What is RAG?

Key Takeaways

so what is retrieval augmented generation so rag basically means that you fix the model the model doesn't change you're not training it anymore it's already pre-trained you're just using the openi API out of the box and then you take some Data Corpus frag is just a way you combine the two so the way it works is you load in some data from your Data Corpus that could be PDFs databases some sort of like semi-structured unstructured data so you take in some these documents chunk it up embed them put them into a factor database now that the data is in your storage system you can basically build this rag pipeline where given a user query you first retrieve the relevant context from the vector database Vector database is exposed an endpoint where you can basically fetch the most similar documents given a user query and then you take this like text and then you stuff it into the prompt so the prompt template looks something like you know here's some context dump the context in here's the question dump the question in and then you get the answer