Earlier quoted context omitted.
It's a great question! Right now, I don't train anything, I've broken the text down to n characters and created embeddings for that subset of text -- then I search for the closest distance / relationships between the question asked. Then I add the text to the prompt, and tell gpt to use those paragraphs to answer the question (to ensure that it doesn't make anything up). This is one of the ways I can get around the t…
Oh! I think I understand. So your software takes a prompt from me, does non-GPT work to find additional context from your source (the books, parsed and re-structured into word vectors or whatnot), and then asks GPT my prompt combined with the added context? Like, “What are the three foobars when considering these passages from a book ?”
- Your question -> vectors with open ai embeddings - Text you uploaded before -> vectors with open ai embeddings
Get the most similar above a certain threshold, and then add it to the prompt saying
"From these articles / paragraphs, answer the user's question: What are the three foobars"
So yep! I preprocess it