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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}
}