We recommend that building an individual environment for each GraphRAG method, for example:
conda create -n lightrag python=3.11
cd lightrag
pip install lightrag-hku
conda create -n hypergraphrag python=3.11
conda activate hypergraphrag
git clone git@github.com:LHRLAB/HyperGraphRAG.git
cd HyperGraphRAG
pip install -r requirements.txt
pip install -e .
├── assets/
├── datasets/
│ ├── contexts/
│ │ ├── 2wikimultihopqa.txt
│ │ ├── agriculture.txt
│ │ ├── hotpotqa.txt
│ │ ├── hypertension.txt
│ │ ├── legal.txt
│ │ └── musique.txt
│ └── questions/
│ ├── 2wikimultihopqa.json
│ ├── agriculture.json
│ ├── hotpotqa.json
│ ├── hypertension.json
│ ├── legal.json
│ └── musique.json
├── deepsearch/
│ ├── components.py
│ └── prompts.py
├── grag_initializers/
│ ├── __init__.py
│ ├── hypergraphrag.py
│ ├── lightrag.py
│ ├── minirag.py
│ └── pathrag.py
├── graphkb/
│ └── lightrag/
│ ├── 2wikimultihopqa/
│ ├── hotpotqa/
│ └── musique/
├── README.md
├── __init__.py
├── build_graph.py
├── config.py
├── graphrags.py
├── infer.py
└── utils.py
Build Graph KB:
python build_graph.py -d musique -g lightrag
Inference:
python infer.py -d musique -m graphsearch -g lightrag
If you find this work useful, please cite:
@article{yang2025graphsearch,
title={GraphSearch: An Agentic Deep Searching Workflow for Graph Retrieval-Augmented Generation},
author={Yang, Cehao and Wu, Xiaojun and Lin, Xueyuan and Xu, Chengjin and Jiang, Xuhui and Sun, Yuanliang and Li, Jia and Xiong, Hui and Guo, Jian},
journal={arXiv preprint arXiv:2509.22009},
year={2025}
}