https://github.com/graph-com/subgraphrag

Simple is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation
https://github.com/graph-com/subgraphrag

gpt-4o graphrag knowledge-graph large-language-models llama llm rag retrieval-augmented-generation subgraphrag

Last synced: about 2 months ago
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Simple is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation

• Host: GitHub
• URL: https://github.com/graph-com/subgraphrag
• Owner: Graph-COM
• License: mit
• Created: 2024-10-29T06:18:14.000Z (12 months ago)
• Default Branch: main
• Last Pushed: 2024-11-20T05:30:39.000Z (11 months ago)
• Last Synced: 2024-12-18T11:04:47.552Z (10 months ago)
• Topics: gpt-4o, graphrag, knowledge-graph, large-language-models, llama, llm, rag, retrieval-augmented-generation, subgraphrag
• Language: Python
• Homepage:
• Size: 32.3 MB
• Stars: 26
• Watchers: 3
• Forks: 5
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

          
# SubgraphRAG, Simple Yet Effective KG-Based RAG

[[Paper]](https://arxiv.org/abs/2410.20724)

![model](framework_241104.png)

## Table of Contents

- [Usage](#usage)

- [Citation](#citation)

- [Frequently Asked Questions (FQA)](#frequently-asked-questions-fqa)

## Usage

SubgraphRAG is a retrieval-and-reasoning pipeline for knowledge-graph-based retrieval-augmented generation. 

1. For the retrieval stage, see [the retrieve folder](./retrieve/).

2. For the reasoning stage, see [the reason folder](./reason/).

## Frequently Asked Questions (FQA)

We welcome your feedback and sincerely appreciate your time! If you encounter bugs or have feature requests, you may [open an issue](../../issues/new) or email us at `{mufei.li, siqi.miao}@gatech.edu`. Your input helps us improve and better serve the community!

## Citation

```tex

@article{li2024subgraphrag,

    title={Simple is Effective: The Roles of Graphs and Large Language Models in Knowledge-Graph-Based Retrieval-Augmented Generation},

    author={Li, Mufei and Miao, Siqi and Li, Pan},

    journal={arXiv preprint arXiv:2410.20724},

    year={2024}

}

```