microsoft/graphrag

A modular graph-based Retrieval-Augmented Generation (RAG) system

73
/ 100
Verified

This system helps you make sense of large amounts of unstructured text data, like research papers or internal documents. It processes your text to identify key entities and relationships, outputting a structured knowledge graph that your AI can then use to answer complex questions or find insights more effectively. This is designed for researchers, analysts, or anyone who needs to extract precise information and reasoning from extensive narrative data using large language models.

31,429 stars. Used by 1 other package. Actively maintained with 8 commits in the last 30 days. Available on PyPI.

Use this if you need to boost your AI's ability to reason about complex, private narrative data by transforming it into a structured knowledge graph.

Not ideal if you have very small datasets or primarily structured data, or if you are not prepared for potentially high processing costs during initial setup.

knowledge-extraction research-analysis document-intelligence data-enrichment information-discovery
Maintenance 17 / 25
Adoption 11 / 25
Maturity 25 / 25
Community 20 / 25

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Stars

31,429

Forks

3,319

Language

Python

License

MIT

Last pushed

Mar 12, 2026

Commits (30d)

8

Dependencies

25

Reverse dependents

1

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