Vector RAG

You previously learned about Retrieval Augmented Generation (RAGFetching relevant context from an external data source as additional context to inform a language model's response.) and the role of retrieversA component that searches a data source and returns the information relevant to a query. Often used to provide context for a language model. in finding relevant information.

One of the challenges of RAG is understanding what the user is asking for and finding the correct information to pass to the LLMA model trained on text to predict the next token, and so to generate language..