RAG Pipeline

The end-to-end technical system that implements retrieval-augmented generation, combining a retrieval component that fetches relevant documents from a knowledge base with a language model that uses those documents to generate grounded, accurate responses. Building a reliable RAG pipeline involves decisions about chunking, embedding, indexing, retrieval, and prompting.