MarkItDown

MarkItDown is a utility for converting various files to Markdown (e.g., for indexing, text analysis, etc). It supports:

• PDF
• PowerPoint
• Word
• Excel
• Images (EXIF metadata and OCR)
• Audio (EXIF metadata and speech transcription)
• HTML
• Text-based formats (CSV, JSON, XML)
• ZIP files (iterates over contents)

To install MarkItDown, use pip: pip install markitdown. Alternatively, you can install it from the source: pip install -e .

Usage

Command-Line

markitdown path-to-file.pdf > document.md

You can also pipe content:

cat path-to-file.pdf | markitdown

Python API

Basic usage in Python:

from markitdown import MarkItDown

md = MarkItDown()
result = md.convert("test.xlsx")
print(result.text_content)

To use Large Language Models for image descriptions, provide llm_client and llm_model:

from markitdown import MarkItDown
from openai import OpenAI

client = OpenAI()
md = MarkItDown(llm_client=client, llm_model="gpt-4o")
result = md.convert("example.jpg")
print(result.text_content)

Docker

docker build -t markitdown:latest .
docker run --rm -i markitdown:latest < ~/your-file.pdf > output.md

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.opensource.microsoft.com.

When you submit a pull request, a CLA bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., status check, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repos using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.

Running Tests and Checks

• Install hatch in your environment and run tests:

  pip install hatch  # Other ways of installing hatch: https://hatch.pypa.io/dev/install/
  hatch shell
  hatch test

  (Alternative) Use the Devcontainer which has all the dependencies installed:

  # Reopen the project in Devcontainer and run:
  hatch test

• Run pre-commit checks before submitting a PR: pre-commit run --all-files

Trademarks

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsoft trademarks or logos is subject to and must follow Microsoft's Trademark & Brand Guidelines. Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship. Any use of third-party trademarks or logos are subject to those third-party's policies.