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Mathieu Virbel
6f0c7c1a5e
* feat(cleanup): add automatic data retention for public instances - Add Celery task to clean up anonymous data after configurable retention period - Delete transcripts, meetings, and orphaned recordings older than retention days - Only runs when PUBLIC_MODE is enabled to prevent accidental data loss - Properly removes all associated files (local and S3 storage) - Add manual cleanup tool for testing and intervention - Configure retention via PUBLIC_DATA_RETENTION_DAYS setting (default: 7 days) Fixes #571 * fix: apply pre-commit formatting fixes * fix: properly delete recording files from storage during cleanup - Add storage deletion for orphaned recordings in both cleanup task and manual tool - Delete from storage before removing database records - Log warnings if storage deletion fails but continue with database cleanup * Apply suggestion from @pr-agent-monadical[bot] Co-authored-by: pr-agent-monadical[bot] <198624643+pr-agent-monadical[bot]@users.noreply.github.com> * Apply suggestion from @pr-agent-monadical[bot] Co-authored-by: pr-agent-monadical[bot] <198624643+pr-agent-monadical[bot]@users.noreply.github.com> * refactor: cleanup_old_data for better logging * fix: linting * test: fix meeting cleanup test to not require room controller - Simplify test by directly inserting meetings into database - Remove dependency on non-existent rooms_controller.create method - Tests now pass successfully * fix: linting * refactor: simplify cleanup tool to use worker implementation - Remove duplicate cleanup logic from manual tool - Use the same _cleanup_old_public_data function from worker - Remove dry-run feature as requested - Prevent code duplication and ensure consistency - Update documentation to reflect changes * refactor: split cleanup worker into smaller functions - Move all imports to the top of the file - Extract cleanup logic into separate functions: - cleanup_old_transcripts() - cleanup_old_meetings() - cleanup_orphaned_recordings() - log_cleanup_results() - Make code more maintainable and testable - Add days parameter support to Celery task - Update manual tool to work with refactored code * feat: add TypedDict typing for cleanup stats - Add CleanupStats TypedDict for better type safety - Update all function signatures to use proper typing - Add return type annotations to _cleanup_old_public_data - Improves code maintainability and IDE support * feat: add CASCADE DELETE to meeting_consent foreign key - Add ondelete="CASCADE" to meeting_consent.meeting_id foreign key - Generate and apply migration to update existing constraint - Remove manual consent deletion from cleanup code - Add unit test to verify CASCADE DELETE behavior * style: linting * fix: alembic migration branchpoint * fix: correct downgrade constraint name in CASCADE DELETE migration * fix: regenerate CASCADE DELETE migration with proper constraint names - Delete problematic migration and regenerate with correct names - Use explicit constraint name in both upgrade and downgrade - Ensure migration works bidirectionally - All tests passing including CASCADE DELETE test * style: linting * refactor: simplify cleanup to use transcripts as entry point - Remove orphaned_recordings cleanup (not part of this PR scope) - Remove separate old_meetings cleanup - Transcripts are now the main entry point for cleanup - Associated meetings and recordings are deleted with their transcript - Use single database connection for all operations - Update tests to reflect new approach * refactor: cleanup and rename functions for clarity - Rename _cleanup_old_public_data to cleanup_old_public_data (make public) - Rename celery task to cleanup_old_public_data_task for clarity - Update docstrings and improve code organization - Remove unnecessary comments and simplify deletion logic - Update tests to use new function names - All tests passing * style: linting\ * style: typing and review * fix: add transaction on cleanup_single_transcript * fix: naming --------- Co-authored-by: pr-agent-monadical[bot] <198624643+pr-agent-monadical[bot]@users.noreply.github.com>
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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