alexsuntop/mineru

https://github.com/opendatalab/MinerU image, use https://github.com/opendatalab/MinerU/blob/master/docker/global/Dockerfile.

Source repo: https://github.com/Sun-ZhenXing/compose-anything.

docker-compose.yaml:

yaml
x-defaults: &defaults
  restart: unless-stopped
  logging:
    driver: json-file
    options:
      max-size: 100m
      max-file: "3"

x-mineru-vllm: &mineru-vllm
  <<: *defaults
  image: ${GLOBAL_REGISTRY:-}alexsuntop/mineru:${MINERU_VERSION:-2.7.3}
  build:
    context: .
    dockerfile: Dockerfile
    platforms:
      - linux/amd64
      - linux/arm64
  environment:
    TZ: ${TZ:-UTC}
    MINERU_MODEL_SOURCE: local
  ulimits:
    memlock: -1
    stack: 67108864
  ipc: host
  deploy:
    resources:
      limits:
        cpus: "16.0"
        memory: 32G
      reservations:
        cpus: "8.0"
        memory: 16G
        devices:
          - driver: nvidia
            device_ids: ["0"]
            capabilities: [gpu]

services:
  mineru-openai-server:
    <<: *mineru-vllm
    profiles:
      - "openai-server"
      - ${COMPOSE_PROFILES:-}
    ports:
      - ${MINERU_PORT_OVERRIDE_VLLM:-30000}:30000
    entrypoint: mineru-openai-server
    command:
      --host 0.0.0.0
      --port 30000
      # --data-parallel-size 2  # If using multiple GPUs, increase throughput using vllm's multi-GPU parallel mode
      # --gpu-memory-utilization 0.9 # If running on a single GPU and encountering VRAM shortage, reduce the KV cache size by this parameter, if VRAM issues persist, try lowering it further to `0.4` or below.
    healthcheck:
      test: ["CMD-SHELL", "curl -f http://localhost:30000/health || exit 1"]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 60s

  mineru-api:
    <<: *mineru-vllm
    profiles: ["api"]
    ports:
      - ${MINERU_PORT_OVERRIDE_API:-8000}:8000
    entrypoint: mineru-api
    command:
      --host 0.0.0.0
      --port 8000
      # parameters for vllm-engine
      # --data-parallel-size 2  # If using multiple GPUs, increase throughput using vllm's multi-GPU parallel mode
      # --gpu-memory-utilization 0.5  # If running on a single GPU and encountering VRAM shortage, reduce the KV cache size by this parameter, if VRAM issues persist, try lowering it further to `0.4` or below.
    healthcheck:
      test:
        [
          "CMD",
          "wget",
          "--no-verbose",
          "--tries=1",
          "--spider",
          "http://localhost:8000/health",
        ]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 60s

  mineru-gradio:
    <<: *mineru-vllm
    profiles: ["gradio"]
    ports:
      - ${MINERU_PORT_OVERRIDE_GRADIO:-7860}:7860
    entrypoint: mineru-gradio
    command:
      --server-name 0.0.0.0
      --server-port 7860
      # --enable-api false  # If you want to disable the API, set this to false
      # --max-convert-pages 20  # If you want to limit the number of pages for conversion, set this to a specific number
      # parameters for vllm-engine
      # --data-parallel-size 2  # If using multiple GPUs, increase throughput using vllm's multi-GPU parallel mode
      # --gpu-memory-utilization 0.5  # If running on a single GPU and encountering VRAM shortage, reduce the KV cache size by this parameter, if VRAM issues persist, try lowering it further to `0.4` or below.
    healthcheck:
      test:
        [
          "CMD",
          "wget",
          "--no-verbose",
          "--tries=1",
          "--spider",
          "http://localhost:7860/",
        ]
      interval: 30s
      timeout: 10s
      retries: 3
      start_period: 60s

VLM backend server:

bash
docker compose up -d

Document parse API:

bash
docker compose --profile api up -d

Gradio WebUI:

bash
docker compose --profile gradio up -d

Test vLLM backend:

bash
pip install mineru
mineru -o ./output -b vlm-http-client -u http://localhost:30000 -p demo.pdf