chore: add missing READMEs

builds/io-paint/.env.example

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+# Docker registry
+DOCKER_REGISTRY=docker.io
+
+# Build version
+BUILD_VERSION=1.6.0
+
+# Hugging Face Endpoint, optional for China users
+# HF_ENDPOINT=https://hf-mirror.com

builds/io-paint/.gitignore

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+/models

builds/io-paint/Dockerfile

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+FROM pytorch/pytorch:2.6.0-cuda12.4-cudnn9-runtime
+ARG DEBIAN_FRONTEND=noninteractive
+ARG VERSION=1.6.0
+
+WORKDIR /workspace
+
+RUN apt-get update && apt-get install -y --no-install-recommends \
+    software-properties-common \
+    libsm6 libxext6 ffmpeg libfontconfig1 libxrender1 libgl1-mesa-glx \
+    curl python3-pip
+RUN apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
+RUN python3 -m pip install --upgrade pip
+RUN pip3 install iopaint==${VERSION} && pip3 cache purge
+
+EXPOSE 8080
+CMD ["iopaint", "start", "--model=lama", "--device=cuda", "--port=8080", "--host=0.0.0.0"]

builds/io-paint/README.md

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+# IOPaint (Lama Cleaner)
+
+[English](./README.md) | [中文](./README.zh.md)
+
+IOPaint (formerly LaMa Cleaner) is a free and open-source inpainting & outpainting tool powered by SOTA AI model.
+
+## Prerequisites
+
+- NVIDIA GPU with CUDA support
+- Docker with NVIDIA runtime support
+
+## Initialization
+
+1. Copy the example environment file:
+
+   ```bash
+   cp .env.example .env
+   ```
+
+2. Start the service:
+
+   ```bash
+   docker compose up -d
+   ```
+
+3. Access the web interface at <http://localhost:8080>
+
+## Services
+
+- `iopaint`: The IOPaint service.
+
+## Configuration
+
+The service runs on port 8080 and uses CUDA device 0 by default.
+
+| Variable          | Description                      | Default     |
+| ----------------- | -------------------------------- | ----------- |
+| `DOCKER_REGISTRY` | Docker registry to use           | `docker.io` |
+| `BUILD_VERSION`   | Build version                    | `latest`    |
+| `HF_ENDPOINT`     | Hugging Face endpoint (optional) | -           |
+
+## Models
+
+Models are automatically downloaded and cached in the `./models` directory on first use.
+
+## GPU Support
+
+This configuration requires an NVIDIA GPU and uses CUDA device 0. Make sure you have:
+
+- NVIDIA drivers installed
+- Docker with NVIDIA runtime support
+- nvidia-docker2 package installed
+
+## Reference
+
+- [Dockerfile](https://github.com/Sanster/IOPaint/blob/main/docker/GPUDockerfile)
+
+## License
+
+Please refer to the official IOPaint project for license information.

builds/io-paint/README.zh.md

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+# IOPaint (Lama Cleaner)
+
+[English](./README.md) | [中文](./README.zh.md)
+
+IOPaint（原 LaMa Cleaner）是一个由最先进的 AI 模型驱动的免费开源图像修复和扩展工具。
+
+## 先决条件
+
+- 支持 CUDA 的 NVIDIA GPU
+- 支持 NVIDIA 运行时的 Docker
+
+## 初始化
+
+1. 复制示例环境文件：
+
+   ```bash
+   cp .env.example .env
+   ```
+
+2. 启动服务：
+
+   ```bash
+   docker compose up -d
+   ```
+
+3. 在 <http://localhost:8080> 访问 Web 界面
+
+## 服务
+
+- `iopaint`: IOPaint 服务。
+
+## 配置
+
+服务默认在端口 8080 运行，使用 CUDA 设备 0。
+
+| 变量              | 描述                      | 默认值      |
+| ----------------- | ------------------------- | ----------- |
+| `DOCKER_REGISTRY` | 使用的 Docker 镜像仓库    | `docker.io` |
+| `BUILD_VERSION`   | 构建版本                  | `latest`    |
+| `HF_ENDPOINT`     | Hugging Face 端点（可选） | -           |
+
+## 模型
+
+模型在首次使用时会自动下载并缓存在 `./models` 目录中。
+
+## GPU 支持
+
+此配置需要 NVIDIA GPU 并使用 CUDA 设备 0。确保你已安装：
+
+- NVIDIA 驱动程序
+- 支持 NVIDIA 运行时的 Docker
+- nvidia-docker2 软件包
+
+请参考官方 IOPaint 项目的许可信息。

builds/io-paint/docker-compose.yaml

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+x-defaults: &defaults
+  restart: unless-stopped
+  logging:
+    driver: json-file
+    options:
+      max-size: 100m
+      max-file: "3"
+
+services:
+  lama-cleaner:
+    <<: *defaults
+    image: ${DOCKER_REGISTRY:-docker.io}/local/lama-cleaner:${BUILD_VERSION:-1.6.0}
+    ports:
+      - 8080:8080
+    build:
+      context: .
+      dockerfile: Dockerfile
+    environment:
+      TZ: ${TZ:-UTC}
+      HF_ENDPOINT: ${HF_ENDPOINT:-}
+    volumes:
+      - ./models:/root/.cache
+    command:
+      - iopaint
+      - start
+      - --model=lama
+      - --device=cuda
+      - --port=8080
+      - --host=0.0.0.0
+    deploy:
+      resources:
+        limits:
+          cpus: '2.0'
+          memory: 4G
+        reservations:
+          cpus: '1.0'
+          memory: 2G
+          devices:
+            - driver: nvidia
+              device_ids: ['0']
+              capabilities: [compute, utility]
+    healthcheck:
+      test: ["CMD", "wget", "--no-verbose", "--tries=1", "--spider", "http://localhost:8080/"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 60s

builds/mineru-vllm/.env.example

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+# MinerU Docker image
+MINERU_DOCKER_IMAGE=alexsuntop/mineru:2.5.4
+
+# Port configurations
+MINERU_PORT_OVERRIDE_VLLM=30000
+MINERU_PORT_OVERRIDE_API=8000
+MINERU_PORT_OVERRIDE_GRADIO=7860

builds/mineru-vllm/Dockerfile

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+# Use the official vllm image for gpu with Ampere architecture and above (Compute Capability>=8.0)
+# Compute Capability version query (https://developer.nvidia.com/cuda-gpus)
+FROM vllm/vllm-openai:v0.10.1.1
+
+# Use the official vllm image for gpu with Turing architecture and below (Compute Capability<8.0)
+# FROM vllm/vllm-openai:v0.10.2
+
+# Install libgl for opencv support & Noto fonts for Chinese characters
+RUN apt-get update && \
+    apt-get install -y \
+        fonts-noto-core \
+        fonts-noto-cjk \
+        fontconfig \
+        libgl1 && \
+    fc-cache -fv && \
+    apt-get clean && \
+    rm -rf /var/lib/apt/lists/*
+
+# Install mineru latest
+RUN python3 -m pip install -U 'mineru[core]' --break-system-packages && \
+    python3 -m pip cache purge
+
+# Download models and update the configuration file
+RUN /bin/bash -c "mineru-models-download -s huggingface -m all"
+
+# Set the entry point to activate the virtual environment and run the command line tool
+ENTRYPOINT ["/bin/bash", "-c", "export MINERU_MODEL_SOURCE=local && exec \"$@\"", "--"]

builds/mineru-vllm/README.md

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+# MinerU v2
+
+[English](./README.md) | [中文](./README.zh.md)
+
+This service runs MinerU v2. See the [Reference Documentation](https://opendatalab.github.io/MinerU/zh/usage/quick_usage/).
+
+## Start Services
+
+- **VLM backend server**:
+
+  ```bash
+  docker compose --profile vllm-server 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 -p demo.pdf -o ./output -b vlm-http-client -u http://localhost:30000
+```
+
+## Services
+
+- `mineru-vllm-server`: The VLM backend server.
+- `mineru-api`: The document parsing API.
+- `mineru-gradio`: The Gradio WebUI.
+
+## Configuration
+
+- `MINERU_DOCKER_IMAGE`: The Docker image for MinerU, default is `alexsuntop/mineru:2.5.4`.
+- `MINERU_PORT_OVERRIDE_VLLM`: The host port for the VLLM server, default is `30000`.
+- `MINERU_PORT_OVERRIDE_API`: The host port for the API service, default is `8000`.
+- `MINERU_PORT_OVERRIDE_GRADIO`: The host port for the Gradio WebUI, default is `7860`.

builds/mineru-vllm/README.zh.md

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+# MinerU v2
+
+[English](./README.md) | [中文](./README.zh.md)
+
+此服务运行 MinerU v2。请参阅[参考文档](https://opendatalab.github.io/MinerU/zh/usage/quick_usage/)。
+
+## 启动服务
+
+- **VLM 后端服务器**:
+
+  ```bash
+  docker compose --profile vllm-server up -d
+  ```
+
+- **文档解析 API**:
+
+  ```bash
+  docker compose --profile api up -d
+  ```
+
+- **Gradio WebUI**:
+
+  ```bash
+  docker compose --profile gradio up -d
+  ```
+
+## 测试 vLLM 后端
+
+```bash
+pip install mineru
+mineru -p demo.pdf -o ./output -b vlm-http-client -u http://localhost:30000
+```
+
+## 服务
+
+- `mineru-vllm-server`: VLM 后端服务器。
+- `mineru-api`: 文档解析 API。
+- `mineru-gradio`: Gradio WebUI。
+
+## 配置
+
+- `MINERU_DOCKER_IMAGE`: MinerU 的 Docker 镜像，默认为 `alexsuntop/mineru:2.5.4`。
+- `MINERU_PORT_OVERRIDE_VLLM`: VLLM 服务器的主机端口，默认为 `30000`。
+- `MINERU_PORT_OVERRIDE_API`: API 服务的主机端口，默认为 `8000`。
+- `MINERU_PORT_OVERRIDE_GRADIO`: Gradio WebUI 的主机端口，默认为 `7860`。

builds/mineru-vllm/docker-compose.yaml

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+x-defaults: &defaults
+  restart: unless-stopped
+  logging:
+    driver: json-file
+    options:
+      max-size: 100m
+      max-file: "3"
+
+x-mineru-vllm: &mineru-vllm
+  <<: *defaults
+  image: ${MINERU_DOCKER_IMAGE:-alexsuntop/mineru:2.6.2}
+  build:
+    context: .
+    dockerfile: Dockerfile
+  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-vllm-server:
+    <<: *mineru-vllm
+    profiles: ["vllm-server"]
+    ports:
+      - ${MINERU_PORT_OVERRIDE_VLLM:-30000}:30000
+    entrypoint: mineru-vllm-server
+    command:
+      - --host 0.0.0.0
+      - --port 30000
+
+      # If using multiple GPUs, increase throughput using vllm's multi-GPU parallel mode.
+      # - --data-parallel-size 2
+      # 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.
+      # - --gpu-memory-utilization 0.5
+
+    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
+
+      # If using multiple GPUs, increase throughput using vllm's multi-GPU parallel mode.
+      # - --data-parallel-size 2
+      # 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.
+      # - --gpu-memory-utilization 0.5
+    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 the vllm engine for Gradio
+      - --enable-vllm-engine true
+      # If you want to disable the API, set this to false
+      # - --enable-api false
+      # If you want to limit the number of pages for conversion, set this to a specific number
+      # - --max-convert-pages 20
+
+      # If using multiple GPUs, increase throughput using vllm's multi-GPU parallel mode.
+      # - --data-parallel-size 2
+      # 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.
+      # - --gpu-memory-utilization 0.5
+    healthcheck:
+      test: ["CMD", "wget", "--no-verbose", "--tries=1", "--spider", "http://localhost:7860/"]
+      interval: 30s
+      timeout: 10s
+      retries: 3
+      start_period: 60s