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openreader/docs-site/docs/deploy/compute-worker.md
Richard R 09e8898683 feat(pdf,config): implement stale parse-state healing and unify op stale window config 
Introduce automatic healing for stale PDF parse states in API routes. Add
`isDocumentParseStateStale` utility and use a shared `COMPUTE_OP_STALE_MS`
environment variable (with config getter) to control the stale window for both
worker op replacement and app-side parse-state healing. Update documentation and
environment variable references to reflect new config.

Enables automatic marking of stuck parses as failed, improving reliability and
retry behavior in distributed compute environments.
2026-05-22 01:21:18 -06:00

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title: Compute Worker (NATS JetStream)
---
Use this guide for `COMPUTE_MODE=worker` deployments where heavy compute runs outside the Next.js app server.
## Overview
The compute worker handles:
- Whisper word alignment operations
- PDF layout parsing operations
The app server submits operations to `POST /ops`, reuses in-flight work via required `opKey`, and consumes status updates via `GET /ops/:opId/events` (SSE). Queue durability and retries are backed by NATS JetStream WorkQueue consumers and NATS KV.
## Published image
- App server image: `ghcr.io/richardr1126/openreader`
- Compute worker image: `ghcr.io/richardr1126/openreader-compute-worker`
- Compute worker image (example pinned tag): `ghcr.io/richardr1126/openreader-compute-worker:refactor-ppdoclayoutv3-onnx-layout-parsing`
## Worker environment variables
Required:
- `COMPUTE_WORKER_TOKEN`: bearer token expected by worker routes
- `NATS_URL`: NATS server connection string (JetStream enabled)
- `S3_BUCKET`
- `S3_REGION`
- `S3_ACCESS_KEY_ID`
- `S3_SECRET_ACCESS_KEY`
> [!IMPORTANT]
> **S3 credentials cannot be left blank/empty** when running in worker mode.
> While the main Next.js server can generate random, dynamic S3 keys on-the-fly when `USE_EMBEDDED_WEED_MINI=true` and `S3_*` vars are blank, the compute worker runs in a separate process and cannot connect to SeaweedFS using those dynamically generated keys.
> To use the compute worker with the embedded SeaweedFS, you **must configure identical, stable S3 credentials** (e.g. `S3_ACCESS_KEY_ID` and `S3_SECRET_ACCESS_KEY`) in both the root `.env` and the compute worker `.env` files.
Common optional:
- `NATS_CREDS`: raw user credentials file content (JWT + private key), ideal for cloud container environments where mounting files is difficult.
- `NATS_CREDS_FILE`: path to a `.creds` file on the server.
- `S3_ENDPOINT` (for non-AWS S3-compatible storage)
- `S3_FORCE_PATH_STYLE=true` (for many S3-compatible providers)
- `S3_PREFIX=openreader`
- `COMPUTE_WORKER_HOST=0.0.0.0`
- `PORT=8081` (local/manual; on Railway platform injects this)
- `COMPUTE_LOG_FORMAT=pretty` (default) or `json`
Advanced tuning (usually leave unset unless you need overrides):
- `COMPUTE_PREWARM_MODELS=true`
- `COMPUTE_JOB_CONCURRENCY=1` (shared total compute jobs across whisper + PDF)
- `COMPUTE_WHISPER_TIMEOUT_MS=30000`
- `COMPUTE_PDF_TIMEOUT_MS=300000`
- `WHISPER_MODEL_BASE_URL=https://huggingface.co/onnx-community/whisper-base_timestamped/resolve/main` (optional override)
- `PDF_LAYOUT_MODEL_BASE_URL=https://huggingface.co/Bei0001/PP-DocLayoutV3-ONNX/resolve/main` (optional override)
- `COMPUTE_PDF_JOB_ATTEMPTS=1` (PDF layout retry attempts)
- `COMPUTE_JOBS_STREAM_MAX_BYTES=268435456` (256MB JetStream jobs stream cap)
- `COMPUTE_JOB_STATES_MAX_BYTES=67108864` (64MB JetStream KV bucket cap)
- `COMPUTE_OP_STALE_MS=1800000` (stale op replacement window)
## App server environment variables (worker mode)
Set on the Next.js app server:
```env
COMPUTE_MODE=worker
# Local worker example:
# COMPUTE_WORKER_URL=http://localhost:8081
# Cloud worker example (Railway):
COMPUTE_WORKER_URL=https://<railway-worker-domain>
COMPUTE_WORKER_TOKEN=<same-token-as-worker>
# Optional shared timeout overrides (keep equal to worker service values):
# COMPUTE_WHISPER_TIMEOUT_MS=30000
# COMPUTE_PDF_TIMEOUT_MS=300000
# COMPUTE_OP_STALE_MS=1800000
```
Model artifact overrides (`WHISPER_MODEL_BASE_URL`, `PDF_LAYOUT_MODEL_BASE_URL`) are worker runtime variables and should be set on the compute worker service environment.
`COMPUTE_OP_STALE_MS` is shared by both services in worker mode:
- Worker: opKey stale replacement window in compute op state.
- App server: stale PDF parse-state healing window (`/api/documents/[id]/parsed*`).
Set the same value on app + worker envs.
`COMPUTE_MODE=worker` has no local fallback. If worker is unavailable, affected requests fail.
## Production notes
- Worker mode assumes shared object storage is reachable by both app server and worker.
- Non-exposed embedded `weed mini` is not supported with external worker mode.
- Protect `COMPUTE_WORKER_TOKEN` and avoid exposing worker routes publicly without auth.
## Health endpoints
- `GET /health/live`
- `GET /health/ready`
## Synadia Cloud + Railway Setup (Complete Guide)
Use this end-to-end guide when your queue backend is Synadia Cloud (NGS) and your worker runs on Railway.
### 1. Create Synadia account and credentials
1. Create a Synadia Cloud account and create/select your NGS environment.
2. Create a user or service account for OpenReader compute worker access.
3. Download the generated credentials file (usually `<name>.creds`) and keep it secure.
You will use:
- `NATS_URL=tls://connect.ngs.global:4222`
- The full `.creds` file content
### 2. Deploy compute worker on Railway
Create a Railway service from:
```text
ghcr.io/richardr1126/openreader-compute-worker:refactor-ppdoclayoutv3-onnx-layout-parsing
```
Railway injects a dynamic `PORT` env var and routes traffic there.
Do not hardcode Railway ingress to `8081`; keep service networking enabled and use the public Railway URL.
### 3. Configure Railway worker environment variables
Set these in the Railway worker service:
```env
COMPUTE_WORKER_HOST=0.0.0.0
# Local/manual only:
# PORT=8081
# Railway: rely on injected PORT
COMPUTE_WORKER_TOKEN=<long-random-shared-token>
# Optional advanced tuning overrides (defaults shown):
# COMPUTE_PREWARM_MODELS=true
# COMPUTE_JOB_CONCURRENCY=1
# COMPUTE_WHISPER_TIMEOUT_MS=30000
# COMPUTE_PDF_TIMEOUT_MS=300000
# WHISPER_MODEL_BASE_URL=https://huggingface.co/onnx-community/whisper-base_timestamped/resolve/main
# PDF_LAYOUT_MODEL_BASE_URL=https://huggingface.co/Bei0001/PP-DocLayoutV3-ONNX/resolve/main
# COMPUTE_PDF_JOB_ATTEMPTS=1
# COMPUTE_JOBS_STREAM_MAX_BYTES=268435456
# COMPUTE_JOB_STATES_MAX_BYTES=67108864
NATS_URL=tls://connect.ngs.global:4222
NATS_CREDS="-----BEGIN NATS USER JWT-----
...
------END USER NKEY SEED------"
S3_BUCKET=<bucket>
S3_REGION=<region>
S3_ACCESS_KEY_ID=<key>
S3_SECRET_ACCESS_KEY=<secret>
S3_ENDPOINT=<optional-for-s3-compatible-providers>
S3_FORCE_PATH_STYLE=true
S3_PREFIX=openreader
```
Notes:
- `NATS_CREDS` should be the full Synadia `.creds` file content, including begin/end markers.
- Keep `COMPUTE_WORKER_TOKEN` identical between app server and worker.
- On Railway, leave `PORT` managed by the platform.
- If your platform supports mounted files, you can use `NATS_CREDS_FILE` instead of `NATS_CREDS`.
- `COMPUTE_JOBS_STREAM_MAX_BYTES` and `COMPUTE_JOB_STATES_MAX_BYTES` are optional; defaults are `268435456` (256MiB) and `67108864` (64MiB).
### 4. Configure the OpenReader app server (worker mode)
Set these env vars on the app server:
```env
COMPUTE_MODE=worker
COMPUTE_WORKER_URL=https://<railway-worker-domain>
COMPUTE_WORKER_TOKEN=<same-token-as-worker>
```
### 5. Verify health
After deploy, check:
- `GET https://<railway-worker-domain>/health/live`
- `GET https://<railway-worker-domain>/health/ready`
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