Files
reflector/server
Mathieu Virbel da700069d9 Add webhook events storage to meetings model
- Add events column as JSON type to meetings table with default empty array
- Add events: List[Dict[str, Any]] field to Meeting model
- Create migration 2890b5104577 for events column and apply successfully
- Add MeetingController helper methods for event storage:
  - add_event() for generic event storage with timestamps
  - participant_joined(), participant_left() for participant tracking
  - recording_started(), recording_stopped() for recording events
  - get_events() for event retrieval
- Update Jitsi webhook endpoints to store events:
  - Store participant join/leave events with data and timestamps
  - Store recording start/stop events from Prosody webhooks
  - Store recording completion events from Jibri finalize script
- Events stored with type, timestamp, and data for webhook history tracking
- Fix linting and formatting issues

Addresses PR feedback point 12: save webhook events in meetings events field
2025-09-02 17:53:35 -06:00
..
2025-02-03 16:11:01 +01:00
2025-08-20 20:56:45 -04:00
2025-07-16 18:10:11 -06:00
2023-08-29 10:58:27 +02:00
2025-07-16 18:10:11 -06:00

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')"

.