- 基于OpenSPG项目的落地实例。
KAG 是基于 OpenSPG 引擎和大型语言模型的逻辑推理问答框架，用于构建垂直领域知识库的逻辑推理问答解决方案。KAG 可以有效克服传统 RAG 向量相似度计算的歧义性和 OpenIE 引入的 GraphRAG 的噪声问题。KAG 支持逻辑推理、多跳事实问答等，并且明显优于目前的 SOTA 方法。
GitHub: https://github.com/OpenSPG/KAG
官网: https://openspg.github.io/v2/docs_ch
KAG introduction and applications: https://github.com/orgs/OpenSPG/discussions/52
如果您使用本软件，请以下面的方式引用：
- KAG: Boosting LLMs in Professional Domains via Knowledge Augmented Generation
- KGFabric: A Scalable Knowledge Graph Warehouse for Enterprise Data Interconnection
@article{liang2024kag,
title={KAG: Boosting LLMs in Professional Domains via Knowledge Augmented Generation},
author={Liang, Lei and Sun, Mengshu and Gui, Zhengke and Zhu, Zhongshu and Jiang, Zhouyu and Zhong, Ling and Zhao, Peilong and Bo, Zhongpu and Yang, Jin and others},
journal={arXiv preprint arXiv:2409.13731},
year={2024}
}
@article{yikgfabric,
title={KGFabric: A Scalable Knowledge Graph Warehouse for Enterprise Data Interconnection},
author={Yi, Peng and Liang, Lei and Da Zhang, Yong Chen and Zhu, Jinye and Liu, Xiangyu and Tang, Kun and Chen, Jialin and Lin, Hao and Qiu, Leijie and Zhou, Jun}
}梁磊，孙梦姝，桂正科，朱仲书，江洲钰，钟玲，赵培龙，伯仲璞，阳进，熊怀东，袁琳，徐军，汪兆洋，张志强，张文，陈华钧，陈文光，周俊，王昊奋