folder2md4llms 0.1.1

Enhanced tool to concatenate folder contents into markdown format for LLM consumption

folder2md4llms

Enhanced tool to concatenate folder contents into markdown format for LLM consumption, inspired by gpt-repository-loader with significant improvements.

✨ Features

• 📝 Markdown-first output - Professional formatting with table of contents, syntax highlighting, and structured sections
• 📁 Folder structure visualization - ASCII tree representation of directory structure
• 📊 Repository statistics - File counts, sizes, and language breakdown
• 📄 Document conversion - PDF, DOCX, XLSX files converted to text/markdown
• 🔧 Binary file analysis - Intelligent descriptions for images, archives, and executables
• ⚙️ Highly configurable - YAML configuration files and comprehensive CLI options
• 🚀 Fast and efficient - Multi-threaded processing with progress tracking
• 🔍 Smart filtering - Advanced ignore patterns with glob support
• 📋 Multiple output formats - Markdown, HTML, and plain text support

🚀 Quick Start

Installation

# Install using uv (recommended)
uv add folder2md4llms

# Or using pip
pip install folder2md4llms

Basic Usage

# Process current directory
folder2md .

# Process specific directory with custom output
folder2md /path/to/repo --output analysis.md

# Skip tree generation and copy to clipboard
folder2md /path/to/repo --no-tree --clipboard

# Verbose mode with custom settings
folder2md /path/to/repo --verbose --max-file-size 2097152

📖 Documentation

• API Documentation - Complete API reference
• Configuration Guide - Configuration options and examples
• File Type Support - Supported file formats

🛠️ Development

Setup

# Clone the repository
git clone https://github.com/AI-driven-Optical-Biology-Laboratory/folder2md4llms.git
cd folder2md4llms

# Create virtual environment and install dependencies
uv venv
uv sync --dev

# Install pre-commit hooks
make install-hooks

Development Commands

# Format code
make format

# Run linting
make lint

# Run tests
make test

# Run tests with coverage
make test-cov

# Run all checks
make check

# Run pre-commit on all files
make pre-commit

Testing

# Run all tests
uv run pytest

# Run specific test file
uv run pytest tests/test_cli.py

# Run with coverage
uv run pytest --cov=folder2md4llms --cov-report=term-missing

🎯 Use Cases

• AI/ML Projects - Prepare codebases for LLM analysis and code review
• Documentation - Generate comprehensive project overviews
• Code Analysis - Create structured summaries for large repositories
• Knowledge Management - Convert project structures into searchable markdown
• Team Onboarding - Provide new team members with project overviews

🔧 Configuration

Basic Configuration

Create a folder2md.yaml file in your repository:

# Output settings
output_format: markdown
include_tree: true
include_stats: true

# Processing options
convert_docs: true
describe_binaries: true
max_file_size: 1048576  # 1MB

# Document conversion
pdf_max_pages: 50
xlsx_max_sheets: 10

Ignore Patterns

Create a .folder2md_ignore file:

# Version control
.git/
.svn/

# Build artifacts
__pycache__/
*.pyc
node_modules/
build/
dist/

# IDE files
.vscode/
.idea/

# Custom patterns
*.secret
temp/

📊 Output Format

The generated markdown includes:

1. 📑 Table of Contents - Navigation links to all sections
2. 📁 Folder Structure - ASCII tree representation
3. 📊 Repository Statistics - File counts, sizes, and language breakdown
4. 📄 Source Code - Syntax-highlighted code blocks
5. 📋 Documents - Converted document content
6. 🔧 Binary Files & Assets - Descriptions of non-text files

🔄 Improvements over gptrepo

• Enhanced Output: Markdown formatting with table of contents and syntax highlighting
• Document Conversion: PDF, DOCX, XLSX files automatically converted
• Binary Analysis: Intelligent descriptions for images, archives, and executables
• Advanced Filtering: Glob patterns and hierarchical ignore rules
• Configuration: YAML configuration files and extensive CLI options
• Performance: Multi-threaded processing with progress tracking
• Extensibility: Modular architecture for easy extension

🤝 Contributing

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

1. Fork the repository
2. Create your feature branch (git checkout -b feature/amazing-feature)
3. Commit your changes (git commit -m 'Add some amazing feature')
4. Push to the branch (git push origin feature/amazing-feature)
5. Open a Pull Request

📄 License

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

🙏 Acknowledgments

• Inspired by gpt-repository-loader by mpoon
• Built with modern Python tooling: uv, ruff, pytest

👤 Author

Ricardo Henriques - @ricardohenriques

Email: [e-mail]