Many developers try to build retrieval-augmented generation (RAG) experiences to interact with information from unstructured data using only vector search and struggle to get to the results that they…

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The LLM Knowledge Graph Builder enhances retrieval-augmented generation (RAG) by transforming unstructured data into a structured knowledge graph. It imports documents, splits them into chunks, generates text embeddings, and uses various language models to extract entities and their relationships. The latest update introduces several features such as community summaries, parallel retrievers, and expanded model support, improving user experience and data interaction. The tool supports multiple retrievers running in parallel, guided extraction instructions, and includes metrics for retriever evaluation.

LLM Knowledge Graph Builder — First Release of 2025