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Would you use a self-hosted, AI-powered search engine for your favorite sites? (lemmy.ca)

submitted 1 year ago by lautan@lemmy.ca to c/selfhosted@lemmy.world

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For context I created a video search engine last year, I shut it down and put the data online. You can read about it here: https://www.bendangelo.me/2024/07/16/failed-attempt-at-creating-a-video-search-engine/

I put that project on hold because of scaling issues, anyway I'm back with an other idea. I've been frustrated with how AI slop is ruining the internet and recently it's been hitting Youitube pretty hard with AI videos. I’m brainstorming a tool for people to selfhost:

Self-hosted crawler: Pick which sites/videos to index (blogs, forums, YT channels, etc.). AI chat interface: Ask questions like, “Show me Rust tutorials from 2023” or “Summarize recent posts about homelab backups.” Optional sharing: Pool indexes with trusted friends/communities.

Why? No Google/YouTube spam—only content you choose. Works offline (archive forums, videos, docs). Local AI (Mistral) or cloud (paid) for smarter searches.

Would this be useful to you? What sites would you crawl? Any killer features I’m missing?

Prototype in progress—just testing interest!

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[–] CameronDev@programming.dev 2 points 1 year ago

I didn't say you can't have a GPU, but to me, its wasteful. I keep my jellyfin server off when not in use, and use WoL to start it when its needed.

I have played with local LLMs, and the models I used were unimpressive, but without knowing what the OP has in mind, we cant know how much power it will use. If it just spins up the GPU once a day for 20 minutes, probably okay, you won't even notice it. But anyone like me who doesn't already have a GPU in their lab will probably notice it quite clearly on their power bill.

A megacorps server farm is huge, but its also amortised over millions of users, they probably don't need 1-1 GPU to customers, so the efficiency isnt necessarily bad. (Although at the moment, given megacorps are tripping over themselves to throw compute at LLM training, this may not be true)