📄️ 📘 What is RAG?
RAG, short for Retrieval Augmented Generation, is a technique to enhance the quality of responses generated by a large language model (LLM), by augmenting its pre-trained knowledge with information retrieved from external sources. This results is more accurate responses from the LLM by grounding them in real, contextually relevant data.
📄️ 📘 When to use RAG?
RAG is best suited for the following:
📄️ 📘 Components of a RAG system
RAG systems have two main components: Retrieval and Generation.