# Deploying MinerU with Docker

MinerU provides a convenient Docker deployment method, which helps quickly set up the environment and solve some tricky environment compatibility issues.

## Build Docker Image using Dockerfile:

```bash
wget https://gcore.jsdelivr.net/gh/opendatalab/MinerU@master/docker/global/Dockerfile
docker build -t mineru-sglang:latest -f Dockerfile .
```

> [!TIP]
> The [Dockerfile](https://github.com/opendatalab/MinerU/blob/master/docker/global/Dockerfile) uses `lmsysorg/sglang:v0.4.8.post1-cu126` as the base image by default, supporting Turing/Ampere/Ada Lovelace/Hopper platforms.
> If you are using the newer `Blackwell` platform, please modify the base image to `lmsysorg/sglang:v0.4.8.post1-cu128-b200` before executing the build operation.

## Docker Description

MinerU's Docker uses `lmsysorg/sglang` as the base image, so it includes the `sglang` inference acceleration framework and necessary dependencies by default. Therefore, on compatible devices, you can directly use `sglang` to accelerate VLM model inference.

> [!NOTE]
> Requirements for using `sglang` to accelerate VLM model inference:
> 
> - Device must have Turing architecture or later graphics cards with 8GB+ available VRAM.
> - The host machine's graphics driver should support CUDA 12.6 or higher; `Blackwell` platform should support CUDA 12.8 or higher. You can check the driver version using the `nvidia-smi` command.
> - Docker container must have access to the host machine's graphics devices.
>
> If your device doesn't meet the above requirements, you can still use other features of MinerU, but cannot use `sglang` to accelerate VLM model inference, meaning you cannot use the `vlm-sglang-engine` backend or start the `vlm-sglang-server` service.

## Start Docker Container:

```bash
docker run --gpus all \
  --shm-size 32g \
  -p 30000:30000 -p 7860:7860 -p 8000:8000 \
  --ipc=host \
  -it mineru-sglang:latest \
  /bin/bash
```

After executing this command, you will enter the Docker container's interactive terminal with some ports mapped for potential services. You can directly run MinerU-related commands within the container to use MinerU's features.
You can also directly start MinerU services by replacing `/bin/bash` with service startup commands. For detailed instructions, please refer to the [MinerU Usage Documentation](../usage/index.md).

## Start Services Directly with Docker Compose

We provide a [compose.yaml](https://github.com/opendatalab/MinerU/blob/master/docker/compose.yaml) file that you can use to quickly start MinerU services.

```bash
# Download compose.yaml file
wget https://gcore.jsdelivr.net/gh/opendatalab/MinerU@master/docker/compose.yaml
```

>[!NOTE]
>
>- The `compose.yaml` file contains configurations for multiple services of MinerU, you can choose to start specific services as needed.
>- Different services might have additional parameter configurations, which you can view and edit in the `compose.yaml` file.
>- Due to the pre-allocation of GPU memory by the `sglang` inference acceleration framework, you may not be able to run multiple `sglang` services simultaneously on the same machine. Therefore, ensure that other services that might use GPU memory have been stopped before starting the `vlm-sglang-server` service or using the `vlm-sglang-engine` backend.

- Start `sglang-server` service and connect to `sglang-server` via `vlm-sglang-client` backend:
  ```bash
  docker compose -f compose.yaml --profile mineru-sglang-server up -d
  ```
  >[!TIP]
  >In another terminal, connect to sglang server via sglang client (only requires CPU and network, no sglang environment needed)
  > ```bash
  > mineru -p <input_path> -o <output_path> -b vlm-sglang-client -u http://<server_ip>:30000
  > ```

- Start API service:
  ```bash
  docker compose -f compose.yaml --profile mineru-api up -d
  ```
  >[!TIP]
  >Access `http://<server_ip>:8000/docs` in your browser to view the API documentation.

- Start Gradio WebUI service:
  ```bash
  docker compose -f compose.yaml --profile mineru-gradio up -d
  ```
  >[!TIP]
  >
  >- Access `http://<server_ip>:7860` in your browser to use the Gradio WebUI.
  >- Access `http://<server_ip>:7860/?view=api` to use the Gradio API.
