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KAG: Knowledge Augmented Generation for LLM Reasoning in Professional Domains

KAG is a powerful logical form-guided reasoning and retrieval framework built upon the OpenSPG engine and Large Language Models. It is specifically designed to create robust logical reasoning and factual Q&A solutions for specialized domain knowledge bases. This framework effectively overcomes the limitations of traditional RAG vector similarity calculation models and the noise often introduced by GraphRAG approaches.