MinerU Extension Modules Installation Guide

MinerU supports installing extension modules on demand based on different needs to enhance functionality or support specific model backends.

Common Scenarios

Core Functionality Installation

The core module is the core dependency of MinerU, containing common parsing features but not optional modules such as vllm/lmdeploy/s3. Installing this module ensures the basic functionality of MinerU works properly.

uv pip install "mineru[core]"

Using S3 Input and Output

If you need to read from or write to S3, install the s3 extension module.

uv pip install "mineru[s3]"

Using vllm to Accelerate VLM Model Inference

[!NOTE] vllm and lmdeploy have nearly identical VLM inference acceleration effects and usage methods. You can choose one of them to install and use based on your actual needs, but it is not recommended to install both modules simultaneously to avoid potential dependency conflicts.

The vllm module provides acceleration support for VLM model inference, suitable for graphics cards with Volta architecture and later (8GB+ VRAM). Installing this module can significantly improve model inference speed.

uv pip install "mineru[core,vllm]"

[!TIP]

• Because the vllm extra now allows the 0.21 series, the default installation usually resolves to the newer vllm version allowed by the current range. Make sure the host GPU driver supports the CUDA runtime required by the installed vllm package; the default path requires a CUDA 13.0-compatible driver.
• If you need a CUDA 12.9-compatible environment, follow the vllm official documentation to select the matching CUDA installation path, or use the vllm/vllm-openai:v0.21.0-cu129 base image from the Docker deployment workflow.
• If exceptions occur during installation of the extra package including vllm, you can also refer to the vllm official documentation to troubleshoot them.

Using lmdeploy to Accelerate VLM Model Inference

[!NOTE] vllm and lmdeploy have nearly identical VLM inference acceleration effects and usage methods. You can choose one of them to install and use based on your actual needs, but it is not recommended to install both modules simultaneously to avoid potential dependency conflicts.

The lmdeploy module provides acceleration support for VLM model inference, suitable for graphics cards with Volta architecture and later (8GB+ VRAM). Installing this module can significantly improve model inference speed.

uv pip install "mineru[core,lmdeploy]"

[!TIP] If exceptions occur during installation of the extra package including lmdeploy, please refer to the lmdeploy official documentation to try to resolve the issue.

Installing Lightweight Client to Connect to OpenAI-compatible servers (for vlm-http-client mode)

If you need to install a lightweight client on edge devices to connect to an OpenAI-compatible server for using VLM mode, you can install the basic mineru package, which is very lightweight and suitable for devices with only CPU and network connectivity.

uv pip install mineru
mineru -p <input_path> -o <output_path> -b vlm-http-client -u http://127.0.0.1:30000

Installing Lightweight Client to Connect to OpenAI-compatible servers (for hybrid-http-client mode)

If you need to install a lightweight client on edge devices to connect to an OpenAI-compatible server for using hybrid mode, you can install the mineru pipeline extension package, which is relatively lightweight and can be used on devices with only CPU and network connectivity, while running faster on devices that support GPU acceleration.

uv pip install "mineru[pipeline]"
mineru -p <input_path> -o <output_path> -b hybrid-http-client -u http://127.0.0.1:30000

Source: docs/en/quick_start/extension_modules.md