markitdown

To convert PDF and DOCX files to Markdown for LLM processing, you can instantiate the converter and pass your file path to the conversion method. This extracts text content into a token-efficient Markdown format, making it easier for language models to index and extract data from diverse documents.

Yes, you can batch convert multiple documents into Markdown using provided scripts like batch_convert.py and convert_literature.py. These scripts allow you to scale workflows across large collections of files, automating the extraction process for research and knowledge-management purposes.

Converting documents to Markdown supports OCR for images and audio transcripts alongside formats like HTML, CSV, and JSON. This enables diverse workflows by transforming visual and audio content into clean, AI-friendly Markdown text suitable for ingestion into knowledge bases.

You do not strictly need an OpenAI API key for basic Markdown conversion, but it is required for AI-enhanced outputs. Optional OpenRouter or OpenAI integration provides rich image descriptions and data summaries, adding deeper context to your converted Markdown text.

The best way to handle complex document layouts when converting files to Markdown is using optional Azure Document Intelligence support. This integration complements the core conversion process by accurately parsing intricate structures, ensuring cleaner Markdown output for challenging PDF and document formats.

Yes, you can extract text from YouTube links and convert it to Markdown. The conversion tool supports YouTube URLs directly, transforming video transcripts into a token-efficient Markdown format that is easy for language models to process and index.