Retrieval-Augmented Generation: Keep Answers Grounded in Documents

Retrieval-augmented generation (RAG) combines document retrieval with language-model generation. Instead of asking a model to rely only on its learned knowledge, the application retrieves relevant passages and supplies them as context.A typical pipeline extracts text, splits it into chunks, generates embeddings, and stores them in a searchable index. At query time, the system retrieves candidate c...