How Does Rag Work? - Vector Database and LLMs #datascience #naturallanguageprocessing #llm #gpt

Key Takeaways

let's learn about Rag and how it works in 60 seconds rag stands for retrieval augmented generation let's break down each of these and figure out what it means by studying how it works imagine you wanted to pose a question this is a query and you want to question something that belongs in a collection of documents in a rag system we store these documents in a vector database this database stores not only the documents themselves so the raw text but also their embeddings or numerical representation in a rag system this Vector database returns the documents most similar to a user's query next these documents are sent to a large language model think of gp4 and chat GPT in this example alongside these documents the query is also provided this gives the llm a context as well as the documents necessary to fill that context and the original query this allows it to generate a response for the user that is contextually right and has fewer chances of hallucination