What is RAG (Retrieval-Augmented Generation)?

A technique that enhances LLM responses by first retrieving relevant documents from a knowledge base, then including them in the prompt context. RAG reduces hallucination and enables the model to answer questions about your private documents. On Mac, tools like LM Studio and Open WebUI support local RAG pipelines where both the retrieval and generation happen entirely on-device with zero cloud dependency.