RAG, or retrieval-augmented generation, is a new way to understand and create language. It combines two kinds of models. First, retrieve relevant information. Second, generate text from that information. By using both together, RAG does an amazing job.

Retrieval-Augmented generation (RAG) is a powerful technique that combines information retrieval with text generation. This method is particularly useful when you need to generate responses based on specific context extracted from a set of documents.

Retrieval Augmented Generation (RAG) is a technology that combines two powerful aspects of language processing: retrieval and generation. Let's break it down with an analogy: Imagine you're a librarian in a vast library, and you're helping people find information for their research papers.