May 4, 2024, 1:52 p.m. | /u/lapurita

Machine Learning www.reddit.com

At it's essence I guess RAG is about

1. retrieving relevant documents based on the prompt
2. putting the documents into the context window

Number 2 is very straight forward, while number 1 is where I guess more of the important stuff happens. IIRC, most often we do a similarity search here between the prompt embedding and the document embeddings, and retrieve the k-most similar documents.

Ok, at this point we have k documents and put them into context. Now …

context context window documents machinelearning prompt rag search the prompt while

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