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8e438ca285
* dailyco api module (no-mistakes) * daily co library self-review * uncurse * self-review: daily resource leak, uniform types, enable_recording bomb, daily custom error, video_platforms/daily typing, daily timestamp dry * dailyco docs parser * phase 1-2 of daily poll * dailyco poll (no-mistakes) * poll docs * fix tests * forgotten utils file * remove generated daily docs * pr comments * dailyco poll pr review and self-review * daily recording poll api fix * daily recording poll api fix * review * review * fix tests --------- Co-authored-by: Igor Loskutov <igor.loskutoff@gmail.com>
API Key Management
Finding Your User ID
# Get your OAuth sub (user ID) - requires authentication
curl -H "Authorization: Bearer <your_jwt>" http://localhost:1250/v1/me
# Returns: {"sub": "your-oauth-sub-here", "email": "...", ...}
Creating API Keys
curl -X POST http://localhost:1250/v1/user/api-keys \
-H "Authorization: Bearer <your_jwt>" \
-H "Content-Type: application/json" \
-d '{"name": "My API Key"}'
Using API Keys
# Use X-API-Key header instead of Authorization
curl -H "X-API-Key: <your_api_key>" http://localhost:1250/v1/transcripts
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')"
.