Build and Query Knowledge Graphs with LLMs

Knowledge Graphs organize data in a human-like way. GraphRAG enhances LLMs by using a graph-based approach for more effective information retrieval and generation. Graphs reveal cross-document relationships, advancing search systems for data scientists and ML engineers. Neo4j and LangChain enable this complex, production-ready pipeline, setting a high standard for knowledge representation. Streamlit and Docker facilitate demoing and containerizing this efficient workflow.