openreader/compute/worker/.env.example
Richard R f1aa1c3e3b feat(compute): add external compute worker backend and integration
Introduce support for external compute worker mode (`COMPUTE_MODE=worker`) using a new `WorkerComputeBackend`. This enables offloading heavy ONNX Whisper alignment and PDF layout parsing to a standalone worker service (Redis + BullMQ), improving scalability and compatibility with serverless/limited environments.

- Add `@openreader/compute-core` as a shared package for ONNX inference and PDF parsing logic.
- Implement `WorkerComputeBackend` and worker contract/types for remote job execution.
- Update compute backend selection logic and remove previous worker mode guards.
- Extend `WhisperAlignInput` and `PdfLayoutInput` types to support object keys for remote data access.
- Refactor local compute backend to use `@openreader/compute-core` and support both buffer and object key inputs.
- Update job runner, TTS segment alignment, and PDF layout parsing flows to use new compute backend APIs.
- Add scripts, Docker workflow, and documentation for deploying and running the compute worker.
- Update environment variable docs and examples for worker mode, including storage requirements and configuration.
- Document published images and stack changes to reflect the new compute worker architecture.

BREAKING CHANGE: `COMPUTE_MODE=worker` now requires an external compute worker service and S3-compatible object storage. Embedded SeaweedFS (`weed mini`) is not supported in worker mode. See the new documentation for deployment and configuration details.
2026-05-19 15:21:25 -06:00

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# Compute worker bind
COMPUTE_WORKER_HOST=0.0.0.0
COMPUTE_WORKER_PORT=8081
COMPUTE_LOG_FORMAT=pretty
# COMPUTE_LOG_LEVEL=info
# App <-> worker auth
COMPUTE_WORKER_TOKEN=local-compute-token
# Redis/BullMQ
REDIS_URL=redis://redis:6379
# Shared object storage (must be reachable from worker)
S3_BUCKET=openreader-documents
S3_REGION=us-east-1
S3_ACCESS_KEY_ID=devkey
S3_SECRET_ACCESS_KEY=devsecret
S3_PREFIX=openreader
# Optional for non-AWS S3-compatible endpoints:
S3_ENDPOINT=http://host.docker.internal:8333
S3_FORCE_PATH_STYLE=true
# Queue + execution tuning
COMPUTE_QUEUE_MAX_DEPTH=64
COMPUTE_PREWARM_MODELS=true