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---
name: "Build graph-based retrieval workflows with GraphRAG"
slug: "build-graph-based-retrieval-workflows-with-graphrag"
description: "Index private text into graph-backed retrieval structures, tune prompts, and query the resulting knowledge graph for RAG workflows."
github_stars: 33445
verification: "security_reviewed"
source: "https://github.com/microsoft/graphrag"
author: "Microsoft"
publisher_type: "organization"
category: "Data Extraction & Transformation"
framework: "Multi-Framework"
tool_ecosystem:
github_repo: "microsoft/graphrag"
github_stars: 33445
---
# 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](https://microsoft.github.io/graphrag/get_started/).
- 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](https://agentskillexchange.com/skills/build-graph-based-retrieval-workflows-with-graphrag/)
