LangChain GraphRAG

LangChain GraphRAG is an implementation of Microsoft Research’s GraphRAG approach that combines knowledge graphs with retrieval-augmented generation within the LangChain framework. This technique extracts structured information from unstructured text using large language models, constructs knowledge graphs with entities and relationships, builds community hierarchies, and generates summaries to enhance question-answering capabilities. The langchain-graphrag package implements the “From Local to Global” methodology, processing input corpora through graph construction, community detection, and hierarchical summarization. The system leverages the GraphRetriever from langchain-graph-retriever, which combines unstructured similarity search on vectors with structured traversal of metadata properties. This approach enables multi-hop reasoning across connected entities, providing substantially improved performance for complex queries over private datasets compared to traditional RAG systems that rely solely on vector similarity.