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- Create session_decorator.py with @with_session decorator - Decorator automatically manages database sessions for worker tasks - Ensures session stays open for entire task execution - Fixes issue where sessions were closed before being used (e.g., process_meetings) Applied decorator to all worker tasks: - process.py: process_recording, process_meetings, reprocess_failed_recordings - cleanup.py: cleanup_old_public_data_task - ics_sync.py: sync_room_ics, sync_all_ics_calendars, create_upcoming_meetings Benefits: - Consistent session management across all worker tasks - No more manual session_factory context management in tasks - Proper transaction boundaries with automatic begin/commit - Cleaner, more maintainable code - Fixes session lifecycle issues in process_meetings
AWS S3/SQS usage clarification
Whereby.com uploads recordings directly to our S3 bucket when meetings end.
SQS Queue (AWS_PROCESS_RECORDING_QUEUE_URL)
Filled by: AWS S3 Event Notifications
The S3 bucket is configured to send notifications to our SQS queue when new objects are created. This is standard AWS infrastructure - not in our codebase.
AWS S3 → SQS Event Configuration:
- Event Type: s3:ObjectCreated:*
- Filter: *.mp4 files
- Destination: Our SQS queue
Our System's Role
Polls SQS every 60 seconds via /server/reflector/worker/process.py:24-62:
Every 60 seconds, check for new recordings
sqs = boto3.client("sqs", ...) response = sqs.receive_message(QueueUrl=queue_url, ...)
Requeue
uv run /app/requeue_uploaded_file.py TRANSCRIPT_ID
Pipeline Management
Continue stuck pipeline from final summaries (identify_participants) step:
uv run python -c "from reflector.pipelines.main_live_pipeline import task_pipeline_final_summaries; result = task_pipeline_final_summaries.delay(transcript_id='TRANSCRIPT_ID'); print(f'Task queued: {result.id}')"
Run full post-processing pipeline (continues to completion):
uv run python -c "from reflector.pipelines.main_live_pipeline import pipeline_post; pipeline_post(transcript_id='TRANSCRIPT_ID')"
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