title	Git2Doc
emoji	🐢
colorFrom	red
colorTo	purple
sdk	docker
pinned	false
license	apache-2.0

Git2Doc: Automated Repository Documentation Generator

Transform any GitHub repository into comprehensive technical documentation with AI-powered workflow diagrams — automatically.

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Overview

Git2Doc is an intelligent documentation generator that converts GitHub repositories into professional, structured technical documentation using AI-powered analysis. It automatically:

• Analyzes code using Google's Gemini 2.0 Flash model
• Generates workflow diagrams showing project architecture
• Creates comprehensive documentation with proper formatting
• Produces professional PDFs with embedded diagrams
• Applies smart formatting with headings, lists, and bold text

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Key Features

Intelligent Repository Analysis

• Scans entire GitHub repositories using GithubTools
• Identifies files, modules, functions, classes, and dependencies
• Understands code structure and relationships
• Extracts key technical information

Automatic Workflow Diagram Generation

• Creates high-level architectural diagrams (5-10 nodes)
• Visualizes project workflow and data flow
• Renders professional diagrams at 300 DPI
• Embeds diagrams directly into documentation

Comprehensive Documentation

• Generates Introduction and Conclusion sections
• Documents all functions, classes, and methods
• Explains dependencies, integrations, and workflows
• Uses bold formatting for important concepts
• Properly structures content with clear headings

Professional PDF Output

• Creates publication-ready PDFs
• Embeds workflow diagrams at optimal locations
• Supports custom typography (19.5pt headings, 11.5pt body)
• Includes numbered lists and proper spacing
• Handles image embedding and captions

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Workflow Architecture

Git2Doc follows this automated workflow:

Process Flow:

1. main.py — Entry point, handles user input
2. Repository Analysis — Analyzes GitHub repository structure
3. GitHub API — Fetches repository data
4. Gemini AI Model — Interprets code and generates documentation
5. Documentation Generator — Creates structured content
6. Workflow Generator — Produces workflow diagram JSON
7. PDF Export — Generates final PDF with embedded diagram
8. Technical Documentation — Final output files

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Project Structure

Git2Doc/
├── main.py                         # Main orchestration script
├── doc_creation.py                 # PDF generation with image embedding
├── generate_project_workflow.py   # Workflow diagram renderer
├── requirements.txt                # Python dependencies
├── pyproject.toml                  # Project configuration
├── .env                            # Environment variables (create this)
├── assets/                         # Static assets
│   ├── workflow_diagram.png        # Sample workflow diagram
│   └── code2doc_documentation_preview.png
└── examples/                       # Sample outputs
    └── technical_documentation.pdf # Example generated documentation

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Sample Output

Generated Files

After running Git2Doc, you'll get:

File	Description
content.txt	Markdown-formatted documentation with diagram references
technical_documentation.pdf	Professional PDF with embedded workflow diagram
project_workflow.json	Structured workflow data (nodes and edges)
project_workflow_diagram.png	High-resolution workflow diagram (300 DPI)

Example Output

View Sample Documentation PDF →

The generated documentation includes:

• Introduction — Project overview and context
• Workflow Diagram — Visual architecture (automatically inserted)
• Architecture — Component breakdown
• Implementation Details — Functions, classes, and methods
• Dependencies — External integrations
• Conclusion — Key features and takeaways

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Use Cases

• Project Documentation — Auto-generate README and technical docs
• Code Understanding — Quickly understand unfamiliar codebases
• Onboarding — Help new team members learn project structure
• Code Review — Get AI-powered insights into functionality
• Legacy Code — Document undocumented systems
• Architecture Diagrams — Visualize system workflows automatically

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Dependencies

Package	Purpose
agno	AI agent framework for orchestration
google-genai	Google Gemini AI integration
python-dotenv	Environment variable management
PyMuPDF (fitz)	PDF generation and manipulation
Pillow	Image processing for PDF embedding
graphviz	Workflow diagram rendering

Install all dependencies:

uv sync  # or pip install -r requirements.txt

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License

This project is licensed under the Apache License 2.0 - see the LICENSE file for details.

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Contributing

Contributions are welcome! Please feel free to submit a Pull Request.

1. Fork the Project
2. Create your Feature Branch (git checkout -b feature/AmazingFeature)
3. Commit your Changes (git commit -m 'Add some AmazingFeature')
4. Push to the Branch (git push origin feature/AmazingFeature)
5. Open a Pull Request

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Roadmap

• AI-powered repository analysis
• Automatic workflow diagram generation
• PDF generation with embedded diagrams
• Professional formatting and typography
• Multiple output formats (Markdown, HTML)
• Batch processing for multiple repositories
• Custom documentation templates
• Integration with documentation platforms (Read the Docs, GitBook)
• Interactive web UI
• Code quality metrics and analysis
• Automated documentation updates on commits
• Multi-language support (currently Python-focused)

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