Files
reflector/server
Mathieu Virbel dc177af3ff feat: implement service-specific Modal API keys with auto processor pattern (#528)
* fix: refactor modal API key configuration for better separation of concerns

- Split generic MODAL_API_KEY into service-specific keys:
  - TRANSCRIPT_API_KEY for transcription service
  - DIARIZATION_API_KEY for diarization service
  - TRANSLATE_API_KEY for translation service
- Remove deprecated *_MODAL_API_KEY settings
- Add proper validation to ensure URLs are set when using modal processors
- Update README with new configuration format

BREAKING CHANGE: Configuration keys have changed. Update your .env file:
- TRANSCRIPT_MODAL_API_KEY → TRANSCRIPT_API_KEY
- LLM_MODAL_API_KEY → (removed, use TRANSCRIPT_API_KEY)
- Add DIARIZATION_API_KEY and TRANSLATE_API_KEY if using those services

* fix: update Modal backend configuration to use service-specific API keys

- Changed from generic MODAL_API_KEY to service-specific keys:
  - TRANSCRIPT_MODAL_API_KEY for transcription
  - DIARIZATION_MODAL_API_KEY for diarization
  - TRANSLATION_MODAL_API_KEY for translation
- Updated audio_transcript_modal.py and audio_diarization_modal.py to use modal_api_key parameter
- Updated documentation in README.md, CLAUDE.md, and env.example

* feat: implement auto/modal pattern for translation processor

- Created TranscriptTranslatorAutoProcessor following the same pattern as transcript/diarization
- Created TranscriptTranslatorModalProcessor with TRANSLATION_MODAL_API_KEY support
- Added TRANSLATION_BACKEND setting (defaults to "modal")
- Updated all imports to use TranscriptTranslatorAutoProcessor instead of TranscriptTranslatorProcessor
- Updated env.example with TRANSLATION_BACKEND and TRANSLATION_MODAL_API_KEY
- Updated test to expect TranscriptTranslatorModalProcessor name
- All tests passing

* refactor: simplify transcript_translator base class to match other processors

- Moved all implementation from base class to modal processor
- Base class now only defines abstract _translate method
- Follows the same minimal pattern as audio_diarization and audio_transcript base classes
- Updated test mock to use _translate instead of get_translation
- All tests passing

* chore: clean up settings and improve type annotations

- Remove deprecated generic API key variables from settings
- Add comments to group Modal-specific settings
- Improve type annotations for modal_api_key parameters

* fix: typing

* fix: passing key to openai

* test: fix rtc test failing due to change on transcript

It also correctly setup database from sqlite, in case our configuration
is setup to postgres.

* ci: deactivate translation backend by default

* test: fix modal->mock

* refactor: implementing igor review, mock to passthrough
2025-08-04 12:07:30 -06:00
..
2025-02-03 16:11:01 +01:00
2025-07-25 16:24:06 -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')"