langchain-pymupdf4llm 1.27.2

An integration package connecting PyMuPDF4LLM to LangChain

langchain-pymupdf4llm

An independent LangChain integration package connecting PyMuPDF4LLM to LangChain as a document loader.

Introduction

langchain-pymupdf4llm integrates PyMuPDF4LLM with LangChain as a document loader. It extracts PDF content into Markdown for LLM and retrieval-augmented generation workflows.

Licensing

This package depends directly on pymupdf4llm / pymupdf, which are published by Artifex under AGPL/commercial terms. Because this integration wraps that stack directly, this repository is distributed under AGPL-3.0-only.

If you distribute software or provide a network service that uses this package, you must evaluate your own AGPL compliance obligations. If you cannot comply with the AGPL, obtain an appropriate commercial license for the PyMuPDF stack from Artifex instead of relying on this package under the AGPL.

langchain-core remains MIT-licensed and is compatible with this package's AGPL license. See NOTICE for third-party attribution details.

Features

PyMuPDF4LLM provides Markdown extraction for standard text, tables, headers, lists, code blocks, multi-column pages, images, and vector graphics.

This integration adds LangChain loader and parser APIs, including optional image description replacement when an image parser is provided.

Requirements

• Python 3.10 or higher
• LangChain Core v1.0.0 or higher
• PyMuPDF4LLM v1.27.2.1 up to, but not including, v1.28.0

Installation

Install the package using pip:

pip install -U langchain-pymupdf4llm

Before installing, make sure the AGPL/commercial licensing model of the PyMuPDF stack works for your use case.

For optional image parsing capabilities, you may also want to install:

pip install langchain-community

Licensing Correction For Existing Users

Earlier releases of this package were incorrectly labeled as MIT. The package has always depended on the AGPL/commercial PyMuPDF stack, so existing users should re-evaluate whether their usage and redistribution model is compatible with that dependency chain.

Future corrective releases should:

1. Keep the AGPL package metadata and repository license files aligned.
2. Clearly disclose the licensing correction in release notes.
3. Deprecate or supersede the incorrectly labeled release on package indexes where possible.

Usage

from langchain_pymupdf4llm import PyMuPDF4LLMLoader

loader = PyMuPDF4LLMLoader(
    file_path="/path/to/input.pdf",
    mode="single",
    pages_delimiter="\n\f",
    use_layout=False,
    table_strategy="lines",
)

docs = loader.load()
print(docs[0].page_content[:100])
print(docs[0].metadata)

Use lazy_load() to stream documents:

for doc in loader.lazy_load():
    print(doc.metadata)

Use the parser with LangChain blob loaders:

from langchain_community.document_loaders import FileSystemBlobLoader
from langchain_community.document_loaders.generic import GenericLoader
from langchain_pymupdf4llm import PyMuPDF4LLMParser

loader = GenericLoader(
    blob_loader=FileSystemBlobLoader(path="path/to/docs/", glob="*.pdf"),
    blob_parser=PyMuPDF4LLMParser(),
)

Development

Open the workspace in the devcontainer, then install dependencies manually:

uv sync --group dev --group test --group lint --group typing

Install lightweight pre-commit hooks for formatting and hygiene checks:

uv run pre-commit install

Common commands are available as Cursor/VS Code tasks:

• uv sync
• test
• coverage
• lint
• format
• typecheck
• jupyter

JupyterLab is configured as a foreground task on port 8888. It does not start automatically when the container starts.

Run checks locally:

uv run --group test python -m pytest
uv run pytest --cov=src/langchain_pymupdf4llm --cov-report=term-missing --cov-fail-under=90
uv run black --check .
uv run ruff check .
uv run mypy .
uv run pre-commit run --all-files

The default pytest run disables sockets and skips tests marked network. To run network tests explicitly:

uv run --group test python -m pytest --force-enable-socket -m network

Creating Test Documents

To recreate the example PDF documents from LaTeX with deterministic PDF metadata:

cd ./tests/examples
SOURCE_DATE_EPOCH=1704067200 FORCE_SOURCE_DATE=1 pdflatex -interaction=nonstopmode sample_1.tex

Jupyter Notebooks

Start JupyterLab from the devcontainer:

uv run jupyter lab --ip 0.0.0.0 --port 8888 --no-browser

Contribute

Issues and pull requests are welcome on the GitHub repository.