url2md4ai 0.1.2

🚀 Lean Python tool for extracting clean, LLM-optimized markdown from web pages. Handles dynamic content with Playwright + Trafilatura for maximum information extraction efficiency.

🚀 url2md4ai

🎯 A lean Python tool for extracting clean, LLM-optimized markdown from web pages.

Perfect for AI applications that need high-quality text extraction from both static and dynamic web content. It combines Playwright for JavaScript rendering with Trafilatura for intelligent content extraction, delivering clean markdown ready for LLM processing.

🎯 Why url2md4ai?

Traditional tools extract everything: ads, cookie banners, navigation menus, social media widgets...
url2md4ai extracts only what matters: clean, structured content ready for LLM processing.

# Example: Extract job posting from Satispay careers page
url2md4ai convert "https://www.satispay.com/careers/job-posting" --show-metadata

# Result: 97% noise reduction (from 51KB to 9KB)
# ✅ Clean job title, description, requirements, benefits
# ❌ No cookie banners, ads, or navigation clutter

Perfect for:

• 🤖 AI content analysis workflows
• 📊 LLM-based information extraction
• 🔍 Web scraping for research and analysis
• 📝 Content preprocessing for RAG systems
• 🎯 Automated content monitoring

✨ Features

• 🧠 Smart Content Extraction: Powered by trafilatura for intelligent text extraction from HTML.
• 🚀 Dynamic Content Support: Uses playwright to render JavaScript on web pages, ensuring content from SPAs and dynamic sites is captured.
• 🧹 Clean Output: Removes ads, cookie banners, navigation, and other noise for a cleaner final output.
• 🐍 Simple API: A straightforward Python API and CLI for easy integration into your workflows.
• 📁 Deterministic Filenames: Generates unique, hash-based filenames from URLs for consistent output.

⚡ Lean & Efficient

• 🎯 Focused Purpose: Built specifically for AI/LLM text extraction workflows
• ⚡ Fast Processing: Optional non-JavaScript mode for static content (3x faster)
• 🔧 CLI-First: Simple command-line interface for batch processing and automation
• 🐍 Python API: Clean programmatic access for integration into AI pipelines

🛠️ Production Ready

• 📁 Smart Filenames: Generate unique, deterministic filenames using URL hashes
• 🔄 Batch Processing: Parallel processing support for multiple URLs
• 🎛️ Configurable: Extensive configuration options for different content types
• 📈 Reliable: Built-in retry logic and error handling

🚀 Quick Start

Using uv (Recommended)

# Install uv if you haven't already
curl -LsSf https://astral.sh/uv/install.sh | sh

# Clone and install
git clone https://github.com/mazzasaverio/url2md4ai.git
cd url2md4ai
uv sync

# Install Playwright browsers
uv run playwright install chromium

# Convert your first URL
uv run url2md4ai convert "https://example.com"

Using pip

pip install url2md4ai
playwright install chromium
url2md4ai convert "https://example.com"

Using Docker

See DOCKER_USAGE.md for instructions on how to use the provided Docker setup.

📖 Usage

Command-Line Interface (CLI)

The CLI provides a simple way to convert URLs to markdown or extract raw HTML.

Convert a URL to Markdown

# Convert a single URL and print to console
url2md4ai convert "https://example.com" --no-save

# Save the markdown to the default 'output' directory
url2md4ai convert "https://example.com"

# Specify a custom output directory
url2md4ai convert "https://example.com" --output-dir my_markdown

Extract Raw HTML from a URL

# Get the raw HTML of a page and print it to the console
url2md4ai extract-html "https://example.com"

Convert a Local HTML File

# Convert a local HTML file to markdown
url2md4ai convert-html my_page.html

For more options, use the --help flag with any command:

url2md4ai convert --help

Python API

The Python API provides programmatic access to the content extraction functionality.

import asyncio
from url2md4ai import ContentExtractor

# Initialize the extractor
extractor = ContentExtractor()

async def main():
    url = "https://example.com"

    # Extract clean markdown from a URL
    markdown_result = await extractor.extract_markdown(url)
    if markdown_result:
        print("--- MARKDOWN ---")
        print(markdown_result["markdown"])
        print(f"\\nSaved to: {markdown_result['output_path']}")

    # Extract raw HTML from a URL
    html_content = await extractor.extract_html(url)
    if html_content:
        print("\\n--- HTML ---")
        print(html_content[:200] + "...")  # Print first 200 characters

asyncio.run(main())

Synchronous Usage

For use cases where you can't use asyncio, synchronous wrappers are available:

from url2md4ai import ContentExtractor

extractor = ContentExtractor()
url = "https://example.com"

# Synchronously extract markdown
markdown_result = extractor.extract_markdown_sync(url)
if markdown_result:
    print(markdown_result["markdown"])

# Synchronously extract HTML
html_content = extractor.extract_html_sync(url)
if html_content:
    print(html_content[:200] + "...")

🛠️ Configuration

The behavior of the ContentExtractor can be customized through a Config object or environment variables.

Example: Custom Configuration

from url2md4ai import ContentExtractor, Config

# Customize configuration
config = Config(
    timeout=60,                  # Page load timeout in seconds
    user_agent="MyTestAgent/1.0", # Custom User-Agent
    output_dir="custom_output",  # Default output directory
    browser_headless=True,       # Run Playwright in headless mode
    wait_for_network_idle=True,  # Wait for network to be idle
    page_wait_timeout=2000       # Additional wait time in ms
)

extractor = ContentExtractor(config=config)

# This will use the custom configuration
extractor.extract_markdown_sync("https://example.com")

See src/url2md4ai/config.py for all available configuration options and their corresponding environment variables.

🤝 Contributing

Contributions are welcome! Please feel free to submit a pull request or open an issue.

📄 License

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

📊 Extraction Quality Examples

Before vs After: Real-World Results

# Complex job posting with cookie banners and ads
url2md4ai convert "https://company.com/careers/position" --show-metadata

Before (Raw HTML): 51KB, 797 lines

• ❌ Cookie consent banners
• ❌ Website navigation
• ❌ Social media widgets
• ❌ Advertising content
• ❌ Footer links and legal text

After (url2md4ai): 9KB, 69 lines

• ✅ Job title and description
• ✅ Key requirements
• ✅ Company benefits
• ✅ Application process
• ✅ 97% noise reduction!

Content Types Optimized for LLM

Content Type	Extraction Quality	Best Settings
News Articles	⭐⭐⭐⭐⭐	--no-js (faster)
Job Postings	⭐⭐⭐⭐⭐	--force-js (complete)
Product Pages	⭐⭐⭐⭐	--clean (essential)
Documentation	⭐⭐⭐⭐⭐	--raw (preserve structure)
Blog Posts	⭐⭐⭐⭐⭐	default settings
Social Media	⭐⭐⭐	--force-js required

📈 Roadmap

• Support for more output formats (PDF, DOCX)
• Custom CSS selector filtering
• Integration with popular LLM APIs
• Web UI interface
• Plugin system for custom processors
• Support for authentication-required pages

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Made with ❤️ by Saverio Mazza