According to @_avichawla on Twitter, QueryWeaver is now available on GitHub as an open-source toolkit for optimizing graph-augmented retrieval and natural language queries over knowledge graphs, enabling faster and more accurate LLM answers on FalkorDB. As reported by the FalkorDB GitHub repository, QueryWeaver translates user intents into Cypher-like graph queries, applies retrieval optimization, and returns grounded responses that reduce hallucinations in production RAG pipelines. According to the project README on GitHub, developers can integrate QueryWeaver as a query planning layer for enterprise LLM applications, unlocking business use cases such as customer 360 search, fraud detection graph queries, and supply chain reasoning with measurable latency and precision gains.