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Comment by ipsi

So here's something I've been wanting to do for a while, but have kinda been struggling to figure out _how_ to do it. txtai looks like it has all the tools necessary to do the job, I'm just not sure which tool(s), and how I'd use them.

Basically, I'd like to be able to take PDFs of, say, D&D books, extract that data (this step is, at least, something I can already do), and load it into an LLM to be able to ask questions like:

* What does the feat "Sentinel" do?

* Who is Elminster?

* Which God(s) do Elves worship in Faerûn?

* Where I can I find the spell "Crusader's Mantle"?

And so on. Given this data is all under copyright, I'd probably have to stick to using a local LLM to avoid problems. And, while I wouldn't expect it to have good answers to all (or possibly any!) of those questions, I'd nevertheless love to be able to give it a try.

I'm just not sure where to start - I think I'd want to fine-tune an existing model since this is all natural language content, but I get a bit lost after that. Do I need to pre-process the content to add extra information that I can't fetch relatively automatically. e.g., page numbers are simple to add in, but would I need to mark out things like chapter/section headings, or in-character vs out-of-character text? Do I need to add all the content in as a series of questions and answers, like "What information is on page 52 of the Player's Handbook? => <text of page>"?

parent ipsi 2 years ago

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