URL to Markdown API

Transform any web content into clean, LLM-ready Markdown with a single API call! This powerful FastAPI service seamlessly converts web pages, documents, and multimedia content into structured Markdown format, making it perfect for AI/ML pipelines, content aggregation, and data processing workflows.

🚀 Key Features

• Universal Content Support: Convert web articles, YouTube videos, PDFs, Office documents, and more
• LLM-Optimized Output: Clean, structured Markdown perfect for AI/ML processing
• Rich Media Handling: Extract metadata from images, audio files, and videos
• Smart Processing: OCR for images, transcription for audio, and intelligent content extraction
• Simple Integration: RESTful API with clear error handling and response codes

🌐 Live Demo

Try it now at markdown.nimk.ir - Transform any URL into clean Markdown instantly!

Example 1: Converting a Web Article

GET https://markdown.nimk.ir/https://ask.library.arizona.edu/faq/407985

This will convert the library FAQ article into clean, readable Markdown format.

Example 2: Converting a YouTube Video

GET https://markdown.nimk.ir/https://www.youtube.com/watch?v=dQw4w9WgXcQ

This will extract the video title, description, and other metadata in Markdown format.

Features

• Convert web pages to clean Markdown optimized for LLM processing
• Support for various content types including:
  • Web articles and HTML content
  • YouTube videos
  • PDF documents
  • PowerPoint presentations
  • Word documents
  • Excel spreadsheets
  • Images (with EXIF metadata and OCR)
  • Audio files (with metadata and transcription)
  • Text-based formats (CSV, JSON, XML)
  • ZIP files (processes contents)
• Automatic URL protocol handling
• Clean error handling with appropriate HTTP status codes

Why Markdown for LLMs?

• Structured Format: Markdown provides a clean, hierarchical structure that LLMs can easily parse and understand
• Consistent Representation: Different content types are normalized into a unified text format
• Preserved Semantics: Headers, lists, and emphasis are maintained in a way that preserves document structure
• Reduced Noise: Removes unnecessary formatting and styling, focusing on content
• Enhanced Accessibility: Makes content more accessible for text analysis and natural language processing

Installation

Standard Installation

1. Clone the repository
2. Install dependencies:

pip install -r requirements.txt

Docker Deployment

1. Using Docker Compose (Recommended)

docker-compose up -d

This will build and start the service in detached mode. The API will be available at http://localhost:8000

2. Using Docker directly

# Build the image
docker build -t url-to-markdown .

# Run the container
docker run -d -p 8000:8000 url-to-markdown

Usage

Start the server:

uvicorn main:app --reload

The API will be available at http://localhost:8000

API Endpoint

GET /{url}

The URL should be URL-encoded if it contains special characters.

Example Use Cases

1. Converting YouTube Videos

   GET http://localhost:8000/www.youtube.com/watch?v=dQw4w9WgXcQ
   

   This will return the video title, description, and metadata in Markdown format.

2. Converting PDF Documents

   GET http://localhost:8000/https://pdfobject.com/pdf/sample.pdf
   

   This will convert the PDF content into readable Markdown text.

3. Converting Web Articles

   GET http://localhost:8000/https://dev.to/iw4p/scraping-tweets-without-twitter-api-and-free-5g9c
   

   This will convert the article content into clean Markdown format.

Response Format

Successful response: Plain text Markdown content

# Article Title

## Content

[Article content in Markdown format]

Error Responses

• 400: URL processing failed
• 415: Unsupported URL format
• 500: Internal server error

Development

This project uses:

• FastAPI for the web framework
• MarkItDown for content conversion
• Python 3.12+

License

MIT License