What is Retrieval-Augmented Generation (RAG) in Large Language Models?

Retrieval-Augmented Generation combines external knowledge retrieval with generative models to improve factual accuracy and contextual grounding.

Large Language Models store knowledge implicitly in parameters, but this creates limitations:

RAG solves this by integrating retrieval systems into generation pipelines.

Architecture:

Core components:

Embedding Models: