openreader/compute/core/src/pdf-layout/model/manifest.json
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

31 lines
844 B
JSON

{
"name": "pp-doclayoutv3",
"version": "Bei0001/PP-DocLayoutV3-ONNX@main",
"files": [
{
"path": "model.onnx",
"sha256": "c0721928ff08741bb208ebed539c77170db5234a68cb7e546e6cc9bc172a695b",
"size": 5088167
},
{
"path": "model.onnx.data",
"sha256": "34df3e4b79d7bbbf82abce1b4f3cde3d540fa57ad42ec8905c352b97c408d437",
"size": 136774480
},
{
"path": "config.json",
"sha256": "3cf834b91d23a756b1519bce4db42c09e852f3e35c35092dd5a3e253a50c071a",
"size": 2460
},
{
"path": "preprocessor_config.json",
"sha256": "519fe0187a43a1ca429e3ad8317bab8700f0d5e8fb3a6e3a0a413ffac078ba42",
"size": 575
},
{
"path": "LICENSE.txt",
"sha256": "578a6ba6f86b0692a8f719843f575a3eebf4705768ac5c37d149f441208f601f",
"size": 195
}
]
}