MegaParse: A Precision Document Parser Built for LLMs

Converting PDF, Word, PPT, Excel and CSV documents into formats suitable for large language models (LLMs) improves accessibility, readability, and processing efficiency, and enables richer semantic analysis.

MegaParse is an open‑source universal document parser released by the quivr team (34.5K GitHub stars).

MegaParse Key Features

Information integrity – ensures loss‑less extraction.

High efficiency – fast parsing speed.

Broad format support – text, PDF, PPT, Excel, CSV, Word.

Quick Start

Install MegaParse: pip install megaparse Add your OpenAI API key to a .env file: OPENAI_API_KEY=CHANGE_ME Install poppler and tesseract. poppler is a PDF rendering library.

tesseract is an open‑source OCR engine with 60.1K GitHub stars.

Create app.py with the following code:

from megaparse import MegaParse

megaparse = MegaParse(file_path="./test.pdf")
document = megaparse.load()
print(document.content)
megaparse.save_md(content, "./test.md")

Run the script:

python app.py

Development Roadmap

The project is actively evolving; upcoming features are outlined in the roadmap image.

https://github.com/QuivrHQ/MegaParse

References

quivr: https://github.com/QuivrHQ/quivr

poppler: https://poppler.freedesktop.org/

tesseract: https://github.com/tesseract-ocr/tesseract