Build graph-based retrieval workflows with GraphRAG

Que fait Build graph-based retrieval workflows with GraphRAG ?

Index private text into graph-backed retrieval structures, tune prompts, and query the resulting knowledge graph for RAG workflows.

Prerequisites

Python, GraphRAG CLI/package, LLM credentials, bounded text corpus

Installation

Requirements and caveats from upstream:

• trademarks or logos is subject to and must follow
• Use of Microsoft trademarks or logos in modified versions of this project must not cause confusion or imply Microsoft sponsorship.

Basic usage or getting-started notes:

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

• 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 offe...

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

• Source: https://github.com/microsoft/graphrag

• Extracted from upstream docs: https://raw.githubusercontent.com/microsoft/graphrag/HEAD/README.md

Documentation

• https://microsoft.github.io/graphrag/

Source

• Agent Skill Exchange