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 .
βββ assets/
βββ datasets/
β βββ contexts/
β β βββ 2wikimultihopqa.txt
β β βββ agriculture.txt
β β βββ hotpotqa.txt
β β βββ hypertension.txt
β β βββ legal.txt
β β βββ musique.txt
β βββ questions/
β βββ 2wikimultihopqa.json
β βββ agriculture.json
β βββ hotpotqa.json
β βββ hypertension.json
β βββ legal.json
β βββ musique.json
βββ deepsearch/
β βββ components.py
β βββ prompts.py
βββ grag_initializers/
β βββ __init__.py
β βββ hypergraphrag.py
β βββ lightrag.py
β βββ minirag.py
β βββ pathrag.py
βββ graphkb/
β βββ lightrag/
β βββ 2wikimultihopqa/
β βββ hotpotqa/
β βββ musique/
βββ README.md
βββ __init__.py
βββ build_graph.py
βββ config.py
βββ graphrags.py
βββ infer.py
βββ 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} }