pdf-process-mineru
PDF document parsing tool based on local MinerU, supports converting PDF to Markdown, JSON, and other machine-readable formats.
How do I install this agent skill?
npx skills add https://skills.volces.com --skill pdf-process-mineruIs this agent skill safe to install?
- Socketpass
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What does this agent skill do?
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:
file_path(string, required): Absolute path to the PDF fileoutput_dir(string, required): Absolute path to the output directorybackend(string, optional): Parsing backend, options:hybrid-auto-engine(default),pipeline,vlm-auto-enginelanguage(string, optional): OCR language code, such asen(English),ch(Chinese),ja(Japanese), etc., defaults to auto-detectionenable_formula(boolean, optional): Whether to enable formula recognition, defaults to trueenable_table(boolean, optional): Whether to enable table extraction, defaults to truestart_page(integer, optional): Start page number (starting from 0), defaults to 0end_page(integer, optional): End page number (starting from 0), defaults to -1 meaning parse all pages
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:
file_path(string, required): Absolute path to the PDF fileoutput_dir(string, required): Absolute path to the output directorybackend(string, optional): Parsing backend, options:hybrid-auto-engine(default),pipeline,vlm-auto-enginelanguage(string, optional): OCR language code, such asen(English),ch(Chinese),ja(Japanese), etc., defaults to auto-detectionenable_formula(boolean, optional): Whether to enable formula recognition, defaults to trueenable_table(boolean, optional): Whether to enable table extraction, defaults to truestart_page(integer, optional): Start page number (starting from 0), defaults to 0end_page(integer, optional): End page number (starting from 0), defaults to -1 meaning parse all pages
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
- Python Version: 3.10-3.13
- Operating System: Linux / Windows / macOS 14.0+
- Memory:
- Using
pipelinebackend: minimum 16GB, recommended 32GB+ - Using
hybrid/vlmbackend: minimum 16GB, recommended 32GB+
- Using
- Disk Space: minimum 20GB (SSD recommended)
- GPU (optional):
pipelinebackend: supports CPU-onlyhybrid/vlmbackend: requires NVIDIA GPU (Volta architecture and above) or Apple Silicon
Use Cases
- Academic Paper Parsing: Extract structured content such as formulas, tables, and images
- Technical Document Conversion: Convert PDF documents to Markdown for version control and online publishing
- OCR Processing: Process scanned PDFs and garbled PDFs
- Multilingual Documents: Supports OCR recognition for 109 languages
- Batch Processing: Batch convert multiple PDF documents
Backend Selection Recommendations
- hybrid-auto-engine (default): Balanced accuracy and speed, suitable for most scenarios
- pipeline: Suitable for CPU-only environments, best compatibility
- vlm-auto-engine: Highest accuracy, requires GPU acceleration
Notes
- File Paths: All paths must be absolute paths
- Output Directory: Non-existent directories will be created automatically
- Performance: Using GPU can significantly improve parsing speed
- Page Numbers: Page numbers start counting from 0
- Memory: Processing large documents may consume more memory
Troubleshooting
Common Issues
-
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 installcan resolve most dependency conflicts
-
Insufficient Memory:
- Use
pipelinebackend - Limit parsing pages:
start_pageandend_page - Reduce virtual memory allocation
- Use
-
Slow Parsing Speed:
- Enable GPU acceleration
- Use
hybrid-auto-enginebackend - Disable unnecessary features (formulas, tables)
-
Low OCR Accuracy:
- Specify the correct document language
- Ensure the backend supports OCR (use
pipelineorhybrid-*)
Related Resources
- MinerU Official Documentation: https://opendatalab.github.io/MinerU/
- MinerU GitHub: https://github.com/opendatalab/MinerU
- Online Demo: https://mineru.net/
How can the creator link this skill?
Add the canonical catalog link to the repository README so users can inspect current installs and available audits. The publishing guide covers the complete discovery path.
<a href="https://skillzs.dev/skills/skills.volces.com/pdf-process-mineru">View pdf-process-mineru on skillZs</a>