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That's because PDFs are the hard part. If you're starting with small pieces of text, RAG becomes much much easier.
by petesergeant 1y ago
That's because PDFs are the hard part. If you're starting with small pieces of text, RAG becomes much much easier.
- imperfect_light 1y agoMy question is less about PDFs and more about the notion that all the facts needed for the RAG are in documents. In my experience just a fraction of the questions that might be useful exist in a document somewhere. There must be a variation of RAGs that are pulling not from documents, but from databases using some semantic model.
- petesergeant 1y agoSure, but the process for this is laughably easy: you render the text with a minimum amount of text to place it into context, and submit that to whatever your embedding-maker is to get the embedding. You could potentially store the embedding in the same DB row if you have a DB that's happy with vector searches.