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Mathieu Virbel
e0c71c5548
- Replace __table__.join() with ORM-style joins using select_from().outerjoin() - Replace __table__.delete() with delete(Model) in tests - Migrate from **row.__dict__ to model_validate() with ConfigDict(from_attributes=True) - Add ConfigDict(from_attributes=True) to all Pydantic models for proper SQLAlchemy model conversion - Update all controller methods to use model_validate() instead of dict unpacking This completes the migration to SQLAlchemy 2.0 recommended patterns while maintaining backwards compatibility and improving code consistency.
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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