KAG aims to make full use of the advantages of Knowledge Graph and vector retrieval, and bi-directionally enhance large language models and knowledge graphs through four aspects to solve RAG challenges: (1) LLM-friendly knowledge representation, (2) Knowledge Graph and original text The mutual index between fragments, (3) a hybrid reasoning engine guided by logical forms, (4) knowledge alignment with semantic reasoning.