Retrieval-Augmented Generation (RAG) has become the go-to method for building reliable AI applications that depend on external data, since it helps overcome LLM limitations, cuts down hallucinations, and delivers expert-level responses grounded in trusted sources. As interest in RAG rises, so does the need for tools that make it easier to explore, test, and refine […]The post How to Build a RAG Application with AutoRAG? appeared first on Analytics Vidhya.