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Descentralized AI book reading server (self.selfhosted)

submitted 1 week ago by altphoto to c/selfhosted@lemmy.world

14 comments fedilink hide all child comments

OK you read the headline.

Imagine if Caliber had an AI tool that trained itself on all its books such that a user could ask a question regarding those specific books. And then extrapolate. Imagine if anyone anywhere could then ask questions to your local AI and get answers without actually sharing your books.

Right now I host my own Caliber server but I don't even know if I can search a term and get a particular book that contains thar term. I think it can search the title and metadata. I'm probably wrong. But the point is that it could be so much more. And it could circumvent the copyright laws that have always held back knowledge.

Like maybe my car broke down and I could ask IA why and how to fix it. Then it would start asking for the make and model and what sort of sounds it made. It would then search forums, our books and formulate an answer composed in the form of a book specifically written for me about my car's particular problem and how to solve it. Maybe better just a speech that you could listen to while fixing the car step by step...."now look a little to the left and you'll find a large box with 3 screws...."

It would be awesome to have that locally for my books and have access to everyone else's knowledge in books too.

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[–] Cyberflunk@lemmy.world 2 points 6 days ago (1 children)

What are you talking about? RAG is a method you use. It only has limitations you design. Your datastore can be whatever you want it to be. The llm performs a tool use YOU define. RAG isn't one thing. You can build a rag system out of flat files or a huge vector datastore. You determine how much data is returned to the context window. Python and chromadb easily scales to gigabytes, on consumer hardware, completely suitable for local rag.

[–] rumba@lemmy.zip 2 points 6 days ago

I explained what I did, and how it worked.

generally, this: https://www.youtube.com/watch?v=qV1Ab0qWyT8

the numbers came from my experience, ymmv.