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https://github.com/Monadical-SAS/reflector.git
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Mathieu Virbel
406164033d
* feat: add litellm backend implementation * refactor: improve generate/completion methods for base LLM * refactor: remove tokenizer logic * style: apply code formatting * fix: remove hallucinations from LLM responses * refactor: comprehensive LLM and summarization rework * chore: remove debug code * feat: add structured output support to LiteLLM * refactor: apply self-review improvements * docs: add model structured output comments * docs: update model structured output comments * style: apply linting and formatting fixes * fix: resolve type logic bug * refactor: apply PR review feedback * refactor: apply additional PR review feedback * refactor: apply final PR review feedback * fix: improve schema passing for LLMs without structured output * feat: add PR comments and logger improvements * docs: update README and add HTTP logging * feat: improve HTTP logging * feat: add summary chunking functionality * fix: resolve title generation runtime issues * refactor: apply self-review improvements * style: apply linting and formatting * feat: implement LiteLLM class structure * style: apply linting and formatting fixes * docs: env template model name fix * chore: remove older litellm class * chore: format * refactor: simplify OpenAILLM * refactor: OpenAILLM tokenizer * refactor: self-review * refactor: self-review * refactor: self-review * chore: format * chore: remove LLM_USE_STRUCTURED_OUTPUT from envs * chore: roll back migration lint changes * chore: roll back migration lint changes * fix: make summary llm configuration optional for the tests * fix: missing f-string * fix: tweak the prompt for summary title * feat: try llamaindex for summarization * fix: complete refactor of summary builder using llamaindex and structured output when possible * fix: separate prompt as constant * fix: typings * fix: enhance prompt to prevent mentioning others subject while summarize one * fix: various changes after self-review * fix: from igor review --------- Co-authored-by: Igor Loskutov <igor.loskutoff@gmail.com>
1.3 KiB
1.3 KiB
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')"