pdf-parser-mineru

Tool List

1. pdf_to_markdown

Convert PDF documents to Markdown format, preserving document structure, formulas, tables, and images.

Description: Use MinerU to parse PDF documents and output in Markdown format, supporting OCR, formula recognition, table extraction, and other features.

Parameters:

Return Value:

{
  "success": true,
  "output_path": "/path/to/output",
  "markdown_content": "Converted Markdown content...",
  "images": ["List of image paths"],
  "tables": ["List of table information"],
  "formula_count": 10
}

Examples:

python .claude/skills/pdf-process/script/pdf_parser.py \
  '{"name": "pdf_to_markdown", "arguments": {"file_path": "/path/to/document.pdf", "output_dir": "/path/to/output"}}'
Use specific backend
python .claude/skills/pdf-process/script/pdf_parser.py \
  '{"name": "pdf_to_markdown", "arguments": {"file_path": "/path/to/document.pdf", "output_dir": "/path/to/output", "backend": "pipeline"}}'
Parse specific pages
python .claude/skills/pdf-process/script/pdf_parser.py \
  '{"name": "pdf_to_markdown", "arguments": {"file_path": "/path/to/document.pdf", "output_dir": "/path/to/output", "start_page": 0, "end_page": 5}}'

2. pdf_to_json

Convert PDF documents to JSON format, including detailed layout and structural information.

Description: Use MinerU to parse PDF documents and output in JSON format, containing structured information such as text blocks, images, tables, formulas, etc.

Parameters:

Return Value:

{
  "success": true,
  "output_path": "/path/to/output.json",
  "pages": [
    {
      "page_no": 0,
      "page_size": [595, 842],
      "blocks": [
        {
          "type": "text",
          "text": "Text content",
          "bbox": [x, y, x, y]
        }
      ],
      "images": [],
      "tables": [],
      "formulas": []
    }
  ],
  "metadata": {
    "total_pages": 10,
    "author": "Author",
    "title": "Title"
  }
}

Examples:

python .claude/skills/pdf-process/script/pdf_parser.py \
  '{"name": "pdf_to_json", "arguments": {"file_path": "/path/to/document.pdf", "output_dir": "/path/to/output"}}'
Use specific backend and language
python .claude/skills/pdf-process/script/pdf_parser.py \
  '{"name": "pdf_to_json", "arguments": {"file_path": "/path/to/document.pdf", "output_dir": "/path/to/output", "backend": "hybrid-auto-engine", "language": "ch"}}'

Installation Instructions

1. Install MinerU

# Update pip and install uv
pip install --upgrade pip
pip install uv
Install MinerU (including all features)
uv pip install -U "mineru[all]"

2. Verify Installation

# Check if MinerU is installed successfully
mineru --version
Test basic functionality
mineru --help

3. System Requirements

Use Cases

1. Academic Paper Parsing: Extract structured content such as formulas, tables, and images 2. Technical Document Conversion: Convert PDF documents to Markdown for version control and online publishing 3. OCR Processing: Process scanned PDFs and garbled PDFs 4. Multilingual Documents: Supports OCR recognition for 109 languages 5. Batch Processing: Batch convert multiple PDF documents

Backend Selection Recommendations

Notes

1. File Paths: All paths must be absolute paths 2. Output Directory: Non-existent directories will be created automatically 3. Performance: Using GPU can significantly improve parsing speed 4. Page Numbers: Page numbers start counting from 0 5. Memory: Processing large documents may consume more memory

Troubleshooting

Common Issues

1. Installation Failure: - Ensure using Python 3.10-3.13 - Windows only supports Python 3.10-3.12 (ray does not support 3.13) - Using uv pip install can resolve most dependency conflicts

2. Insufficient Memory: - Use pipeline backend - Limit parsing pages: start_page and end_page - Reduce virtual memory allocation

3. Slow Parsing Speed: - Enable GPU acceleration - Use hybrid-auto-engine backend - Disable unnecessary features (formulas, tables)

4. Low OCR Accuracy: - Specify the correct document language - Ensure the backend supports OCR (use pipeline or hybrid-*)

Related Resources

1. File Paths: All paths must be absolute paths 2. Output Directory: Non-existent directories will be created automatically 3. Performance: Using GPU can significantly improve parsing speed 4. Page Numbers: Page numbers start counting from 0 5. Memory: Processing large documents may consume more memory