GraphRAG Accelerator

Welcome to the GraphRAG solution accelerator! This accelerator builds on top of the graphrag python package and exposes API endpoints hosted on Azure, which can be used to trigger indexing pipelines and enable querying of the graphrag knowledge graph.

This repository presents a methodology for running a hosted service 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: The GraphRAG Accelerator uses multiple Azure services and may incur substantial costs. It is meant to host a high-utilization API with auto-scaling and user access control. Please see the deployment bicep for further detail on the services used.

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

For FAQ and our roadmap, please visit aka.ms/graphrag

Getting Started with GraphRAG on Azure

Deployment Guide

To deploy the solution accelerator, see the deployment guide. This will result in a full deployment of graphrag as an API. Afterwards, check out the Quickstart notebook for a demonstration of various API calls.

Development Guide

Interested in contributing? Check out the development guide.

How to file issues and get help

This project uses GitHub Issues to track bugs and feature requests. Please search the existing issues before filing new issues to avoid duplicates. For new issues, file your bug or feature request as a new Issue.

Contributing

This project welcomes contributions and suggestions. Most contributions require you to agree to a Contributor License Agreement (CLA) declaring that you have the right to, and actually do, grant us the rights to use your contribution. For details, visit https://cla.microsoft.com.

When you submit a pull request, a CLA-bot will automatically determine whether you need to provide a CLA and decorate the PR appropriately (e.g., label, comment). Simply follow the instructions provided by the bot. You will only need to do this once across all repositories using our CLA.

This project has adopted the Microsoft Open Source Code of Conduct. For more information see the Code of Conduct FAQ or contact [email protected] with any additional questions or comments.

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.