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MarkItDown is a lightweight Python utility for converting various files to Markdown for use with LLMs and related text analysis pipelines. To this end, it is most comparable totextract, but with a focus on preserving important document structure and content as Markdown (including: headings, lists, tables, links, etc.) While the output is often reasonably presentable and human-friendly, it is meant to be consumed by text analysis tools -- and may not be the best option for high-fidelity document conversions for human consumption.

MarkItDown currently supports the conversion from:

• 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)
• Youtube URLs
• EPubs
• ... and more!

Markdown is extremely close to plain text, with minimal markup or formatting, but stillprovides a way to represent important document structure. Mainstream LLMs, such asOpenAI's GPT-4o, natively "speak" Markdown, and often incorporate Markdown into theirresponses unprompted. This suggests that they have been trained on vast amounts ofMarkdown-formatted text, and understand it well. As a side benefit, Markdown conventionsare also highly token-efficient.

MarkItDown requires Python 3.10 or higher. It is recommended to use a virtual environment to avoid dependency conflicts.

With the standard Python installation, you can create and activate a virtual environment using the following commands:

python -m venv .venvsource .venv/bin/activate

If usinguv, you can create a virtual environment with:

uv venv --python=3.12 .venvsource .venv/bin/activate# NOTE: Be sure to use 'uv pip install' rather than just 'pip install' to install packages in this virtual environment

If you are using Anaconda, you can create a virtual environment with:

conda create -n markitdown python=3.12conda activate markitdown

To install MarkItDown, use pip:pip install 'markitdown[all]'. Alternatively, you can install it from the source:

git clone git@github.com:microsoft/markitdown.gitcd markitdownpip install -e'packages/markitdown[all]'

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

Or use-o to specify the output file:

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

You can also pipe content:

cat path-to-file.pdf| markitdown

MarkItDown has optional dependencies for activating various file formats. Earlier in this document, we installed all optional dependencies with the[all] option. However, you can also install them individually for more control. For example:

pip install'markitdown[pdf, docx, pptx]'

will install only the dependencies for PDF, DOCX, and PPTX files.

At the moment, the following optional dependencies are available:

• [all] Installs all optional dependencies
• [pptx] Installs dependencies for PowerPoint files
• [docx] Installs dependencies for Word files
• [xlsx] Installs dependencies for Excel files
• [xls] Installs dependencies for older Excel files
• [pdf] Installs dependencies for PDF files
• [outlook] Installs dependencies for Outlook messages
• [az-doc-intel] Installs dependencies for Azure Document Intelligence
• [audio-transcription] Installs dependencies for audio transcription of wav and mp3 files
• [youtube-transcription] Installs dependencies for fetching YouTube video transcription

MarkItDown also supports 3rd-party plugins. Plugins are disabled by default. To list installed plugins:

markitdown --list-plugins

To enable plugins use:

markitdown --use-plugins path-to-file.pdf

To find available plugins, search GitHub for the hashtag#markitdown-plugin. To develop a plugin, seepackages/markitdown-sample-plugin.

To use Microsoft Document Intelligence for conversion:

markitdown path-to-file.pdf -o document.md -d -e"<document_intelligence_endpoint>"

More information about how to set up an Azure Document Intelligence Resource can be foundhere

Basic usage in Python:

frommarkitdownimportMarkItDownmd=MarkItDown(enable_plugins=False)# Set to True to enable pluginsresult=md.convert("test.xlsx")print(result.text_content)

Document Intelligence conversion in Python:

frommarkitdownimportMarkItDownmd=MarkItDown(docintel_endpoint="<document_intelligence_endpoint>")result=md.convert("test.pdf")print(result.text_content)

To use Large Language Models for image descriptions, providellm_client andllm_model:

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

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

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

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

This project has adopted theMicrosoft Open Source Code of Conduct.For more information see theCode of Conduct FAQ orcontactopencode@microsoft.com with any additional questions or comments.

You can help by looking at issues or helping review PRs. Any issue or PR is welcome, but we have also marked some as 'open for contribution' and 'open for reviewing' to help facilitate community contributions. These are ofcourse just suggestions and you are welcome to contribute in any way you like.

• Navigate to the MarkItDown package:

  cd packages/markitdown

• Installhatch in your environment and run tests:

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

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

  # Reopen the project in Devcontainer and run:hatchtest

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

You can also contribute by creating and sharing 3rd party plugins. Seepackages/markitdown-sample-plugin for more details.

This project may contain trademarks or logos for projects, products, or services. Authorized use of Microsofttrademarks or logos is subject to and must followMicrosoft'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.