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Are there public examples of working products using RAG, compared with fine-tuning or training from scratch?


The OpenAI assistants API is an implementation of a RAG pipeline. It performs both RAG on any documents you upload, and on any conversation you have with it that exceeds the context.



Not public but internally I wrote a tool to help us respond to RFPs. You pass in a question from a new RFP and it outputs surprisingly great answers most of the time. Is writing 75%+ of our RFP responses now (naturally we review and adjust sometimes and as needed). And best of all it was very quickly hacked together and it’s actually useful. Copied questions/answers from all previous ones into a doc, and am using OpenAI embeddings api + FAISS vector db + GPT-4 to load the chunks + store the embeddings + process the resulting chunks.


Amazon Q is (at least partially) a RAG implementation.




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