RAG

As Large Language Models (LLMs) transition from simple chatbots to autonomous agents, the methods we use to feed them data must evolve. While Retrieval-Augmented Generation (RAG) remains the industry standard for grounding models in external data, its “vanilla” implementation—converting text chunks into vectors for semantic lookup—often falters when faced with interconnected documents, technical jargon, or […]