Docling-Serve Plugins: PP-DocLayout-V3 + GLM-OCR

A patched docling-serve Docker image that bundles two community plugins:

Available images

Image	Based on	Architectures	Notes
ghcr.io/dcc-bs/dcc-docling-serve	docling-serve	linux/amd64, linux/arm64	Base image, packages from PyPI
ghcr.io/dcc-bs/dcc-docling-serve-cpu	docling-serve-cpu	linux/amd64, linux/arm64	CPU-only, torch from PyTorch CPU index
ghcr.io/dcc-bs/dcc-docling-serve-cu128	docling-serve-cu128	linux/amd64	CUDA 12.8, torch from cu128 index
ghcr.io/dcc-bs/dcc-docling-serve-cu130	docling-serve-cu130	linux/amd64, linux/arm64	CUDA 13.0, torch from cu130 index

Each image is tagged with the upstream docling-serve version (e.g. v2.3.0) and :latest.

Plugins

Plugin	PyPI	Purpose
docling-glm-ocr	pip install docling-glm-ocr	Remote OCR via a vLLM-hosted GLM-OCR model
docling-pp-doc-layout	pip install docling-pp-doc-layout	Local layout detection via PP-DocLayout-V3

The plugins are selectable per-request through the standard docling-serve API:

• Layout -- layout_custom_config: { "kind": "ppdoclayout-v3" }
• OCR -- ocr_engine: "glm-ocr-remote"

The patched Gradio UI also exposes all engines as selectable options.

Architecture

flowchart TD
    subgraph doclingServe ["dcc-docling-serve"]
        LP["PP-DocLayout-V3 plugin"]
        OP["GLM-OCR plugin"]
    end

    subgraph vllmServer [vLLM Server]
        GLMOCR["zai-org/GLM-OCR"]
    end

    OP -- "remote OCR" --> GLMOCR

Loading

Quickstart

1) Prerequisites

• Docker with GPU support (NVIDIA)
• A HuggingFace token with access to the GLM-OCR model

2) Configure

Copy .env.example to .env and set the required variables:

cp .env.example .env
# edit .env — at minimum set HF_TOKEN

Variable	Description	Default
HF_TOKEN	HuggingFace token for downloading GLM-OCR (required)	—
HF_CACHE_DIR	Host directory for the HF model cache	.hf-cache
VLLM_HOST_PORT	Host port for the vLLM server	8001
DOCLING_HOST_PORT	Host port for docling-serve	5001
DOCLING_SERVE_TAG	Upstream docling-serve image tag	latest
DOCLING_SERVE_LOG_LEVEL	Log level for docling-serve	INFO

3) Start the stack

make docker-up

This starts two services:

Service	Purpose
vllm-glm-ocr	vLLM server hosting zai-org/GLM-OCR (GPU 1)
docling-serve	Docling API + Gradio UI with both plugins (GPU 0)

The Gradio UI is available at http://localhost:5001.

4) Convert a document

Remote GLM-OCR OCR with PP-DocLayout-V3 layout:

curl -X POST http://localhost:5001/v1/convert/source \
  -H 'Content-Type: application/json' \
  -d '{
    "options": {
      "ocr_engine": "glm-ocr-remote",
      "layout_custom_config": { "kind": "ppdoclayout-v3" }
    },
    "sources": [{"kind": "http", "url": "https://arxiv.org/pdf/2501.17887"}]
  }'

Docker Compose

The compose.yaml references the pre-built image from GHCR:

ghcr.io/dcc-bs/dcc-docling-serve:latest

Service	Image
vllm-glm-ocr	ghcr.io/dcc-bs/vllm:v0.16.0-cu130
docling-serve	ghcr.io/dcc-bs/dcc-docling-serve:latest

Environment variables are documented in .env.example.

make docker-up    # start all services
make docker-down  # stop all services

Building the image locally

To build the patched docling-serve image from source:

make docker-build

This runs docker build against plugins/Dockerfile.docling-serve and tags the result as docling-serve-plugins:latest.

Running the locally built image

To test the local image without pushing it to GHCR, use the compose stack but override the image name via DOCLING_SERVE_TAG and a matching tag alias, or run docling-serve directly with docker run:

docker run --add-host=host.docker.internal:host-gateway --rm \
  --gpus device=0 \
  -p 5001:5001 \
  -e DOCLING_SERVE_ENABLE_UI=true \
  -e DOCLING_SERVE_ENABLE_REMOTE_SERVICES=true \
  -e DOCLING_SERVE_ALLOW_EXTERNAL_PLUGINS=true \
  -e GLMOCR_REMOTE_OCR_API_URL=http://host.docker.internal:8001/v1/chat/completions \
  docling-serve-plugins:latest

The Gradio UI is then available at http://localhost:5001.

Alternatively, re-tag the local image to match the compose service name and use the normal make docker-up flow:

make docker-build
docker tag docling-serve-plugins:latest ghcr.io/dcc-bs/dcc-docling-serve:latest
make docker-up

Plugin configuration

All plugins are fully configurable via environment variables, making them suitable for zero-code deployment in Docker / Compose environments. Explicit GlmOcrRemoteOptions and PPDocLayoutV3Options constructor arguments always take precedence when using the Python SDK directly.

GLM-OCR remote OCR — environment variables

Variable	Description	Default
GLMOCR_REMOTE_OCR_API_URL	vLLM chat completion URL	http://localhost:8001/v1/chat/completions
GLMOCR_REMOTE_OCR_MODEL_NAME	Model name sent to vLLM	zai-org/GLM-OCR
GLMOCR_REMOTE_OCR_PROMPT	Text prompt sent with each image crop	built-in default
GLMOCR_REMOTE_OCR_TIMEOUT	HTTP timeout per crop (seconds)	120
GLMOCR_REMOTE_OCR_MAX_TOKENS	Max tokens per completion	16384
GLMOCR_REMOTE_OCR_SCALE	Image crop rendering scale	3.0
GLMOCR_REMOTE_OCR_MAX_IMAGE_PIXELS	Pixel budget per crop	4500000
GLMOCR_REMOTE_OCR_MAX_CONCURRENT_REQUESTS	Max concurrent API requests	10
GLMOCR_REMOTE_OCR_MAX_RETRIES	Max retry attempts for HTTP errors	3
GLMOCR_REMOTE_OCR_RETRY_BACKOFF_FACTOR	Exponential backoff factor for retries	2.0
GLMOCR_REMOTE_OCR_LANG	Comma-separated language hint(s)	en
GLMOCR_REMOTE_OCR_API_KEY	Bearer token for Authorization header	unset (no header sent)

PP-DocLayout-V3 layout — environment variables

Variable	Description	Default
PP_DOC_LAYOUT_MODEL_NAME	HuggingFace model repo ID	PaddlePaddle/PP-DocLayoutV3_safetensors
PP_DOC_LAYOUT_CONFIDENCE_THRESHOLD	Minimum detection confidence (0.0–1.0)	0.5
PP_DOC_LAYOUT_BATCH_SIZE	Batch size for layout inference	8
PP_DOC_LAYOUT_CREATE_ORPHAN_CLUSTERS	Create clusters for orphaned elements (true/false)	true
PP_DOC_LAYOUT_KEEP_EMPTY_CLUSTERS	Retain empty clusters in results (true/false)	false
PP_DOC_LAYOUT_SKIP_CELL_ASSIGNMENT	Skip table-cell assignment (true/false)	false

Boolean variables accept true, 1, yes (case-insensitive) as truthy; anything else is false.

SDK option reference

All environment variables above correspond to fields on GlmOcrRemoteOptions and PPDocLayoutV3Options. See the individual plugin READMEs for the full option reference:

• docling-glm-ocr README
• docling-pp-doc-layout README

Health-probe log muting

Kubernetes/Compose liveness probes hitting GET /health produce two INFO records per probe (docling_serve.app "Health check requested" and the matching uvicorn.access line). The image ships plugins/mute_health_logs.py, installed into site-packages as dcc_mute_health_logs.py plus a .pth file that imports it at interpreter startup. It attaches logging.Filters to those two loggers — no upstream docling-serve file is modified, so it survives upstream updates. The filters sit on the Logger objects, not on handlers, so docling-serve's own setup_logging() (which only swaps handlers/levels) does not undo them.

Variable	Description	Default
DCC_MUTE_HEALTH_LOGS	Set to 0/false/no to disable muting	1
DCC_MUTE_HEALTH_PATHS	Comma-separated request paths to mute in the access log	/health

Python SDK usage

The plugins can also be used directly with the docling Python SDK (without docling-serve). See examples/convert_with_plugins.py:

from docling.datamodel.base_models import InputFormat
from docling.datamodel.pipeline_options import PdfPipelineOptions
from docling.document_converter import DocumentConverter, PdfFormatOption

from docling_glm_ocr import GlmOcrRemoteOptions
from docling_pp_doc_layout.options import PPDocLayoutV3Options

pipeline_options = PdfPipelineOptions(
    allow_external_plugins=True,
    ocr_options=GlmOcrRemoteOptions(api_url="..."),
    layout_options=PPDocLayoutV3Options(),
)

converter = DocumentConverter(format_options={InputFormat.PDF: PdfFormatOption(pipeline_options=pipeline_options)})
result = converter.convert("https://arxiv.org/pdf/2501.17887")
print(result.document.export_to_markdown())

vLLM GLM-OCR container

Standalone command to run the GLM-OCR vLLM server:

docker run -d \
  --rm --name ocr-glm \
  --gpus device=1 \
  --ipc=host \
  -p 8001:8000 \
  -v "${HOME}/.cache/huggingface:/root/.cache/huggingface" \
  -e "HF_TOKEN=${HF_TOKEN:-}" \
  -e "LD_LIBRARY_PATH=/lib/x86_64-linux-gnu" \
  ghcr.io/dcc-bs/vllm:v0.16.0-cu130 \
  zai-org/GLM-OCR \
  --served-model-name zai-org/GLM-OCR \
  --port 8000 \
  --trust-remote-code \
  --max-num-batched-tokens 8192

Required: --max-num-batched-tokens 8192

Without this flag, vLLM will reject any high-resolution image with HTTP 400.

In vLLM 0.16.0+ (v1 engine), the encoder cache size is derived from max_num_batched_tokens (default 2048 when chunked prefill is enabled):

encoder_cache_size = max(max_num_batched_tokens, model_max_tokens_per_image)
                   = max(2048, 4800)  ←  4800 is GLM-OCR's model floor
                   = 4800 tokens      ←  too small for real documents

The Glm46VImageProcessor encodes images at approximately 784 pixels per token (patch_size=14 × merge_size=2, squared). A typical A4 page rendered at scale 3× (1785 × 2526 px) produces 5760 tokens; a phone-photo crop at scale 3× can reach 6120 tokens — both exceed the default 4800-token cache and are rejected.

Setting --max-num-batched-tokens 8192 raises the encoder cache to max(8192, 4800) = 8192 tokens, which covers all real-world inputs with comfortable headroom.

Note: --limit-mm-per-prompt does not control the encoder cache size in vLLM 0.16.0. That flag only limits the count of images per request.

Testing

Setup (dev)

make install

Format and lint

make check

Runs ruff format (auto-format) and ruff check --fix (auto-fix lint errors) locally. The CI workflow runs these as read-only checks.

Unit tests

make test

Smoke test (local SDK)

Tests the plugins directly via the Python SDK, without a running docling-serve instance. Requires the plugin repos checked out as siblings of this repo:

./smoke_test.sh
# or with a custom vLLM URL:
GLMOCR_REMOTE_OCR_API_URL=http://host:8001/v1/chat/completions ./smoke_test.sh

End-to-end tests

The e2e tests require a running stack (docling-serve + vLLM). They use the images in data/ to validate conversion through both plugins.

export DOCLING_SERVE_URL=http://localhost:5001
make test

Tests are skipped automatically when DOCLING_SERVE_URL is not set.

CI/CD

CI (.github/workflows/ci.yml)

Runs on push/PR: lint with ruff.

Docker image (.github/workflows/docling-serve.yml)

Builds and pushes the patched docling-serve image to GHCR. Triggered on:

• Push to main when files in plugins/ change
• Manual dispatch (with configurable upstream tag)

License

MIT