michael 1c22872e69 fix: use dedicated whisper worker with FFmpeg dispatch pattern ... Changed the Whisper transcription to run on dedicated whisper-worker using the same dispatch pattern as FFmpeg: 1. apply_async() to dispatch to the whisper queue 2. Poll with ready() using async sleep to avoid blocking 3. Use allow_join_result() context manager 4. Get result only after task is ready This ensures Whisper runs with concurrency=1 on a dedicated worker to prevent memory overload while still allowing the render task to wait for results without deadlocking. 🤖 Generated with [Claude Code](https://claude.com/claude-code) Co-Authored-By: Claude Opus 4.5 <noreply@anthropic.com>		2025-12-27 08:53:53 -06:00
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__pycache__	removed mongodb change stream monitoring, added global websockets monitoring for notifications, broke symmetry between toasts and persistent notifications (and refined which notifications get sent and how)	2025-08-25 15:48:18 -05:00
__init__.py	feat: add Whisper-based pause point refinement for audio descriptions	2025-12-27 08:27:48 -06:00
ffmpeg_operations.py	feat: add dedicated ffmpeg queue to prevent server overload	2025-12-26 17:56:23 -06:00
ingest_and_ai.py	fix: broadcast WebSocket updates for ingesting and ai_processing status	2025-12-27 07:38:25 -06:00
notify.py	added websockets for live job status updates with toast notifications on job list page	2025-08-24 19:41:23 -05:00
render_accessible_video.py	fix: use dedicated whisper worker with FFmpeg dispatch pattern	2025-12-27 08:53:53 -06:00
translate_and_synthesize.py	feat: add accessible video (MP4 with embedded audio descriptions)	2025-12-26 11:06:41 -06:00
whisper_transcribe.py	fix: use dedicated whisper worker with FFmpeg dispatch pattern	2025-12-27 08:53:53 -06:00