If you’re starting with large language models, you must have heard of RAG (Retrieval-Augmented Generation). It’s the magic that lets AI chatbots talk about your data—your company’s PDFs, your private notes, or any new information—without “hallucinating.” It might sound complex, but the core logic of a simple RAG pipeline can be boiled down to six simple steps. We’re going to walk through the “conductor” script that runs this pipeline, showing you how data flows from a raw ...
