Document Processing Library PyMuPDF Releases Version 2.0, Consolidating Three Packages to Simplify LLM Data Pipelines

South Korean document AI company Epapyrus announced on October 27 that its open-source document processing library, PyMuPDF, has been updated to version 2.0. The core change in this release is the consolidation of three previously independent packages—the base engine PyMuPDF, the Large Language Model (LLM) data conversion tool PyMuPDF4LLM, and the layout analysis engine PyMuPDF Layout—into a single PyMuPDF package. Developers can now obtain all functionalities with a single pip install pymupdf command, eliminating the need to manage separate versions or adhere to specific import orders.

The new version includes built-in Graph Neural Network (GNN)-based layout analysis, capable of accurately identifying reading order in multi-column documents, footnotes, and tables, and converting extracted results directly into Markdown or JSON formats suitable for LLM input. Epapyrus stated that the process runs entirely on CPUs, requiring no GPUs or cloud calls. Compared to solutions relying on Vision-Language Models (VLMs), hardware resource consumption is approximately one-hundredth, with speed improvements of up to ten times. This makes it suitable for local or closed-network environments with strict data privacy requirements.

For existing users, PyMuPDF 2.0 maintains backward compatibility. Legacy import pymupdf4llm statements continue to work via a compatibility layer, and original MuPDF engine functions, license policies, and rendering/editing capabilities remain unchanged. According to Vice President Kim Jung-ah, PyMuPDF's global cumulative downloads have exceeded 1.2 billion.