#ai ## What is RAG? Imagine you have a super smart robot friend. This robot can read a lot of books and knows a lot of things. But sometimes, when you ask it a question, it needs to go look in its big library of books to find the right answer. RAG, which stands for "Retrieval-Augmented Generation," is like giving your robot friend a magical way to quickly find the answers it needs. It can go to its library, pick out the right book, and then use its special robot brain to tell you the answer in a way that makes sense. In fact, RAG is a model architecture that combines elements of both retrieval and generation to improve the performance of AI systems on tasks involving text generation and understanding. ## RAG and [[GPT]] RAG and GPT are not the same thing, but they can work together like a team of superheroes! Imagine RAG as a detective who can find important information in a big library of books. It's really good at searching and finding the right books. Now, GPT is like a storyteller. It can take the information that the detective (RAG) found and turn it into a nice story or answer. It's really good at talking and explaining things. So, RAG finds the facts, and GPT makes those facts sound interesting and easy to understand. ## How to implement RAG?