Rafhan Mazaya FathurrahmanandClaude Sonnet 5
e60ab63154
Backend (app-pfm-ocr-v2/backend): - Product/SKU scan feature complete: trained DINOv2 index (118 reference photos, 16 SKU classes) and YOLO classifier (83.3% top-1 val accuracy), fixed scripts/install-pipeline.sh (was missing ultralytics/torch), fully browser-verified end-to-end on /scan-pfm. Mobile m-scan-pfm page cancelled (Flutter app handles mobile; web UI is desktop-only for pipeline testing). - Fixed a real data-loss bug: Save Ground Truth (scan-pfm and the DO-flow's manual-label) was silently writing into the pfm-web-app container's ephemeral filesystem instead of the host, because /sources wasn't bind-mounted in docker-compose.yml. Added the mount, recovered an orphaned entry. - accounts.password is now bcrypt-hashed (bcryptjs, idempotent migration in db/init.ts) instead of plaintext; login route compares hashes. - /api/v1/documents/* (list, PUT, upload) now enforces real 401 auth, matching what the Flutter client already sends. The "classic" routes deliberately stay open — they're dev-only web UI with no login flow and won't exist in production. - OCR accuracy investigated end-to-end: real baseline is 95.10% overall (target met; accuracy_report.md was stale at 75.04%, now flagged). Fixed one genuine parser.ts bug (SO/DO field duplication in the global fallback regex); remaining gaps are OCR/layout-model limitations, not parser bugs. - Adopted a standalone copy of the fhanyuh/agents-settings e/n workflow scoped to backend/ (AGENTS.md Part A/B split, SKILLS.md, plans/, docs/), independent of the root copy which now covers Flutter only. - next-implementation.md deleted; content folded into backend/plans/next-enhancements.md for traceability. Root: - Adopted fhanyuh/agents-settings kit (AGENTS.md, SKILLS.md, plans/, docs/feature-list.md), scoped to the Flutter app only. - Pending documents queue now persists to Hive (lib/core/storage) instead of memory-only, surviving an app kill mid-upload. Removed backend_backup/ (stale Express/Prisma prototype, superseded by pfm-web-app) and the completed plans/next-enhancement-plan.md checklist. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>
139 lines
4.9 KiB
Markdown
139 lines
4.9 KiB
Markdown
# vLLM Service — Full Reference
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Detail split out of `../AGENTS.md` (2026-07-08, to keep that file under the
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Agents Settings Kit's 256-line threshold once the `e`/`n` workflow was appended
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to it). `AGENTS.md` keeps the short version — architecture, quick start, the
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env var table, file map — and links here for everything else.
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## Issue recording — naming and template
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```
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issues/{NN}-{slug}.md
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```
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| Part | Rule | Example |
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|------|------|---------|
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| `{NN}` | Two-digit running number (`01`, `02`, …). Increment from the highest existing file. | `03` |
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| `{slug}` | Lowercase kebab-case summary of the problem | `gpu-memory-startup-failure` |
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Full example: `issues/04-gpu-memory-startup-failure.md`
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### File template
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```markdown
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# Issue {NN}: {Short title}
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## Problem
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What failed, with exact error message or symptom.
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## Context
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Environment, command run, relevant config (`.env`, `config/vllm_config.yaml`).
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## Solution
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What fixed it, or current workaround / open status.
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## References
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Links, related issue files, or AGENTS.md sections.
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```
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Check `issues/` for the next number:
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```bash
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ls issues/*.md 2>/dev/null | sort
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```
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## Client usage
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After the server is running:
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```bash
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# CLI
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uv run paddleocr doc_parser \
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--input https://paddle-model-ecology.bj.bcebos.com/paddlex/imgs/demo_image/paddleocr_vl_demo.png \
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--vl_rec_backend vllm-server \
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--vl_rec_server_url http://localhost:8118/v1
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```
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```python
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from paddleocr import PaddleOCRVL
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pipeline = PaddleOCRVL(
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vl_rec_backend="vllm-server",
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vl_rec_server_url="http://127.0.0.1:8118/v1",
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)
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output = pipeline.predict("path/to/image.png")
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```
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Note: The full PaddleOCR-VL client should run in a **separate** environment if it needs PaddlePaddle GPU + Transformers. This repo is the isolated vLLM server only.
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## Tuning vLLM
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Edit `config/vllm_config.yaml`:
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```yaml
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gpu-memory-utilization: 0.8
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max-num-seqs: 128
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```
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Reference: [PaddleOCR-VL vLLM parameter tuning](https://www.paddleocr.ai/latest/en/version3.x/pipeline_usage/PaddleOCR-VL.html#331-server-side-parameter-adjustment)
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## Troubleshooting
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See `issues/` for full write-ups. Quick pointers:
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| Symptom | Issue file |
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|---------|------------|
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| `paddleocr install_genai_server_deps` / `No module named pip` | [01-genai-server-deps-pip-in-uv-venv.md](../issues/01-genai-server-deps-pip-in-uv-venv.md) |
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| flash-attn wheel incompatible with Python version | [02-flash-attn-wheel-python-version-mismatch.md](../issues/02-flash-attn-wheel-python-version-mismatch.md) |
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| `uv pip` targets wrong venv from another project | [03-active-virtual-env-from-other-project.md](../issues/03-active-virtual-env-from-other-project.md) |
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| Free memory below `gpu-memory-utilization` on startup | [04-gpu-memory-startup-failure.md](../issues/04-gpu-memory-startup-failure.md) |
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| `TokenizersBackend has no attribute all_special_tokens_extended` | [05-transformers-tokenizers-incompatibility.md](../issues/05-transformers-tokenizers-incompatibility.md) |
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| Extracted images not shown in Gradio demo (raw base64 in markdown) | [06-extracted-images-raw-base64-not-displayed.md](../issues/06-extracted-images-raw-base64-not-displayed.md) |
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### flash-attn build failures
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Install the prebuilt wheel after `uv sync` (see `scripts/install.sh`):
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```bash
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FLASH_ATTN_WHEEL="https://github.com/mjun0812/flash-attention-prebuild-wheels/releases/download/v0.3.14/flash_attn-2.8.2+cu128torch2.8-cp312-cp312-linux_x86_64.whl" \
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./scripts/install.sh
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```
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Pick the wheel matching your Python and CUDA versions from [flash-attention prebuild wheels](https://mjunya.com/flash-attention-prebuild-wheels/). Details: [02-flash-attn-wheel-python-version-mismatch.md](../issues/02-flash-attn-wheel-python-version-mismatch.md).
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Note: `paddleocr install_genai_server_deps` uses `pip` internally and is incompatible with uv-managed venvs. See [01-genai-server-deps-pip-in-uv-venv.md](../issues/01-genai-server-deps-pip-in-uv-venv.md). This repo installs the vLLM stack via `uv sync` + `uv pip`.
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### `TokenizersBackend has no attribute all_special_tokens_extended`
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Pin transformers (already in `pyproject.toml`):
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```bash
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uv pip install "transformers==4.57.6"
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```
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See [05-transformers-tokenizers-incompatibility.md](../issues/05-transformers-tokenizers-incompatibility.md).
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### Do not install `paddlepaddle-gpu` in this venv
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vLLM and PaddlePaddle GPU conflict. This server env uses `paddleocr[doc-parser]` without Paddle GPU.
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### GPU memory on startup
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If vLLM reports free memory below `gpu-memory-utilization`, either:
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- Set `CUDA_VISIBLE_DEVICES` to a less-busy GPU
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- Lower `gpu-memory-utilization` in `config/vllm_config.yaml` (e.g. `0.75` or `0.7`)
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See [04-gpu-memory-startup-failure.md](../issues/04-gpu-memory-startup-failure.md).
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### Health check
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```bash
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curl -s http://localhost:8118/v1/models | jq .
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```
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## References
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- [PaddleOCR-VL usage tutorial](https://www.paddleocr.ai/latest/en/version3.x/pipeline_usage/PaddleOCR-VL.html)
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- [PaddleOCR genai_server FAQ](https://github.com/PaddlePaddle/PaddleOCR/discussions/16822)
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