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pdf-parser-mineruPDF parser mineru 文档

Agent Skill

pdf-parser-mineru 用于整理文档、README、Markdown 和说明材料,适合在 OpenClaw 中需要把零散信息整理成结构清晰的文档时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

49,644

周安装

2,048

GitHub Stars

公开资料未说明

下载量

16,220
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:pdf-parser-mineru(PDF parser mineru 文档)
来源仓库:https://github.com/baokui/pdf-parser-mineru
安装命令:
openclaw skills install pdf-parser-mineru
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

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openclaw skills install pdf-parser-mineru

简介

基于本地MinerU的PDF文档解析工具,支持将PDF转换为Markdown、JSON等机器可读格式。

SKILL.md

name
pdf-process-mineru
description
PDF document parsing tool based on local MinerU, supports converting PDF to Markdown, JSON, and other machine-readable formats.

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 file
  • output_dir (string, required): Absolute path to the output directory
  • backend (string, optional): Parsing backend, options: hybrid-auto-engine (default), pipeline, vlm-auto-engine
  • language (string, optional): OCR language code, such as en (English), ch (Chinese), ja (Japanese), etc., defaults to auto-detection
  • enable_formula (boolean, optional): Whether to enable formula recognition, defaults to true
  • enable_table (boolean, optional): Whether to enable table extraction, defaults to true
  • start_page (integer, optional): Start page number (starting from 0), defaults to 0
  • end_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 file
  • output_dir (string, required): Absolute path to the output directory
  • backend (string, optional): Parsing backend, options: hybrid-auto-engine (default), pipeline, vlm-auto-engine
  • language (string, optional): OCR language code, such as en (English), ch (Chinese), ja (Japanese), etc., defaults to auto-detection
  • enable_formula (boolean, optional): Whether to enable formula recognition, defaults to true
  • enable_table (boolean, optional): Whether to enable table extraction, defaults to true
  • start_page (integer, optional): Start page number (starting from 0), defaults to 0
  • end_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 pipeline backend: minimum 16GB, recommended 32GB+ - Using hybrid/vlm backend: minimum 16GB, recommended 32GB+

  • Disk Space: minimum 20GB (SSD recommended)
  • GPU (optional):

- pipeline backend: supports CPU-only - hybrid/vlm backend: requires NVIDIA GPU (Volta architecture and above) or Apple Silicon

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

  • 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

  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

  1. Insufficient Memory:

- Use pipeline backend - Limit parsing pages: start_page and end_page - Reduce virtual memory allocation

  1. Slow Parsing Speed:

- Enable GPU acceleration - Use hybrid-auto-engine backend - Disable unnecessary features (formulas, tables)

  1. Low OCR Accuracy:

- Specify the correct document language - Ensure the backend supports OCR (use pipeline or hybrid-*)

Related Resources

  • MinerU Official Documentation: https://opendatalab.github.io/MinerU/
  • MinerU GitHub: https://github.com/opendatalab/MinerU
  • Online Demo: https://mineru.net/

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能力 2

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能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

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能力 5

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

83.97%
按下载量换算13,620

安全审计

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Static analysis

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权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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