docs-to-markdown 0.1.1

A tool to crawl documentation sites and convert them to Markdown format

docs-to-markdown 🚀 | Convert online documentation into Markdown by simply providing a URL

Perfect for converting libraries, SDKs, and other documentation for use with LLMs and AI Agents.

What is docs-to-markdown?

docs-to-markdown is a simple and fast tool that crawls online documentation from a given URL and converts it into Markdown files. Just provide the URL of the documentation you want to convert, and the tool will handle the rest. Whether you need a single consolidated file or multiple files, it streamlines your workflow for feeding content into your LLM and optimizing your AI prompts.

Features ✨

• Flexible Conversion: Convert documentation into one file or split into multiple files based on your needs.
• Intelligent Filtering: Extract only the sections you need to include in your LLM's context.
• AI-Optimized: Tailored for seamless integration with LLMs, AI Agents, and other AI systems.
• User-Friendly: Easy-to-use commands and a straightforward interface for quick results.

Installation 💻

Install directly from PyPI:

pip install docs-to-markdown

Usage 🚀

The tool provides flexible options for converting online documentation to Markdown format:

Basic Usage

docs-to-markdown https://example.com/docs --doc_name example_docs

With LLM Filtering (using GPT-4)

docs-to-markdown https://example.com/docs --llm-filtering --doc_name example_docs

Note: When using --llm-filtering, you need to set your OpenAI API key via:

• Command line: --openai-key "sk-..."
• Environment variable: OPENAI_API_KEY
• .env file

Output Options

Generate multiple files (preserving site structure):

docs-to-markdown https://example.com/docs --doc_name example_docs --output multiple

Generate a single consolidated file:

docs-to-markdown https://example.com/docs --doc_name example_docs --output single

Additional Parameters

• --max_depth: Maximum crawling depth (default: 2)
• --output_dir: Output directory (default: current directory)
• --llm-filtering: Use GPT-4 to filter and clean content
• --openai-key: OpenAI API key for LLM filtering

The tool will create a directory named by your doc_name parameter containing the Markdown files.

Development 🛠️

Developer Setup

Clone the project from GitHub:

git clone https://github.com/fdagostino/docs-to-markdown.git
cd docs-to-markdown

Install the required dependencies:

pip install -r requirements.txt

(Optional) It's recommended to use a virtual environment for development:

python -m venv .venv
source .venv/bin/activate  # On macOS/Linux or `.venv\Scripts\activate` on Windows

To run and test the project locally, simply invoke:

python docs_to_markdown.py https://example.com/docs --doc_name example_docs

You can also use additional flags (e.g., --llm-filtering, --output multiple) as needed during development.

Developed 100% with AI 🤖

This project was entirely developed using 🤖🤖🤖 and the amazing library Crawl4AI.

Contributing & Reporting Issues 🤝

We welcome contributions and feedback to help improve docs-to-markdown.

How to Contribute

• Fork the Repository: Click the "Fork" button on GitHub to create your own copy.
• Clone Your Fork:

  git clone https://github.com/YOUR_USERNAME/docs-to-markdown.git
  cd docs-to-markdown
  

• Create a Feature Branch:

  git checkout -b feature/your-feature-name
  

• Implement Your Changes
• Submit a Pull Request: Open a pull request against the main repository when your changes are ready.

How to Report Issues

• Visit the Issues Page: Please report bugs or feature requests at https://github.com/fdagostino/docs-to-markdown/issues.
• Before Reporting: Check if the issue has already been reported.
• Provide Details: When opening a new issue, include a clear description, steps to reproduce (if applicable), and any relevant error messages.

Your contributions and feedback are highly appreciated!

Support Me ❤️

If you find this tool useful, please consider supporting me on ko‑fi:

My 🤖 makes 🔧🔧🔧 for 🫵. Help me buy some ⚡⚡⚡ to feed them!

License 📄

This project is licensed under the terms found in LICENSE.md.