Skip to main content

GraphRAG: A graph-based retrieval-augmented generation (RAG) system.

Project description

GraphRAG

👉 Microsoft Research Blog Post
👉 Read the docs
👉 GraphRAG Arxiv

Overview

The GraphRAG project is a data pipeline and transformation suite that is designed to extract meaningful, structured data from unstructured text using the power of LLMs.

To learn more about GraphRAG and how it can be used to enhance your LLM's ability to reason about your private data, please visit the Microsoft Research Blog Post.

Quickstart

To get started with the GraphRAG system we recommend trying the command line quickstart.

Repository Guidance

This repository presents a methodology for using knowledge graph memory structures to enhance LLM outputs. Please note that the provided code serves as a demonstration and is not an officially supported Microsoft offering.

⚠️ Warning: GraphRAG indexing can be an expensive operation, please read all of the documentation to understand the process and costs involved, and start small.

Diving Deeper

Prompt Tuning

Using GraphRAG with your data out of the box may not yield the best possible results. We strongly recommend to fine-tune your prompts following the Prompt Tuning Guide in our documentation.

Versioning

Please see the breaking changes document for notes on our approach to versioning the project.

Always run uv run poe init --root [path] --force between minor version bumps to ensure you have the latest config format. Run the provided migration notebook between major version bumps if you want to avoid re-indexing prior datasets. Note that this will overwrite your configuration and prompts, so backup if necessary.

Responsible AI FAQ

See RAI_TRANSPARENCY.md

Trademarks

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

Privacy

Microsoft Privacy Statement

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

graphrag-3.1.1.tar.gz (161.5 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

graphrag-3.1.1-py3-none-any.whl (298.8 kB view details)

Uploaded Python 3

File details

Details for the file graphrag-3.1.1.tar.gz.

File metadata

  • Download URL: graphrag-3.1.1.tar.gz
  • Upload date:
  • Size: 161.5 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.6.17

File hashes

Hashes for graphrag-3.1.1.tar.gz
Algorithm Hash digest
SHA256 3e7d82f1036340da209e5a630d04d398263d2a522eb1b2630b067cfa0055580b
MD5 56c2e0ac1f5a008c0dfd4d3efdd9b3cb
BLAKE2b-256 b394a6c8fe5dc08f75d318f256d98d982b70522de8c8c77ce029bb2b1b63c80f

See more details on using hashes here.

File details

Details for the file graphrag-3.1.1-py3-none-any.whl.

File metadata

  • Download URL: graphrag-3.1.1-py3-none-any.whl
  • Upload date:
  • Size: 298.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: uv/0.6.17

File hashes

Hashes for graphrag-3.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 646deaa22893dcd14f740ceb8c99cc5112b51677f1db05c413489ab2c4048702
MD5 2ce0171df276b30fe79839c594c737e7
BLAKE2b-256 7663d7b065a35b5b158bb5e8bfd5a7d2d63647d16b9628f2d8c3447a36bb46de

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page