific with times and app names.\"\"\",\n },\n}\n\n\ndef _build_context(for_date: date) -> dict[str, str]:\n apps = app_time(for_date)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(for_date, limit=20)\n url_lines = \"\\n\".join(\n f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls\n )\n\n ui_rows = ui_event_summary(for_date)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(for_date, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(for_date)\n\n return {\n \"app_time\": app_lines or \"(no app data)\",\n \"browser_urls\": url_lines or \"(no browser data)\",\n \"ui_events\": ui_lines or \"(no UI event data)\",\n \"ocr_text\": ocr_lines or \"(no screen data)\",\n \"audio\": audio[:3000] if len(audio) > 3000 else audio,\n }\n\n\ndef generate(\n summary_type: str = \"day_recap\",\n for_date: date | None = None,\n api_key: str | None = None,\n) -> dict[str, Any]:\n \"\"\"Generate an AI summary. Returns dict with 'title', 'content', 'date'.\"\"\"\n import anthropic\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\n \"title\": \"Error\",\n \"content\": \"ANTHROPIC_API_KEY not set. Add it to your .env file.\",\n \"date\": str(d),\n }\n\n spec = SUMMARY_TYPES.get(summary_type)\n if not spec:\n return {\"title\": \"Error\", \"content\": f\"Unknown summary type: {summary_type}\", \"date\": str(d)}\n\n stats = summary_stats(d)\n if stats[\"total_frames\"] == 0:\n return {\n \"title\": spec[\"title\"],\n \"content\": f\"No screen data found for {d}.\",\n \"date\": str(d),\n }\n\n ctx = _build_context(d)\n prompt = spec[\"prompt\"].format(**ctx)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": prompt}],\n )\n\n return {\n \"title\": spec[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","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":"Read all pipe.md files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"for f in /volume1/screenpipe/pipes/*/pipe.md; do echo \"=== $f ===\"; cat \"$f\"; 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":"=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: AI Habits\ndescription: \"How you use AI tools — patterns and insights\"\nicon: \"🤖\"\nfeatured: true\n---\n\nSearch my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## AI Tools Used\n- List each tool with approximate time spent (e.g. \"Claude: ~45min\")\n\n## What I Used Them For\n- For each tool: coding, writing, research, or brainstorming\n\n## Usage Patterns\n- Do I switch between tools? Use them in bursts or steadily?\n\n## Effectiveness\n- Which tool appeared alongside completed work vs. abandoned attempts\n\nIf no AI usage is found, say so clearly. End with: \"**Tip:** [one suggestion to use AI tools more effectively]\"\n\n=== /volume1/screenpipe/pipes/day-recap/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n\n=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.\n\n=== /volume1/screenpipe/pipes/standup-update/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Standup Update\ndescription: \"What you did, what's next, and any blockers\"\nicon: \"🏢\"\nfeatured: true\n---\n\nBased on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Yesterday\n- What I worked on (name specific projects, files, tools, PRs)\n\n## Today\n- What I will work on next (based on unfinished tasks and recent activity)\n\n## Blockers\n- Issues I hit — errors, slow builds, waiting on someone\n- If no blockers, write \"None\"\n\nKeep it under 150 words. Copy-paste ready for a team standup.\n\n=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Time Breakdown\ndescription: \"Where your time went — by app, project, and category\"\nicon: \"⏱\"\nfeatured: false\n---\n\nAnalyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.\n\nRead screenpipe skill first.\n\nUse this exact format with durations and percentages:\n\n## By Application\n- List each app with duration and percentage, sorted by time (e.g. \"VS Code: 2h 15min (28%)\")\n\n## By Category\n- Group into: coding, meetings, browsing, writing, communication, other\n- Show hours and percentage per category\n\n## By Project\n- Group related activities by project/topic. Name specific repos or tasks.\n\n## Productivity Score\n- Calculate: focused_work_hours / total_hours as a percentage\n- Focused = coding + writing. Unfocused = browsing + switching.\n\nEnd with: \"**Suggestion:** [one specific change to improve tomorrow's productivity]\"\n\n=== /volume1/screenpipe/pipes/video-export/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Export Video Clip\ndescription: \"Create a video of your recent screen activity\"\nicon: \"🎬\"\nfeatured: false\n---\n\nExport a video of my screen activity from the last 5 minutes.\n\nRead screenpipe skill first.\n\nUse the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.\n\nIf the export is large, suggest a lower fps or shorter time range.","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 clear picture. The pipes are markdown prompt templates in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe/pipes/","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but there's no code to actually load and run them —","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"has its own hardcoded prompts instead.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Here's what I'll implement:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/pipes.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— two new endpoints:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"GET /api/pipes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /api/pipes/{pipe_id}/run","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cli.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— a","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"command to run pipes from the terminal","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Let me build it:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check browser_urls signature","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/consumers/activity.py | grep \"def browser_urls\" -A 5","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":"def browser_urls(\n for_date: date | None = None,\n app_name: str | None = None,\n ts_from: str | None = None,\n ts_to: str | None = None,\n limit: int = 30,","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":"pipes.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipes.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"143 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"\"\"\"Dynamic pipe loader and runner.\"\"\"\nimport os\nimport re\nfrom datetime import date\nfrom pathlib import Path\nfrom typing import Any\n\n\ndef _parse_frontmatter(text: str) -> tuple[dict, str]:\n if not text.startswith(\"---\"):\n return {}, text\n try:\n end = text.index(\"---\", 3)\n except ValueError:\n return {}, text\n fm_text = text[3:end].strip()\n body = text[end + 3:].strip()\n meta: dict = {}\n for line in fm_text.splitlines():\n if \":\" in line:\n k, _, v = line.partition(\":\")\n meta[k.strip()] = v.strip().strip('\"')\n return meta, body\n\n\ndef load_pipes(pipes_dir: Path) -> list[dict]:\n if not pipes_dir.exists():\n return []\n pipes = []\n for pipe_dir in sorted(pipes_dir.iterdir()):\n if not pipe_dir.is_dir() or pipe_dir.name.startswith(\".\"):\n continue\n pipe_md = pipe_dir / \"pipe.md\"\n if not pipe_md.exists():\n continue\n text = pipe_md.read_text(encoding=\"utf-8\")\n meta, body = _parse_frontmatter(text)\n if meta.get(\"enabled\", \"true\").lower() == \"false\":\n continue\n body = re.sub(r\"Read screenpipe skill first\\.?\\n?\", \"\", body).strip()\n pipes.append({\n \"id\": pipe_dir.name,\n \"title\": meta.get(\"title\", pipe_dir.name),\n \"description\": meta.get(\"description\", \"\"),\n \"icon\": meta.get(\"icon\", \"\"),\n \"schedule\": meta.get(\"schedule\", \"manual\"),\n \"featured\": meta.get(\"featured\", \"false\").lower() == \"true\",\n \"prompt\": body,\n })\n return pipes\n\n\ndef _build_system(d: date, stats: dict) -> str:\n from consumers.activity import app_time, browser_urls, ui_event_summary\n from consumers.ocr import deduplicated_text\n from consumers.audio import formatted_transcript\n\n apps = app_time(d)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(d, limit=20)\n url_lines = \"\\n\".join(f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls)\n\n ui_rows = ui_event_summary(d)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(d, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(d)\n if len(audio) > 3000:\n audio = audio[:3000]\n\n return f\"\"\"You are analyzing screenpipe data — recordings of a person's computer activity.\n\n## App usage (minutes per app):\n{app_lines or '(no app data)'}\n\n## Browser URLs visited:\n{url_lines or '(no browser data)'}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_lines or '(no UI event data)'}\n\n## Screen content (sampled every 5 minutes):\n{ocr_lines or '(no screen data)'}\n\n## Audio / speech:\n{audio or '(no audio data)'}\n\nDate: {d}\nTotal frames recorded: {stats['total_frames']}\"\"\"\n\n\ndef run_pipe(\n pipe_id: str,\n for_date: date | None = None,\n api_key: str | None = None,\n pipes_dir: Path | None = None,\n) -> dict[str, Any]:\n import anthropic\n from consumers.activity import summary_stats\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\"title\": \"Error\", \"content\": \"ANTHROPIC_API_KEY not set.\", \"date\": str(d)}\n\n _pipes_dir = pipes_dir or Path(os.environ.get(\"PIPES_DIR\", \"/data/pipes\"))\n all_pipes = {p[\"id\"]: p for p in load_pipes(_pipes_dir)}\n\n if pipe_id not in all_pipes:\n return {\"title\": \"Error\", \"content\": f\"Pipe not found: {pipe_id}\", \"date\": str(d)}\n\n pipe = all_pipes[pipe_id]\n stats = summary_stats(d)\n\n if stats[\"total_frames\"] == 0:\n return {\"title\": pipe[\"title\"], \"content\": f\"No screen data found for {d}.\", \"date\": str(d)}\n\n system = _build_system(d, stats)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n system=system,\n messages=[{\"role\": \"user\", \"content\": pipe[\"prompt\"]}],\n )\n\n return {\n \"title\": pipe[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the API endpoints to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the pipe endpoints at the end of main.py, before the closing summary section:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 14 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the CLI command to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 40 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Done. Here's how to run pipes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to run pipes","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to run pipes","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via Docker (inside the running container):","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"docker exec -it screenpipe-app python cli.py pipe --list\ndocker exec -it screenpipe-app python cli.py pipe day-recap\ndocker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via the API","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(once the container is running on port 8766):","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# List pipes\ncurl http://localhost:8766/api/pipes\n\n# Run a pipe\ncurl -X POST \"http://localhost:8766/api/pipes/day-recap/run\"\ncurl -X POST \"http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rebuild and restart","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to pick up the changes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"cd /volume1/screenpipe/app\ndocker compose up --build -d","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"How it works:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Each","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The \"Read screenpipe skill first\" line is stripped automatically.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The pipes directory inside Docker is","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data/pipes","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(since","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"→","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). You can override it with a","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"PIPES_DIR","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"env var if needed.","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":"AXButton","text":"pipe.md","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"where to place api key and can I use different keys","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":"Read .env file","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/.env","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":"ANTHROPIC_API_KEY=your_key_here","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Where to place the key:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"app/.env","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"app/.env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— replace","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"your_key_here","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with your actual key:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"ANTHROPIC_API_KEY=sk-ant-...","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"That file is loaded by","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"load_dotenv()","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"at startup and is excluded from git via","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".gitignore","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Can you use different keys per pipe?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Not currently — all pipes share the one key from","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". But you can add per-pipe key support by adding an","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"api_key","depth":24,"on_screen":false,"role_description":"text"}]...
|
250811703306051361
|
-8763496496607803284
|
idle
|
accessibility
|
NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST "http://localhost:8766/api/pipes/day-recap/run"
curl -X POST "http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25"
Rebuild and restart
to pick up the changes:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
How it works:
Each
pipe.md
file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The "Read screenpipe skill first" line is stripped automatically.
The pipes directory inside Docker is
/data/pipes
(since
/volume1/screenpipe
→
/data
). You can override it with a
PIPES_DIR
env var if needed.
Message actions
pipe.md
pipe.md
where to place api key and can I use different keys
Thinking
Thinking
Bash
Read .env file
IN
cat /volume1/screenpipe/app/.env
Copy code to clipboard
OUT
[ENV_SECRET]
Where to place the key:
app/.env
app/.env
— replace
your_key_here
with your actual key:
Copy code to clipboard
[ENV_SECRET]
That file is loaded by
load_dotenv()
at startup and is excluded from git via
.gitignore
.
Can you use different keys per pipe?
Not currently — all pipes share the one key from
.env
. But you can add per-pipe key support by adding an
api_key...
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2026-05-11T17:06:16.597103+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519176597_m1.jpg...
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Code
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Implement and run pipe l… — screenpipe [SSH: nas]
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl [URL_WITH_CREDENTIALS] sudo docker exec -it screenpipe-app python cli.py pipe day-recap --date 2026-04-20
Running pipe 'day-recap' for 2026-04-20...
Traceback (most recent call last):
File "/app/cli.py", line 245, in <module>
cli()
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1161, in __call__
return self.main(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1082, in main
rv = self.invoke(ctx)
^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1697, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1443, in invoke
return ctx.invoke(self.callback, **ctx.params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 788, in invoke
return __callback(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/app/cli.py", line 225, in pipe
result = run_pipe(pipe_id, target, pipes_dir=pipes_dir)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/app/consumers/pipes.py", line 130, in run_pipe
message = client.messages.create(
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_utils/_utils.py", line 275, in wrapper
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/resources/messages/messages.py", line 953, in create
return self._post(
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py", line 1336, in post
return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py", line 1013, in request
return self._request(
^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py", line 1117, in _request
raise self._make_status_error_from_response(err.response) from None
anthropic.AuthenticationError: Error code: 401 - {'type': 'error', 'error': {'type': 'authentication_error', 'message': 'invalid x-api-key'}, 'request_id': 'req_011CaSoR75WgV8fTcHTYJMDY'}
Adm1n@DXP4800PLUS-B5F8:/volume1/screenpipe/app$
Thinking
Thinking
The container started before you updated the
.env
, so it's using the old placeholder key. Restart it to pick up the new one:
Copy code to clipboard
cd /volume1/screenpipe/app
sudo docker compose restart screenpipe-app
Then try again:
Copy code to clipboard
sudo docker exec -it screenpipe-app python cli.py pipe day-recap --date 2026-04-20
Message actions
Adm1n@DXP4800PLUS-B5F8:/volume1/screenpipe/app$ sudo docker exec -it screenpipe-app python cli.py pipe day-recap --date 2026-04-20
Running pipe 'day-recap' for 2026-04-20...
Traceback (most recent call last):
File "/app/cli.py", line 245, in <module>
cli()
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1161, in __call__
return self.main(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1082, in main
rv = self.invoke(ctx)
^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1697, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1443, in invoke
return ctx.invoke(self.callback, **ctx.params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 788, in invoke
return __callback(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/app/cli.py", line 225, in pipe
result = run_pipe(pipe_id, target, pipes_dir=pipes_dir)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/app/consumers/pipes.py", line 130, in run_pipe
message = client.messages.create(
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_utils/_utils.py", line 275, in wrapper
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/resources/messages/messages.py", line 953, in create
return self._post(
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py", line 1336, in post
return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py", line 1013, in request
return self._request(
^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py", line 1117, in _request
raise self._make_status_error_from_response(err.response) from None
anthropic.AuthenticationError: Error code: 401 - {'type': 'error', 'error': {'type': 'authentication_error', 'message': 'invalid x-api-key'}, 'request_id': 'req_011CaSoaWfbMTbPTbw5PpBu1'}
Adm1n@DXP4800PLUS-B5F8:/volume1/screenpipe/app$
Message actions...
|
[{"role":"AXRadioButton","text [{"role":"AXRadioButton","text":"Explorer (⇧⌘E)","depth":19,"on_screen":true,"role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":true,"is_expanded":true},{"role":"AXStaticText","text":"","depth":22,"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Search (⇧⌘F)","depth":19,"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,"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Source Control (⌃⇧G) - 10 pending changes","depth":19,"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,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"10","depth":22,"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Run and Debug (⇧⌘D)","depth":19,"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,"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Remote Explorer","depth":19,"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,"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Extensions (⇧⌘X) - 2 require update","depth":19,"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,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"2","depth":22,"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Claude Code","depth":19,"on_screen":true,"role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"Containers","depth":19,"on_screen":true,"role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXHeading","text":"EXPLORER","depth":17,"on_screen":true,"role_description":"heading"},{"role":"AXStaticText","text":"EXPLORER","depth":18,"on_screen":true,"role_description":"text"},{"role":"AXButton","text":"Explorer Section: screenpipe [SSH: nas]","depth":21,"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":true},{"role":"AXStaticText","text":"","depth":23,"on_screen":true,"role_description":"text"},{"role":"AXHeading","text":"Explorer Section: screenpipe [SSH: nas]","depth":22,"on_screen":true,"role_description":"heading"},{"role":"AXStaticText","text":"SCREENPIPE [SSH: 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unless-stopped\n ports:\n - \"8766:8000\"\n volumes:\n - /volume1/screenpipe:/data\n env_file:\n - .env\n environment:\n TZ: Europe/Sofia\n DB_PATH: /data/db.sqlite\n\n sqlite-web-archive:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-archive\n restart: unless-stopped\n ports:\n - \"8767:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/archive.db\"]\n\n sqlite-web-live:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-live\n restart: unless-stopped\n ports:\n - \"8768:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", 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their contents","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo \"=== $d ===\"; ls \"$d\"; 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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\n=== /volume1/screenpipe/pipes/ai-habits/ ===\npipe.md\n=== /volume1/screenpipe/pipes/day-recap/ ===\npipe.md\n=== /volume1/screenpipe/pipes/meeting-summary/ ===\npipe.md\n=== /volume1/screenpipe/pipes/standup-update/ ===\npipe.md\n=== /volume1/screenpipe/pipes/time-breakdown/ ===\npipe.md\n=== /volume1/screenpipe/pipes/video-export/ ===\npipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read pipe markdown files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo \"===\" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50","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":"---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.","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":"Read summary consumer","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py","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":"activity.py\naudio.py\nelements.py\n__init__.py\ninteractions.py\nocr.py\n__pycache__\nreport.py\nsummary.py\n\"\"\"AI summary generator using Claude.\"\"\"\nimport os\nfrom datetime import date\nfrom typing import Any\n\nfrom consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary\nfrom consumers.ocr import deduplicated_text\nfrom consumers.audio import formatted_transcript\n\n\nSUMMARY_TYPES = {\n \"day_recap\": {\n \"title\": \"Day Recap\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a concise day recap using EXACTLY this format:\n\n## Summary\nOne sentence: what I mainly worked on today.\n\n## Accomplishments\n- Top 3 things I finished, with approximate times\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things seen or heard, with timestamps\n\n## Unfinished Work\n- What to continue tomorrow\n\n## Patterns\n- Apps used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with:\n**Next step:** [most important thing to continue]\"\"\",\n },\n \"standup\": {\n \"title\": \"Standup Update\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a brief standup update:\n\n**Yesterday:** What I worked on (2-3 bullets)\n**Today:** What I plan to continue (1-2 bullets)\n**Blockers:** Any issues observed (or \"None\")\n\nKeep it under 150 words. Only report what's verifiable from the data.\"\"\",\n },\n \"focus_time\": {\n \"title\": \"Focus & Distraction Analysis\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\nAnalyze focus vs distraction patterns:\n\n## Deep Work Periods\n- When and how long were sustained focus sessions?\n- What was being worked on?\n\n## Distractions\n- Which apps/sites were used recreationally?\n- How much time was lost to context switching?\n\n## Recommendations\n- 2-3 concrete suggestions to improve focus tomorrow\n\nBe specific with times and app names.\"\"\",\n },\n}\n\n\ndef _build_context(for_date: date) -> dict[str, str]:\n apps = app_time(for_date)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(for_date, limit=20)\n url_lines = \"\\n\".join(\n f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls\n )\n\n ui_rows = ui_event_summary(for_date)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(for_date, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(for_date)\n\n return {\n \"app_time\": app_lines or \"(no app data)\",\n \"browser_urls\": url_lines or \"(no browser data)\",\n \"ui_events\": ui_lines or \"(no UI event data)\",\n \"ocr_text\": ocr_lines or \"(no screen data)\",\n \"audio\": audio[:3000] if len(audio) > 3000 else audio,\n }\n\n\ndef generate(\n summary_type: str = \"day_recap\",\n for_date: date | None = None,\n api_key: str | None = None,\n) -> dict[str, Any]:\n \"\"\"Generate an AI summary. Returns dict with 'title', 'content', 'date'.\"\"\"\n import anthropic\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\n \"title\": \"Error\",\n \"content\": \"ANTHROPIC_API_KEY not set. Add it to your .env file.\",\n \"date\": str(d),\n }\n\n spec = SUMMARY_TYPES.get(summary_type)\n if not spec:\n return {\"title\": \"Error\", \"content\": f\"Unknown summary type: {summary_type}\", \"date\": str(d)}\n\n stats = summary_stats(d)\n if stats[\"total_frames\"] == 0:\n return {\n \"title\": spec[\"title\"],\n \"content\": f\"No screen data found for {d}.\",\n \"date\": str(d),\n }\n\n ctx = _build_context(d)\n prompt = spec[\"prompt\"].format(**ctx)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": prompt}],\n )\n\n return {\n \"title\": spec[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","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":"Read all pipe.md files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"for f in /volume1/screenpipe/pipes/*/pipe.md; do echo \"=== $f ===\"; cat \"$f\"; 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":"=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: AI Habits\ndescription: \"How you use AI tools — patterns and insights\"\nicon: \"🤖\"\nfeatured: true\n---\n\nSearch my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## AI Tools Used\n- List each tool with approximate time spent (e.g. \"Claude: ~45min\")\n\n## What I Used Them For\n- For each tool: coding, writing, research, or brainstorming\n\n## Usage Patterns\n- Do I switch between tools? Use them in bursts or steadily?\n\n## Effectiveness\n- Which tool appeared alongside completed work vs. abandoned attempts\n\nIf no AI usage is found, say so clearly. End with: \"**Tip:** [one suggestion to use AI tools more effectively]\"\n\n=== /volume1/screenpipe/pipes/day-recap/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n\n=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.\n\n=== /volume1/screenpipe/pipes/standup-update/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Standup Update\ndescription: \"What you did, what's next, and any blockers\"\nicon: \"🏢\"\nfeatured: true\n---\n\nBased on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Yesterday\n- What I worked on (name specific projects, files, tools, PRs)\n\n## Today\n- What I will work on next (based on unfinished tasks and recent activity)\n\n## Blockers\n- Issues I hit — errors, slow builds, waiting on someone\n- If no blockers, write \"None\"\n\nKeep it under 150 words. Copy-paste ready for a team standup.\n\n=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Time Breakdown\ndescription: \"Where your time went — by app, project, and category\"\nicon: \"⏱\"\nfeatured: false\n---\n\nAnalyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.\n\nRead screenpipe skill first.\n\nUse this exact format with durations and percentages:\n\n## By Application\n- List each app with duration and percentage, sorted by time (e.g. \"VS Code: 2h 15min (28%)\")\n\n## By Category\n- Group into: coding, meetings, browsing, writing, communication, other\n- Show hours and percentage per category\n\n## By Project\n- Group related activities by project/topic. Name specific repos or tasks.\n\n## Productivity Score\n- Calculate: focused_work_hours / total_hours as a percentage\n- Focused = coding + writing. Unfocused = browsing + switching.\n\nEnd with: \"**Suggestion:** [one specific change to improve tomorrow's productivity]\"\n\n=== /volume1/screenpipe/pipes/video-export/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Export Video Clip\ndescription: \"Create a video of your recent screen activity\"\nicon: \"🎬\"\nfeatured: false\n---\n\nExport a video of my screen activity from the last 5 minutes.\n\nRead screenpipe skill first.\n\nUse the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.\n\nIf the export is large, suggest a lower fps or shorter time range.","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 clear picture. The pipes are markdown prompt templates in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe/pipes/","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but there's no code to actually load and run them —","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"has its own hardcoded prompts instead.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Here's what I'll implement:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/pipes.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— two new endpoints:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"GET /api/pipes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /api/pipes/{pipe_id}/run","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cli.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— a","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"command to run pipes from the terminal","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Let me build it:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check browser_urls signature","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/consumers/activity.py | grep \"def browser_urls\" -A 5","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":"def browser_urls(\n for_date: date | None = None,\n app_name: str | None = None,\n ts_from: str | None = None,\n ts_to: str | None = None,\n limit: int = 30,","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":"pipes.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipes.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"143 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"\"\"\"Dynamic pipe loader and runner.\"\"\"\nimport os\nimport re\nfrom datetime import date\nfrom pathlib import Path\nfrom typing import Any\n\n\ndef _parse_frontmatter(text: str) -> tuple[dict, str]:\n if not text.startswith(\"---\"):\n return {}, text\n try:\n end = text.index(\"---\", 3)\n except ValueError:\n return {}, text\n fm_text = text[3:end].strip()\n body = text[end + 3:].strip()\n meta: dict = {}\n for line in fm_text.splitlines():\n if \":\" in line:\n k, _, v = line.partition(\":\")\n meta[k.strip()] = v.strip().strip('\"')\n return meta, body\n\n\ndef load_pipes(pipes_dir: Path) -> list[dict]:\n if not pipes_dir.exists():\n return []\n pipes = []\n for pipe_dir in sorted(pipes_dir.iterdir()):\n if not pipe_dir.is_dir() or pipe_dir.name.startswith(\".\"):\n continue\n pipe_md = pipe_dir / \"pipe.md\"\n if not pipe_md.exists():\n continue\n text = pipe_md.read_text(encoding=\"utf-8\")\n meta, body = _parse_frontmatter(text)\n if meta.get(\"enabled\", \"true\").lower() == \"false\":\n continue\n body = re.sub(r\"Read screenpipe skill first\\.?\\n?\", \"\", body).strip()\n pipes.append({\n \"id\": pipe_dir.name,\n \"title\": meta.get(\"title\", pipe_dir.name),\n \"description\": meta.get(\"description\", \"\"),\n \"icon\": meta.get(\"icon\", \"\"),\n \"schedule\": meta.get(\"schedule\", \"manual\"),\n \"featured\": meta.get(\"featured\", \"false\").lower() == \"true\",\n \"prompt\": body,\n })\n return pipes\n\n\ndef _build_system(d: date, stats: dict) -> str:\n from consumers.activity import app_time, browser_urls, ui_event_summary\n from consumers.ocr import deduplicated_text\n from consumers.audio import formatted_transcript\n\n apps = app_time(d)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(d, limit=20)\n url_lines = \"\\n\".join(f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls)\n\n ui_rows = ui_event_summary(d)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(d, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(d)\n if len(audio) > 3000:\n audio = audio[:3000]\n\n return f\"\"\"You are analyzing screenpipe data — recordings of a person's computer activity.\n\n## App usage (minutes per app):\n{app_lines or '(no app data)'}\n\n## Browser URLs visited:\n{url_lines or '(no browser data)'}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_lines or '(no UI event data)'}\n\n## Screen content (sampled every 5 minutes):\n{ocr_lines or '(no screen data)'}\n\n## Audio / speech:\n{audio or '(no audio data)'}\n\nDate: {d}\nTotal frames recorded: {stats['total_frames']}\"\"\"\n\n\ndef run_pipe(\n pipe_id: str,\n for_date: date | None = None,\n api_key: str | None = None,\n pipes_dir: Path | None = None,\n) -> dict[str, Any]:\n import anthropic\n from consumers.activity import summary_stats\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\"title\": \"Error\", \"content\": \"ANTHROPIC_API_KEY not set.\", \"date\": str(d)}\n\n _pipes_dir = pipes_dir or Path(os.environ.get(\"PIPES_DIR\", \"/data/pipes\"))\n all_pipes = {p[\"id\"]: p for p in load_pipes(_pipes_dir)}\n\n if pipe_id not in all_pipes:\n return {\"title\": \"Error\", \"content\": f\"Pipe not found: {pipe_id}\", \"date\": str(d)}\n\n pipe = all_pipes[pipe_id]\n stats = summary_stats(d)\n\n if stats[\"total_frames\"] == 0:\n return {\"title\": pipe[\"title\"], \"content\": f\"No screen data found for {d}.\", \"date\": str(d)}\n\n system = _build_system(d, stats)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n system=system,\n messages=[{\"role\": \"user\", \"content\": pipe[\"prompt\"]}],\n )\n\n return {\n \"title\": pipe[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the API endpoints to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the pipe endpoints at the end of main.py, before the closing summary section:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 14 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the CLI command to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 40 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Done. Here's how to run pipes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to run pipes","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to run pipes","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via Docker (inside the running container):","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"docker exec -it screenpipe-app python cli.py pipe --list\ndocker exec -it screenpipe-app python cli.py pipe day-recap\ndocker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via the API","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(once the container is running on port 8766):","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# List pipes\ncurl http://localhost:8766/api/pipes\n\n# Run a pipe\ncurl -X POST \"http://localhost:8766/api/pipes/day-recap/run\"\ncurl -X POST \"http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rebuild and restart","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to pick up the changes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"cd /volume1/screenpipe/app\ndocker compose up --build -d","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"How it works:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Each","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The \"Read screenpipe skill first\" line is stripped automatically.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The pipes directory inside Docker is","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data/pipes","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(since","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"→","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"). You can override it with a","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"PIPES_DIR","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"env var if needed.","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":"AXButton","text":"pipe.md","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"where to place api key and can I use different keys","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":"Read .env file","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/.env","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":"ANTHROPIC_API_KEY=your_key_here","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Where to place the key:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"app/.env","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"app/.env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— replace","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"your_key_here","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"with your actual key:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"ANTHROPIC_API_KEY=sk-ant-...","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"That file is loaded by","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"load_dotenv()","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"at startup and is excluded from git via","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".gitignore","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Can you use different keys per pipe?","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Not currently — all pipes share the one key from","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". But you can add per-pipe key support by adding an","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"api_key","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"field to the pipe's frontmatter:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"---\ntitle: Meeting Summary\napi_key_env: ANTHROPIC_KEY_MEETINGS\n---","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Then in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/pipes.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/pipes.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", read it in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"_parse_frontmatter","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and pass it through","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"run_pipe","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":". Want me to add that?","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":"AXButton","text":"pipe.md","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"can I use mistral or other llm? or is is build for antrophic only","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":"Currently it's Anthropic-only — the code calls the","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"anthropic","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"SDK directly in both","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/pipes.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/pipes.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"consumers/summary.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Adding other providers is straightforward since Mistral, Ollama, OpenRouter, Groq, and most modern LLMs expose an OpenAI-compatible API. The cleanest approach: add the","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"openai","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"package and let you configure the provider via","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".env","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# Anthropic (default)\nANTHROPIC_API_KEY=sk-ant-...\n\n# OR: any OpenAI-compatible provider\nLLM_PROVIDER=openai-compatible\nLLM_BASE_URL=https://api.mistral.ai/v1\nLLM_API_KEY=your-mistral-key\nLLM_MODEL=mistral-small-latest","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"This would cover Mistral, Ollama (","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"http://localhost:11434/v1","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"), OpenRouter, Groq, etc. with one code path.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Want me to implement that? It's a small change — a","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"_call_llm(system, user_prompt)","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"helper in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipes.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"that branches on","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"LLM_PROVIDER","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", and","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"openai","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"added to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"requirements.txt","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","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":"lets test it with anthropic first, how to run pipe","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":"Check if container is running","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cd /volume1/screenpipe/app && docker compose ps 2>/dev/null || docker ps --filter name=screenpipe","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\npermission denied while trying to connect to the Docker daemon socket at unix:///var/run/docker.sock: Get \"http://%2Fvar%2Frun%2Fdocker.sock/v1.45/containers/json?filters=%7B%22name%22%3A%7B%22screenpipe%22%3Atrue%7D%7D\": dial unix /var/run/docker.sock: connect: permission denied","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"I don't have Docker socket access, so you'll need to run these yourself. Here are your options:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option A — via Docker (if container is already running):","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# List available pipes\ndocker exec -it screenpipe-app python cli.py pipe --list\n\n# Run a specific pipe\ndocker exec -it screenpipe-app python cli.py pipe day-recap","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option B — rebuild first (since we added new files), then run:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"cd /volume1/screenpipe/app\ndocker compose up --build -d\ndocker exec -it screenpipe-app python cli.py pipe day-recap","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Option C — via the API","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(if container is up on port 8766):","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# List pipes\ncurl http://localhost:8766/api/pipes\n\n# Run a pipe\ncurl -X POST http://localhost:8766/api/pipes/day-recap/run","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"day-recap","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"or","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"standup-update","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipes are the best ones to test first since they use all data sources. Which option works for you?","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":"how ot run for specifiday","depth":25,"on_screen":true,"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":"Docker exec:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"docker exec -it screenpipe-app python cli.py pipe day-recap --date 2026-04-25\n# or shortcuts:\ndocker exec -it screenpipe-app python cli.py pipe day-recap --date yesterday\ndocker exec -it screenpipe-app python cli.py pipe day-recap --date today","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"API:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"on_screen":true,"help_text":"Copy code","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"curl -X POST \"http://localhost:8766/api/pipes/day-recap/run?d=2026-04-25\"","depth":25,"on_screen":true,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Adm1n@DXP4800PLUS-B5F8:/volume1/screenpipe/app$ sudo docker exec -it screenpipe-app python cli.py pipe day-recap --date 2026-04-20\nRunning pipe 'day-recap' for 2026-04-20...\nTraceback (most recent call last):\n File \"/app/cli.py\", line 245, in <module>\n cli()\n File \"/usr/local/lib/python3.12/site-packages/click/core.py\", line 1161, in __call__\n return self.main(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/click/core.py\", line 1082, in main\n rv = self.invoke(ctx)\n ^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/click/core.py\", line 1697, in invoke\n return _process_result(sub_ctx.command.invoke(sub_ctx))\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/click/core.py\", line 1443, in invoke\n return ctx.invoke(self.callback, **ctx.params)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/click/core.py\", line 788, in invoke\n return __callback(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/app/cli.py\", line 225, in pipe\n result = run_pipe(pipe_id, target, pipes_dir=pipes_dir)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/app/consumers/pipes.py\", line 130, in run_pipe\n message = client.messages.create(\n ^^^^^^^^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/anthropic/_utils/_utils.py\", line 275, in wrapper\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/anthropic/resources/messages/messages.py\", line 953, in create\n return self._post(\n ^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py\", line 1336, in post\n return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py\", line 1013, in request\n return self._request(\n ^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py\", line 1117, in _request\n raise self._make_status_error_from_response(err.response) from None\nanthropic.AuthenticationError: Error code: 401 - {'type': 'error', 'error': {'type': 'authentication_error', 'message': 'invalid x-api-key'}, 'request_id': 'req_011CaSoR75WgV8fTcHTYJMDY'}\nAdm1n@DXP4800PLUS-B5F8:/volume1/screenpipe/app$","depth":26,"on_screen":true,"role_description":"text"},{"role":"AXButton","text":"Thinking","depth":23,"on_screen":true,"role_description":"disclosure triangle","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Thinking","depth":24,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"The container started before you updated the","depth":23,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":".env","depth":24,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":", so it's using the old placeholder key. Restart it to pick up the new one:","depth":23,"on_screen":true,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"on_screen":true,"help_text":"Copy code","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cd /volume1/screenpipe/app\nsudo docker compose restart screenpipe-app","depth":25,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"Then try again:","depth":23,"on_screen":true,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"on_screen":true,"help_text":"Copy code","role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"sudo docker exec -it screenpipe-app python cli.py pipe day-recap --date 2026-04-20","depth":25,"on_screen":true,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"Adm1n@DXP4800PLUS-B5F8:/volume1/screenpipe/app$ sudo docker exec -it screenpipe-app python cli.py pipe day-recap --date 2026-04-20\nRunning pipe 'day-recap' for 2026-04-20...\nTraceback (most recent call last):\n File \"/app/cli.py\", line 245, in <module>\n cli()\n File \"/usr/local/lib/python3.12/site-packages/click/core.py\", line 1161, in __call__\n return self.main(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/click/core.py\", line 1082, in main\n rv = self.invoke(ctx)\n ^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/click/core.py\", line 1697, in invoke\n return _process_result(sub_ctx.command.invoke(sub_ctx))\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/click/core.py\", line 1443, in invoke\n return ctx.invoke(self.callback, **ctx.params)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/click/core.py\", line 788, in invoke\n return __callback(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/app/cli.py\", line 225, in pipe\n result = run_pipe(pipe_id, target, pipes_dir=pipes_dir)\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/app/consumers/pipes.py\", line 130, in run_pipe\n message = client.messages.create(\n ^^^^^^^^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/anthropic/_utils/_utils.py\", line 275, in wrapper\n return func(*args, **kwargs)\n ^^^^^^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/anthropic/resources/messages/messages.py\", line 953, in create\n return self._post(\n ^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py\", line 1336, in post\n return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))\n ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py\", line 1013, in request\n return self._request(\n ^^^^^^^^^^^^^^\n File \"/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py\", line 1117, in _request\n raise self._make_status_error_from_response(err.response) from None\nanthropic.AuthenticationError: Error code: 401 - {'type': 'error', 'error': {'type': 'authentication_error', 'message': 'invalid x-api-key'}, 'request_id': 'req_011CaSoaWfbMTbPTbw5PpBu1'}\nAdm1n@DXP4800PLUS-B5F8:/volume1/screenpipe/app$","depth":26,"on_screen":true,"role_description":"text"},{"role":"AXButton","text":"Message actions","depth":24,"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false}]...
|
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-8484554665838539576
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idle
|
accessibility
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NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl [URL_WITH_CREDENTIALS] sudo docker exec -it screenpipe-app python cli.py pipe day-recap --date 2026-04-20
Running pipe 'day-recap' for 2026-04-20...
Traceback (most recent call last):
File "/app/cli.py", line 245, in <module>
cli()
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1161, in __call__
return self.main(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1082, in main
rv = self.invoke(ctx)
^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1697, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1443, in invoke
return ctx.invoke(self.callback, **ctx.params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 788, in invoke
return __callback(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/app/cli.py", line 225, in pipe
result = run_pipe(pipe_id, target, pipes_dir=pipes_dir)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/app/consumers/pipes.py", line 130, in run_pipe
message = client.messages.create(
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_utils/_utils.py", line 275, in wrapper
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/resources/messages/messages.py", line 953, in create
return self._post(
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py", line 1336, in post
return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py", line 1013, in request
return self._request(
^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py", line 1117, in _request
raise self._make_status_error_from_response(err.response) from None
anthropic.AuthenticationError: Error code: 401 - {'type': 'error', 'error': {'type': 'authentication_error', 'message': 'invalid x-api-key'}, 'request_id': 'req_011CaSoR75WgV8fTcHTYJMDY'}
Adm1n@DXP4800PLUS-B5F8:/volume1/screenpipe/app$
Thinking
Thinking
The container started before you updated the
.env
, so it's using the old placeholder key. Restart it to pick up the new one:
Copy code to clipboard
cd /volume1/screenpipe/app
sudo docker compose restart screenpipe-app
Then try again:
Copy code to clipboard
sudo docker exec -it screenpipe-app python cli.py pipe day-recap --date 2026-04-20
Message actions
Adm1n@DXP4800PLUS-B5F8:/volume1/screenpipe/app$ sudo docker exec -it screenpipe-app python cli.py pipe day-recap --date 2026-04-20
Running pipe 'day-recap' for 2026-04-20...
Traceback (most recent call last):
File "/app/cli.py", line 245, in <module>
cli()
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1161, in __call__
return self.main(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1082, in main
rv = self.invoke(ctx)
^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1697, in invoke
return _process_result(sub_ctx.command.invoke(sub_ctx))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 1443, in invoke
return ctx.invoke(self.callback, **ctx.params)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/click/core.py", line 788, in invoke
return __callback(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/app/cli.py", line 225, in pipe
result = run_pipe(pipe_id, target, pipes_dir=pipes_dir)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/app/consumers/pipes.py", line 130, in run_pipe
message = client.messages.create(
^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_utils/_utils.py", line 275, in wrapper
return func(*args, **kwargs)
^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/resources/messages/messages.py", line 953, in create
return self._post(
^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py", line 1336, in post
return cast(ResponseT, self.request(cast_to, opts, stream=stream, stream_cls=stream_cls))
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py", line 1013, in request
return self._request(
^^^^^^^^^^^^^^
File "/usr/local/lib/python3.12/site-packages/anthropic/_base_client.py", line 1117, in _request
raise self._make_status_error_from_response(err.response) from None
anthropic.AuthenticationError: Error code: 401 - {'type': 'error', 'error': {'type': 'authentication_error', 'message': 'invalid x-api-key'}, 'request_id': 'req_011CaSoaWfbMTbPTbw5PpBu1'}
Adm1n@DXP4800PLUS-B5F8:/volume1/screenpipe/app$
Message actions...
|
21058
|
NULL
|
NULL
|
NULL
|
|
21059
|
921
|
0
|
2026-05-11T17:06:04.025574+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519164025_m2.jpg...
|
Code
|
Implement and run pipe l… — screenpipe [SSH: nas]
|
True
|
NULL
|
monitor_2
|
NULL
|
NULL
|
NULL
|
NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST "http://localhost:8766/api/pipes/day-recap/run"
curl -X POST "http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25"
Rebuild and restart
to pick up the changes:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
How it works:
Each
pipe.md
file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The "Read screenpipe skill first" line is stripped automatically.
The pipes directory inside Docker is
/data/pipes...
|
[{"role":"AXRadioButton","text [{"role":"AXRadioButton","text":"Explorer (⇧⌘E)","depth":19,"bounds":{"left":0.0,"top":0.047885075,"width":0.015957447,"height":0.03830806},"on_screen":true,"role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":true,"is_expanded":true},{"role":"AXStaticText","text":"","depth":22,"bounds":{"left":0.0039893617,"top":0.057462092,"width":0.007978723,"height":0.01915403},"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Search (⇧⌘F)","depth":19,"bounds":{"left":0.0,"top":0.08619314,"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":0.09577015,"width":0.007978723,"height":0.01915403},"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Source Control (⌃⇧G) - 10 pending changes","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":"AXStaticText","text":"10","depth":22,"bounds":{"left":0.00831117,"top":0.1452514,"width":0.003656915,"height":0.008778931},"on_screen":true,"lines":[{"char_start":0,"char_count":1,"bounds":{"left":0.00831117,"top":0.14604948,"width":0.0016622341,"height":0.007980846}},{"char_start":1,"char_count":1,"bounds":{"left":0.009973404,"top":0.14604948,"width":0.0023271276,"height":0.007980846}}],"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 update","depth":19,"bounds":{"left":0.0,"top":0.23942538,"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":0.2490024,"width":0.007978723,"height":0.01915403},"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"2","depth":22,"bounds":{"left":0.009640957,"top":0.2601756,"width":0.0019946808,"height":0.008778931},"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Claude 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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":"/volume1/screenpipe/.DS_Store\n/volume1/screenpipe/screenpipe.db\n/volume1/screenpipe/screenpipe_sync.sh\n/volume1/screenpipe/app_settings.json\n/volume1/screenpipe/.gitignore\n/volume1/screenpipe/archive.db\n/volume1/screenpipe/db.sqlite\n/volume1/screenpipe/db.sqlite-wal\n/volume1/screenpipe/db.sqlite-shm\n/volume1/screenpipe/#recycle/desktop.ini\n/volume1/screenpipe/#recycle/db.sqlite\n/volume1/screenpipe/#recycle/Copy #1 of db.sqlite\n/volume1/screenpipe/#recycle/.DS_Store\n/volume1/screenpipe/#recycle/Copy #2 of db.sqlite\n/volume1/screenpipe/#recycle/archive.db\n/volume1/screenpipe/#recycle/Copy #1 of archive.db\n/volume1/screenpipe/#recycle/Copy #2 of archive.db\n/volume1/screenpipe/#recycle/Copy #3 of archive.db\n/volume1/screenpipe/#recycle/Copy #4 of archive.db\n/volume1/screenpipe/#recycle/Copy #5 of archive.db\n/volume1/screenpipe/#recycle/Copy #3 of db.sqlite\n/volume1/screenpipe/#recycle/Copy #4 of db.sqlite\n/volume1/screenpipe/#recycle/Copy #6 of archive.db\n/volume1/screenpipe/#recycle/test.txt\n/volume1/screenpipe/#recycle/Copy #7 of archive.db\n/volume1/screenpipe/#recycle/Copy #8 of archive.db\n/volume1/screenpipe/#recycle/archive.db-journal\n/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #5 of db.sqlite\n/volume1/screenpipe/pipes/.DS_Store\n/volume1/screenpipe/app/.env\n/volume1/screenpipe/app/cli.py\n/volume1/screenpipe/app/.DS_Store\n/volume1/screenpipe/app/db.py\n/volume1/screenpipe/app/docker-compose.yml\n/volume1/screenpipe/app/main.py\n/volume1/screenpipe/app/requirements.txt\n/volume1/screenpipe/app/Dockerfile\n/volume1/screenpipe/data/.DS_Store\n/volume1/screenpipe/.git/description\n/volume1/screenpipe/.git/HEAD\n/volume1/screenpipe/.git/index\n/volume1/screenpipe/.git/COMMIT_EDITMSG\n/volume1/screenpipe/#recycle/data/.DS_Store\n---\napp\napp_settings.json\narchive.db\ndata\ndb.sqlite\ndb.sqlite-shm\ndb.sqlite-wal\npipes\n#recycle\nscreenpipe.db\nscreenpipe_sync.sh","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check pipes directory and docker-compose","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml","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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\ncli.py\nconsumers\ndb.py\ndocker-compose.yml\nDockerfile\nmain.py\n__pycache__\nrequirements.txt\nstatic\nservices:\n screenpipe-app:\n build: .\n container_name: screenpipe-app\n restart: unless-stopped\n ports:\n - \"8766:8000\"\n volumes:\n - /volume1/screenpipe:/data\n env_file:\n - .env\n environment:\n TZ: Europe/Sofia\n DB_PATH: /data/db.sqlite\n\n sqlite-web-archive:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-archive\n restart: unless-stopped\n ports:\n - \"8767:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/archive.db\"]\n\n sqlite-web-live:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-live\n restart: unless-stopped\n ports:\n - \"8768:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/db.sqlite\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"requirements.txt","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"requirements.txt","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Inspect a pipe directory","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/","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":"pipe.md\npipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"List all pipes and their contents","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo \"=== $d ===\"; ls \"$d\"; 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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\n=== /volume1/screenpipe/pipes/ai-habits/ ===\npipe.md\n=== /volume1/screenpipe/pipes/day-recap/ ===\npipe.md\n=== /volume1/screenpipe/pipes/meeting-summary/ ===\npipe.md\n=== /volume1/screenpipe/pipes/standup-update/ ===\npipe.md\n=== /volume1/screenpipe/pipes/time-breakdown/ ===\npipe.md\n=== /volume1/screenpipe/pipes/video-export/ ===\npipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read pipe markdown files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo \"===\" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50","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":"---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.","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":"Read summary consumer","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py","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":"activity.py\naudio.py\nelements.py\n__init__.py\ninteractions.py\nocr.py\n__pycache__\nreport.py\nsummary.py\n\"\"\"AI summary generator using Claude.\"\"\"\nimport os\nfrom datetime import date\nfrom typing import Any\n\nfrom consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary\nfrom consumers.ocr import deduplicated_text\nfrom consumers.audio import formatted_transcript\n\n\nSUMMARY_TYPES = {\n \"day_recap\": {\n \"title\": \"Day Recap\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a concise day recap using EXACTLY this format:\n\n## Summary\nOne sentence: what I mainly worked on today.\n\n## Accomplishments\n- Top 3 things I finished, with approximate times\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things seen or heard, with timestamps\n\n## Unfinished Work\n- What to continue tomorrow\n\n## Patterns\n- Apps used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with:\n**Next step:** [most important thing to continue]\"\"\",\n },\n \"standup\": {\n \"title\": \"Standup Update\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a brief standup update:\n\n**Yesterday:** What I worked on (2-3 bullets)\n**Today:** What I plan to continue (1-2 bullets)\n**Blockers:** Any issues observed (or \"None\")\n\nKeep it under 150 words. Only report what's verifiable from the data.\"\"\",\n },\n \"focus_time\": {\n \"title\": \"Focus & Distraction Analysis\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\nAnalyze focus vs distraction patterns:\n\n## Deep Work Periods\n- When and how long were sustained focus sessions?\n- What was being worked on?\n\n## Distractions\n- Which apps/sites were used recreationally?\n- How much time was lost to context switching?\n\n## Recommendations\n- 2-3 concrete suggestions to improve focus tomorrow\n\nBe specific with times and app names.\"\"\",\n },\n}\n\n\ndef _build_context(for_date: date) -> dict[str, str]:\n apps = app_time(for_date)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(for_date, limit=20)\n url_lines = \"\\n\".join(\n f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls\n )\n\n ui_rows = ui_event_summary(for_date)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(for_date, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(for_date)\n\n return {\n \"app_time\": app_lines or \"(no app data)\",\n \"browser_urls\": url_lines or \"(no browser data)\",\n \"ui_events\": ui_lines or \"(no UI event data)\",\n \"ocr_text\": ocr_lines or \"(no screen data)\",\n \"audio\": audio[:3000] if len(audio) > 3000 else audio,\n }\n\n\ndef generate(\n summary_type: str = \"day_recap\",\n for_date: date | None = None,\n api_key: str | None = None,\n) -> dict[str, Any]:\n \"\"\"Generate an AI summary. Returns dict with 'title', 'content', 'date'.\"\"\"\n import anthropic\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\n \"title\": \"Error\",\n \"content\": \"ANTHROPIC_API_KEY not set. Add it to your .env file.\",\n \"date\": str(d),\n }\n\n spec = SUMMARY_TYPES.get(summary_type)\n if not spec:\n return {\"title\": \"Error\", \"content\": f\"Unknown summary type: {summary_type}\", \"date\": str(d)}\n\n stats = summary_stats(d)\n if stats[\"total_frames\"] == 0:\n return {\n \"title\": spec[\"title\"],\n \"content\": f\"No screen data found for {d}.\",\n \"date\": str(d),\n }\n\n ctx = _build_context(d)\n prompt = spec[\"prompt\"].format(**ctx)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": prompt}],\n )\n\n return {\n \"title\": spec[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","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":"Read all pipe.md files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"for f in /volume1/screenpipe/pipes/*/pipe.md; do echo \"=== $f ===\"; cat \"$f\"; 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":"=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: AI Habits\ndescription: \"How you use AI tools — patterns and insights\"\nicon: \"🤖\"\nfeatured: true\n---\n\nSearch my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## AI Tools Used\n- List each tool with approximate time spent (e.g. \"Claude: ~45min\")\n\n## What I Used Them For\n- For each tool: coding, writing, research, or brainstorming\n\n## Usage Patterns\n- Do I switch between tools? Use them in bursts or steadily?\n\n## Effectiveness\n- Which tool appeared alongside completed work vs. abandoned attempts\n\nIf no AI usage is found, say so clearly. End with: \"**Tip:** [one suggestion to use AI tools more effectively]\"\n\n=== /volume1/screenpipe/pipes/day-recap/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n\n=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.\n\n=== /volume1/screenpipe/pipes/standup-update/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Standup Update\ndescription: \"What you did, what's next, and any blockers\"\nicon: \"🏢\"\nfeatured: true\n---\n\nBased on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Yesterday\n- What I worked on (name specific projects, files, tools, PRs)\n\n## Today\n- What I will work on next (based on unfinished tasks and recent activity)\n\n## Blockers\n- Issues I hit — errors, slow builds, waiting on someone\n- If no blockers, write \"None\"\n\nKeep it under 150 words. Copy-paste ready for a team standup.\n\n=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Time Breakdown\ndescription: \"Where your time went — by app, project, and category\"\nicon: \"⏱\"\nfeatured: false\n---\n\nAnalyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.\n\nRead screenpipe skill first.\n\nUse this exact format with durations and percentages:\n\n## By Application\n- List each app with duration and percentage, sorted by time (e.g. \"VS Code: 2h 15min (28%)\")\n\n## By Category\n- Group into: coding, meetings, browsing, writing, communication, other\n- Show hours and percentage per category\n\n## By Project\n- Group related activities by project/topic. Name specific repos or tasks.\n\n## Productivity Score\n- Calculate: focused_work_hours / total_hours as a percentage\n- Focused = coding + writing. Unfocused = browsing + switching.\n\nEnd with: \"**Suggestion:** [one specific change to improve tomorrow's productivity]\"\n\n=== /volume1/screenpipe/pipes/video-export/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Export Video Clip\ndescription: \"Create a video of your recent screen activity\"\nicon: \"🎬\"\nfeatured: false\n---\n\nExport a video of my screen activity from the last 5 minutes.\n\nRead screenpipe skill first.\n\nUse the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.\n\nIf the export is large, suggest a lower fps or shorter time range.","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 clear picture. The pipes are markdown prompt templates in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe/pipes/","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but there's no code to actually load and run them —","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"has its own hardcoded prompts instead.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Here's what I'll implement:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/pipes.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— two new endpoints:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"GET /api/pipes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /api/pipes/{pipe_id}/run","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cli.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— a","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"command to run pipes from the terminal","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Let me build it:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check browser_urls signature","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/consumers/activity.py | grep \"def browser_urls\" -A 5","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":"def browser_urls(\n for_date: date | None = None,\n app_name: str | None = None,\n ts_from: str | None = None,\n ts_to: str | None = None,\n limit: int = 30,","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":"pipes.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipes.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"143 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"\"\"\"Dynamic pipe loader and runner.\"\"\"\nimport os\nimport re\nfrom datetime import date\nfrom pathlib import Path\nfrom typing import Any\n\n\ndef _parse_frontmatter(text: str) -> tuple[dict, str]:\n if not text.startswith(\"---\"):\n return {}, text\n try:\n end = text.index(\"---\", 3)\n except ValueError:\n return {}, text\n fm_text = text[3:end].strip()\n body = text[end + 3:].strip()\n meta: dict = {}\n for line in fm_text.splitlines():\n if \":\" in line:\n k, _, v = line.partition(\":\")\n meta[k.strip()] = v.strip().strip('\"')\n return meta, body\n\n\ndef load_pipes(pipes_dir: Path) -> list[dict]:\n if not pipes_dir.exists():\n return []\n pipes = []\n for pipe_dir in sorted(pipes_dir.iterdir()):\n if not pipe_dir.is_dir() or pipe_dir.name.startswith(\".\"):\n continue\n pipe_md = pipe_dir / \"pipe.md\"\n if not pipe_md.exists():\n continue\n text = pipe_md.read_text(encoding=\"utf-8\")\n meta, body = _parse_frontmatter(text)\n if meta.get(\"enabled\", \"true\").lower() == \"false\":\n continue\n body = re.sub(r\"Read screenpipe skill first\\.?\\n?\", \"\", body).strip()\n pipes.append({\n \"id\": pipe_dir.name,\n \"title\": meta.get(\"title\", pipe_dir.name),\n \"description\": meta.get(\"description\", \"\"),\n \"icon\": meta.get(\"icon\", \"\"),\n \"schedule\": meta.get(\"schedule\", \"manual\"),\n \"featured\": meta.get(\"featured\", \"false\").lower() == \"true\",\n \"prompt\": body,\n })\n return pipes\n\n\ndef _build_system(d: date, stats: dict) -> str:\n from consumers.activity import app_time, browser_urls, ui_event_summary\n from consumers.ocr import deduplicated_text\n from consumers.audio import formatted_transcript\n\n apps = app_time(d)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(d, limit=20)\n url_lines = \"\\n\".join(f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls)\n\n ui_rows = ui_event_summary(d)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(d, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(d)\n if len(audio) > 3000:\n audio = audio[:3000]\n\n return f\"\"\"You are analyzing screenpipe data — recordings of a person's computer activity.\n\n## App usage (minutes per app):\n{app_lines or '(no app data)'}\n\n## Browser URLs visited:\n{url_lines or '(no browser data)'}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_lines or '(no UI event data)'}\n\n## Screen content (sampled every 5 minutes):\n{ocr_lines or '(no screen data)'}\n\n## Audio / speech:\n{audio or '(no audio data)'}\n\nDate: {d}\nTotal frames recorded: {stats['total_frames']}\"\"\"\n\n\ndef run_pipe(\n pipe_id: str,\n for_date: date | None = None,\n api_key: str | None = None,\n pipes_dir: Path | None = None,\n) -> dict[str, Any]:\n import anthropic\n from consumers.activity import summary_stats\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\"title\": \"Error\", \"content\": \"ANTHROPIC_API_KEY not set.\", \"date\": str(d)}\n\n _pipes_dir = pipes_dir or Path(os.environ.get(\"PIPES_DIR\", \"/data/pipes\"))\n all_pipes = {p[\"id\"]: p for p in load_pipes(_pipes_dir)}\n\n if pipe_id not in all_pipes:\n return {\"title\": \"Error\", \"content\": f\"Pipe not found: {pipe_id}\", \"date\": str(d)}\n\n pipe = all_pipes[pipe_id]\n stats = summary_stats(d)\n\n if stats[\"total_frames\"] == 0:\n return {\"title\": pipe[\"title\"], \"content\": f\"No screen data found for {d}.\", \"date\": str(d)}\n\n system = _build_system(d, stats)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n system=system,\n messages=[{\"role\": \"user\", \"content\": pipe[\"prompt\"]}],\n )\n\n return {\n \"title\": pipe[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the API endpoints to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the pipe endpoints at the end of main.py, before the closing summary section:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 14 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the CLI command to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":23,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 40 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Done. Here's how to run pipes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXHeading","text":"How to run pipes","depth":22,"on_screen":false,"role_description":"heading"},{"role":"AXStaticText","text":"How to run pipes","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via Docker (inside the running container):","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"docker exec -it screenpipe-app python cli.py pipe --list\ndocker exec -it screenpipe-app python cli.py pipe day-recap\ndocker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Via the API","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"(once the container is running on port 8766):","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"# List pipes\ncurl http://localhost:8766/api/pipes\n\n# Run a pipe\ncurl -X POST \"http://localhost:8766/api/pipes/day-recap/run\"\ncurl -X POST \"http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25\"","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Rebuild and restart","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"to pick up the changes:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Copy code to clipboard","depth":23,"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":"cd /volume1/screenpipe/app\ndocker compose up --build -d","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"How it works:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Each","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The \"Read screenpipe skill first\" line is stripped automatically.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"The pipes directory inside Docker is","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/data/pipes","depth":24,"on_screen":false,"role_description":"text"}]...
|
-2613766441503901608
|
-8763496505197737748
|
idle
|
accessibility
|
NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines
Now add the CLI command to
cli.py
cli.py
:
Edit
cli.py
cli.py
Added 40 lines
Done. Here's how to run pipes:
How to run pipes
How to run pipes
Via Docker (inside the running container):
Copy code to clipboard
docker exec -it screenpipe-app python cli.py pipe --list
docker exec -it screenpipe-app python cli.py pipe day-recap
docker exec -it screenpipe-app python cli.py pipe standup-update --date yesterday
Via the API
(once the container is running on port 8766):
Copy code to clipboard
# List pipes
curl http://localhost:8766/api/pipes
# Run a pipe
curl -X POST "http://localhost:8766/api/pipes/day-recap/run"
curl -X POST "http://localhost:8766/api/pipes/standup-update/run?d=2026-04-25"
Rebuild and restart
to pick up the changes:
Copy code to clipboard
cd /volume1/screenpipe/app
docker compose up --build -d
How it works:
Each
pipe.md
file is loaded dynamically — the frontmatter provides metadata and the body becomes the user prompt. Screenpipe data (app usage, browser URLs, OCR, audio) is injected as a Claude system message so the pipe prompt can reference it naturally. The "Read screenpipe skill first" line is stripped automatically.
The pipes directory inside Docker is
/data/pipes...
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NULL
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NULL
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NULL
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NULL
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21058
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NULL
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0
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2026-05-11T17:05:46.228349+00:00
|
/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519146228_m1.jpg...
|
Code
|
Implement and run pipe l… — screenpipe [SSH: nas]
|
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
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines...
|
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Problems","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":"0","depth":17,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"","depth":17,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"0","depth":17,"on_screen":true,"role_description":"text"},{"role":"AXButton","text":"Forwarded Ports: 8766","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":"1","depth":17,"on_screen":true,"role_description":"text"},{"role":"AXButton","text":"Notifications","depth":16,"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Sign In","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":"Sign In","depth":17,"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"Info: Setting up SSH Host nas: Setting up SSH tunnel","depth":12,"on_screen":false,"role_description":"text"},{"role":"AXButton","text":"Implement and run pipe logic","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":"main.py","depth":23,"on_screen":false,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"lets implement logic with pipes. how can I run 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":"Let me look at the current project structure to understand what's already in place.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"List project files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"find /volume1/screenpipe -type f | head -50 && echo \"---\" && ls /volume1/screenpipe","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":"/volume1/screenpipe/.DS_Store\n/volume1/screenpipe/screenpipe.db\n/volume1/screenpipe/screenpipe_sync.sh\n/volume1/screenpipe/app_settings.json\n/volume1/screenpipe/.gitignore\n/volume1/screenpipe/archive.db\n/volume1/screenpipe/db.sqlite\n/volume1/screenpipe/db.sqlite-wal\n/volume1/screenpipe/db.sqlite-shm\n/volume1/screenpipe/#recycle/desktop.ini\n/volume1/screenpipe/#recycle/db.sqlite\n/volume1/screenpipe/#recycle/Copy #1 of db.sqlite\n/volume1/screenpipe/#recycle/.DS_Store\n/volume1/screenpipe/#recycle/Copy #2 of db.sqlite\n/volume1/screenpipe/#recycle/archive.db\n/volume1/screenpipe/#recycle/Copy #1 of archive.db\n/volume1/screenpipe/#recycle/Copy #2 of archive.db\n/volume1/screenpipe/#recycle/Copy #3 of archive.db\n/volume1/screenpipe/#recycle/Copy #4 of archive.db\n/volume1/screenpipe/#recycle/Copy #5 of archive.db\n/volume1/screenpipe/#recycle/Copy #3 of db.sqlite\n/volume1/screenpipe/#recycle/Copy #4 of db.sqlite\n/volume1/screenpipe/#recycle/Copy #6 of archive.db\n/volume1/screenpipe/#recycle/test.txt\n/volume1/screenpipe/#recycle/Copy #7 of archive.db\n/volume1/screenpipe/#recycle/Copy #8 of archive.db\n/volume1/screenpipe/#recycle/archive.db-journal\n/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal\n/volume1/screenpipe/#recycle/Copy #5 of db.sqlite\n/volume1/screenpipe/pipes/.DS_Store\n/volume1/screenpipe/app/.env\n/volume1/screenpipe/app/cli.py\n/volume1/screenpipe/app/.DS_Store\n/volume1/screenpipe/app/db.py\n/volume1/screenpipe/app/docker-compose.yml\n/volume1/screenpipe/app/main.py\n/volume1/screenpipe/app/requirements.txt\n/volume1/screenpipe/app/Dockerfile\n/volume1/screenpipe/data/.DS_Store\n/volume1/screenpipe/.git/description\n/volume1/screenpipe/.git/HEAD\n/volume1/screenpipe/.git/index\n/volume1/screenpipe/.git/COMMIT_EDITMSG\n/volume1/screenpipe/#recycle/data/.DS_Store\n---\napp\napp_settings.json\narchive.db\ndata\ndb.sqlite\ndb.sqlite-shm\ndb.sqlite-wal\npipes\n#recycle\nscreenpipe.db\nscreenpipe_sync.sh","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check pipes directory and docker-compose","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml","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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\ncli.py\nconsumers\ndb.py\ndocker-compose.yml\nDockerfile\nmain.py\n__pycache__\nrequirements.txt\nstatic\nservices:\n screenpipe-app:\n build: .\n container_name: screenpipe-app\n restart: unless-stopped\n ports:\n - \"8766:8000\"\n volumes:\n - /volume1/screenpipe:/data\n env_file:\n - .env\n environment:\n TZ: Europe/Sofia\n DB_PATH: /data/db.sqlite\n\n sqlite-web-archive:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-archive\n restart: unless-stopped\n ports:\n - \"8767:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/archive.db\"]\n\n sqlite-web-live:\n image: ghcr.io/coleifer/sqlite-web:latest\n container_name: screenpipe-sqlweb-live\n restart: unless-stopped\n ports:\n - \"8768:8080\"\n volumes:\n - /volume1/screenpipe:/data\n command: [\"-H\", \"0.0.0.0\", \"-r\", \"/data/db.sqlite\"]","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"requirements.txt","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"requirements.txt","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Inspect a pipe directory","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/","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":"pipe.md\npipe.md","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"cli.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"cli.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"List all pipes and their contents","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo \"=== $d ===\"; ls \"$d\"; 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":"ai-habits\nday-recap\nmeeting-summary\nstandup-update\ntime-breakdown\nvideo-export\n=== /volume1/screenpipe/pipes/ai-habits/ ===\npipe.md\n=== /volume1/screenpipe/pipes/day-recap/ ===\npipe.md\n=== /volume1/screenpipe/pipes/meeting-summary/ ===\npipe.md\n=== /volume1/screenpipe/pipes/standup-update/ ===\npipe.md\n=== /volume1/screenpipe/pipes/time-breakdown/ ===\npipe.md\n=== /volume1/screenpipe/pipes/video-export/ ===\npipe.md","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read pipe markdown files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo \"===\" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50","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":"---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.","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":"Read summary consumer","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py","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":"activity.py\naudio.py\nelements.py\n__init__.py\ninteractions.py\nocr.py\n__pycache__\nreport.py\nsummary.py\n\"\"\"AI summary generator using Claude.\"\"\"\nimport os\nfrom datetime import date\nfrom typing import Any\n\nfrom consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary\nfrom consumers.ocr import deduplicated_text\nfrom consumers.audio import formatted_transcript\n\n\nSUMMARY_TYPES = {\n \"day_recap\": {\n \"title\": \"Day Recap\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a concise day recap using EXACTLY this format:\n\n## Summary\nOne sentence: what I mainly worked on today.\n\n## Accomplishments\n- Top 3 things I finished, with approximate times\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things seen or heard, with timestamps\n\n## Unfinished Work\n- What to continue tomorrow\n\n## Patterns\n- Apps used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with:\n**Next step:** [most important thing to continue]\"\"\",\n },\n \"standup\": {\n \"title\": \"Standup Update\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\n## Audio/speech:\n{audio}\n\nWrite a brief standup update:\n\n**Yesterday:** What I worked on (2-3 bullets)\n**Today:** What I plan to continue (1-2 bullets)\n**Blockers:** Any issues observed (or \"None\")\n\nKeep it under 150 words. Only report what's verifiable from the data.\"\"\",\n },\n \"focus_time\": {\n \"title\": \"Focus & Distraction Analysis\",\n \"prompt\": \"\"\"\\\nYou are analyzing a person's computer activity for the day.\n\n## App usage (minutes per app):\n{app_time}\n\n## Browser URLs visited:\n{browser_urls}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_events}\n\n## Screen content (sampled every 5 minutes):\n{ocr_text}\n\nAnalyze focus vs distraction patterns:\n\n## Deep Work Periods\n- When and how long were sustained focus sessions?\n- What was being worked on?\n\n## Distractions\n- Which apps/sites were used recreationally?\n- How much time was lost to context switching?\n\n## Recommendations\n- 2-3 concrete suggestions to improve focus tomorrow\n\nBe specific with times and app names.\"\"\",\n },\n}\n\n\ndef _build_context(for_date: date) -> dict[str, str]:\n apps = app_time(for_date)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(for_date, limit=20)\n url_lines = \"\\n\".join(\n f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls\n )\n\n ui_rows = ui_event_summary(for_date)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(for_date, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(for_date)\n\n return {\n \"app_time\": app_lines or \"(no app data)\",\n \"browser_urls\": url_lines or \"(no browser data)\",\n \"ui_events\": ui_lines or \"(no UI event data)\",\n \"ocr_text\": ocr_lines or \"(no screen data)\",\n \"audio\": audio[:3000] if len(audio) > 3000 else audio,\n }\n\n\ndef generate(\n summary_type: str = \"day_recap\",\n for_date: date | None = None,\n api_key: str | None = None,\n) -> dict[str, Any]:\n \"\"\"Generate an AI summary. Returns dict with 'title', 'content', 'date'.\"\"\"\n import anthropic\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\n \"title\": \"Error\",\n \"content\": \"ANTHROPIC_API_KEY not set. Add it to your .env file.\",\n \"date\": str(d),\n }\n\n spec = SUMMARY_TYPES.get(summary_type)\n if not spec:\n return {\"title\": \"Error\", \"content\": f\"Unknown summary type: {summary_type}\", \"date\": str(d)}\n\n stats = summary_stats(d)\n if stats[\"total_frames\"] == 0:\n return {\n \"title\": spec[\"title\"],\n \"content\": f\"No screen data found for {d}.\",\n \"date\": str(d),\n }\n\n ctx = _build_context(d)\n prompt = spec[\"prompt\"].format(**ctx)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n messages=[{\"role\": \"user\", \"content\": prompt}],\n )\n\n return {\n \"title\": spec[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","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":"Read all pipe.md files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"for f in /volume1/screenpipe/pipes/*/pipe.md; do echo \"=== $f ===\"; cat \"$f\"; 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":"=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: AI Habits\ndescription: \"How you use AI tools — patterns and insights\"\nicon: \"🤖\"\nfeatured: true\n---\n\nSearch my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## AI Tools Used\n- List each tool with approximate time spent (e.g. \"Claude: ~45min\")\n\n## What I Used Them For\n- For each tool: coding, writing, research, or brainstorming\n\n## Usage Patterns\n- Do I switch between tools? Use them in bursts or steadily?\n\n## Effectiveness\n- Which tool appeared alongside completed work vs. abandoned attempts\n\nIf no AI usage is found, say so clearly. End with: \"**Tip:** [one suggestion to use AI tools more effectively]\"\n\n=== /volume1/screenpipe/pipes/day-recap/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Day Recap\ndescription: \"Today's accomplishments, key moments, and unfinished work\"\nicon: \"📋\"\nfeatured: true\n---\n\nAnalyze my screen and audio recordings from today (last 16 hours only). \n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Summary\nOne sentence: what I mainly did today.\n\n## Accomplishments\n- Top 3 things I finished, with timestamps (e.g. \"2:30 PM\")\n- Name specific apps, files, or projects\n\n## Key Moments\n- Important things I saw, said, or heard — with timestamps\n\n## Unfinished Work\n- What I should continue tomorrow — name the app/file/task\n\n## Patterns\n- Apps I used most, topics that came up repeatedly\n\nOnly report what you can verify from the data. End with: \"**Next step:** [most important thing to continue]\"\n\n=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Meeting Summary\ndescription: \"Summarize meeting transcript with key takeaways and action items\"\nicon: \"🤝\"\nfeatured: false\n---\n\nSummarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Meeting Summary\nOne sentence: what this meeting was about.\n\n## Key Takeaways\n- Top 3-5 important points discussed\n- Include who said what when relevant\n\n## Action Items\n- [ ] Task — assigned to whom, deadline if mentioned\n- [ ] Task — assigned to whom\n\n## Decisions Made\n- List any decisions or agreements reached\n\n## Open Questions\n- Anything unresolved or needing follow-up\n\nKeep it concise and actionable.\n\n=== /volume1/screenpipe/pipes/standup-update/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Standup Update\ndescription: \"What you did, what's next, and any blockers\"\nicon: \"🏢\"\nfeatured: true\n---\n\nBased on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.\n\nRead screenpipe skill first.\n\nUse this exact format:\n\n## Yesterday\n- What I worked on (name specific projects, files, tools, PRs)\n\n## Today\n- What I will work on next (based on unfinished tasks and recent activity)\n\n## Blockers\n- Issues I hit — errors, slow builds, waiting on someone\n- If no blockers, write \"None\"\n\nKeep it under 150 words. Copy-paste ready for a team standup.\n\n=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Time Breakdown\ndescription: \"Where your time went — by app, project, and category\"\nicon: \"⏱\"\nfeatured: false\n---\n\nAnalyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.\n\nRead screenpipe skill first.\n\nUse this exact format with durations and percentages:\n\n## By Application\n- List each app with duration and percentage, sorted by time (e.g. \"VS Code: 2h 15min (28%)\")\n\n## By Category\n- Group into: coding, meetings, browsing, writing, communication, other\n- Show hours and percentage per category\n\n## By Project\n- Group related activities by project/topic. Name specific repos or tasks.\n\n## Productivity Score\n- Calculate: focused_work_hours / total_hours as a percentage\n- Focused = coding + writing. Unfocused = browsing + switching.\n\nEnd with: \"**Suggestion:** [one specific change to improve tomorrow's productivity]\"\n\n=== /volume1/screenpipe/pipes/video-export/pipe.md ===\n---\nschedule: manual\nenabled: true\ntemplate: true\ntitle: Export Video Clip\ndescription: \"Create a video of your recent screen activity\"\nicon: \"🎬\"\nfeatured: false\n---\n\nExport a video of my screen activity from the last 5 minutes.\n\nRead screenpipe skill first.\n\nUse the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.\n\nIf the export is large, suggest a lower fps or shorter time range.","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 clear picture. The pipes are markdown prompt templates in","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"/volume1/screenpipe/pipes/","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":", but there's no code to actually load and run them —","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/summary.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"has its own hardcoded prompts instead.","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Here's what I'll implement:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"consumers/pipes.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— two new endpoints:","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"GET /api/pipes","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"and","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"POST /api/pipes/{pipe_id}/run","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cli.py","depth":26,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"— a","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"pipe","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"command to run pipes from the terminal","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Let me build it:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check browser_urls signature","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"cat /volume1/screenpipe/app/consumers/activity.py | grep \"def browser_urls\" -A 5","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":"def browser_urls(\n for_date: date | None = None,\n app_name: str | None = None,\n ts_from: str | None = None,\n ts_to: str | None = None,\n limit: int = 30,","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":"pipes.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"pipes.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"143 lines","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"\"\"\"Dynamic pipe loader and runner.\"\"\"\nimport os\nimport re\nfrom datetime import date\nfrom pathlib import Path\nfrom typing import Any\n\n\ndef _parse_frontmatter(text: str) -> tuple[dict, str]:\n if not text.startswith(\"---\"):\n return {}, text\n try:\n end = text.index(\"---\", 3)\n except ValueError:\n return {}, text\n fm_text = text[3:end].strip()\n body = text[end + 3:].strip()\n meta: dict = {}\n for line in fm_text.splitlines():\n if \":\" in line:\n k, _, v = line.partition(\":\")\n meta[k.strip()] = v.strip().strip('\"')\n return meta, body\n\n\ndef load_pipes(pipes_dir: Path) -> list[dict]:\n if not pipes_dir.exists():\n return []\n pipes = []\n for pipe_dir in sorted(pipes_dir.iterdir()):\n if not pipe_dir.is_dir() or pipe_dir.name.startswith(\".\"):\n continue\n pipe_md = pipe_dir / \"pipe.md\"\n if not pipe_md.exists():\n continue\n text = pipe_md.read_text(encoding=\"utf-8\")\n meta, body = _parse_frontmatter(text)\n if meta.get(\"enabled\", \"true\").lower() == \"false\":\n continue\n body = re.sub(r\"Read screenpipe skill first\\.?\\n?\", \"\", body).strip()\n pipes.append({\n \"id\": pipe_dir.name,\n \"title\": meta.get(\"title\", pipe_dir.name),\n \"description\": meta.get(\"description\", \"\"),\n \"icon\": meta.get(\"icon\", \"\"),\n \"schedule\": meta.get(\"schedule\", \"manual\"),\n \"featured\": meta.get(\"featured\", \"false\").lower() == \"true\",\n \"prompt\": body,\n })\n return pipes\n\n\ndef _build_system(d: date, stats: dict) -> str:\n from consumers.activity import app_time, browser_urls, ui_event_summary\n from consumers.ocr import deduplicated_text\n from consumers.audio import formatted_transcript\n\n apps = app_time(d)\n app_lines = \"\\n\".join(f\"- {a['app_name']}: {a['minutes']} min\" for a in apps[:20])\n\n urls = browser_urls(d, limit=20)\n url_lines = \"\\n\".join(f\"- {u['browser_url'][:100]} ({u['minutes']} min)\" for u in urls)\n\n ui_rows = ui_event_summary(d)\n ui_lines = \"\\n\".join(\n f\"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches\"\n for r in ui_rows[:15]\n )\n\n ocr_rows = deduplicated_text(d, chunk_minutes=5)\n ocr_lines = \"\\n\".join(\n f\"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}\"\n for r in ocr_rows[:100]\n )\n\n audio = formatted_transcript(d)\n if len(audio) > 3000:\n audio = audio[:3000]\n\n return f\"\"\"You are analyzing screenpipe data — recordings of a person's computer activity.\n\n## App usage (minutes per app):\n{app_lines or '(no app data)'}\n\n## Browser URLs visited:\n{url_lines or '(no browser data)'}\n\n## UI activity per app (clicks / keystrokes / app-switches):\n{ui_lines or '(no UI event data)'}\n\n## Screen content (sampled every 5 minutes):\n{ocr_lines or '(no screen data)'}\n\n## Audio / speech:\n{audio or '(no audio data)'}\n\nDate: {d}\nTotal frames recorded: {stats['total_frames']}\"\"\"\n\n\ndef run_pipe(\n pipe_id: str,\n for_date: date | None = None,\n api_key: str | None = None,\n pipes_dir: Path | None = None,\n) -> dict[str, Any]:\n import anthropic\n from consumers.activity import summary_stats\n\n d = for_date or date.today()\n key = api_key or os.environ.get(\"ANTHROPIC_API_KEY\", \"\")\n if not key:\n return {\"title\": \"Error\", \"content\": \"ANTHROPIC_API_KEY not set.\", \"date\": str(d)}\n\n _pipes_dir = pipes_dir or Path(os.environ.get(\"PIPES_DIR\", \"/data/pipes\"))\n all_pipes = {p[\"id\"]: p for p in load_pipes(_pipes_dir)}\n\n if pipe_id not in all_pipes:\n return {\"title\": \"Error\", \"content\": f\"Pipe not found: {pipe_id}\", \"date\": str(d)}\n\n pipe = all_pipes[pipe_id]\n stats = summary_stats(d)\n\n if stats[\"total_frames\"] == 0:\n return {\"title\": pipe[\"title\"], \"content\": f\"No screen data found for {d}.\", \"date\": str(d)}\n\n system = _build_system(d, stats)\n\n client = anthropic.Anthropic(api_key=key)\n message = client.messages.create(\n model=\"claude-haiku-4-5-20251001\",\n max_tokens=1024,\n system=system,\n messages=[{\"role\": \"user\", \"content\": pipe[\"prompt\"]}],\n )\n\n return {\n \"title\": pipe[\"title\"],\n \"content\": message.content[0].text,\n \"date\": str(d),\n \"stats\": stats,\n }","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the API endpoints to","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"main.py","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":":","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 1 line","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Now add the pipe endpoints at the end of main.py, before the closing summary section:","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Edit","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"main.py","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"main.py","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Added 14 lines","depth":24,"on_screen":false,"role_description":"text"}]...
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idle
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accessibility
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NULL
|
Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
app
__pycache__
consumers
static
.env
cli.py
M
db.py
docker-compose.yml
Dockerfile
M
main.py
M
requirements.txt
M
data
logs
pipes
.gitignore
app_settings.json
archive.db
archive.db-bak
U
db.sqlite
db.sqlite-shm
db.sqlite-wal
screenpipe_sync_updated.sh
U
screenpipe_sync.sh
screenpipe.db
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
app_settings.json, Editor Group 1
screenpipe_sync.sh, Editor Group 1
pipe.md, Editor Group 1
.env, Editor Group 1
[ENV_SECRET]
[ENV_SECRET]
Implement and run pipe l…, Editor Group 2
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports - 1 forwarded port
PORTS
1
remote SSH: nas
SSH: nas
screenpipe (Git) - master*, Checkout Branch/Tag...
master*
screenpipe (Git) - Synchronize Changes
No Problems
0
0
Forwarded Ports: 8766
1
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: Setting up SSH tunnel
Implement and run pipe logic
Session history
New session
Message actions
main.py
main.py
lets implement logic with pipes. how can I run it?
Thinking
Thinking
Let me look at the current project structure to understand what's already in place.
Bash
List project files
IN
find /volume1/screenpipe -type f | head -50 && echo "---" && ls /volume1/screenpipe
Copy code to clipboard
OUT
/volume1/screenpipe/.DS_Store
/volume1/screenpipe/screenpipe.db
/volume1/screenpipe/screenpipe_sync.sh
/volume1/screenpipe/app_settings.json
/volume1/screenpipe/.gitignore
/volume1/screenpipe/archive.db
/volume1/screenpipe/db.sqlite
/volume1/screenpipe/db.sqlite-wal
/volume1/screenpipe/db.sqlite-shm
/volume1/screenpipe/#recycle/desktop.ini
/volume1/screenpipe/#recycle/db.sqlite
/volume1/screenpipe/#recycle/Copy #1 of db.sqlite
/volume1/screenpipe/#recycle/.DS_Store
/volume1/screenpipe/#recycle/Copy #2 of db.sqlite
/volume1/screenpipe/#recycle/archive.db
/volume1/screenpipe/#recycle/Copy #1 of archive.db
/volume1/screenpipe/#recycle/Copy #2 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of archive.db
/volume1/screenpipe/#recycle/Copy #4 of archive.db
/volume1/screenpipe/#recycle/Copy #5 of archive.db
/volume1/screenpipe/#recycle/Copy #3 of db.sqlite
/volume1/screenpipe/#recycle/Copy #4 of db.sqlite
/volume1/screenpipe/#recycle/Copy #6 of archive.db
/volume1/screenpipe/#recycle/test.txt
/volume1/screenpipe/#recycle/Copy #7 of archive.db
/volume1/screenpipe/#recycle/Copy #8 of archive.db
/volume1/screenpipe/#recycle/archive.db-journal
/volume1/screenpipe/#recycle/Copy #1 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #2 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #3 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #4 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #6 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #7 of archive.db-journal
/volume1/screenpipe/#recycle/Copy #5 of db.sqlite
/volume1/screenpipe/pipes/.DS_Store
/volume1/screenpipe/app/.env
/volume1/screenpipe/app/cli.py
/volume1/screenpipe/app/.DS_Store
/volume1/screenpipe/app/db.py
/volume1/screenpipe/app/docker-compose.yml
/volume1/screenpipe/app/main.py
/volume1/screenpipe/app/requirements.txt
/volume1/screenpipe/app/Dockerfile
/volume1/screenpipe/data/.DS_Store
/volume1/screenpipe/.git/description
/volume1/screenpipe/.git/HEAD
/volume1/screenpipe/.git/index
/volume1/screenpipe/.git/COMMIT_EDITMSG
/volume1/screenpipe/#recycle/data/.DS_Store
---
app
app_settings.json
archive.db
data
db.sqlite
db.sqlite-shm
db.sqlite-wal
pipes
#recycle
screenpipe.db
screenpipe_sync.sh
Read
main.py
main.py
Bash
Check pipes directory and docker-compose
IN
ls /volume1/screenpipe/pipes/ && ls /volume1/screenpipe/app/ && cat /volume1/screenpipe/app/docker-compose.yml
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
cli.py
consumers
db.py
docker-compose.yml
Dockerfile
main.py
__pycache__
requirements.txt
static
services:
screenpipe-app:
build: .
container_name: screenpipe-app
restart: unless-stopped
ports:
- "8766:8000"
volumes:
- /volume1/screenpipe:/data
env_file:
- .env
environment:
TZ: Europe/Sofia
DB_PATH: /data/db.sqlite
sqlite-web-archive:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-archive
restart: unless-stopped
ports:
- "8767:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/archive.db"]
sqlite-web-live:
image: ghcr.io/coleifer/sqlite-web:latest
container_name: screenpipe-sqlweb-live
restart: unless-stopped
ports:
- "8768:8080"
volumes:
- /volume1/screenpipe:/data
command: ["-H", "[IP_ADDRESS]", "-r", "/data/db.sqlite"]
Read
requirements.txt
requirements.txt
Bash
Inspect a pipe directory
IN
ls /volume1/screenpipe/pipes/day-recap/ && cat /volume1/screenpipe/pipes/day-recap/pipe.json 2>/dev/null || ls /volume1/screenpipe/pipes/day-recap/
Copy code to clipboard
OUT
pipe.md
pipe.md
Read
cli.py
cli.py
Bash
List all pipes and their contents
IN
ls /volume1/screenpipe/pipes/ && for d in /volume1/screenpipe/pipes/*/; do echo "=== $d ==="; ls "$d"; done
Copy code to clipboard
OUT
ai-habits
day-recap
meeting-summary
standup-update
time-breakdown
video-export
=== /volume1/screenpipe/pipes/ai-habits/ ===
pipe.md
=== /volume1/screenpipe/pipes/day-recap/ ===
pipe.md
=== /volume1/screenpipe/pipes/meeting-summary/ ===
pipe.md
=== /volume1/screenpipe/pipes/standup-update/ ===
pipe.md
=== /volume1/screenpipe/pipes/time-breakdown/ ===
pipe.md
=== /volume1/screenpipe/pipes/video-export/ ===
pipe.md
Bash
Read pipe markdown files
IN
cat /volume1/screenpipe/pipes/day-recap/pipe.md && echo "===" && cat /volume1/screenpipe/pipes/meeting-summary/pipe.md 2>/dev/null | head -50
Copy code to clipboard
OUT
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
Thinking
Thinking
Bash
Read summary consumer
IN
ls /volume1/screenpipe/app/consumers/ && cat /volume1/screenpipe/app/consumers/summary.py
Copy code to clipboard
OUT
activity.py
audio.py
elements.py
__init__.py
interactions.py
ocr.py
__pycache__
report.py
summary.py
"""AI summary generator using Claude."""
import os
from datetime import date
from typing import Any
from consumers.activity import app_time, summary_stats, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
SUMMARY_TYPES = {
"day_recap": {
"title": "Day Recap",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a concise day recap using EXACTLY this format:
## Summary
One sentence: what I mainly worked on today.
## Accomplishments
- Top 3 things I finished, with approximate times
- Name specific apps, files, or projects
## Key Moments
- Important things seen or heard, with timestamps
## Unfinished Work
- What to continue tomorrow
## Patterns
- Apps used most, topics that came up repeatedly
Only report what you can verify from the data. End with:
**Next step:** [most important thing to continue]""",
},
"standup": {
"title": "Standup Update",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
## Audio/speech:
{audio}
Write a brief standup update:
**Yesterday:** What I worked on (2-3 bullets)
**Today:** What I plan to continue (1-2 bullets)
**Blockers:** Any issues observed (or "None")
Keep it under 150 words. Only report what's verifiable from the data.""",
},
"focus_time": {
"title": "Focus & Distraction Analysis",
"prompt": """\
You are analyzing a person's computer activity for the day.
## App usage (minutes per app):
{app_time}
## Browser URLs visited:
{browser_urls}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_events}
## Screen content (sampled every 5 minutes):
{ocr_text}
Analyze focus vs distraction patterns:
## Deep Work Periods
- When and how long were sustained focus sessions?
- What was being worked on?
## Distractions
- Which apps/sites were used recreationally?
- How much time was lost to context switching?
## Recommendations
- 2-3 concrete suggestions to improve focus tomorrow
Be specific with times and app names.""",
},
}
def _build_context(for_date: date) -> dict[str, str]:
apps = app_time(for_date)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(for_date, limit=20)
url_lines = "\n".join(
f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls
)
ui_rows = ui_event_summary(for_date)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(for_date, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(for_date)
return {
"app_time": app_lines or "(no app data)",
"browser_urls": url_lines or "(no browser data)",
"ui_events": ui_lines or "(no UI event data)",
"ocr_text": ocr_lines or "(no screen data)",
"audio": audio[:3000] if len(audio) > 3000 else audio,
}
def generate(
summary_type: str = "day_recap",
for_date: date | None = None,
api_key: str | None = None,
) -> dict[str, Any]:
"""Generate an AI summary. Returns dict with 'title', 'content', 'date'."""
import anthropic
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {
"title": "Error",
"content": "ANTHROPIC_API_KEY not set. Add it to your .env file.",
"date": str(d),
}
spec = SUMMARY_TYPES.get(summary_type)
if not spec:
return {"title": "Error", "content": f"Unknown summary type: {summary_type}", "date": str(d)}
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {
"title": spec["title"],
"content": f"No screen data found for {d}.",
"date": str(d),
}
ctx = _build_context(d)
prompt = spec["prompt"].format(**ctx)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
messages=[{"role": "user", "content": prompt}],
)
return {
"title": spec["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Thinking
Thinking
Bash
Read all pipe.md files
IN
for f in /volume1/screenpipe/pipes/*/pipe.md; do echo "=== $f ==="; cat "$f"; echo; done
Copy code to clipboard
OUT
=== /volume1/screenpipe/pipes/ai-habits/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: AI Habits
description: "How you use AI tools — patterns and insights"
icon: "🤖"
featured: true
---
Search my recordings from the last 24 hours for AI tool usage. Use app_name filter for each tool separately: ChatGPT, Claude, Copilot, Cursor, Gemini, Perplexity. Use limit=5 per search, max 6 searches total.
Read screenpipe skill first.
Use this exact format:
## AI Tools Used
- List each tool with approximate time spent (e.g. "Claude: ~45min")
## What I Used Them For
- For each tool: coding, writing, research, or brainstorming
## Usage Patterns
- Do I switch between tools? Use them in bursts or steadily?
## Effectiveness
- Which tool appeared alongside completed work vs. abandoned attempts
If no AI usage is found, say so clearly. End with: "**Tip:** [one suggestion to use AI tools more effectively]"
=== /volume1/screenpipe/pipes/day-recap/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Day Recap
description: "Today's accomplishments, key moments, and unfinished work"
icon: "📋"
featured: true
---
Analyze my screen and audio recordings from today (last 16 hours only).
Read screenpipe skill first.
Use this exact format:
## Summary
One sentence: what I mainly did today.
## Accomplishments
- Top 3 things I finished, with timestamps (e.g. "2:30 PM")
- Name specific apps, files, or projects
## Key Moments
- Important things I saw, said, or heard — with timestamps
## Unfinished Work
- What I should continue tomorrow — name the app/file/task
## Patterns
- Apps I used most, topics that came up repeatedly
Only report what you can verify from the data. End with: "**Next step:** [most important thing to continue]"
=== /volume1/screenpipe/pipes/meeting-summary/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Meeting Summary
description: "Summarize meeting transcript with key takeaways and action items"
icon: "🤝"
featured: false
---
Summarize the meeting transcript provided in the context. Include key takeaways and action items. If the meeting is marked as ongoing, note that and summarize what's available so far.
Read screenpipe skill first.
Use this exact format:
## Meeting Summary
One sentence: what this meeting was about.
## Key Takeaways
- Top 3-5 important points discussed
- Include who said what when relevant
## Action Items
- [ ] Task — assigned to whom, deadline if mentioned
- [ ] Task — assigned to whom
## Decisions Made
- List any decisions or agreements reached
## Open Questions
- Anything unresolved or needing follow-up
Keep it concise and actionable.
=== /volume1/screenpipe/pipes/standup-update/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Standup Update
description: "What you did, what's next, and any blockers"
icon: "🏢"
featured: true
---
Based on my recordings from the last 24 hours, generate a standup update. Use limit=10 per search, max 3 searches total.
Read screenpipe skill first.
Use this exact format:
## Yesterday
- What I worked on (name specific projects, files, tools, PRs)
## Today
- What I will work on next (based on unfinished tasks and recent activity)
## Blockers
- Issues I hit — errors, slow builds, waiting on someone
- If no blockers, write "None"
Keep it under 150 words. Copy-paste ready for a team standup.
=== /volume1/screenpipe/pipes/time-breakdown/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Time Breakdown
description: "Where your time went — by app, project, and category"
icon: "⏱"
featured: false
---
Analyze my app usage from today (last 12 hours). Use limit=10 per search, max 4 searches. Prefer /raw_sql with COUNT/GROUP BY queries.
Read screenpipe skill first.
Use this exact format with durations and percentages:
## By Application
- List each app with duration and percentage, sorted by time (e.g. "VS Code: 2h 15min (28%)")
## By Category
- Group into: coding, meetings, browsing, writing, communication, other
- Show hours and percentage per category
## By Project
- Group related activities by project/topic. Name specific repos or tasks.
## Productivity Score
- Calculate: focused_work_hours / total_hours as a percentage
- Focused = coding + writing. Unfocused = browsing + switching.
End with: "**Suggestion:** [one specific change to improve tomorrow's productivity]"
=== /volume1/screenpipe/pipes/video-export/pipe.md ===
---
schedule: manual
enabled: true
template: true
title: Export Video Clip
description: "Create a video of your recent screen activity"
icon: "🎬"
featured: false
---
Export a video of my screen activity from the last 5 minutes.
Read screenpipe skill first.
Use the POST /frames/export endpoint with the time range and fps=1.0. Then show me the exported video file path as an inline code block so I can watch it.
If the export is large, suggest a lower fps or shorter time range.
Thinking
Thinking
Now I have a clear picture. The pipes are markdown prompt templates in
/volume1/screenpipe/pipes/
, but there's no code to actually load and run them —
consumers/summary.py
has its own hardcoded prompts instead.
Here's what I'll implement:
consumers/pipes.py
— dynamically loads pipe.md files and runs them via Claude (data injected as system message, pipe body as user prompt)
main.py
— two new endpoints:
GET /api/pipes
and
POST /api/pipes/{pipe_id}/run
cli.py
— a
pipe
command to run pipes from the terminal
Let me build it:
Bash
Check browser_urls signature
IN
cat /volume1/screenpipe/app/consumers/activity.py | grep "def browser_urls" -A 5
Copy code to clipboard
OUT
def browser_urls(
for_date: date | None = None,
app_name: str | None = None,
ts_from: str | None = None,
ts_to: str | None = None,
limit: int = 30,
Write
pipes.py
pipes.py
143 lines
"""Dynamic pipe loader and runner."""
import os
import re
from datetime import date
from pathlib import Path
from typing import Any
def _parse_frontmatter(text: str) -> tuple[dict, str]:
if not text.startswith("---"):
return {}, text
try:
end = text.index("---", 3)
except ValueError:
return {}, text
fm_text = text[3:end].strip()
body = text[end + 3:].strip()
meta: dict = {}
for line in fm_text.splitlines():
if ":" in line:
k, _, v = line.partition(":")
meta[k.strip()] = v.strip().strip('"')
return meta, body
def load_pipes(pipes_dir: Path) -> list[dict]:
if not pipes_dir.exists():
return []
pipes = []
for pipe_dir in sorted(pipes_dir.iterdir()):
if not pipe_dir.is_dir() or pipe_dir.name.startswith("."):
continue
pipe_md = pipe_dir / "pipe.md"
if not pipe_md.exists():
continue
text = pipe_md.read_text(encoding="utf-8")
meta, body = _parse_frontmatter(text)
if meta.get("enabled", "true").lower() == "false":
continue
body = re.sub(r"Read screenpipe skill first\.?\n?", "", body).strip()
pipes.append({
"id": pipe_dir.name,
"title": meta.get("title", pipe_dir.name),
"description": meta.get("description", ""),
"icon": meta.get("icon", ""),
"schedule": meta.get("schedule", "manual"),
"featured": meta.get("featured", "false").lower() == "true",
"prompt": body,
})
return pipes
def _build_system(d: date, stats: dict) -> str:
from consumers.activity import app_time, browser_urls, ui_event_summary
from consumers.ocr import deduplicated_text
from consumers.audio import formatted_transcript
apps = app_time(d)
app_lines = "\n".join(f"- {a['app_name']}: {a['minutes']} min" for a in apps[:20])
urls = browser_urls(d, limit=20)
url_lines = "\n".join(f"- {u['browser_url'][:100]} ({u['minutes']} min)" for u in urls)
ui_rows = ui_event_summary(d)
ui_lines = "\n".join(
f"- {r['app_name']}: {r['clicks']} clicks, {r['keystrokes']} keys, {r['switches']} switches"
for r in ui_rows[:15]
)
ocr_rows = deduplicated_text(d, chunk_minutes=5)
ocr_lines = "\n".join(
f"[{r['bucket']}] {r['app_name']} / {r['window_name'] or ''}: {r['text'][:200]}"
for r in ocr_rows[:100]
)
audio = formatted_transcript(d)
if len(audio) > 3000:
audio = audio[:3000]
return f"""You are analyzing screenpipe data — recordings of a person's computer activity.
## App usage (minutes per app):
{app_lines or '(no app data)'}
## Browser URLs visited:
{url_lines or '(no browser data)'}
## UI activity per app (clicks / keystrokes / app-switches):
{ui_lines or '(no UI event data)'}
## Screen content (sampled every 5 minutes):
{ocr_lines or '(no screen data)'}
## Audio / speech:
{audio or '(no audio data)'}
Date: {d}
Total frames recorded: {stats['total_frames']}"""
def run_pipe(
pipe_id: str,
for_date: date | None = None,
api_key: str | None = None,
pipes_dir: Path | None = None,
) -> dict[str, Any]:
import anthropic
from consumers.activity import summary_stats
d = for_date or date.today()
key = api_key or os.environ.get("ANTHROPIC_API_KEY", "")
if not key:
return {"title": "Error", "content": "ANTHROPIC_API_KEY not set.", "date": str(d)}
_pipes_dir = pipes_dir or Path(os.environ.get("PIPES_DIR", "/data/pipes"))
all_pipes = {p["id"]: p for p in load_pipes(_pipes_dir)}
if pipe_id not in all_pipes:
return {"title": "Error", "content": f"Pipe not found: {pipe_id}", "date": str(d)}
pipe = all_pipes[pipe_id]
stats = summary_stats(d)
if stats["total_frames"] == 0:
return {"title": pipe["title"], "content": f"No screen data found for {d}.", "date": str(d)}
system = _build_system(d, stats)
client = anthropic.Anthropic(api_key=key)
message = client.messages.create(
model="claude-haiku-4-5-20251001",
max_tokens=1024,
system=system,
messages=[{"role": "user", "content": pipe["prompt"]}],
)
return {
"title": pipe["title"],
"content": message.content[0].text,
"date": str(d),
"stats": stats,
}
Now add the API endpoints to
main.py
:
Edit
main.py
main.py
Added 1 line
Edit
main.py
main.py
Added 1 line
Now add the pipe endpoints at the end of main.py, before the closing summary section:
Edit
main.py
main.py
Added 14 lines...
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Implement and run pipe l… — screenpipe [SSH: nas]
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
...
|
[{"role":"AXRadioButton","text [{"role":"AXRadioButton","text":"Explorer (⇧⌘E)","depth":19,"bounds":{"left":0.0,"top":0.047885075,"width":0.015957447,"height":0.03830806},"on_screen":true,"role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":true,"is_expanded":true},{"role":"AXStaticText","text":"","depth":22,"bounds":{"left":0.0039893617,"top":0.057462092,"width":0.007978723,"height":0.01915403},"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Search (⇧⌘F)","depth":19,"bounds":{"left":0.0,"top":0.08619314,"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":0.09577015,"width":0.007978723,"height":0.01915403},"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Source Control (⌃⇧G) - 10 pending changes","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":"AXStaticText","text":"10","depth":22,"bounds":{"left":0.00831117,"top":0.1452514,"width":0.003656915,"height":0.008778931},"on_screen":true,"lines":[{"char_start":0,"char_count":1,"bounds":{"left":0.00831117,"top":0.14604948,"width":0.0016622341,"height":0.007980846}},{"char_start":1,"char_count":1,"bounds":{"left":0.009973404,"top":0.14604948,"width":0.0023271276,"height":0.007980846}}],"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 update","depth":19,"bounds":{"left":0.0,"top":0.23942538,"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":0.2490024,"width":0.007978723,"height":0.01915403},"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"2","depth":22,"bounds":{"left":0.009640957,"top":0.2601756,"width":0.0019946808,"height":0.008778931},"on_screen":true,"role_description":"text"},{"role":"AXRadioButton","text":"Claude Code","depth":19,"bounds":{"left":0.0,"top":0.27773345,"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":"AXRadioButton","text":"Containers","depth":19,"bounds":{"left":0.0,"top":0.3160415,"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":"AXHeading","text":"EXPLORER","depth":17,"bounds":{"left":0.022606382,"top":0.047885075,"width":0.018949468,"height":0.02793296},"on_screen":true,"role_description":"heading"},{"role":"AXStaticText","text":"EXPLORER","depth":18,"bounds":{"left":0.022606382,"top":0.056664005,"width":0.018949468,"height":0.0103751},"on_screen":true,"lines":[{"char_start":0,"char_count":1,"bounds":{"left":0.022606382,"top":0.056664005,"width":0.0023271276,"height":0.0103751}},{"char_start":1,"char_count":7,"bounds":{"left":0.024933511,"top":0.056664005,"width":0.01662234,"height":0.0103751}}],"role_description":"text"},{"role":"AXButton","text":"Explorer Section: screenpipe [SSH: nas]","depth":21,"bounds":{"left":0.015957447,"top":0.07581804,"width":0.09940159,"height":0.017557861},"on_screen":true,"role_description":"button","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":true},{"role":"AXStaticText","text":"","depth":23,"bounds":{"left":0.01662234,"top":0.07821229,"width":0.005319149,"height":0.012769354},"on_screen":true,"role_description":"text"},{"role":"AXHeading","text":"Explorer Section: screenpipe [SSH: nas]","depth":22,"bounds":{"left":0.022606382,"top":0.07581804,"width":0.045877658,"height":0.017557861},"on_screen":true,"role_description":"heading"},{"role":"AXStaticText","text":"SCREENPIPE [SSH: NAS]","depth":23,"bounds":{"left":0.022606382,"top":0.079010375,"width":0.045877658,"height":0.0103751},"on_screen":true,"lines":[{"char_start":0,"char_count":1,"bounds":{"left":0.022606382,"top":0.07980846,"width":0.0026595744,"height":0.0103751}},{"char_start":1,"char_count":20,"bounds":{"left":0.025265958,"top":0.07980846,"width":0.043218084,"height":0.0103751}}],"role_description":"text"},{"role":"AXStaticText","text":"","depth":26,"bounds":{"left":0.019614361,"top":0.09577015,"width":0.005319149,"height":0.012769354},"on_screen":true,"role_description":"text"},{"role":"AXStaticText","text":"#recycle","depth":27,"bounds":{"left":0.025930852,"top":0.09577015,"width":0.017287234,"height":0.011971269},"on_screen":true,"lines":[{"char_start":0,"char_count":1,"bounds":{"left":0.025930852,"top":0.096568234,"width":0.0026595744,"height":0.011971269}},{"char_start":1,"char_count":7,"bounds":{"left":0.028590426,"top":0.096568234,"width":0.01462766,"height":0.011971269}}],"role_description":"text"},{"role":"AXStaticText","text":"","depth":26,"bounds":{"left":0.019614361,"top":0.11332801,"width":0.005319149,"height":0.012769354},"on_screen":true,"role_description":"text"}]...
|
2566114542653050165
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-5588096438698815092
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visual_change
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accessibility
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NULL
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Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G) - 10 pending changes
10
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Claude Code
Containers
EXPLORER
EXPLORER
Explorer Section: screenpipe [SSH: nas]
Explorer Section: screenpipe [SSH: nas]
SCREENPIPE [SSH: NAS]
#recycle
...
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Code
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.env — screenpipe [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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NULL
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Explorer (⇧⌘E)
|
[{"role":"AXRadioButton","text [{"role":"AXRadioButton","text":"Explorer (⇧⌘E)","depth":19,"bounds":{"left":0.0,"top":0.047885075,"width":0.015957447,"height":0.03830806},"on_screen":true,"role_description":"tab","subrole":"AXTabButton","is_enabled":true,"is_focused":false,"is_selected":true,"is_expanded":true}]...
|
7739306290408768343
|
-3240057942383108413
|
visual_change
|
hybrid
|
NULL
|
Explorer (⇧⌘E)
selectionViewlerminalWindowmelp100% Explorer (⇧⌘E)
selectionViewlerminalWindowmelp100% C. Q. Mon 11 May 20:05:27env — screenpipe SSH: nasдeV SCREENPIPE [SSH: NAS]> #recyclevapoconsumers> static.env* cli.py# db.pv# docker-compose.vml* Dockerfile# main.pv=requirements.txt• data>logs→oinec• aitianore* aoo settinas.ison=archive.db=archive.db-bal= do salite= dh calite-chmE dh calite-wall$ screennine svnc undated shi$ screenpipe_sync.shE screennine dhs apo settinas.isonscreenpipe_sync.sh•pipe.md• .envapp> @.envANTHROPIC [ENV_SECRET] ...•4 C;Implement and run pipe I... XPROBLEMSOUTPUTDEBUG CONSOLE+v0u.laxOUTIING1 TIMELINE*SSH: nas@0A0taacalaSpaces: 4 UTF-8 LF Dotenv88 SignIn...
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Code
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Visual Studio Code
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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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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
No Folder Opened Section
NO FOLDER OPENED
NO FOLDER OPENED
Connected to remote.
Open Folder
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
Open Chat
⌃
⌘
I
Show All Commands
⇧
⌘
P
Open Recent
⌃
R
Open File or Folder
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O
New Untitled Text File
⌘
N
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Debug Console (⇧⌘Y)
DEBUG CONSOLE
Terminal (⌃`)
TERMINAL
Ports
PORTS
remote SSH: nas
SSH: nas
No Problems
0
0
No Ports Forwarded
0
Notifications
Sign In
Sign In
Info: Downloading VS Code Server...
Open Folder
/volume1/screenpipe/
7 Results
OK
Show Local
..
..
.git
.git
#recycle
#recycle
app
app
data
data
logs
logs
pipes
pipes...
|
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var
var
volume1
volume1...
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Claude Code
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Remote Explorer
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Finder••DOCKER+ +FileEditViewGoWindowHelp₴81DEV (docker)₴2APP (-zsh)ScrmService->syncOpportunity('374720564');ScrmService-›matchByName('Robot');APP (-zsh)-zsh-zsh>0 ll*5screenpipe"100% <78• Mon 11 May 20:05:09T81O ₴6-zsh*7 |+end diffAPPFixed 4 of 5666 files in 146.870 seconds, 60.00 MB memory usedWhat's next:Try Docker Debug for seamless, persistentdebugging tools in any container or image → docker debug docker_lamp_1Learn moreat [URL_WITH_CREDENTIALS] ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ csfixdocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diffPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.PHP runtime: 8.3.30Running analysis on 7 cores with 10 files per process.Parallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!Loadedconfig default from".php-cs-fixer.dist.php".5666/5666 [100%Fixed 0 of 5666 files in 66.457 seconds, 60.00 MB memory usedWhat's next:Try Docker Debug for seamless, persistent debugging tools in any container or image » docker debug docker_1amp_1Learn more at https://docs.docker.com/go/debug-cli/lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ I...
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/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519109245_m2.jpg...
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Code
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Visual Studio Code
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True
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monitor_2
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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)
Containers
EXPLORER
EXPLORER
No Folder Opened Section
NO FOLDER OPENED
NO FOLDER OPENED
Connected to remote.
Open Folder
Outline Section
OUTLINE
OUTLINE
Timeline Section
TIMELINE
TIMELINE
Open Chat
⌃
⌘
I
Show All Commands
⇧
⌘
P
Open Recent
⌃
R
Open File or Folder
⌘
O
New Untitled Text File
⌘
N
Problems (⇧⌘M)
PROBLEMS
Output (⇧⌘U)
OUTPUT
Terminal (⌃`)
TERMINAL
Ports
PORTS
remote SSH: nas
SSH: nas
No Problems
0
0
No Ports Forwarded
0
Notifications
Sign In
Sign In
Info: Downloading VS Code Server......
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Search (⇧⌘F)
Source Control (⌃⇧ Explorer (⇧⌘E)
Search (⇧⌘F)
Source Control (⌃⇧G)
Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X)
Containers
EXPLORER
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No Folder Opened Section
NO FOLDER OPENED
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Connected to remote.
Open Folder
Outline Section
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Open Chat
⌃
⌘
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Show All Commands
⇧
⌘
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Open Recent
⌃
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Open File or Folder
⌘
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New Untitled Text File
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Problems (⇧⌘M)
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Terminal (⌃`)
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remote SSH: nas
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Info: Downloading VS Code Server......
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NULL
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Code
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Visual Studio Code
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True
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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)
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⌃
⌘
I
Show All Commands
⇧
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Info: Setting up SSH Host nas: (details) Initializing VS Code Server
Setting up SSH Host 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)
Open Chat
⌃
⌘
I
Show All Commands
⇧
⌘
P
Open Recent
⌃
R
Open File or Folder
⌘
O
New Untitled Text File
⌘
N
Opening Remote...
Opening Remote...
No Problems
0
0
No Ports Forwarded
0
Notifications
Sign In
Sign In
Info: Setting up SSH Host nas: (details) Initializing VS Code Server
Setting up SSH Host nas: (
details
details
) Initializing VS Code Server...
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Client.php (Working Tree) (Client.php) — app — 9 p Client.php (Working Tree) (Client.php) — app — 9 problems in this file • Modified...
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Finder••DOCKER+ +FileEditViewGoWindowHelp- ₴81DEV Finder••DOCKER+ +FileEditViewGoWindowHelp- ₴81DEV (docker)₴2APP (-zsh)ScrmService->syncOpportunity('374720564');ScrmService-›matchByName('Robot');APP (-zsh)-zsh-zsh>0 ll*5screenpipe"100% <78• Mon 11 May 20:05:02T81O ₴6-zsh*7 |+end diffAPPFixed 4 of 5666 files in 146.870 seconds, 60.00 MB memory usedWhat's next:Try Docker Debug for seamless, persistentdebugging tools in any container or image → docker debug docker_lamp_1Learn moreat [URL_WITH_CREDENTIALS] ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ csfixdocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diffPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.PHP runtime: 8.3.30Running analysis on 7 cores with 10 files per process.Parallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!Loadedconfig default from".php-cs-fixer.dist.php".5666/5666 [100%Fixed 0 of 5666 files in 66.457 seconds, 60.00 MB memory usedWhat's next:Try Docker Debug for seamless, persistent debugging tools in any container or image » docker debug docker_1amp_1Learn more at https://docs.docker.com/go/debug-cli/lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ I...
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Finder••DOCKER+ +FileEditViewGoWindowHelp- ₴81DEV Finder••DOCKER+ +FileEditViewGoWindowHelp- ₴81DEV (docker)₴2APP (-zsh)ScrmService->syncOpportunity('374720564');ScrmService-›matchByName('Robot');APP (-zsh)-zsh-zsh>0 ll*5screenpipe"100% <78• Mon 11 May 20:05:02T81O ₴6-zsh*7 |+end diffAPPFixed 4 of 5666 files in 146.870 seconds, 60.00 MB memory usedWhat's next:Try Docker Debug for seamless, persistentdebugging tools in any container or image → docker debug docker_lamp_1Learn moreat [URL_WITH_CREDENTIALS] ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ csfixdocker exec -it docker_lamp_1 ./vendor/bin/php-cs-fixer fix --config=.php-cs-fixer.dist.php -v --using-cache=no --diffPHP CS Fixer 3.87.1 Alexander by Fabien Potencier, Dariusz Ruminski and contributors.PHP runtime: 8.3.30Running analysis on 7 cores with 10 files per process.Parallel runner is an experimental feature and may be unstable, use it at your own risk. Feedback highly appreciated!Loadedconfig default from".php-cs-fixer.dist.php".5666/5666 [100%Fixed 0 of 5666 files in 66.457 seconds, 60.00 MB memory usedWhat's next:Try Docker Debug for seamless, persistent debugging tools in any container or image » docker debug docker_1amp_1Learn more at https://docs.docker.com/go/debug-cli/lukas@Lukas-Kovaliks-MacBook-Pro-Jiminny ~/jiminny/app (JY-20725-handle-HS-search-rate-limit) $ I...
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Client.php (Working Tree) (Client.php) — app — 9 p Client.php (Working Tree) (Client.php) — app — 9 problems in this file • Modified...
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selectionLàChanges• .env.local• .env.nikiloca,• .e selectionLàChanges• .env.local• .env.nikiloca,• .env.otherEids.txtraw_sal_query.sg* WEBHOOK_FILTERING_IMPLEMENT# JiminnyDebugCommand.php app/d## SimulateWebhooksCommand.php a.w CreateMockAskJiminnvReportResult.w logaina.pho confid* favicon.ico publicif CanAccessAiReportsTest.php testsl..V GRAPHO JY-20725 code r.• JY-20725 add more tests Lukas KovMerae branch 'master' into .IY-20818.)Merge pull request #12057 from jimin..10.IY-20819• Increase download transer.i Merge pul nequest 412057 rom in in..Merao null roauoct #12052 from liminотро зы rадкеы 206Merge branch 'master' into JY-20817.Merge pull request #12047 from jimin.• JY-20662 Removed word boost para.JY-20817: Fix deleting old tracks mih…Merge pull request #12043 from jimin.Merge branch "master' into Jy-19938.Merge pull request #12044 from fimin.• Jy-19938 Added consent informationJY-19938 reorder array mao ilianJY-19938: Address PR review comme.Windovhhl100% L2Mon 11 May 20:05:02wMatchActivitvCrmData.ohp#* Client.php > * Client > getRateLimitCacheKey()keview fate limit nanaling for huospouo..• Now run all affected tests to verify everything passes:use Hubspot Client crm Pipelines ModelPipel1nestage:use Hubsoot Cllent Crm Properties Model Property:HubSoot Discovery Discovery:21 use liminnvlFycentionc|SocialAccountTokenTnvalidFycentioneuse Jiminny services \crm\hubspoc\raginac1on\hubspocraginaclonserviceruse 1lluminare support racades keals'use Throwable;public const string MIN API VERSION = '2':private HubspotPaginationService $paginationService;orivare nuospoclokenmanager scokenmanager.SocialAccountService ssocialAccountService.HubsootPaginationService SpaginationService.narent:: construct(<socialAccountService).E\Client\Crm\Deals\Model\SimplePublicObjectWithAssociations as DealWithAssociations;nubspocre cencrenmoogects (mode l oamp ceruo excooyeccanput,HubSpot\Client\Crm\Objects\Model\SimplePublic0bjectWithAssociations as ObjectWithAssociatinubspottelencier rapeuines modelierror,Hubspot Client\ Crm Pipelines Model PipeLinestage:use Hubspot Cluent Crm Provertles Model Property:use HubSpot Discovery Discovery:use Jiminny Excentions CrmExcention:Jiminny\Exceptions\RateLimitException;liminnvl Fycentioncl CocialAdDo you wande to client phangesYour changes will be lost if you don't1uluminace supporc racadesSaveDon't SaveCancelclacs Client eytends Raceflienipublic const suring MIN APL VERSION = '2"strind BasE URL ="httos:ao1.hubaot.com':private HubspotPaginationService $paginationService;privare nuospoctokenmanager stokenmanader.pubLso 1ulAtcounscovste S50cia1AccountService,HubspotPaginationService SpaginationServicelnarent:. construct((socialAccountService).$this->paginationService = SpaginationService:sthis->setBaseUriself::BASEURL):>setVersion(self::MTN APT VERSION):Commandrunniinan.backaroundwithT0.hhu@az8okOntont..beina_waltitien tor/natvate/tmo//alande-50V/-lsers-mkas_Kimilnny_ann/1ca08117hd_3248-Ac62-h226-2ard• Bash Check test outoucat /ortvate/tmo/claude=501/-Users-Lukas-11m1nny=aoo/cae81700-3648-4C63-0356-211d87412e4d/tasks/bhugaz8vk.output 22/dev/null ta1l =30PHPlInit 11.5.55 bv Sebhastian Beramann and contributorslPHP 8.3.30• All 120 tests pass. Here's a summary of every change made to address the review feedback:Issue 1 - Batch APl calls bypass rate-limit handlingDatchkeadubjects() now wraps tne sbatchtont1gl'ap1")→>read(...) call inside executekequest(), so 42gs Trom batch enapoints are caugnt by theon propagates to the iobmiddleware instead of being swallowed by handleBatchError() andre-wrapped as CrmExceptionIssue 2 - Misleading cache key nameClient.php:120 — Renamed hubspt: ratelimit:portal:%d • hubspot: ratelimit: cont10:%d. Ine key was already scoped to the contig record ID (not a Hubspot portal ID):TwllentnhosvkukV.oth.methods.chandedIrom.nmhlt. o.nvateNather.cinthelnteriace.andinoiihino.ouiisitle.exccntaReomecthoallc.ihem.the.GirectatesiicuinIssue 5 - Test constants duolicated from oroduction codeIDS ) and inlined the concrete boundary value?with comments (e.g. 'expectedMax' => 605. // 600 + 5 jitter). If the middleware constants change, these tests will now fail rather than silently pass against stale expectedIssue 6 - Double-clamoing in RateLimitExcentsionDatallmiliswcaatanaha?ho.ahmaina.mavodt.tho.constatorKaitnatvAatarmyllaav/1araTiho.manoatviltnallanaaznnzamatodlinazamator/inhilahMatchActivitvCrmData.php:172 — Added a three-line comment explaining that RateLimitExcention onlv reaches failed() when retrvüntil() expires while the iob is still+0M Client.ohralalUTF-8 LF PHP 88 Signin 8.3P...
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selectionLàChanges• .env.local• .env.nikiloca,• .e selectionLàChanges• .env.local• .env.nikiloca,• .env.otherEids.txtraw_sal_query.sg* WEBHOOK_FILTERING_IMPLEMENT# JiminnyDebugCommand.php app/d## SimulateWebhooksCommand.php a.w CreateMockAskJiminnvReportResult.w logaina.pho confid* favicon.ico publicif CanAccessAiReportsTest.php testsl..V GRAPHO JY-20725 code r.• JY-20725 add more tests Lukas KovMerae branch 'master' into .IY-20818.)Merge pull request #12057 from jimin..10.IY-20819• Increase download transer.i Merge pul nequest 412057 rom in in..Merao null roauoct #12052 from liminотро зы rадкеы 206Merge branch 'master' into JY-20817.Merge pull request #12047 from jimin.• JY-20662 Removed word boost para.JY-20817: Fix deleting old tracks mih…Merge pull request #12043 from jimin.Merge branch "master' into Jy-19938.Merge pull request #12044 from fimin.• Jy-19938 Added consent informationJY-19938 reorder array mao ilianJY-19938: Address PR review comme.Windovhhl100% L2Mon 11 May 20:05:02wMatchActivitvCrmData.ohp#* Client.php > * Client > getRateLimitCacheKey()keview fate limit nanaling for huospouo..• Now run all affected tests to verify everything passes:use Hubspot Client crm Pipelines ModelPipel1nestage:use Hubsoot Cllent Crm Properties Model Property:HubSoot Discovery Discovery:21 use liminnvlFycentionc|SocialAccountTokenTnvalidFycentioneuse Jiminny services \crm\hubspoc\raginac1on\hubspocraginaclonserviceruse 1lluminare support racades keals'use Throwable;public const string MIN API VERSION = '2':private HubspotPaginationService $paginationService;orivare nuospoclokenmanager scokenmanager.SocialAccountService ssocialAccountService.HubsootPaginationService SpaginationService.narent:: construct(<socialAccountService).E\Client\Crm\Deals\Model\SimplePublicObjectWithAssociations as DealWithAssociations;nubspocre cencrenmoogects (mode l oamp ceruo excooyeccanput,HubSpot\Client\Crm\Objects\Model\SimplePublic0bjectWithAssociations as ObjectWithAssociatinubspottelencier rapeuines modelierror,Hubspot Client\ Crm Pipelines Model PipeLinestage:use Hubspot Cluent Crm Provertles Model Property:use HubSpot Discovery Discovery:use Jiminny Excentions CrmExcention:Jiminny\Exceptions\RateLimitException;liminnvl Fycentioncl CocialAdDo you wande to client phangesYour changes will be lost if you don't1uluminace supporc racadesSaveDon't SaveCancelclacs Client eytends Raceflienipublic const suring MIN APL VERSION = '2"strind BasE URL ="httos:ao1.hubaot.com':private HubspotPaginationService $paginationService;privare nuospoctokenmanager stokenmanader.pubLso 1ulAtcounscovste S50cia1AccountService,HubspotPaginationService SpaginationServicelnarent:. construct((socialAccountService).$this->paginationService = SpaginationService:sthis->setBaseUriself::BASEURL):>setVersion(self::MTN APT VERSION):Commandrunniinan.backaroundwithT0.hhu@az8okOntont..beina_waltitien tor/natvate/tmo//alande-50V/-lsers-mkas_Kimilnny_ann/1ca08117hd_3248-Ac62-h226-2ard• Bash Check test outoucat /ortvate/tmo/claude=501/-Users-Lukas-11m1nny=aoo/cae81700-3648-4C63-0356-211d87412e4d/tasks/bhugaz8vk.output 22/dev/null ta1l =30PHPlInit 11.5.55 bv Sebhastian Beramann and contributorslPHP 8.3.30• All 120 tests pass. Here's a summary of every change made to address the review feedback:Issue 1 - Batch APl calls bypass rate-limit handlingDatchkeadubjects() now wraps tne sbatchtont1gl'ap1")→>read(...) call inside executekequest(), so 42gs Trom batch enapoints are caugnt by theon propagates to the iobmiddleware instead of being swallowed by handleBatchError() andre-wrapped as CrmExceptionIssue 2 - Misleading cache key nameClient.php:120 — Renamed hubspt: ratelimit:portal:%d • hubspot: ratelimit: cont10:%d. Ine key was already scoped to the contig record ID (not a Hubspot portal ID):TwllentnhosvkukV.oth.methods.chandedIrom.nmhlt. o.nvateNather.cinthelnteriace.andinoiihino.ouiisitle.exccntaReomecthoallc.ihem.the.GirectatesiicuinIssue 5 - Test constants duolicated from oroduction codeIDS ) and inlined the concrete boundary value?with comments (e.g. 'expectedMax' => 605. // 600 + 5 jitter). If the middleware constants change, these tests will now fail rather than silently pass against stale expectedIssue 6 - Double-clamoing in RateLimitExcentsionDatallmiliswcaatanaha?ho.ahmaina.mavodt.tho.constatorKaitnatvAatarmyllaav/1araTiho.manoatviltnallanaaznnzamatodlinazamator/inhilahMatchActivitvCrmData.php:172 — Added a three-line comment explaining that RateLimitExcention onlv reaches failed() when retrvüntil() expires while the iob is still+0M Client.ohralalUTF-8 LF PHP 88 Signin 8.3P...
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JY-20725 code review suggestions
Lukas Kovalik
JY-20725-handle-HS-search-rate-limit
JY-20725 add more tests
Lukas Kovalik
JY-20725 add tests
Lukas Kovalik
JY-20725 add HS rate limit handling on activities rematching
Lukas Kovalik
Merge pull request #12056 from jiminny/JY-20818-move-AJ-reports-to-separated-datadog-metric
Lukas Kovalik
origin/master
Merge branch 'master' into JY-20818-move-AJ-reports-to-separated-datadog-metric
Lukas Kovalik
Merge pull request #12057 from jiminny/JY-20819-increase-download-transctip-rate-limit
mihailmihaylovjiminny
JY-20819: Increase download transcription rate limit
mihail.mihaylov
JY-20818 move ask jiminny reports to its own datadog metric
Lukas Kovalik
Merge pull request #12052 from jiminny/JY-20817-fix-deleting-old-tracks
mihailmihaylovjiminny
Merge branch 'master' into JY-20817-fix-deleting-old-tracks
mihailmihaylovjiminny
Merge pull request #12047 from jiminny/JY-20662-remove-word-boost
ilian-jiminny
JY-20662 return void
ilian
JY-20662 Removed word_boost parameter from Assembly transcription request
ilian
JY-20817: Fix deleting old tracks
mihail.mihaylov
Merge pull request #12043 from jiminny/JY-19938-bot-status-in-csv-es
ilian-jiminny
Merge branch 'master' into JY-19938-bot-status-in-csv-es
ilian-jiminny
Merge pull request #12044 from jiminny/JY-19938-ES-mapping-update
ilian-jiminny
JY-19938 Added consent information and recording error reason to Elastic Search mapping
ilian
JY-19938 reorder array map
ilian
JY-19938: Address PR review comments
ilian
HandleHubspotRateLimitTest.php (Working Tree) (HandleHubspotRateLimitTest.php), Editor Group 1
ClientTest.php (Working Tree) (ClientTest.php), Editor Group 1
Client.php (Working Tree) (Client.php), Editor Group 1
MatchActivityCrmData.php (Working Tree) (MatchActivityCrmData.php), Editor Group 1
MatchActivityCrmData.php, Editor Group 1
RateLimitException.php (Working Tree) (RateLimitException.php), Editor Group 1
Client.php, preview, Editor Group 1
Review rate limit handli…, Editor Group 2
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git-commit Lukas Kovalik (1 hour ago)
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Review rate limit handling for HubSpot job queue
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RateLimitException.php#9-9
RateLimitException.php#9-9
Reveiw the diff. Mostly
@app/Jobs/Crm/MatchActivityCrmData.php
,
@app/Exceptions/RateLimitException.php
,
@app/Jobs/Middleware/HandleHubspotRateLimit.php
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Explorer (⇧⌘E) - 1 unsaved file
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12
.env.local
M
.env.nikilocal
U
.env.other
U
ids.txt
U
raw_sql_query.sql
U
WEBHOOK_FILTERING_IMPLEMENTATION.md
U
JiminnyDebugCommand.php
app/Console/Commands
M
SimulateWebhooksCommand.php
app/Console/Commands/Crm/Hubspot
U
CreateMockAskJiminnyReportResultCommand.php
app/Console/Commands/Reports
U
logging.php
config
M
favicon.ico
public
U
CanAccessAiReportsTest.php
tests/Unit/Policies
U
Graph Section
GRAPH
GRAPH
JY-20725 code review suggestions
Lukas Kovalik
JY-20725-handle-HS-search-rate-limit
JY-20725 add more tests
Lukas Kovalik
JY-20725 add tests
Lukas Kovalik
JY-20725 add HS rate limit handling on activities rematching
Lukas Kovalik
Merge pull request #12056 from jiminny/JY-20818-move-AJ-reports-to-separated-datadog-metric
Lukas Kovalik
origin/master
Merge branch 'master' into JY-20818-move-AJ-reports-to-separated-datadog-metric
Lukas Kovalik
Merge pull request #12057 from jiminny/JY-20819-increase-download-transctip-rate-limit
mihailmihaylovjiminny
JY-20819: Increase download transcription rate limit
mihail.mihaylov
JY-20818 move ask jiminny reports to its own datadog metric
Lukas Kovalik
Merge pull request #12052 from jiminny/JY-20817-fix-deleting-old-tracks
mihailmihaylovjiminny
Merge branch 'master' into JY-20817-fix-deleting-old-tracks
mihailmihaylovjiminny
Merge pull request #12047 from jiminny/JY-20662-remove-word-boost
ilian-jiminny
JY-20662 return void
ilian
JY-20662 Removed word_boost parameter from Assembly transcription request
ilian
JY-20817: Fix deleting old tracks
mihail.mihaylov
Merge pull request #12043 from jiminny/JY-19938-bot-status-in-csv-es
ilian-jiminny
Merge branch 'master' into JY-19938-bot-status-in-csv-es
ilian-jiminny
Merge pull request #12044 from jiminny/JY-19938-ES-mapping-update
ilian-jiminny
JY-19938 Added consent information and recording error reason to Elastic Search mapping
ilian
JY-19938 reorder array map
ilian
JY-19938: Address PR review comments
ilian
HandleHubspotRateLimitTest.php (Working Tree) (HandleHubspotRateLimitTest.php), Editor Group 1
ClientTest.php (Working Tree) (ClientTest.php), Editor Group 1
Client.php (Working Tree) (Client.php), Editor Group 1
MatchActivityCrmData.php (Working Tree) (MatchActivityCrmData.php), Editor Group 1
MatchActivityCrmData.php, Editor Group 1
RateLimitException.php (Working Tree) (RateLimitException.php), Editor Group 1
Client.php, preview, Editor Group 1
Review rate limit handli…, Editor Group 2
remote
app (Git) - JY-20725-handle-HS-search-rate-limit*, Checkout Branch/Tag...
JY-20725-handle-HS-search-rate-limit*
app (Git) - Synchronize Changes
Errors: 6, Warnings: 11, Infos: 28
6
11
28
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8.3, Language Level: 8.3
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PHP
LF
UTF-8
Spaces: 4
Ln 120, Col 1
git-commit Lukas Kovalik (1 hour ago)
Lukas Kovalik (1 hour ago)
Diff editor
Clear
Review rate limit handling for HubSpot job queue
Session history
New session
Message actions
RateLimitException.php#9-9
RateLimitException.php#9-9
Reveiw the diff. Mostly
@app/Jobs/Crm/MatchActivityCrmData.php
,
@app/Exceptions/RateLimitException.php
,
@app/Jobs/Middleware/HandleHubspotRateLimit.php
,
@app/Services/Crm/Hubspot/Client.php
and...
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/Users/lukas/jiminny/app/app/Services/Crm/Hubspot/ /Users/lukas/jiminny/app/app/Services/Crm/Hubspot/Client.php...
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NULL
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21039
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918
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21
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2026-05-11T17:04:56.994910+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-11/1778 /Users/lukas/.screenpipe/data/data/2026-05-11/1778519096994_m1.jpg...
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Code
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Client.php (Working Tree) (Client.php) — app — 9 p Client.php (Working Tree) (Client.php) — app — 9 problems in this file • Modified...
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Explorer (⇧⌘E) - 1 unsaved file
1
Search (⇧⌘F)
Explorer (⇧⌘E) - 1 unsaved file
1
Search (⇧⌘F)
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Run and Debug (⇧⌘D)
Remote Explorer
Extensions (⇧⌘X) - 2 require update
2
Testing
Claude Code
SOURCE CONTROL
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Changes Section
CHANGES
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Commit Changes on "JY-20725-handle-HS-search-rate-limit"
Commit
More Actions...
Changes
12
.env.local
M
.env.nikilocal
U
.env.other
U
ids.txt
U
raw_sql_query.sql
U
WEBHOOK_FILTERING_IMPLEMENTATION.md
U
JiminnyDebugCommand.php
app/Console/Commands
M
SimulateWebhooksCommand.php
app/Console/Commands/Crm/Hubspot
U
CreateMockAskJiminnyReportResultCommand.php
app/Console/Commands/Reports
U
logging.php
config
M
favicon.ico
public
U
CanAccessAiReportsTest.php
tests/Unit/Policies
U
Graph Section
GRAPH
GRAPH
JY-20725 code review suggestions
Lukas Kovalik
JY-20725-handle-HS-search-rate-limit
JY-20725 add more tests
Lukas Kovalik
JY-20725 add tests
Lukas Kovalik
JY-20725 add HS rate limit handling on activities rematching
Lukas Kovalik
Merge pull request #12056 from jiminny/JY-20818-move-AJ-reports-to-separated-datadog-metric
Lukas Kovalik
origin/master
Merge branch 'master' into JY-20818-move-AJ-reports-to-separated-datadog-metric
Lukas Kovalik
Merge pull request #12057 from jiminny/JY-20819-increase-download-transctip-rate-limit
mihailmihaylovjiminny
JY-20819: Increase download transcription rate limit
mihail.mihaylov
JY-20818 move ask jiminny reports to its own datadog metric
Lukas Kovalik
Merge pull request #12052 from jiminny/JY-20817-fix-deleting-old-tracks
mihailmihaylovjiminny
Merge branch 'master' into JY-20817-fix-deleting-old-tracks
mihailmihaylovjiminny
Merge pull request #12047 from jiminny/JY-20662-remove-word-boost
ilian-jiminny
JY-20662 return void
ilian
JY-20662 Removed word_boost parameter from Assembly transcription request
ilian
JY-20817: Fix deleting old tracks
mihail.mihaylov
Merge pull request #12043 from jiminny/JY-19938-bot-status-in-csv-es
ilian-jiminny
Merge branch 'master' into JY-19938-bot-status-in-csv-es
ilian-jiminny
Merge pull request #12044 from jiminny/JY-19938-ES-mapping-update
ilian-jiminny
JY-19938 Added consent information and recording error reason to Elastic Search mapping
ilian
JY-19938 reorder array map
ilian
JY-19938: Address PR review comments
ilian
HandleHubspotRateLimitTest.php (Working Tree) (HandleHubspotRateLimitTest.php), Editor Group 1
ClientTest.php (Working Tree) (ClientTest.php), Editor Group 1
Client.php (Working Tree) (Client.php), Editor Group 1
MatchActivityCrmData.php (Working Tree) (MatchActivityCrmData.php), Editor Group 1
MatchActivityCrmData.php, Editor Group 1
RateLimitException.php (Working Tree) (RateLimitException.php), Editor Group 1
Client.php, preview, Editor Group 1
Review rate limit handli…, Editor Group 2
remote
app (Git) - JY-20725-handle-HS-search-rate-limit*, Checkout Branch/Tag...
JY-20725-handle-HS-search-rate-limit*
app (Git) - Synchronize Changes
Errors: 6, Warnings: 11, Infos: 28
6
11
28
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PHP
LF
UTF-8
Spaces: 4
Ln 120, Col 1
git-commit Lukas Kovalik (1 hour ago)
Lukas Kovalik (1 hour ago)
Diff editor
Clear
Review rate limit handling for HubSpot job queue
Session history
New session
Message actions
RateLimitException.php#9-9
RateLimitException.php#9-9
Reveiw the diff. Mostly
@app/Jobs/Crm/MatchActivityCrmData.php
,
@app/Exceptions/RateLimitException.php
,
@app/Jobs/Middleware/HandleHubspotRateLimit.php
,
@app/Services/Crm/Hubspot/Client.php
and
@app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php
. The issue is I am trying to make sure that instant spike of MatchActivityCrmData jobs willl handle 429 exceptions from hubspot. Revewi ti carefully and try to see potential issues and bottlenecks. Also RateLimitException was changerd from LogicException to RuntimeException. Is it ok. This exception is used by other paerts of code. Will ti break anything?
Thought for 5s
Thought for 5s
I'll review the implementation carefully. Let me first check how
RateLimitException
is used elsewhere and look at the test files and
PaginationState
.
Bash
Find all usages of RateLimitException outside the changed files
IN
grep -rn "RateLimitException" /Users/lukas/jiminny/app/app --include="*.php" | grep -v "HandleHubspotRateLimit\|MatchActivityCrmData\|Client.php\|RateLimitException.php"
Copy code to clipboard
OUT
/Users/lukas/jiminny/app/app/Component/ActionItems/Jobs/GenerateActionItemsJob.php:13:use Jiminny\Exceptions\RateLimitException;
/Users/lukas/jiminny/app/app/Component/ActionItems/Jobs/GenerateActionItemsJob.php:51: GuzzleException|HttpBadRequestException|JsonException|RateLimitException|UnexpectedValueException $exception
/Users/lukas/jiminny/app/app/Component/AiCallScoring/Jobs/GenerateAiCallScoringJob.php:17:use Jiminny\Exceptions\RateLimitException;
/Users/lukas/jiminny/app/app/Component/AiCallScoring/Jobs/GenerateAiCallScoringJob.php:68: RateLimitException |
/Users/lukas/jiminny/app/app/Component/TranscriptionSummary/Jobs/SummarizeTranscriptionJob.php:15:use Jiminny\Exceptions\RateLimitException;
/Users/lukas/jiminny/app/app/Component/TranscriptionSummary/Jobs/SummarizeTranscriptionJob.php:58: GuzzleException|HttpBadRequestException|JsonException|RateLimitException|UnexpectedValueException $exception
/Users/lukas/jiminny/app/app/Component/AiActivityType/Jobs/GenerateAiActivityTypeJob.php:19:use Jiminny\Exceptions\RateLimitException;
/Users/lukas/jiminny/app/app/Component/AiActivityType/Jobs/GenerateAiActivityTypeJob.php:76: RateLimitException |
/Users/lukas/jiminny/app/app/Services/Crm/Hubspot/HubspotClientInterface.php:8:use Jiminny\Exceptions\RateLimitException;
/Users/lukas/jiminny/app/app/Services/Crm/Hubspot/HubspotClientInterface.php:50: * @throws RateLimitException When rate limit is hit
/Users/lukas/jiminny/app/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php:195: // RateLimitException and other exceptions are re-thrown as-is
Read
PaginationState.php
PaginationState.php
Read
HandleHubspotRateLimitTest.php
HandleHubspotRateLimitTest.php
Bash
Check how RateLimitException is used in GenerateActionItemsJob
IN
grep -rn "RateLimitException\|LogicException\|RuntimeException" /Users/lukas/jiminny/app/app/Component/ActionItems/Jobs/GenerateActionItemsJob.php | head -20...
|
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Let me first check how","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"RateLimitException","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"is used elsewhere and look at the test files and","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"PaginationState","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":".","depth":23,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Find all usages of RateLimitException outside the changed files","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"grep -rn \"RateLimitException\" /Users/lukas/jiminny/app/app --include=\"*.php\" | grep -v \"HandleHubspotRateLimit\\|MatchActivityCrmData\\|Client.php\\|RateLimitException.php\"","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":"/Users/lukas/jiminny/app/app/Component/ActionItems/Jobs/GenerateActionItemsJob.php:13:use Jiminny\\Exceptions\\RateLimitException;\n/Users/lukas/jiminny/app/app/Component/ActionItems/Jobs/GenerateActionItemsJob.php:51: GuzzleException|HttpBadRequestException|JsonException|RateLimitException|UnexpectedValueException $exception\n/Users/lukas/jiminny/app/app/Component/AiCallScoring/Jobs/GenerateAiCallScoringJob.php:17:use Jiminny\\Exceptions\\RateLimitException;\n/Users/lukas/jiminny/app/app/Component/AiCallScoring/Jobs/GenerateAiCallScoringJob.php:68: RateLimitException |\n/Users/lukas/jiminny/app/app/Component/TranscriptionSummary/Jobs/SummarizeTranscriptionJob.php:15:use Jiminny\\Exceptions\\RateLimitException;\n/Users/lukas/jiminny/app/app/Component/TranscriptionSummary/Jobs/SummarizeTranscriptionJob.php:58: GuzzleException|HttpBadRequestException|JsonException|RateLimitException|UnexpectedValueException $exception\n/Users/lukas/jiminny/app/app/Component/AiActivityType/Jobs/GenerateAiActivityTypeJob.php:19:use Jiminny\\Exceptions\\RateLimitException;\n/Users/lukas/jiminny/app/app/Component/AiActivityType/Jobs/GenerateAiActivityTypeJob.php:76: RateLimitException |\n/Users/lukas/jiminny/app/app/Services/Crm/Hubspot/HubspotClientInterface.php:8:use Jiminny\\Exceptions\\RateLimitException;\n/Users/lukas/jiminny/app/app/Services/Crm/Hubspot/HubspotClientInterface.php:50: * @throws RateLimitException When rate limit is hit\n/Users/lukas/jiminny/app/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php:195: // RateLimitException and other exceptions are re-thrown as-is","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"PaginationState.php","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"PaginationState.php","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Read","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXLink","text":"HandleHubspotRateLimitTest.php","depth":24,"on_screen":false,"role_description":"link","is_enabled":true,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXStaticText","text":"HandleHubspotRateLimitTest.php","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Bash","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"Check how RateLimitException is used in GenerateActionItemsJob","depth":24,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"IN","depth":25,"on_screen":false,"role_description":"text"},{"role":"AXStaticText","text":"grep -rn \"RateLimitException\\|LogicException\\|RuntimeException\" /Users/lukas/jiminny/app/app/Component/ActionItems/Jobs/GenerateActionItemsJob.php | head -20","depth":25,"on_screen":false,"role_description":"text"}]...
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ids.txt
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raw_sql_query.sql
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WEBHOOK_FILTERING_IMPLEMENTATION.md
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JiminnyDebugCommand.php
app/Console/Commands
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SimulateWebhooksCommand.php
app/Console/Commands/Crm/Hubspot
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CreateMockAskJiminnyReportResultCommand.php
app/Console/Commands/Reports
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JY-20725 code review suggestions
Lukas Kovalik
JY-20725-handle-HS-search-rate-limit
JY-20725 add more tests
Lukas Kovalik
JY-20725 add tests
Lukas Kovalik
JY-20725 add HS rate limit handling on activities rematching
Lukas Kovalik
Merge pull request #12056 from jiminny/JY-20818-move-AJ-reports-to-separated-datadog-metric
Lukas Kovalik
origin/master
Merge branch 'master' into JY-20818-move-AJ-reports-to-separated-datadog-metric
Lukas Kovalik
Merge pull request #12057 from jiminny/JY-20819-increase-download-transctip-rate-limit
mihailmihaylovjiminny
JY-20819: Increase download transcription rate limit
mihail.mihaylov
JY-20818 move ask jiminny reports to its own datadog metric
Lukas Kovalik
Merge pull request #12052 from jiminny/JY-20817-fix-deleting-old-tracks
mihailmihaylovjiminny
Merge branch 'master' into JY-20817-fix-deleting-old-tracks
mihailmihaylovjiminny
Merge pull request #12047 from jiminny/JY-20662-remove-word-boost
ilian-jiminny
JY-20662 return void
ilian
JY-20662 Removed word_boost parameter from Assembly transcription request
ilian
JY-20817: Fix deleting old tracks
mihail.mihaylov
Merge pull request #12043 from jiminny/JY-19938-bot-status-in-csv-es
ilian-jiminny
Merge branch 'master' into JY-19938-bot-status-in-csv-es
ilian-jiminny
Merge pull request #12044 from jiminny/JY-19938-ES-mapping-update
ilian-jiminny
JY-19938 Added consent information and recording error reason to Elastic Search mapping
ilian
JY-19938 reorder array map
ilian
JY-19938: Address PR review comments
ilian
HandleHubspotRateLimitTest.php (Working Tree) (HandleHubspotRateLimitTest.php), Editor Group 1
ClientTest.php (Working Tree) (ClientTest.php), Editor Group 1
Client.php (Working Tree) (Client.php), Editor Group 1
MatchActivityCrmData.php (Working Tree) (MatchActivityCrmData.php), Editor Group 1
MatchActivityCrmData.php, Editor Group 1
RateLimitException.php (Working Tree) (RateLimitException.php), Editor Group 1
Client.php, preview, Editor Group 1
Review rate limit handli…, Editor Group 2
remote
app (Git) - JY-20725-handle-HS-search-rate-limit*, Checkout Branch/Tag...
JY-20725-handle-HS-search-rate-limit*
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git-commit Lukas Kovalik (1 hour ago)
Lukas Kovalik (1 hour ago)
Diff editor
Clear
Review rate limit handling for HubSpot job queue
Session history
New session
Message actions
RateLimitException.php#9-9
RateLimitException.php#9-9
Reveiw the diff. Mostly
@app/Jobs/Crm/MatchActivityCrmData.php
,
@app/Exceptions/RateLimitException.php
,
@app/Jobs/Middleware/HandleHubspotRateLimit.php
,
@app/Services/Crm/Hubspot/Client.php
and
@app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php
. The issue is I am trying to make sure that instant spike of MatchActivityCrmData jobs willl handle 429 exceptions from hubspot. Revewi ti carefully and try to see potential issues and bottlenecks. Also RateLimitException was changerd from LogicException to RuntimeException. Is it ok. This exception is used by other paerts of code. Will ti break anything?
Thought for 5s
Thought for 5s
I'll review the implementation carefully. Let me first check how
RateLimitException
is used elsewhere and look at the test files and
PaginationState
.
Bash
Find all usages of RateLimitException outside the changed files
IN
grep -rn "RateLimitException" /Users/lukas/jiminny/app/app --include="*.php" | grep -v "HandleHubspotRateLimit\|MatchActivityCrmData\|Client.php\|RateLimitException.php"
Copy code to clipboard
OUT
/Users/lukas/jiminny/app/app/Component/ActionItems/Jobs/GenerateActionItemsJob.php:13:use Jiminny\Exceptions\RateLimitException;
/Users/lukas/jiminny/app/app/Component/ActionItems/Jobs/GenerateActionItemsJob.php:51: GuzzleException|HttpBadRequestException|JsonException|RateLimitException|UnexpectedValueException $exception
/Users/lukas/jiminny/app/app/Component/AiCallScoring/Jobs/GenerateAiCallScoringJob.php:17:use Jiminny\Exceptions\RateLimitException;
/Users/lukas/jiminny/app/app/Component/AiCallScoring/Jobs/GenerateAiCallScoringJob.php:68: RateLimitException |
/Users/lukas/jiminny/app/app/Component/TranscriptionSummary/Jobs/SummarizeTranscriptionJob.php:15:use Jiminny\Exceptions\RateLimitException;
/Users/lukas/jiminny/app/app/Component/TranscriptionSummary/Jobs/SummarizeTranscriptionJob.php:58: GuzzleException|HttpBadRequestException|JsonException|RateLimitException|UnexpectedValueException $exception
/Users/lukas/jiminny/app/app/Component/AiActivityType/Jobs/GenerateAiActivityTypeJob.php:19:use Jiminny\Exceptions\RateLimitException;
/Users/lukas/jiminny/app/app/Component/AiActivityType/Jobs/GenerateAiActivityTypeJob.php:76: RateLimitException |
/Users/lukas/jiminny/app/app/Services/Crm/Hubspot/HubspotClientInterface.php:8:use Jiminny\Exceptions\RateLimitException;
/Users/lukas/jiminny/app/app/Services/Crm/Hubspot/HubspotClientInterface.php:50: * @throws RateLimitException When rate limit is hit
/Users/lukas/jiminny/app/app/Services/Crm/Hubspot/Pagination/HubspotPaginationService.php:195: // RateLimitException and other exceptions are re-thrown as-is
Read
PaginationState.php
PaginationState.php
Read
HandleHubspotRateLimitTest.php
HandleHubspotRateLimitTest.php
Bash
Check how RateLimitException is used in GenerateActionItemsJob
IN
grep -rn "RateLimitException\|LogicException\|RuntimeException" /Users/lukas/jiminny/app/app/Component/ActionItems/Jobs/GenerateActionItemsJob.php | head -20...
|
21037
|
/Users/lukas/jiminny/app/app/Services/Crm/Hubspot/ /Users/lukas/jiminny/app/app/Services/Crm/Hubspot/Client.php...
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