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29600
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1182
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51
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2026-05-13T06:41:26.149396+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778654486149_m1.jpg...
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iTerm2
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screenpipe"
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1
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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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whisper_init_state: kv pad size = 2.36 MB
whi whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T09:39:16.701157Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T09:40:56.137357Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=124268356982924160, trigger=visual_change)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T09:41:18.500151Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
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[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"whisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T09:39:16.701157Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T09:40:56.137357Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=124268356982924160, trigger=visual_change)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T09:41:18.500151Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks","depth":4,"on_screen":true,"value":"whisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T09:39:16.701157Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T09:40:56.137357Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=124268356982924160, trigger=visual_change)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T09:41:18.500151Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.0,"top":0.05888889,"width":0.19722222,"height":0.026666667},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.004166667,"top":0.06333333,"width":0.011111111,"height":0.017777778},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (-zsh)","depth":2,"bounds":{"left":0.19722222,"top":0.05888889,"width":0.196875,"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":0.2013889,"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":0.3940972,"top":0.05888889,"width":0.196875,"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":0.3982639,"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":0.59097224,"top":0.05888889,"width":0.196875,"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":0.5951389,"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":0.7878472,"top":0.05888889,"width":0.196875,"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":0.7920139,"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":0.95625,"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":0.47152779,"top":0.033333335,"width":0.058333334,"height":0.017777778},"on_screen":true,"role_description":"text"}]...
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whisper_init_state: kv pad size = 2.36 MB
whi whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T09:39:16.701157Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T09:40:56.137357Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=124268356982924160, trigger=visual_change)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T09:41:18.500151Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
DOCKER
Close Tab
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screenpipe"
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⌥⌘1
screenpipe"...
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29598
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2026-05-13T06:41:26.342992+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778654486342_m2.jpg...
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iTerm2
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screenpipe"
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1
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monitor_2
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whisper_init_state: kv pad size = 2.36 MB
whi whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T09:39:16.701157Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T09:40:56.137357Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=124268356982924160, trigger=visual_change)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T09:41:18.500151Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
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[{"role":"AXTextArea","text [{"role":"AXTextArea","text":"whisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T09:39:16.701157Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T09:40:56.137357Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=124268356982924160, trigger=visual_change)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T09:41:18.500151Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks","depth":4,"on_screen":true,"value":"whisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T09:39:16.701157Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks\n2026-05-13T09:40:56.137357Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=124268356982924160, trigger=visual_change)\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\nwhisper_backend_init_gpu: device 0: Metal (type: 1)\nwhisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)\nwhisper_backend_init_gpu: using Metal backend\nggml_metal_init: allocating\nggml_metal_init: found device: Apple M1\nggml_metal_init: picking default device: Apple M1\nggml_metal_init: use fusion = true\nggml_metal_init: use concurrency = true\nggml_metal_init: use graph optimize = true\nwhisper_backend_init: using BLAS backend\nwhisper_init_state: kv self size = 3.15 MB\nwhisper_init_state: kv cross size = 9.44 MB\nwhisper_init_state: kv pad size = 2.36 MB\nwhisper_init_state: compute buffer (conv) = 14.17 MB\nwhisper_init_state: compute buffer (encode) = 65.96 MB\nwhisper_init_state: compute buffer (cross) = 8.50 MB\nwhisper_init_state: compute buffer (decode) = 96.83 MB\nggml_metal_free: deallocating\n2026-05-13T09:41:18.500151Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks","is_focused":true},{"role":"AXRadioButton","text":"DOCKER","depth":2,"bounds":{"left":0.27027926,"top":1.0,"width":0.0944149,"height":-0.042298436},"on_screen":true,"role_description":"radio button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXButton","text":"Close Tab","depth":3,"bounds":{"left":0.27227393,"top":1.0,"width":0.005319149,"height":-0.04549086},"on_screen":true,"role_description":"button","is_enabled":false,"is_focused":false,"is_selected":false,"is_expanded":false},{"role":"AXRadioButton","text":"DEV (-zsh)","depth":2,"bounds":{"left":0.36469415,"top":1.0,"width":0.09424867,"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":0.36668882,"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":0.45894283,"top":1.0,"width":0.09424867,"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":0.4609375,"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":0.5531915,"top":1.0,"width":0.09424867,"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":0.55518615,"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":0.64744014,"top":1.0,"width":0.09424867,"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":0.64943486,"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":0.7280585,"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":0.49601063,"top":1.0,"width":0.027925532,"height":-0.02394259},"on_screen":true,"role_description":"text"}]...
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7630033865666081751
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-852231706446596640
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idle
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accessibility
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NULL
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whisper_init_state: kv pad size = 2.36 MB
whi whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T09:39:16.701157Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
2026-05-13T09:40:56.137357Z INFO screenpipe_engine::event_driven_capture: content dedup: skipping capture for monitor 1 (hash=124268356982924160, trigger=visual_change)
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
whisper_backend_init_gpu: device 0: Metal (type: 1)
whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)
whisper_backend_init_gpu: using Metal backend
ggml_metal_init: allocating
ggml_metal_init: found device: Apple M1
ggml_metal_init: picking default device: Apple M1
ggml_metal_init: use fusion = true
ggml_metal_init: use concurrency = true
ggml_metal_init: use graph optimize = true
whisper_backend_init: using BLAS backend
whisper_init_state: kv self size = 3.15 MB
whisper_init_state: kv cross size = 9.44 MB
whisper_init_state: kv pad size = 2.36 MB
whisper_init_state: compute buffer (conv) = 14.17 MB
whisper_init_state: compute buffer (encode) = 65.96 MB
whisper_init_state: compute buffer (cross) = 8.50 MB
whisper_init_state: compute buffer (decode) = 96.83 MB
ggml_metal_free: deallocating
2026-05-13T09:41:18.500151Z INFO screenpipe_audio::audio_manager::manager: reconciliation: transcribed 50 orphaned chunks
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SelectionViewGoRunTerminalWindow1 archive.db-bak U SelectionViewGoRunTerminalWindow1 archive.db-bak Uv screenpipe (SSH: nas)• _ #recycie• tr app-archive.do.oak-pre-installid# screenpine.db# synes screenplpe sulite data to a NAs archive dacabase lappeno-only, no delecions).# ALSO copIes the day's video/Trame daca Tolder to the NAs./screenpipe sync. sh•/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)* syncs a speciric date# syncs today so far# Cron example (runs at 3am daily):0 3 * * * /Users/lukas/•screenpipe/screenpipe_sync.sh > /Users/lukas/ •screenpipe/sync.log 2>&1-euo pipefailCONFIGDB_SRC="S(SCREENPIPE_DB:-SHOME/,screenpipe/db.sqlite}"NAS MOUNT="SINAS MOUNI:= Volumes screenplpe"NAS _MOUNT="S (NAS_MOUNT:-/vo lume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT_START=$(date +%s)10g() €local msg="[$(date '+8Y-&m-&d %H:AM:85')] $*"echo "Smso" tee-a "SLOG FILE'step() (local now=s date +%s)local elapsed=$( ( now - SCRIPT_START ))local min=s elapsed 60local sec=selapsed & 60)printf "\n[+802dm%02ds] > %s\n" "Smin" "Ssec" "S*" | tee -a "SLOG FILE"run_sqlite_heredoc) €local Labele"silLocal sal="s2"local stares date +%s)printf "4-365 " "$label"sqlites "SDB_SRC" «< "Ssql" &local oides!local soinerqr q t qсtвtnдeвee te9local 1=0while kill -0 "Spid" 2>/dev/null; doprintf "n%-36s %s " "$labe]" "s{spinisil}"ies(G + 1 % 10 ))sleep 0.2wait "Soid"if Src -ne 0 : then%-36s x FATLED\n" "Slabel" | tee -a "SLOG FILEexit Srelocal dur=s(( S(date +%s) - start ))nrintf "n8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "s dur % 60 "" 1 tep ca "cloG FTIE™Clack* SSH: nasomaster 00A0 Д3$0| [Platform] Planning... in 17 m100% Lz?.Wed 13 May 9:43:270OKvLets think about how to split the scriot @screenoioe svnc.sh it is bia already. How can I split it to multiole smaller scriot for easierN+ GPlan SWE-1,6WCascade O0 0...
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SelectionViewGoRunTerminalWindow1 archive.db-bak U SelectionViewGoRunTerminalWindow1 archive.db-bak Uv screenpipe (SSH: nas)• _ #recycie• tr app-archive.do.oak-pre-installid# screenpine.db# synes screenplpe sulite data to a NAs archive dacabase lappeno-only, no delecions).# ALSO copIes the day's video/Trame daca Tolder to the NAs./screenpipe sync. sh•/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)* syncs a speciric date# syncs today so far# Cron example (runs at 3am daily):0 3 * * * /Users/lukas/•screenpipe/screenpipe_sync.sh > /Users/lukas/ •screenpipe/sync.log 2>&1-euo pipefailCONFIGDB_SRC="S(SCREENPIPE_DB:-SHOME/,screenpipe/db.sqlite}"NAS MOUNT="SINAS MOUNI:= Volumes screenplpe"NAS _MOUNT="S (NAS_MOUNT:-/vo lume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT_START=$(date +%s)10g() €local msg="[$(date '+8Y-&m-&d %H:AM:85')] $*"echo "Smso" tee-a "SLOG FILE'step() (local now=s date +%s)local elapsed=$( ( now - SCRIPT_START ))local min=s elapsed 60local sec=selapsed & 60)printf "\n[+802dm%02ds] > %s\n" "Smin" "Ssec" "S*" | tee -a "SLOG FILE"run_sqlite_heredoc) €local Labele"silLocal sal="s2"local stares date +%s)printf "4-365 " "$label"sqlites "SDB_SRC" «< "Ssql" &local oides!local soinerqr q t qсtвtnдeвee te9local 1=0while kill -0 "Spid" 2>/dev/null; doprintf "n%-36s %s " "$labe]" "s{spinisil}"ies(G + 1 % 10 ))sleep 0.2wait "Soid"if Src -ne 0 : then%-36s x FATLED\n" "Slabel" | tee -a "SLOG FILEexit Srelocal dur=s(( S(date +%s) - start ))nrintf "n8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "s dur % 60 "" 1 tep ca "cloG FTIE™Clack* SSH: nasomaster 00A0 Д3$0| [Platform] Planning... in 17 m100% Lz?.Wed 13 May 9:43:270OKvLets think about how to split the scriot @screenoioe svnc.sh it is bia already. How can I split it to multiole smaller scriot for easierN+ GPlan SWE-1,6WCascade O0 0...
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HomeActivityFllesLateMoreSlackcalVIewJiminny ...# HomeActivityFllesLateMoreSlackcalVIewJiminny ...# confusion-clinic# curiosity lab# engineering# general# jiminny-bg# platform-tickets# product launches* random# releases# soha-ofhce# support# thank-yous# the people of jimi..^ Direct messages.2o Stoyan TanevGalva Dimitrovae Steliyan GeorgievPetko KashinskiAneliva AngelovaStefka Stoyanova8 Vasil VasilevNikolav Ivanov3 Aneliva Angelova. ...Lukas Kovalik y...#: AopsSii lira GloudToastMistonWindowHelpQ Describe what you are looking for"rreleases8 22MessagesUe Filese BookmarksTrom uminnvicorhvicamboserYesterday ~2026050jiminny/app Added by GitHubcircec APP 3:17 PM• Deployment Successful!rrolectWhen:05/12/202612:17:31lag;View JooCircleCl APP 6:52 PMNew commits aeploved to rropnet rroa-US[b73e2931([URL_WITH_CREDENTIALS] svnc.shit is bia already. How can I split it to multiole smaller scriot for easierLet me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preter• A librarv aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sho)Separate executable scriots that can be run independentiA mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibilitv: Do vou want the sinale > screenpive sync.sh to still work as-is (sourcing the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etcdation would be a moderate split with a lib/ directory:• Lib/screenpipe sync_db.sh - all DB operations (tables, indexes, sync, ris, verity)• Lib/screenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mind?munl..Ask anvthind+ GPlanSWE-1.6*SSH: nas iômaster @0A0 (3lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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HomeActivityFllesLateMoreSlackcalVIewJiminny ...# HomeActivityFllesLateMoreSlackcalVIewJiminny ...# confusion-clinic# curiosity lab# engineering# general# jiminny-bg# platform-tickets# product launches* random# releases# soha-ofhce# support# thank-yous# the people of jimi..^ Direct messages.2o Stoyan TanevGalva Dimitrovae Steliyan GeorgievPetko KashinskiAneliva AngelovaStefka Stoyanova8 Vasil VasilevNikolav Ivanov3 Aneliva Angelova. ...Lukas Kovalik y...#: AopsSii lira GloudToastMistonWindowHelpQ Describe what you are looking for"rreleases8 22MessagesUe Filese BookmarksTrom uminnvicorhvicamboserYesterday ~2026050jiminny/app Added by GitHubcircec APP 3:17 PM• Deployment Successful!rrolectWhen:05/12/202612:17:31lag;View JooCircleCl APP 6:52 PMNew commits aeploved to rropnet rroa-US[b73e2931([URL_WITH_CREDENTIALS] svnc.shit is bia already. How can I split it to multiole smaller scriot for easierLet me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preter• A librarv aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sho)Separate executable scriots that can be run independentiA mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibilitv: Do vou want the sinale > screenpive sync.sh to still work as-is (sourcing the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etcdation would be a moderate split with a lib/ directory:• Lib/screenpipe sync_db.sh - all DB operations (tables, indexes, sync, ris, verity)• Lib/screenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mind?munl..Ask anvthind+ GPlanSWE-1.6*SSH: nas iômaster @0A0 (3lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak UwuPlatrorm Planhine… In 1on100% 5• wea 15 May 9.40.13•0к.+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak UwuPlatrorm Planhine… In 1on100% 5• wea 15 May 9.40.13•0к.+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKERD SlackFileEditViewGoHistoryWindowHelpscreeilDOCKERDEV (-zsh)О 882APP (-zshwhisper_init_state:kv crosssize =9.44 MBwhisper_init_state:kv padsize2.36 MBwhisper_init_state:compute buffer (conv)whisper_init_state:computebuffer (encode) =whisper_init_state:compute buffer (cross)=whisper_init_state: computebuffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu:device 0: Metal (type: 1)whisper_backend_init_gpu:found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init:founddevice:Apple M1ggml_metal_init:pickingdefault device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init: use graph optimize=truewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type:1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init: use concurrency= trueggml_metal_init: use graph optimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13109:43:20.5374032INFO screenpipe_audio::audio_manager::manager: reconciliatior| [Platform] Planning... in 15 m100% <8• Wed 13 May 9:45:16•••EDHomeDMsActivityFilesLater..•More→Describe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan Tanev% Galya Dimitrovao Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKERD SlackFileEditViewGoHistoryWindowHelpscreeilDOCKERDEV (-zsh)О 882APP (-zshwhisper_init_state:kv crosssize =9.44 MBwhisper_init_state:kv padsize2.36 MBwhisper_init_state:compute buffer (conv)whisper_init_state:computebuffer (encode) =whisper_init_state:compute buffer (cross)=whisper_init_state: computebuffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu:device 0: Metal (type: 1)whisper_backend_init_gpu:found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init:founddevice:Apple M1ggml_metal_init:pickingdefault device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init: use graph optimize=truewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type:1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init: use concurrency= trueggml_metal_init: use graph optimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13109:43:20.5374032INFO screenpipe_audio::audio_manager::manager: reconciliatior| [Platform] Planning... in 15 m100% <8• Wed 13 May 9:45:16•••EDHomeDMsActivityFilesLater..•More→Describe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan Tanev% Galya Dimitrovao Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak UwuPlatrorm Planhine… In 1on100% 5• wea 13 May 9.40.44•П (кк'+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak UwuPlatrorm Planhine… In 1on100% 5• wea 13 May 9.40.44•П (кк'+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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2026-05-13T06:45:46.780954+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778654746780_m1.jpg...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKERD SlackFileEditViewGoHistoryWindowHelpscreeilDOCKERDEV (-zsh)О 882APP (-zshwhisper_init_state:kv crosssize =9.44 MBwhisper_init_state:kv padsize2.36 MBwhisper_init_state:compute buffer (conv)whisper_init_state:computebuffer (encode) =whisper_init_state:compute buffer (cross)=whisper_init_state: computebuffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu:device 0: Metal (type: 1)whisper_backend_init_gpu:found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init:founddevice:Apple M1ggml_metal_init:pickingdefault device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init: use graph optimize=truewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type:1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init: use concurrency= trueggml_metal_init: use graph optimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13109:45:22.2210592INFO screenpipe_audio::audio_manager::manager: reconciliatior| [Platform] Planning... in 15 m100% <8• Wed 13 May 9:45:46•••EDHomeDMsActivityFilesLater..•More→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan Tanev% Galya Dimitrovao Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKERD SlackFileEditViewGoHistoryWindowHelpscreeilDOCKERDEV (-zsh)О 882APP (-zshwhisper_init_state:kv crosssize =9.44 MBwhisper_init_state:kv padsize2.36 MBwhisper_init_state:compute buffer (conv)whisper_init_state:computebuffer (encode) =whisper_init_state:compute buffer (cross)=whisper_init_state: computebuffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu:device 0: Metal (type: 1)whisper_backend_init_gpu:found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init:founddevice:Apple M1ggml_metal_init:pickingdefault device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init: use graph optimize=truewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type:1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init: use concurrency= trueggml_metal_init: use graph optimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13109:45:22.2210592INFO screenpipe_audio::audio_manager::manager: reconciliatior| [Platform] Planning... in 15 m100% <8• Wed 13 May 9:45:46•••EDHomeDMsActivityFilesLater..•More→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan Tanev% Galya Dimitrovao Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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2026-05-13T06:46:14.943263+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778654774943_m2.jpg...
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slackv screenpipe [SSH: nas)- #recycle• tr app# sc slackv screenpipe [SSH: nas)- #recycle• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U100% 12P• wea 13 May 9.40.14•П (кк'+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)- #recycle• tr app# sc slackv screenpipe [SSH: nas)- #recycle• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U100% 12P• wea 13 May 9.40.14•П (кк'+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKERD SlackFileEditViewGoHistoryWindowHelpscreeilDOCKERDEV (-zsh)О 882APP (-zshwhisper_init_state:kv crosssize =9.44 MBwhisper_init_state:kv padsize2.36 MBwhisper_init_state:compute buffer (conv)whisper_init_state:computebuffer (encode) =whisper_init_state:compute buffer (cross)=whisper_init_state: computebuffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu:device 0: Metal (type: 1)whisper_backend_init_gpu:found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init:founddevice:Apple M1ggml_metal_init:pickingdefault device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init: use graph optimize=truewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type:1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init: use concurrency= trueggml_metal_init: use graph optimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13109:45:22.2210592INFO screenpipe_audio::audio_manager::manager: reconciliatior•••EDHomeDMsActivityFilesLater..•More| [Platform] Planning... in 14 m100% <8• Wed 13 May 9:46:16→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan Tanev®. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKERD SlackFileEditViewGoHistoryWindowHelpscreeilDOCKERDEV (-zsh)О 882APP (-zshwhisper_init_state:kv crosssize =9.44 MBwhisper_init_state:kv padsize2.36 MBwhisper_init_state:compute buffer (conv)whisper_init_state:computebuffer (encode) =whisper_init_state:compute buffer (cross)=whisper_init_state: computebuffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu:device 0: Metal (type: 1)whisper_backend_init_gpu:found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init:founddevice:Apple M1ggml_metal_init:pickingdefault device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init: use graph optimize=truewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type:1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init: use concurrency= trueggml_metal_init: use graph optimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13109:45:22.2210592INFO screenpipe_audio::audio_manager::manager: reconciliatior•••EDHomeDMsActivityFilesLater..•More| [Platform] Planning... in 14 m100% <8• Wed 13 May 9:46:16→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan Tanev®. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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slackv screenpipe [SSH: nas)- #recycle• tr app# sc slackv screenpipe [SSH: nas)- #recycle• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U100% 5• wea 13 May 9.40.44•П (кк'+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)- #recycle• tr app# sc slackv screenpipe [SSH: nas)- #recycle• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U100% 5• wea 13 May 9.40.44•П (кк'+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• 881DEV (-zsh)О 882APP (-zshwhisper_init_state:compute buffer(decode) =96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)S 0: de:t21 Ctype: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocating9gml_metal_init:found device: Apple M1ggml_metal_init:pickingdefault device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init: use graph optimizetruewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize=3.15MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)St: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init: use fusion= trueggml_metal_init: use concurrency= trueggml_metal_init: use graph optimize = truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13T09:45:22.221059ZINFO screenpipe_audio::audio_manager::manager: reconciliatiortip: wirescreenpipe into claude with one command:claude mcp add screenpipe -- npx -y screenpipe-mcpthen ask claude to build a pipe that tracks who you are, your todos, and how you•••EDHomeDMsActivityFilesLater..•More| [Platform] Planning... in 14 m100% <8• Wed 13 May 9:46:47→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan TanevP. Galya Dimitrovao Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• 881DEV (-zsh)О 882APP (-zshwhisper_init_state:compute buffer(decode) =96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)S 0: de:t21 Ctype: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocating9gml_metal_init:found device: Apple M1ggml_metal_init:pickingdefault device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init: use graph optimizetruewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize=3.15MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)St: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init: use fusion= trueggml_metal_init: use concurrency= trueggml_metal_init: use graph optimize = truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13T09:45:22.221059ZINFO screenpipe_audio::audio_manager::manager: reconciliatiortip: wirescreenpipe into claude with one command:claude mcp add screenpipe -- npx -y screenpipe-mcpthen ask claude to build a pipe that tracks who you are, your todos, and how you•••EDHomeDMsActivityFilesLater..•More| [Platform] Planning... in 14 m100% <8• Wed 13 May 9:46:47→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan TanevP. Galya Dimitrovao Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U4uPlatorm Plannino… In 13h100% 5• wea 13 May 9.4/.14•П к \+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U4uPlatorm Plannino… In 13h100% 5• wea 13 May 9.4/.14•П к \+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778654838380_m1.jpg...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• 881DEV (-zsh)О 882APP (-zshwhisper_init_state:compute buffer(decode) =96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)S 0: de:t21 Ctype: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocating9gml_metal_init:found device: Apple M1ggml_metal_init:pickingdefault device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init: use graph optimizetruewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize=3.15MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)St: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init: use fusion= trueggml_metal_init: use concurrency= trueggml_metal_init: use graph optimize = truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13T09:45:22.221059ZINFO screenpipe_audio::audio_manager::manager: reconciliatiortip: wirescreenpipe into claude with one command:claude mcp add screenpipe -- npx -y screenpipe-mcpthen ask claude to build a pipe that tracks who you are, your todos, and how you| [Platform] Planning... in 13 m100% <8• Wed 13 May 9:47:17•••EDHomeDMsActivityFilesLater..•More→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan TanevP. Galya Dimitrovao Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• 881DEV (-zsh)О 882APP (-zshwhisper_init_state:compute buffer(decode) =96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)S 0: de:t21 Ctype: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocating9gml_metal_init:found device: Apple M1ggml_metal_init:pickingdefault device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init: use graph optimizetruewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize=3.15MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)St: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init: use fusion= trueggml_metal_init: use concurrency= trueggml_metal_init: use graph optimize = truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13T09:45:22.221059ZINFO screenpipe_audio::audio_manager::manager: reconciliatiortip: wirescreenpipe into claude with one command:claude mcp add screenpipe -- npx -y screenpipe-mcpthen ask claude to build a pipe that tracks who you are, your todos, and how you| [Platform] Planning... in 13 m100% <8• Wed 13 May 9:47:17•••EDHomeDMsActivityFilesLater..•More→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan TanevP. Galya Dimitrovao Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U4uPlatorm Plannino… In 13h100% 5• wea 13 May 9.4/.40•П (кк'+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U4uPlatorm Plannino… In 13h100% 5• wea 13 May 9.4/.40•П (кк'+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKERD SlackFileEditViewGoHistoryWindowHelpscreeilDOCKERDEV (-zsh)О 882APP (-zshwhisper_init_state:kv crosssize =9.44 MBwhisper_init_state:kv padsize2.36 MBwhisper_init_state:compute buffer (conv)whisper_init_state:computebuffer (encode) =whisper_init_state:compute buffer (cross)=whisper_init_state: computebuffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu:device 0: Metal (type: 1)whisper_backend_init_gpu:found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init:founddevice:Apple M1ggml_metal_init:pickingdefault device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init: use graph optimize=truewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type:1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init: use concurrency= trueggml_metal_init: use graph optimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13T09:47:23.926431ZINFO screenpipe_audio::audio_manager::manager: reconciliatior•••EDHomeDMsActivityFilesLater..•More| [Platform] Planning... in 13 m100% <8• Wed 13 May 9:47:48→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan Tanev®. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKERD SlackFileEditViewGoHistoryWindowHelpscreeilDOCKERDEV (-zsh)О 882APP (-zshwhisper_init_state:kv crosssize =9.44 MBwhisper_init_state:kv padsize2.36 MBwhisper_init_state:compute buffer (conv)whisper_init_state:computebuffer (encode) =whisper_init_state:compute buffer (cross)=whisper_init_state: computebuffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu:device 0: Metal (type: 1)whisper_backend_init_gpu:found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init:founddevice:Apple M1ggml_metal_init:pickingdefault device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init: use graph optimize=truewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type:1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init: use concurrency= trueggml_metal_init: use graph optimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13T09:47:23.926431ZINFO screenpipe_audio::audio_manager::manager: reconciliatior•••EDHomeDMsActivityFilesLater..•More| [Platform] Planning... in 13 m100% <8• Wed 13 May 9:47:48→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan Tanev®. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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2026-05-13T06:48:17.451319+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778654897451_m2.jpg...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U4uPlarorm Plannino…. In 12 n100% 5wea 15 May 9.40.1/•П (кк'+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U4uPlarorm Plannino…. In 12 n100% 5wea 15 May 9.40.1/•П (кк'+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKERD SlackFileEditViewGoHistoryWindowHelpscreeilDOCKERDEV (-zsh)О 882APP (-zshwhisper_init_state:whisper_init_state:kv padsize2.36 MBcompute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state:compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type:1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init: use graph optimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize =2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu:device 0: Metal (type: 1)whisper_backend_init_gpu: found GPUdevice 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrencytrueggml_metal_init: use graph optimizetruewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13T09:47:23.926431Z2026-05-13109:48:16.7576122INFO screenpipe_audio::audio_manager::manager: reconciliatiorINFO screenpipe_engine::snapshot_compaction: snapshot compac*•••EDHomeDMsActivityFilesLater..•MoreJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan Tanev®. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast| [Platform] Planning... in 12 m100% <8• Wed 13 May 9:48:19→Describe what you are looking for# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKERD SlackFileEditViewGoHistoryWindowHelpscreeilDOCKERDEV (-zsh)О 882APP (-zshwhisper_init_state:whisper_init_state:kv padsize2.36 MBcompute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state:compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type:1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init: use graph optimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize =2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu:device 0: Metal (type: 1)whisper_backend_init_gpu: found GPUdevice 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrencytrueggml_metal_init: use graph optimizetruewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13T09:47:23.926431Z2026-05-13109:48:16.7576122INFO screenpipe_audio::audio_manager::manager: reconciliatiorINFO screenpipe_engine::snapshot_compaction: snapshot compac*•••EDHomeDMsActivityFilesLater..•MoreJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan Tanev®. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast| [Platform] Planning... in 12 m100% <8• Wed 13 May 9:48:19→Describe what you are looking for# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U4uPlarorm Plannino…. In 12 n100% 5.• wea 13 May 9.40.4.•0к.+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U4uPlarorm Plannino…. In 12 n100% 5.• wea 13 May 9.40.4.•0к.+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whi SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whisper_init_state:compute buffer(encode)=whisper_init_state:compute buffer (cross)=whisper_init_state: compute buffer (decode) =DEV (-zsh)65.96 MB8.50 MB96.83 MBО 882ggml_metal_free:deallocatingwhisper_backend_init_gpu:device 0: Metal (type: 1)whisper_backend_init_gpu:found GPUdevice 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrencytrueggml_metal_init:usegraph optimizetruewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init: use fusion= trueggml_metal_init: use concurrency= trueggml_metal_init: use graph optimize = truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13709:47:23.926431Z2026-05-13T09:48:16.757612Z2026-05-13T09:48:20.955425Z2026-05-13109:48:25.5876362INFO screenpipe_audio::audio_manager::manager: reconciliatioiINFO screenpipe_engine::snapshot_compaction: snapshot compac-INFO screenpipe_engine::snapshot_compaction: snapshot compac*INFO screenpipe_engine::snapshot_compaction: snapshot compac*screeilAPP (-zsh•••EDHomeDMsActivityFilesLater..•MoreJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan Tanev®. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast| [Platform] Planning... in 12 m100% <8• Wed 13 May 9:48:49→Describe what you are looking for# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whi SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whisper_init_state:compute buffer(encode)=whisper_init_state:compute buffer (cross)=whisper_init_state: compute buffer (decode) =DEV (-zsh)65.96 MB8.50 MB96.83 MBО 882ggml_metal_free:deallocatingwhisper_backend_init_gpu:device 0: Metal (type: 1)whisper_backend_init_gpu:found GPUdevice 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrencytrueggml_metal_init:usegraph optimizetruewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init: use fusion= trueggml_metal_init: use concurrency= trueggml_metal_init: use graph optimize = truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13709:47:23.926431Z2026-05-13T09:48:16.757612Z2026-05-13T09:48:20.955425Z2026-05-13109:48:25.5876362INFO screenpipe_audio::audio_manager::manager: reconciliatioiINFO screenpipe_engine::snapshot_compaction: snapshot compac-INFO screenpipe_engine::snapshot_compaction: snapshot compac*INFO screenpipe_engine::snapshot_compaction: snapshot compac*screeilAPP (-zsh•••EDHomeDMsActivityFilesLater..•MoreJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan Tanev®. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast| [Platform] Planning... in 12 m100% <8• Wed 13 May 9:48:49→Describe what you are looking for# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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2026-05-13T06:49:18.722859+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778654958722_m2.jpg...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak UYPlatorm Plannino. In 11h100% 5• wea 15 May 9.49.10•0к.+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak UYPlatorm Plannino. In 11h100% 5• wea 15 May 9.49.10•0к.+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whi SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whisper_init_state:compute buffer(encode)=whisper_init_state:compute buffer (cross)=whisper_init_state: compute buffer (decode) =DEV (-zsh)65.96 MB8.50 MB96.83 MBО 882ggml_metal_free:deallocatingwhisper_backend_init_gpu:device 0: Metal (type: 1)whisper_backend_init_gpu:found GPUdevice 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrencytrueggml_metal_init:usegraph optimizetruewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init: use fusion= trueggml_metal_init: use concurrency= trueggml_metal_init: use graph optimize = truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13709:47:23.926431Z2026-05-13T09:48:16.757612Z2026-05-13T09:48:20.955425Z2026-05-13109:48:25.5876362INFO screenpipe_audio::audio_manager::manager: reconciliatioiINFO screenpipe_engine::snapshot_compaction: snapshot compac-INFO screenpipe_engine::snapshot_compaction: snapshot compac*INFO screenpipe_engine::snapshot_compaction: snapshot compac*screeilAPP (-zsh•••EDHomeDMsActivityFilesLater..•More| [Platform] Planning... in 11 m100% <8• Wed 13 May 9:49:20→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan Tanev®. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whi SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whisper_init_state:compute buffer(encode)=whisper_init_state:compute buffer (cross)=whisper_init_state: compute buffer (decode) =DEV (-zsh)65.96 MB8.50 MB96.83 MBО 882ggml_metal_free:deallocatingwhisper_backend_init_gpu:device 0: Metal (type: 1)whisper_backend_init_gpu:found GPUdevice 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrencytrueggml_metal_init:usegraph optimizetruewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init: use fusion= trueggml_metal_init: use concurrency= trueggml_metal_init: use graph optimize = truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13709:47:23.926431Z2026-05-13T09:48:16.757612Z2026-05-13T09:48:20.955425Z2026-05-13109:48:25.5876362INFO screenpipe_audio::audio_manager::manager: reconciliatioiINFO screenpipe_engine::snapshot_compaction: snapshot compac-INFO screenpipe_engine::snapshot_compaction: snapshot compac*INFO screenpipe_engine::snapshot_compaction: snapshot compac*screeilAPP (-zsh•••EDHomeDMsActivityFilesLater..•More| [Platform] Planning... in 11 m100% <8• Wed 13 May 9:49:20→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan Tanev®. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak UYPlatorm Plannino. In 11h100% 5• wea 13 May 9.49.49•П (кк'+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak UYPlatorm Plannino. In 11h100% 5• wea 13 May 9.49.49•П (кк'+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• 881whisper_init_state:compute buffer(cross)whisper_init_state:compute buffer(decode) =DEV (-zsh)8.50 MB96.83 MBO 82APP (-zshggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency=trueggml_metal_init: use graphoptimizetruewhisper_backend_init: using BLASbackendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: founddevice: Apple M1ggml_metal_init:pickingdefault device: Apple M1ggml_metal_init: use fusion= trueggml_metal_init: use concurrency=trueggml_metal_init: use graph optimize=truewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: computebuffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13T09:49:25.619097ZINFO screenpipe_audio::audio_manager::manager: reconciliatior2026-05-13709:49:49.934388ZWARNscreenpipe_audio::core::run_record_and_transcribe: no usvice hijack by another app), triggering reconnect2026-05-13T09:49:49.934455ZWARN screenpipe_audio::audio_manager::manager: recording foratafrom soundcore AeroClip(input) for 30s (suspected device hijack by another process)HomeDMsActivityFilesLater..•More| [Platform] Planning... in 11 m100% <8• Wed 13 May 9:49:50ED→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan Tanev®. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• 881whisper_init_state:compute buffer(cross)whisper_init_state:compute buffer(decode) =DEV (-zsh)8.50 MB96.83 MBO 82APP (-zshggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency=trueggml_metal_init: use graphoptimizetruewhisper_backend_init: using BLASbackendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: founddevice: Apple M1ggml_metal_init:pickingdefault device: Apple M1ggml_metal_init: use fusion= trueggml_metal_init: use concurrency=trueggml_metal_init: use graph optimize=truewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: computebuffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13T09:49:25.619097ZINFO screenpipe_audio::audio_manager::manager: reconciliatior2026-05-13709:49:49.934388ZWARNscreenpipe_audio::core::run_record_and_transcribe: no usvice hijack by another app), triggering reconnect2026-05-13T09:49:49.934455ZWARN screenpipe_audio::audio_manager::manager: recording foratafrom soundcore AeroClip(input) for 30s (suspected device hijack by another process)HomeDMsActivityFilesLater..•More| [Platform] Planning... in 11 m100% <8• Wed 13 May 9:49:50ED→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan Tanev®. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U4uPlatorm Plannino…. In 10n100% 5.• wea 15 May 9.o0.19•П (кк'+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U4uPlatorm Plannino…. In 10n100% 5.• wea 15 May 9.o0.19•П (кк'+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• 881DEV (-zsh)O 82APP (-zshggml_metal_init:allocatingggml_metal_init:found device:Apple M1ggml_metal_init:picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrencytrueggml_metal_init:use graph optimizetruewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state:compute buffer(encode)whisper_init_state:computebuffer (cross)whisper_init_state:compute buffer (decode)14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu:using Metal backendggml_metal_init: allocatingggml_metal_init:founddevice: Apple M1ggml_metal_init:picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init:use graph optimize=truewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize3.15MBwhisper_init_state: kv cross size =9.44MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state:computebuffer (cross)whisper_init_state:computebuffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13109:49:25.6190972INFO screenpipe_audio::audio_manager::manager: reconciliatior2026-05-13T09:49:49.934388ZWARN screenpipe_audio::core::run_record_and_transcribe: no usvice hijack by another app), triggering reconnect2026-05-13109:49:49.9344552WARN screenpipe_audio::audio_manager::manager: recordingatafromsoundcore AeroClipfor 30s (suspected device hijack by anotherprocess)2026-05-13T09:49:51.830359ZWARN screenpipe_audio::audio_manager::device_monitor: [DEVICIr restart2026-05-13709:49:51.83046522026-05-13T09:49:51.865918Z2026-05-13T09:49:51.866007Z2026-05-13109:49:51.8660502INFOscreenpipe_audio::device::device_manager: Stopping devi‹INFOscreenpipe_audio::device::device_manager: starting recolINFO screenpipe_audio::audio_manager::device_monitor: restar-INFO screenpipe_audio::core::run_record_and_transcribe: star-| [Platform] Planning... in 10 m100% <8• Wed 13 May 9:50:21•••EDHomeDMsActivityFilesLater..•More→Describe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan Tanev. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka StoyanovaB. Vasil VasilevNikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• 881DEV (-zsh)O 82APP (-zshggml_metal_init:allocatingggml_metal_init:found device:Apple M1ggml_metal_init:picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrencytrueggml_metal_init:use graph optimizetruewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state:compute buffer(encode)whisper_init_state:computebuffer (cross)whisper_init_state:compute buffer (decode)14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu:using Metal backendggml_metal_init: allocatingggml_metal_init:founddevice: Apple M1ggml_metal_init:picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init:use graph optimize=truewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize3.15MBwhisper_init_state: kv cross size =9.44MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state:computebuffer (cross)whisper_init_state:computebuffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13109:49:25.6190972INFO screenpipe_audio::audio_manager::manager: reconciliatior2026-05-13T09:49:49.934388ZWARN screenpipe_audio::core::run_record_and_transcribe: no usvice hijack by another app), triggering reconnect2026-05-13109:49:49.9344552WARN screenpipe_audio::audio_manager::manager: recordingatafromsoundcore AeroClipfor 30s (suspected device hijack by anotherprocess)2026-05-13T09:49:51.830359ZWARN screenpipe_audio::audio_manager::device_monitor: [DEVICIr restart2026-05-13709:49:51.83046522026-05-13T09:49:51.865918Z2026-05-13T09:49:51.866007Z2026-05-13109:49:51.8660502INFOscreenpipe_audio::device::device_manager: Stopping devi‹INFOscreenpipe_audio::device::device_manager: starting recolINFO screenpipe_audio::audio_manager::device_monitor: restar-INFO screenpipe_audio::core::run_record_and_transcribe: star-| [Platform] Planning... in 10 m100% <8• Wed 13 May 9:50:21•••EDHomeDMsActivityFilesLater..•More→Describe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan Tanev. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka StoyanovaB. Vasil VasilevNikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U4uPlatorm Plannino…. In 10n100% 5.• wea 15 May 9:o0.o0•П (кк'+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U4uPlatorm Plannino…. In 10n100% 5.• wea 15 May 9:o0.o0•П (кк'+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• 881DEV (-zsh)O 82APP (-zshggml_metal_init:allocatingggml_metal_init:found device:Apple M1ggml_metal_init:picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrencytrueggml_metal_init:use graph optimizetruewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state:compute buffer(encode)whisper_init_state:computebuffer (cross)whisper_init_state:compute buffer (decode)14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu:using Metal backendggml_metal_init: allocatingggml_metal_init:founddevice: Apple M1ggml_metal_init:picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init:use graph optimize=truewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize3.15MBwhisper_init_state: kv cross size =9.44MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state:computebuffer (cross)whisper_init_state:computebuffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13109:49:25.6190972INFO screenpipe_audio::audio_manager::manager: reconciliatior2026-05-13T09:49:49.934388ZWARN screenpipe_audio::core::run_record_and_transcribe: no usvice hijack by another app), triggering reconnect2026-05-13109:49:49.9344552WARN screenpipe_audio::audio_manager::manager: recordingatafromsoundcore AeroClipfor 30s (suspected device hijack by anotherprocess)2026-05-13T09:49:51.830359ZWARN screenpipe_audio::audio_manager::device_monitor: [DEVICIr restart2026-05-13709:49:51.83046522026-05-13T09:49:51.865918Z2026-05-13T09:49:51.866007Z2026-05-13109:49:51.8660502INFOscreenpipe_audio::device::device_manager: Stopping devi‹INFOscreenpipe_audio::device::device_manager: starting recolINFO screenpipe_audio::audio_manager::device_monitor: restar-INFO screenpipe_audio::core::run_record_and_transcribe: star-| [Platform] Planning... in 10 m100% <8• Wed 13 May 9:50:51•••EDHomeDMsActivityFilesLater..•More→Describe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan Tanev. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka StoyanovaB. Vasil VasilevNikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• 881DEV (-zsh)O 82APP (-zshggml_metal_init:allocatingggml_metal_init:found device:Apple M1ggml_metal_init:picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrencytrueggml_metal_init:use graph optimizetruewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state:compute buffer(encode)whisper_init_state:computebuffer (cross)whisper_init_state:compute buffer (decode)14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu:using Metal backendggml_metal_init: allocatingggml_metal_init:founddevice: Apple M1ggml_metal_init:picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init:use graph optimize=truewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize3.15MBwhisper_init_state: kv cross size =9.44MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state:computebuffer (cross)whisper_init_state:computebuffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13109:49:25.6190972INFO screenpipe_audio::audio_manager::manager: reconciliatior2026-05-13T09:49:49.934388ZWARN screenpipe_audio::core::run_record_and_transcribe: no usvice hijack by another app), triggering reconnect2026-05-13109:49:49.9344552WARN screenpipe_audio::audio_manager::manager: recordingatafromsoundcore AeroClipfor 30s (suspected device hijack by anotherprocess)2026-05-13T09:49:51.830359ZWARN screenpipe_audio::audio_manager::device_monitor: [DEVICIr restart2026-05-13709:49:51.83046522026-05-13T09:49:51.865918Z2026-05-13T09:49:51.866007Z2026-05-13109:49:51.8660502INFOscreenpipe_audio::device::device_manager: Stopping devi‹INFOscreenpipe_audio::device::device_manager: starting recolINFO screenpipe_audio::audio_manager::device_monitor: restar-INFO screenpipe_audio::core::run_record_and_transcribe: star-| [Platform] Planning... in 10 m100% <8• Wed 13 May 9:50:51•••EDHomeDMsActivityFilesLater..•More→Describe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan Tanev. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka StoyanovaB. Vasil VasilevNikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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slackv screenpipe [SSH: nas)- #recycle• tr app# sc slackv screenpipe [SSH: nas)- #recycle• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U100% 5.• wea 15 May 9:o1-20+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)- #recycle• tr app# sc slackv screenpipe [SSH: nas)- #recycle• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U100% 5.• wea 15 May 9:o1-20+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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SlackFileEditViewGoHistoryWindowHelpDOCKER• 881DEV SlackFileEditViewGoHistoryWindowHelpDOCKER• 881DEV (-zsh)O 82ggml_metal_init:allocatingggml_metal_init:found device:Apple M1ggml_metal_init:picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrencytrueggml_metal_init:use graph optimizetruewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state:compute buffer(encode)whisper_init_state:computebuffer (cross)whisper_init_state:compute buffer (decode)14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu:using Metal backendggml_metal_init: allocatingggml_metal_init:founddevice: Apple M1ggml_metal_init:picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init:use graph optimize=truewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize3.15MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state:computebuffer (cross)whisper_init_state:computebuffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13109:49:25.6190972INFO screenpipe_audio::audio_manager::manager: reconciliatior2026-05-13T09:49:49.934388ZWARN screenpipe_audio::core::run_record_and_transcribe: no usvice hijack by another app), triggering reconnect2026-05-13109:49:49.9344552WARN screenpipe_audio::audio_manager::manager: recordingatafromsoundcore AeroClipfor 30s (suspected device hijack by anotherprocess)2026-05-13T09:49:51.830359ZWARN screenpipe_audio::audio_manager::device_monitor: [DEVICIr restart2026-05-13709:49:51.83046522026-05-13T09:49:51.865918Z2026-05-13T09:49:51.866007Z2026-05-13109:49:51.8660502INFOscreenpipe_audio::device::device_manager: Stopping devi‹INFOscreenpipe_audio::device::device_manager: starting recolINFO screenpipe_audio::audio_manager::device_monitor: restar-INFO screenpipe_audio::core::run_record_and_transcribe: star-(Platform] Planning... in 9 m100% <8• Wed 13 May 9:51:22screeil•••EDAPP (-zshHomeDMsActivityFilesLater..•More→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan Tanev. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka StoyanovaB. Vasil VasilevNikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpDOCKER• 881DEV SlackFileEditViewGoHistoryWindowHelpDOCKER• 881DEV (-zsh)O 82ggml_metal_init:allocatingggml_metal_init:found device:Apple M1ggml_metal_init:picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrencytrueggml_metal_init:use graph optimizetruewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state:compute buffer(encode)whisper_init_state:computebuffer (cross)whisper_init_state:compute buffer (decode)14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu:using Metal backendggml_metal_init: allocatingggml_metal_init:founddevice: Apple M1ggml_metal_init:picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init:use graph optimize=truewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize3.15MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state:computebuffer (cross)whisper_init_state:computebuffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13109:49:25.6190972INFO screenpipe_audio::audio_manager::manager: reconciliatior2026-05-13T09:49:49.934388ZWARN screenpipe_audio::core::run_record_and_transcribe: no usvice hijack by another app), triggering reconnect2026-05-13109:49:49.9344552WARN screenpipe_audio::audio_manager::manager: recordingatafromsoundcore AeroClipfor 30s (suspected device hijack by anotherprocess)2026-05-13T09:49:51.830359ZWARN screenpipe_audio::audio_manager::device_monitor: [DEVICIr restart2026-05-13709:49:51.83046522026-05-13T09:49:51.865918Z2026-05-13T09:49:51.866007Z2026-05-13109:49:51.8660502INFOscreenpipe_audio::device::device_manager: Stopping devi‹INFOscreenpipe_audio::device::device_manager: starting recolINFO screenpipe_audio::audio_manager::device_monitor: restar-INFO screenpipe_audio::core::run_record_and_transcribe: star-(Platform] Planning... in 9 m100% <8• Wed 13 May 9:51:22screeil•••EDAPP (-zshHomeDMsActivityFilesLater..•More→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan Tanev. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka StoyanovaB. Vasil VasilevNikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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slackv screenpipe [SSH: nas)- #recycle• tr app# sc slackv screenpipe [SSH: nas)- #recycle• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U100% 5• wea 15 May 9:o1.0•0к.+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)- #recycle• tr app# sc slackv screenpipe [SSH: nas)- #recycle• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U100% 5• wea 15 May 9:o1.0•0к.+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whi SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whisper_init_state:compute buffer(cross)whisper_init_state:compute buffer(decode) =DEV (-zsh)8.50 MB96.83 MBO 82ggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency=trueggml_metal_init: use graphoptimizetruewhisper_backend_init: using BLASbackendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: founddevice: Apple M1ggml_metal_init: pickingdefault device: Apple M1ggml_metal_init: use fusion= trueggml_metal_init: use concurrency=trueggml_metal_init: use graph optimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13T09:51:27.373440ZINFO screenpipe_audio::audio_manager::manager: reconciliatiortip: install a starter bundle of pipes:screenpipe install https://screenpi.pe/start.jsonscreeilAPP (-zsh•••EDHomeDMsActivityFilesLater..•More(Platform] Planning... in 9 m100% <8• Wed 13 May 9:51:52→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan Tanev®. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whi SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whisper_init_state:compute buffer(cross)whisper_init_state:compute buffer(decode) =DEV (-zsh)8.50 MB96.83 MBO 82ggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency=trueggml_metal_init: use graphoptimizetruewhisper_backend_init: using BLASbackendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: founddevice: Apple M1ggml_metal_init: pickingdefault device: Apple M1ggml_metal_init: use fusion= trueggml_metal_init: use concurrency=trueggml_metal_init: use graph optimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13T09:51:27.373440ZINFO screenpipe_audio::audio_manager::manager: reconciliatiortip: install a starter bundle of pipes:screenpipe install https://screenpi.pe/start.jsonscreeilAPP (-zsh•••EDHomeDMsActivityFilesLater..•More(Platform] Planning... in 9 m100% <8• Wed 13 May 9:51:52→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan Tanev®. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778655142462_m2.jpg...
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slackv screenpipe [SSH: nas)- #recycle• tr app# sc slackv screenpipe [SSH: nas)- #recycle• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U100% 5• wea 15 May S.oz-L.•0к.+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)- #recycle• tr app# sc slackv screenpipe [SSH: nas)- #recycle• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U100% 5• wea 15 May S.oz-L.•0к.+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whi SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whisper_init_state:compute buffer(cross)whisper_init_state:compute buffer(decode) =DEV (-zsh)8.50 MB96.83 MBO 82ggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency=trueggml_metal_init: use graphoptimizetruewhisper_backend_init: using BLASbackendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: founddevice: Apple M1ggml_metal_init: pickingdefault device: Apple M1ggml_metal_init: use fusion= trueggml_metal_init: use concurrency=trueggml_metal_init: use graph optimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13T09:51:27.373440ZINFO screenpipe_audio::audio_manager::manager: reconciliatiortip: install a starter bundle of pipes:screenpipe install https://screenpi.pe/start.jsonscreeilAPP (-zsh•••EDHomeDMsActivityFilesLater..•More(Platform] Planning... in 8 m100% <8• Wed 13 May 9:52:23→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan Tanev®. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whi SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whisper_init_state:compute buffer(cross)whisper_init_state:compute buffer(decode) =DEV (-zsh)8.50 MB96.83 MBO 82ggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency=trueggml_metal_init: use graphoptimizetruewhisper_backend_init: using BLASbackendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: founddevice: Apple M1ggml_metal_init: pickingdefault device: Apple M1ggml_metal_init: use fusion= trueggml_metal_init: use concurrency=trueggml_metal_init: use graph optimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfsize=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13T09:51:27.373440ZINFO screenpipe_audio::audio_manager::manager: reconciliatiortip: install a starter bundle of pipes:screenpipe install https://screenpi.pe/start.jsonscreeilAPP (-zsh•••EDHomeDMsActivityFilesLater..•More(Platform] Planning... in 8 m100% <8• Wed 13 May 9:52:23→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan Tanev®. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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slackv screenpipe [SSH: nas)- #recycle• tr app# sc slackv screenpipe [SSH: nas)- #recycle• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U100% 5• wea 15 May yioz-oz•0к.+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)- #recycle• tr app# sc slackv screenpipe [SSH: nas)- #recycle• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U100% 5• wea 15 May yioz-oz•0к.+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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SlackFileEditViewGoHistoryWindowHelpDOCKER• 881DEV SlackFileEditViewGoHistoryWindowHelpDOCKER• 881DEV (-zsh)whisper_backend_init_gpu: found GPUdevice 0:Metalwhisper_backend_init_gpu: using Metal backendggml_metal_init: allocating9gml_metal_init:found device: Apple M1ggml_metal_init:picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrencytrueggml_metal_init: use graph optimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode)=whisper_init_state: compute buffer (cross)whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13T09:51:27.373440ZO 82(type: 1, cnt: 0)INFO screenpipe_audio::audio_manager::manager: reconciliatioitip: install a starter bundle of pipes:screenpipe install https://screenpi.pe/start.json2026-05-13709:52:40.567321ZERROR screenpipe_audio::core::stream: an error occurred on the2026-05-13109:52:42.0908462INFO screenpipe_audio::audio_manager::device_monitor:system2026-05-13T09:52:42.092980ZINFO screenpipe_audio::device::device_manager: startingrecoi2026-05-13T09:52:42.093096ZINFO screenpipe_audio::audio_manager::device_monitor:switche2026-05-13T09:52:42.093159ZINFO screenpipe_audio::core::run_record_and_transcribe:stari2026-05-13T09:52:48.101704ZINFOscreenpipe_audio::audio_manager::device_monitor: system2026-05-13T09:52:48.101858ZERROR screenpipe_audio::audio_manager::device_monitor: failedut) not found (willback off)2026-05-13709:52:48.10195422026-05-13T09:52:48.104457ZINFO screenpipe_audio::core::run_record_and_transcribe: stop:WARN screenpipe_audio::audio_manager::device_monitor: [DEVICI2026-05-13109:52:48.1045652LakyLak bose qc35 II (input)2026-05-13T09:52:48.151285Z2026-05-13T09:52:50.107775ZWARN screenpipe_audio::audio_manager::device_monitor:WARN screenpipe_audio::core::run_record_and_transcribe: no alWARN screenpipe_audio::audio_manager::device_monitor:2026-05-13T09:52:50.107875ZLakyLak bose qc35 II (input)2026-05-13709:52:52.1107492WARN screenpipe_audio::audio_manager::device_monitor:WARN screenpipe_audio::audio_manager::device_monitor:2026-05-13T09:52:52.110871ZLakyLak bose qc35 II (input) not foundWARN screenpipe_audio::audio_manager::device_monitor:screeilAPP (-zsh•••EDHomeDMsActivityFilesLater..•More(Platform] Planning... in 8 m100% <8• Wed 13 May 9:52:53→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan TanevP. Galya DimitrovaRo Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil VasilevNikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpDOCKER• 881DEV SlackFileEditViewGoHistoryWindowHelpDOCKER• 881DEV (-zsh)whisper_backend_init_gpu: found GPUdevice 0:Metalwhisper_backend_init_gpu: using Metal backendggml_metal_init: allocating9gml_metal_init:found device: Apple M1ggml_metal_init:picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrencytrueggml_metal_init: use graph optimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode)=whisper_init_state: compute buffer (cross)whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13T09:51:27.373440ZO 82(type: 1, cnt: 0)INFO screenpipe_audio::audio_manager::manager: reconciliatioitip: install a starter bundle of pipes:screenpipe install https://screenpi.pe/start.json2026-05-13709:52:40.567321ZERROR screenpipe_audio::core::stream: an error occurred on the2026-05-13109:52:42.0908462INFO screenpipe_audio::audio_manager::device_monitor:system2026-05-13T09:52:42.092980ZINFO screenpipe_audio::device::device_manager: startingrecoi2026-05-13T09:52:42.093096ZINFO screenpipe_audio::audio_manager::device_monitor:switche2026-05-13T09:52:42.093159ZINFO screenpipe_audio::core::run_record_and_transcribe:stari2026-05-13T09:52:48.101704ZINFOscreenpipe_audio::audio_manager::device_monitor: system2026-05-13T09:52:48.101858ZERROR screenpipe_audio::audio_manager::device_monitor: failedut) not found (willback off)2026-05-13709:52:48.10195422026-05-13T09:52:48.104457ZINFO screenpipe_audio::core::run_record_and_transcribe: stop:WARN screenpipe_audio::audio_manager::device_monitor: [DEVICI2026-05-13109:52:48.1045652LakyLak bose qc35 II (input)2026-05-13T09:52:48.151285Z2026-05-13T09:52:50.107775ZWARN screenpipe_audio::audio_manager::device_monitor:WARN screenpipe_audio::core::run_record_and_transcribe: no alWARN screenpipe_audio::audio_manager::device_monitor:2026-05-13T09:52:50.107875ZLakyLak bose qc35 II (input)2026-05-13709:52:52.1107492WARN screenpipe_audio::audio_manager::device_monitor:WARN screenpipe_audio::audio_manager::device_monitor:2026-05-13T09:52:52.110871ZLakyLak bose qc35 II (input) not foundWARN screenpipe_audio::audio_manager::device_monitor:screeilAPP (-zsh•••EDHomeDMsActivityFilesLater..•More(Platform] Planning... in 8 m100% <8• Wed 13 May 9:52:53→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan TanevP. Galya DimitrovaRo Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil VasilevNikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U4Plauorm Plannino…. In /n100% 5• wea 15 May 9:03.2.•0к.+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U4Plauorm Plannino…. In /n100% 5• wea 15 May 9:03.2.•0к.+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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SlackFileEditViewGoHistoryWindowHelpDOCKERO ₴1whis SlackFileEditViewGoHistoryWindowHelpDOCKERO ₴1whisper_init_state: compute buffer(encode)whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =ggml_metal_free: deallocating2026-05-13T09:51:27.373440ZDEV (-zsh)65.96 MB8.50 MB96.83 MBО 882APP (-zshINFO screenpipe_audio::audio_manager::manager: reconciliatiortip: install a starter bundle of pipes:screenpipe install https://screenpi.pe/start.json2026-05-13T09:52:40.567321ZERROR screenpipe_audio::core::stream:an error occurredon the2026-05-13709:52:42.090846ZINFO screenpipe_audio::audio_manager::device_monitor:system2026-05-13T09:52:42.092980ZINFOscreenpipe_audio::device::device_manager: starting recor2026-05-13T09:52:42.093096ZINFO screenpipe_audio::audio_manager::device_monitor:switch2026-05-13109:52:42.0931592INFO screenpipe_audio::core::run_record_and_transcribe:star-2026-05-13T09:52:48.101704ZINFOscreenpipe_audio::audio_manager::device_monitor: system2026-05-13T09:52:48.101858ZERROR screenpipe_audio::audio_manager::device_monitor: failedut) not found(willbackoff)2026-05-13T09:52:48.101954Z2026-05-13T09:52:48.104457ZINFOscreenpipe_audio::core::run_record_and_transcribe:stop:WARN screenpipe_audio::audio_manager::device_monitor:[DEVICInput)2026-05-13709:52:48.1045652WARN screenpipe_audio::audio_manager::device_monitor:[DEVICILakyLak bose qc35 II (input)not found2026-05-13T09:52:48.151285ZWARN screenpipe_audio::core::run_record_and_transcribe: no al2026-05-13109:52:50.1077752WARN screenpipe_audio::audio_manager::device_monitor:[DEVICInput)2026-05-13T09:52:50.107875ZWARNscreenpipe_audio::audio_manager::device_monitor:[DEVICILakyLak bose qc35 II (input)not found2026-05-13T09:52:52.110749ZWARN screenpipe_audio::audio_manager::device_monitor:[DEVICInput)2026-05-13T09:52:52.110871ZWARN screenpipe_audio::audio_manager::device_monitor:[DEVICILakyLak boseqc35 11 (input)not found2026-05-13T09:52:54.114431ZWARN screenpipe_audio::audio_manager::device_monitor:[DEVICInput)2026-05-13109:52:54.1145652WARN screenpipe_audio::audio_manager::device_monitor:[DEVICILakyLak bose qc35 II (input)not found2026-05-13T09:52:56.119677ZWARN screenpipe_audio::audio_manager::device_monitor:[DEVICInput)2026-05-13T09:52:56.119788ZWARN screenpipe_audio::audio_manager::device_monitor:[DEVICILakyLak bose qc35 II (input)not found2026-05-13T09:52:58.130520ZWARN screenpipe_audio::audio_manager::device_monitor:[DEVICInput)2026-05-13T09:52:58.132511Z2026-05-13709:52:58.13257722026-05-13109:52:58.3927932INFO screenpipe_audio::device::device_manager: starting recorINFO screenpipe_audio::audio_manager::device_monitor:[DEVICIINFO screenpipe_audio::core::run_record_and_transcribe: star-HomeDMsActivityFilesLater...More[Platform] Planning... in 7 m100% <8• Wed 13 May 9:53:24ED→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan TanevP. Galya DimitrovaRo Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka StoyanovaVasil VasilevNikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpDOCKERO ₴1whis SlackFileEditViewGoHistoryWindowHelpDOCKERO ₴1whisper_init_state: compute buffer(encode)whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =ggml_metal_free: deallocating2026-05-13T09:51:27.373440ZDEV (-zsh)65.96 MB8.50 MB96.83 MBО 882APP (-zshINFO screenpipe_audio::audio_manager::manager: reconciliatiortip: install a starter bundle of pipes:screenpipe install https://screenpi.pe/start.json2026-05-13T09:52:40.567321ZERROR screenpipe_audio::core::stream:an error occurredon the2026-05-13709:52:42.090846ZINFO screenpipe_audio::audio_manager::device_monitor:system2026-05-13T09:52:42.092980ZINFOscreenpipe_audio::device::device_manager: starting recor2026-05-13T09:52:42.093096ZINFO screenpipe_audio::audio_manager::device_monitor:switch2026-05-13109:52:42.0931592INFO screenpipe_audio::core::run_record_and_transcribe:star-2026-05-13T09:52:48.101704ZINFOscreenpipe_audio::audio_manager::device_monitor: system2026-05-13T09:52:48.101858ZERROR screenpipe_audio::audio_manager::device_monitor: failedut) not found(willbackoff)2026-05-13T09:52:48.101954Z2026-05-13T09:52:48.104457ZINFOscreenpipe_audio::core::run_record_and_transcribe:stop:WARN screenpipe_audio::audio_manager::device_monitor:[DEVICInput)2026-05-13709:52:48.1045652WARN screenpipe_audio::audio_manager::device_monitor:[DEVICILakyLak bose qc35 II (input)not found2026-05-13T09:52:48.151285ZWARN screenpipe_audio::core::run_record_and_transcribe: no al2026-05-13109:52:50.1077752WARN screenpipe_audio::audio_manager::device_monitor:[DEVICInput)2026-05-13T09:52:50.107875ZWARNscreenpipe_audio::audio_manager::device_monitor:[DEVICILakyLak bose qc35 II (input)not found2026-05-13T09:52:52.110749ZWARN screenpipe_audio::audio_manager::device_monitor:[DEVICInput)2026-05-13T09:52:52.110871ZWARN screenpipe_audio::audio_manager::device_monitor:[DEVICILakyLak boseqc35 11 (input)not found2026-05-13T09:52:54.114431ZWARN screenpipe_audio::audio_manager::device_monitor:[DEVICInput)2026-05-13109:52:54.1145652WARN screenpipe_audio::audio_manager::device_monitor:[DEVICILakyLak bose qc35 II (input)not found2026-05-13T09:52:56.119677ZWARN screenpipe_audio::audio_manager::device_monitor:[DEVICInput)2026-05-13T09:52:56.119788ZWARN screenpipe_audio::audio_manager::device_monitor:[DEVICILakyLak bose qc35 II (input)not found2026-05-13T09:52:58.130520ZWARN screenpipe_audio::audio_manager::device_monitor:[DEVICInput)2026-05-13T09:52:58.132511Z2026-05-13709:52:58.13257722026-05-13109:52:58.3927932INFO screenpipe_audio::device::device_manager: starting recorINFO screenpipe_audio::audio_manager::device_monitor:[DEVICIINFO screenpipe_audio::core::run_record_and_transcribe: star-HomeDMsActivityFilesLater...More[Platform] Planning... in 7 m100% <8• Wed 13 May 9:53:24ED→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan TanevP. Galya DimitrovaRo Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka StoyanovaVasil VasilevNikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whi SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whisper_backend_init_gpu:using Metal backendggml_metal_init: allocatingDEV (-zsh)O 82ggml_metal_init:default device: Apple M1ggml_metal_init:use fusionggml_metal_init:use concurrencyggml_metal_init:graph optimizewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfwhisper_init_state: kv cross size =whisper_init_state: kv padwhisper_init_state:compute buffer (conv)whisper_init_state: computebuffer (encode) =whisper_init_state:buffer (cross)whisper_init_state: compute buffer (decode)14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init: use fusionggml_metal_init: use concurrencyggml_metal_init: use graph optimize = truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self sizewhisper_init_state: kv cross size =whisper_init_state: kv padwhisper_init_state: compute buffer (conv)whisper_init_state:compute buffer (encode) =whisper_init_state:compute buffer (cross)whisper_init_state: computebuffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init: use fusionggml_metal_init: use concurrencyggml_metal_init: use graph optimize = truewhisper_backend_init: using BLAS backendscreeilAPP (-zsh•••EDHomeDMsActivityFilesLater..•More(Platform) Planning... in 7 m100% <8• Wed 13 May 9:53:28→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan TanevP. Galya Dimitrovao Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whi SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whisper_backend_init_gpu:using Metal backendggml_metal_init: allocatingDEV (-zsh)O 82ggml_metal_init:default device: Apple M1ggml_metal_init:use fusionggml_metal_init:use concurrencyggml_metal_init:graph optimizewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfwhisper_init_state: kv cross size =whisper_init_state: kv padwhisper_init_state:compute buffer (conv)whisper_init_state: computebuffer (encode) =whisper_init_state:buffer (cross)whisper_init_state: compute buffer (decode)14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init: use fusionggml_metal_init: use concurrencyggml_metal_init: use graph optimize = truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self sizewhisper_init_state: kv cross size =whisper_init_state: kv padwhisper_init_state: compute buffer (conv)whisper_init_state:compute buffer (encode) =whisper_init_state:compute buffer (cross)whisper_init_state: computebuffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init: use fusionggml_metal_init: use concurrencyggml_metal_init: use graph optimize = truewhisper_backend_init: using BLAS backendscreeilAPP (-zsh•••EDHomeDMsActivityFilesLater..•More(Platform) Planning... in 7 m100% <8• Wed 13 May 9:53:28→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messages2o Stoyan TanevP. Galya Dimitrovao Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U4Plauorm Plannino…. In /n100% 5• wea 15 May 9:03.04•0к.+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)• _ #recycie• tr app# slackv screenpipe [SSH: nas)• _ #recycie• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U4Plauorm Plannino…. In /n100% 5• wea 15 May 9:03.04•0к.+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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2026-05-13T06:53:58.782197+00:00
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• 881whisper_init_state:compute buffer(conv)whisper_init_state:compute buffer(encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =DEV (-zsh)14.17 MB65.96 MB8.50 MB96.83 MBО 882APP (-zshggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init:picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init: use graphoptimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusionggml_metal_init: use concurrencyggml_metal_init: use graph optimize =whisper_backend_init: using BLAS backendwhisper_init_state: kv self sizewhisper_init_state: kv cross size =whisper_init_state: kv padwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)whisper_init_state: compute buffer (decode) =ggml_metal_free: deallocating2026-05-13T09:53:29.299042Z2026-05-13T09:53:29.912060Z2026-05-13109:53:34.0642442INFO screenpipe_audio::audio_manager::manager: reconciliatiorINFO screenpipe_engine::snapshot_compaction: snapshot compac*INFO screenpipe_engine::snapshot_compaction: snapshot compac-•••EDHomeDMsActivityFilesLater..•More(Platform) Planning... in 7 m100% <8• Wed 13 May 9:53:58→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan Tanev. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• 881whisper_init_state:compute buffer(conv)whisper_init_state:compute buffer(encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =DEV (-zsh)14.17 MB65.96 MB8.50 MB96.83 MBО 882APP (-zshggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init:picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init: use graphoptimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusionggml_metal_init: use concurrencyggml_metal_init: use graph optimize =whisper_backend_init: using BLAS backendwhisper_init_state: kv self sizewhisper_init_state: kv cross size =whisper_init_state: kv padwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)whisper_init_state: compute buffer (decode) =ggml_metal_free: deallocating2026-05-13T09:53:29.299042Z2026-05-13T09:53:29.912060Z2026-05-13109:53:34.0642442INFO screenpipe_audio::audio_manager::manager: reconciliatiorINFO screenpipe_engine::snapshot_compaction: snapshot compac*INFO screenpipe_engine::snapshot_compaction: snapshot compac-•••EDHomeDMsActivityFilesLater..•More(Platform) Planning... in 7 m100% <8• Wed 13 May 9:53:58→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan Tanev. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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slackv screenpipe [SSH: nas)- #recycle• tr app# sc slackv screenpipe [SSH: nas)- #recycle• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U100% 5• wea 15 May 9:04-24•П (кк'+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)- #recycle• tr app# sc slackv screenpipe [SSH: nas)- #recycle• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U100% 5• wea 15 May 9:04-24•П (кк'+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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2026-05-13T06:54:29.243534+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778655269243_m1.jpg...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• 881whisper_init_state:compute buffer(conv)whisper_init_state:compute buffer(encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =DEV (-zsh)14.17 MB65.96 MB8.50 MB96.83 MBО 882APP (-zshggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init:picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init: use graphoptimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusionggml_metal_init: use concurrencyggml_metal_init: use graph optimize =whisper_backend_init: using BLAS backendwhisper_init_state: kv self sizewhisper_init_state: kv cross size =whisper_init_state: kv padwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)whisper_init_state: compute buffer (decode) =ggml_metal_free: deallocating2026-05-13T09:53:29.299042Z2026-05-13T09:53:29.912060Z2026-05-13109:53:34.0642442INFO screenpipe_audio::audio_manager::manager: reconciliatiorINFO screenpipe_engine::snapshot_compaction: snapshot compac*INFO screenpipe_engine::snapshot_compaction: snapshot compac-•••EDHomeDMsActivityFilesLater..•More(Platform] Planning... in 6 m100% <8• Wed 13 May 9:54:28→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan Tanev. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• 881whisper_init_state:compute buffer(conv)whisper_init_state:compute buffer(encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =DEV (-zsh)14.17 MB65.96 MB8.50 MB96.83 MBО 882APP (-zshggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init:picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init: use graphoptimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusionggml_metal_init: use concurrencyggml_metal_init: use graph optimize =whisper_backend_init: using BLAS backendwhisper_init_state: kv self sizewhisper_init_state: kv cross size =whisper_init_state: kv padwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)whisper_init_state: compute buffer (decode) =ggml_metal_free: deallocating2026-05-13T09:53:29.299042Z2026-05-13T09:53:29.912060Z2026-05-13109:53:34.0642442INFO screenpipe_audio::audio_manager::manager: reconciliatiorINFO screenpipe_engine::snapshot_compaction: snapshot compac*INFO screenpipe_engine::snapshot_compaction: snapshot compac-•••EDHomeDMsActivityFilesLater..•More(Platform] Planning... in 6 m100% <8• Wed 13 May 9:54:28→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan Tanev. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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29699
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2026-05-13T06:54:55.583177+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778655295583_m2.jpg...
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iTerm2
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slackv screenpipe [SSH: nas)- #recycle• tr app# sc slackv screenpipe [SSH: nas)- #recycle• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U100% 5.• wea 15 May 9:04:04•0к.+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)- #recycle• tr app# sc slackv screenpipe [SSH: nas)- #recycle• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U100% 5.• wea 15 May 9:04:04•0к.+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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2026-05-13T06:54:59.730634+00:00
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778655299730_m1.jpg...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• ₴81whisper_init_state:compute buffer(conv)whisper_init_state:compute buffer(encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =DEV (-zsh)14.17 MB65.96 MB8.50 MB96.83 MBO ₴2APP (-zshggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init: use graphoptimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusionggml_metal_init: use concurrencyggml_metal_init: use graph optimize =whisper_backend_init: using BLAS backendwhisper_init_state: kv self sizewhisper_init_state: kv cross size =whisper_init_state: kv padwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)whisper_init_state: compute buffer (decode) =ggml_metal_free: deallocating2026-05-13T09:53:29.299042Z2026-05-13T09:53:29.912060Z2026-05-13109:53:34.0642442INFO screenpipe_audio::audio_manager::manager: reconciliatiorINFO screenpipe_engine::snapshot_compaction: snapshot compac*INFO screenpipe_engine::snapshot_compaction: snapshot compac-•••EDHomeDMsActivityFilesLater..•More(Platform] Planning... in 6 m100% <8• Wed 13 May 9:54:59→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan Tanev. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• ₴81whisper_init_state:compute buffer(conv)whisper_init_state:compute buffer(encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =DEV (-zsh)14.17 MB65.96 MB8.50 MB96.83 MBO ₴2APP (-zshggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrency= trueggml_metal_init: use graphoptimize= truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size=3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusionggml_metal_init: use concurrencyggml_metal_init: use graph optimize =whisper_backend_init: using BLAS backendwhisper_init_state: kv self sizewhisper_init_state: kv cross size =whisper_init_state: kv padwhisper_init_state: compute buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)whisper_init_state: compute buffer (decode) =ggml_metal_free: deallocating2026-05-13T09:53:29.299042Z2026-05-13T09:53:29.912060Z2026-05-13109:53:34.0642442INFO screenpipe_audio::audio_manager::manager: reconciliatiorINFO screenpipe_engine::snapshot_compaction: snapshot compac*INFO screenpipe_engine::snapshot_compaction: snapshot compac-•••EDHomeDMsActivityFilesLater..•More(Platform] Planning... in 6 m100% <8• Wed 13 May 9:54:59→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan Tanev. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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slackv screenpipe [SSH: nas)- #recycle• tr app# sc slackv screenpipe [SSH: nas)- #recycle• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U100% 5• wea 15 May 9:00.24•П (кк'+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)- #recycle• tr app# sc slackv screenpipe [SSH: nas)- #recycle• tr app# screenpine.dbNNNOC* SSH: nasomaster' 00A0 3Windov> screenpipe sync copy.sh U1 archive.db-bak U100% 5• wea 15 May 9:00.24•П (кк'+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778655359950_m1.jpg...
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SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whi SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whisper_init_state:compute buffer(encode)=whisper_init_state:compute buffer (cross)=whisper_init_state: compute buffer (decode) =DEV (-zsh)65.96 MB8.50 MB96.83 MBО 882ggml_metal_free:deallocatingwhisper_backend_init_gpu:device 0: Metal (type: 1)whisper_backend_init_gpu:found GPUdevice 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrencytrueggml_metal_init:usegraph optimizetruewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: computebuffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init: use concurrency= trueggml_metal_init: use graph optimize = truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13709:55:30.902834Z2026-05-13T09:55:59.919515Z2026-05-13T09:55:59.937467Z2026-05-13T09:55:59.949541ZINFO screenpipe_audio::audio_manager::manager: reconciliatiorINFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSe:INFO screenpipe_engine::event_driven_capture: invalidating p‹INFO sck_rs::stream_manager:stopped 2 persistent stream(s)screeilAPP (-zsh•••EDHomeDMsActivityFilesLater..•More(Platform] Planning... in 5 m100% <478• Wed 13 May 9:56:00→Describe whatJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan Tanev®. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToastFirefoxAuto-install within 6 days#MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whi SlackFileEditViewGoHistoryWindowHelpDOCKER• 881whisper_init_state:compute buffer(encode)=whisper_init_state:compute buffer (cross)=whisper_init_state: compute buffer (decode) =DEV (-zsh)65.96 MB8.50 MB96.83 MBО 882ggml_metal_free:deallocatingwhisper_backend_init_gpu:device 0: Metal (type: 1)whisper_backend_init_gpu:found GPUdevice 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init:use concurrencytrueggml_metal_init:usegraph optimizetruewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize=2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: computebuffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:use fusion= trueggml_metal_init: use concurrency= trueggml_metal_init: use graph optimize = truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv padsize2.36 MBwhisper_init_state: compute buffer (conv)=whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)=whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13709:55:30.902834Z2026-05-13T09:55:59.919515Z2026-05-13T09:55:59.937467Z2026-05-13T09:55:59.949541ZINFO screenpipe_audio::audio_manager::manager: reconciliatiorINFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSe:INFO screenpipe_engine::event_driven_capture: invalidating p‹INFO sck_rs::stream_manager:stopped 2 persistent stream(s)screeilAPP (-zsh•••EDHomeDMsActivityFilesLater..•More(Platform] Planning... in 5 m100% <478• Wed 13 May 9:56:00→Describe whatJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan Tanev®. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka Stoyanova€. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToastFirefoxAuto-install within 6 days#MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778655361320_m1.jpg...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• 881whisper_backend_init_gpu:using Metal backendggml_metal_init: allocatingDEV (-zsh)O 82APP (-zshggml_metal_init:default device: Apple M1ggml_metal_init:use fusionggml_metal_init:use concurrencyggml_metal_init:graph optimizewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfwhisper_init_state: kv cross size =whisper_init_state: kv padwhisper_init_state:compute buffer (conv)whisper_init_state: computebuffer (encode) =whisper_init_state:buffer (cross)whisper_init_state: compute buffer (decode)14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:ggml_metal_init:use concurrencyggml_metal_init:use graph optimizewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfwhisper_init_state: kv cross size =whisper_init_state: kv padwhisper_init_state: compute buffer (conv)whisper_init_state:compute buffer(encode) =whisper_init_state:compute buffer (cross)whisper_init_state: computebuffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13T09:55:30.902834ZINFO screenpipe_audio::audio_manager::manager: reconciliatior2026-05-13T09:55:59.919515ZINFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSe:2026-05-13T09:55:59.937467ZINFO screenpipe_engine::event_driven_capture: invalidating p2026-05-13T09:55:59.949541ZINFO sck_rs::stream_manager:stopped 2 persistent stream(s)2026-05-13T09:56:00.057450Zsck_rs::stream_manager:persistent SCKstream started fo2026-05-13T09:56:00.467079Zscreenpipe_audio::core::run_record_and_transcribe: screxafter sleep/wake on macOs, Windows,and Linux)2026-05-13T09:56:00.467789ZWARNscreenpipe_audio::audio_manager::manager: recording foren unlockforLakyLak bose9c35 II(input) (recovery is automatic via device_monitor)2026-05-13109:56:00.9546932INFO sck_rs::stream_manager:persistent SCK stream started fo(Platform] Planning... in 4 m100% <8• Wed 13 May 9:56:01•••EDHomeDMsActivityFilesLater..•More→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan TanevP. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka StoyanovaB. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• SlackFileEditViewGoHistoryWindowHelpscreeilDOCKER• 881whisper_backend_init_gpu:using Metal backendggml_metal_init: allocatingDEV (-zsh)O 82APP (-zshggml_metal_init:default device: Apple M1ggml_metal_init:use fusionggml_metal_init:use concurrencyggml_metal_init:graph optimizewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfwhisper_init_state: kv cross size =whisper_init_state: kv padwhisper_init_state:compute buffer (conv)whisper_init_state: computebuffer (encode) =whisper_init_state:buffer (cross)whisper_init_state: compute buffer (decode)14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu: device 0: Metal (type: 1)whisper_backend_init_gpu: found GPU device 0: Metal (type: 1, cnt: 0)whisper_backend_init_gpu: using Metal backendggml_metal_init: allocatingggml_metal_init: found device: Apple M1ggml_metal_init: picking default device: Apple M1ggml_metal_init:ggml_metal_init:use concurrencyggml_metal_init:use graph optimizewhisper_backend_init: using BLAS backendwhisper_init_state: kv selfwhisper_init_state: kv cross size =whisper_init_state: kv padwhisper_init_state: compute buffer (conv)whisper_init_state:compute buffer(encode) =whisper_init_state:compute buffer (cross)whisper_init_state: computebuffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13T09:55:30.902834ZINFO screenpipe_audio::audio_manager::manager: reconciliatior2026-05-13T09:55:59.919515ZINFO screenpipe_engine::sleep_monitor: Screen unlocked (CGSe:2026-05-13T09:55:59.937467ZINFO screenpipe_engine::event_driven_capture: invalidating p2026-05-13T09:55:59.949541ZINFO sck_rs::stream_manager:stopped 2 persistent stream(s)2026-05-13T09:56:00.057450Zsck_rs::stream_manager:persistent SCKstream started fo2026-05-13T09:56:00.467079Zscreenpipe_audio::core::run_record_and_transcribe: screxafter sleep/wake on macOs, Windows,and Linux)2026-05-13T09:56:00.467789ZWARNscreenpipe_audio::audio_manager::manager: recording foren unlockforLakyLak bose9c35 II(input) (recovery is automatic via device_monitor)2026-05-13109:56:00.9546932INFO sck_rs::stream_manager:persistent SCK stream started fo(Platform] Planning... in 4 m100% <8• Wed 13 May 9:56:01•••EDHomeDMsActivityFilesLater..•More→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan TanevP. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka StoyanovaB. Vasil Vasilev. Nikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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slackv screenpipe [SSH: nas)- #recycle• tr app# sc slackv screenpipe [SSH: nas)- #recycle• tr app# screenpine.dbNNNNƠC* SSH: nasomaster' 00A0 3> screenpipe sync copy.sh U1 archive.db-bak U100% 5.• wea 15 May 9:00.30•П (кк'+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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slackv screenpipe [SSH: nas)- #recycle• tr app# sc slackv screenpipe [SSH: nas)- #recycle• tr app# screenpine.dbNNNNƠC* SSH: nasomaster' 00A0 3> screenpipe sync copy.sh U1 archive.db-bak U100% 5.• wea 15 May 9:00.30•П (кк'+ .*•Lets think about how to split the scriot @screenoioe svnc.shit is bia already. How can I split it to multiole smaller scriot for easier* synes screenplpe sullte data to a NAs archive dacabase lappenoonly, no delectons).# ALSO copIes the day's video/Trame daca Tolder to the nas./screenpipe sync.sh/screenpipe_sync.sh 2026-04-15# syncs yesterday (default)# syncs today so far#Cron example (runs at sam dally):0 3 ** * /Users/lukas/.screenpipe/screenpipe_sync.sh >> /Users/lukas/.screenpipe/sync.log 2>&1-euo pipera1lCONFICDB SRC="S(SCREENPIPE DB:-$HOME/.screenpipe/db.sqglite}'NAS MOUNT="SINAS MOUNI:= Volumes screenpipe"NAS MOUNT="S(NAS MOUNT:-/volume1/screenpipe}"NAS DB="SNAS_MOUNT/archive.db"NAS DATA="SNAS MOUNl data"LOG FILE="SHOME/.screenpipe/sync.log"HELPERSSCRIPT START=S(date +%s)logo)flocal msa="[S(date '+8Y-&m-%d %H:&M:%S')] S*'echo "Smso" tee-a "SLOG FILE'step•local now=s date +%s)local elapsed=s(( now - SCRIPT START ))local min=s elapsed 60local sec=selapsed & 60)printt "n +%02dm%02ds • %s n" "Smin" "Ssec" "S*" tee -a "SLOG FILE"run salite heredoco) ‹Local Labee"ssol="s2"local stares date +%s)orintt"%-36s " "Slabelsalites "SDB SRC" <c< "ssal"&local oides!spine'rtet qo tae ogerttttgodge tro)llocal 1=0while kill -0 "Spid" 2>/dev/null: do%-36s %s " "$label" "s{spinisil}'printf "nies(G + 1 % 10 ))sleep 0.2wait "Soid'if Src -ne 0 : thenprintf "n%-36s x FATLED\n" "Slabe]" | tee -a "SLOG FTLE"exit Srelocal dur=s(( S(date +%s) - start ))nrintf "rReview 1 file >8-36c J Sdme02dcin" "ciahel" "sll dur 1 69 "" "sl dur % 60 "" I tep ca "slog FTIF!Let me analvze the current script structure to propose a logical split:I can see the script is 420 lines with several distinct logical sections. Before I create a plan, I have a few questions;1. Structure approach: Do you preterA library aooroach where the main scriot sources heloer functions (e.a.. 11b/screenoioe svnc heloers.sh )A mix (some libraries, some executables)2. Directory structure: Are you comfortable creating a 11b/ subdirectory for helper modules, or do you prefer everything in the3. Backward compatibility: Do you want the sinale › screenpioe sync.sh to still work as-is (sourcina the new modules), orare you okay with changing the entry point?A Granularity. How fine-arained should the solit he? For eyamnle.•Moderate split: helpers + do operations + tile operations + mainFine-grained: separate modules for vision data, audio data, FTS. files, etclation would be a moderate split with a lib/ directory:• Lib/screenpipe sync db.sh - all DB operations (tables, indexes, sync, rls, verity)creenpipe sync files.sh - data folder and log copyingDoes this approach align with what you had in mindmunl..Ask anvthind+ GPlanSWE-1.6lized Ln 18, Col 34Spaces: 2 UTF-8 LF Shell Script Team...
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/Users/lukas/.screenpipe/data/data/2026-05-13/1778 /Users/lukas/.screenpipe/data/data/2026-05-13/1778655391834_m1.jpg...
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SlackFileEditViewGoHistoryWindowHelpDOCKER• 881DEV SlackFileEditViewGoHistoryWindowHelpDOCKER• 881DEV (-zsh)O 82ggml_metal_init:whisper_backend_init: using BLAS backendwhisper_init_state: kv self size3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv pad2.36 MBwhisper_init_state:buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)whisper_init_state: compute buffer(decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu:device 0: Metal (type: 1)whisper_backend_init_gpu:Metal(type: 1, cnt: 0)whisper_backend_init_gpu:using Metal backendggml_metal_init: allocatingggml_metal_init:found device:picking default device: Apple M1ggml_metal_init:ggml_metal_init:use concurrencyggml_metal_init: use graph optimize = truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv pad2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state:compute bufferwhisper_init_state: compute buffer (cross)whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13T09:55:30.902834Zscreenpipe_audio::audio_manager::manager: reconciliatior2026-05-13T09:55:59.919515ZINFO screenpipe_engine::sleep_monitor:Screen unlocked (CGSe:2026-05-13709:55:59.937467Zscreenpipe_engine::event_driven_capture: invalidating p2026-05-13T09:55:59.949541Zsck_rs::stream_manager:stopped 2 persistent stream(s)2026-05-13T09:56:00.057450Zsck_rs::stream_manager:persistentSCK stream started fo2026-05-13109:56:00.4670792screenpipe_audio::core::run_record_and_transcribe: screcafter sleep/wake on macOS, Windows,2026-05-13T09:56:00.467789Zscreenpipe_audio::audio_manager::manager: recording foren unlock for LakyLak boseqc35 II (input) (recovery is automatic via device_monitor)2026-05-13T09:56:00.954693Zsck_rs::stream_manager:persistent SCK stream started fo2026-05-13T09:56:01.139229Zscreenpipe_audio::audio_manager::device_monitor: [DEVICI2026-05-13709:56:01.139296Z2026-05-13T09:56:01.388965Z2026-05-13T09:56:01.389052Z2026-05-13109:56:01.3890842screenpipe_audio::device::device_manager: Stopping devi‹screenpipe_audio::device::device_manager: starting recorINFOscreenpipe_audio::audio_manager::device_monitor:restarINFO screenpipe_audio::core::run_record_and_transcribe: star-screeilAPP (-zsh•••EDHomeDMsActivityFilesLater..•More(Platform] Planning... in 4 m100% <8• Wed 13 May 9:56:31→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan TanevP. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka StoyanovaVasil VasilevNikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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SlackFileEditViewGoHistoryWindowHelpDOCKER• 881DEV SlackFileEditViewGoHistoryWindowHelpDOCKER• 881DEV (-zsh)O 82ggml_metal_init:whisper_backend_init: using BLAS backendwhisper_init_state: kv self size3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv pad2.36 MBwhisper_init_state:buffer (conv)whisper_init_state: compute buffer (encode) =whisper_init_state: compute buffer (cross)whisper_init_state: compute buffer(decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocatingwhisper_backend_init_gpu:device 0: Metal (type: 1)whisper_backend_init_gpu:Metal(type: 1, cnt: 0)whisper_backend_init_gpu:using Metal backendggml_metal_init: allocatingggml_metal_init:found device:picking default device: Apple M1ggml_metal_init:ggml_metal_init:use concurrencyggml_metal_init: use graph optimize = truewhisper_backend_init: using BLAS backendwhisper_init_state: kv self size3.15 MBwhisper_init_state: kv cross size =9.44 MBwhisper_init_state: kv pad2.36 MBwhisper_init_state: compute buffer (conv)whisper_init_state:compute bufferwhisper_init_state: compute buffer (cross)whisper_init_state: compute buffer (decode) =14.17 MB65.96 MB8.50 MB96.83 MBggml_metal_free: deallocating2026-05-13T09:55:30.902834Zscreenpipe_audio::audio_manager::manager: reconciliatior2026-05-13T09:55:59.919515ZINFO screenpipe_engine::sleep_monitor:Screen unlocked (CGSe:2026-05-13709:55:59.937467Zscreenpipe_engine::event_driven_capture: invalidating p2026-05-13T09:55:59.949541Zsck_rs::stream_manager:stopped 2 persistent stream(s)2026-05-13T09:56:00.057450Zsck_rs::stream_manager:persistentSCK stream started fo2026-05-13109:56:00.4670792screenpipe_audio::core::run_record_and_transcribe: screcafter sleep/wake on macOS, Windows,2026-05-13T09:56:00.467789Zscreenpipe_audio::audio_manager::manager: recording foren unlock for LakyLak boseqc35 II (input) (recovery is automatic via device_monitor)2026-05-13T09:56:00.954693Zsck_rs::stream_manager:persistent SCK stream started fo2026-05-13T09:56:01.139229Zscreenpipe_audio::audio_manager::device_monitor: [DEVICI2026-05-13709:56:01.139296Z2026-05-13T09:56:01.388965Z2026-05-13T09:56:01.389052Z2026-05-13109:56:01.3890842screenpipe_audio::device::device_manager: Stopping devi‹screenpipe_audio::device::device_manager: starting recorINFOscreenpipe_audio::audio_manager::device_monitor:restarINFO screenpipe_audio::core::run_record_and_transcribe: star-screeilAPP (-zsh•••EDHomeDMsActivityFilesLater..•More(Platform] Planning... in 4 m100% <8• Wed 13 May 9:56:31→QDescribe what you are looking forJiminny ...# confusion-clinic# curiosity_lab# engineering# general# jiminny-bg# platform-tickets# product_launches# random# releases# sofia-office# support# thank-yous# the_people_of jimi...° Direct messagesCo Stoyan TanevP. Galya Dimitrova&. Steliyan Georgiev&. Petko Kashinskie. Aneliya Angelovaa. Stefka StoyanovaVasil VasilevNikolay IvanovAneliya Angelova, ...Lukas Kovalik y... OAppsJira CloudToast# releases8 226 0• MessagesC Files• Bookmarksf861c9e7-M+master' intoYesterdaysecfix/compos..9b89679e - Merge branch 'master' intosecfix/composer-202605074cb55bd1 - Merge pull request #12049 fromjiminny/secfix/composer-20260507jiminny/app| Added by GitHubCircleCI APP 3:17 PMDeployment Successful!Project: appWhen:05/12/202612:17:31Tag:View JobNewCircleCl APP6:52 PMNew commits deployed to Prophet Prod-US:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd7c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)New commits deployed to Prophet Prod-EU:[b73e293](https://github.com/jiminny/prophet/commit/b73e2937fc9b13d5dd/c5f9f8a98a4908c3c7207) - Jy20569 re eval key points 2 (#505) (steliyan-g)Message #releases+Аа..•...
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