MinerU/docs/en/usage/api.md

API Calls or Visual Invocation

1. Directly invoke using Python API: Python Invocation Example

2. Invoke using FastAPI:

   mineru-api --host 127.0.0.1 --port 8000
   

   Visit http://127.0.0.1:8000/docs in your browser to view the API documentation.

3. Use Gradio WebUI or Gradio API:

   # Using pipeline/vlm-transformers/vlm-sglang-client backend
   mineru-gradio --server-name 127.0.0.1 --server-port 7860
   # Or using vlm-sglang-engine/pipeline backend
   mineru-gradio --server-name 127.0.0.1 --server-port 7860 --enable-sglang-engine true
   

   Access http://127.0.0.1:7860 in your browser to use the Gradio WebUI, or visit http://127.0.0.1:7860/?view=api to use the Gradio API.

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• Below are some suggestions and notes for using the sglang acceleration mode:
  
• The sglang acceleration mode currently supports operation on Turing architecture GPUs with a minimum of 8GB VRAM, but you may encounter VRAM shortages on GPUs with less than 24GB VRAM. You can optimize VRAM usage with the following parameters:
  
  • If running on a single GPU and encountering VRAM shortage, reduce the KV cache size by setting --mem-fraction-static 0.5. If VRAM issues persist, try lowering it further to 0.4 or below.
    
  • If you have more than one GPU, you can expand available VRAM using tensor parallelism (TP) mode: --tp-size 2
    
• If you are already successfully using sglang to accelerate VLM inference but wish to further improve inference speed, consider the following parameters:
  
  • If using multiple GPUs, increase throughput using sglang's multi-GPU parallel mode: --dp-size 2
    
  • You can also enable torch.compile to accelerate inference speed by about 15%: --enable-torch-compile
    
• For more information on using sglang parameters, please refer to the sglang official documentation
  
• All sglang-supported parameters can be passed to MinerU via command-line arguments, including those used with the following commands: mineru, mineru-sglang-server, mineru-gradio, mineru-api

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• In any case, you can specify visible GPU devices at the start of a command line by adding the CUDA_VISIBLE_DEVICES environment variable. For example:

  CUDA_VISIBLE_DEVICES=1 mineru -p <input_path> -o <output_path>
  

• This method works for all command-line calls, including mineru, mineru-sglang-server, mineru-gradio, and mineru-api, and applies to both pipeline and vlm backends.

• Below are some common CUDA_VISIBLE_DEVICES settings:

  CUDA_VISIBLE_DEVICES=1 Only device 1 will be seen
  CUDA_VISIBLE_DEVICES=0,1 Devices 0 and 1 will be visible
  CUDA_VISIBLE_DEVICES="0,1" Same as above, quotation marks are optional
  CUDA_VISIBLE_DEVICES=0,2,3 Devices 0, 2, 3 will be visible; device 1 is masked
  CUDA_VISIBLE_DEVICES="" No GPU will be visible
  

• Below are some possible use cases:

  • If you have multiple GPUs and need to specify GPU 0 and GPU 1 to launch 'sglang-server' in multi-GPU mode, you can use the following command:

    CUDA_VISIBLE_DEVICES=0,1 mineru-sglang-server --port 30000 --dp-size 2
    

  • If you have multiple GPUs and need to launch two fastapi services on GPU 0 and GPU 1 respectively, listening on different ports, you can use the following commands:

    # In terminal 1
    CUDA_VISIBLE_DEVICES=0 mineru-api --host 127.0.0.1 --port 8000
    # In terminal 2
    CUDA_VISIBLE_DEVICES=1 mineru-api --host 127.0.0.1 --port 8001
    

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