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This is cool, but how about local semantic search through tens of thousands articles and books. Sure I'm not the first, there should be some tools already.

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I definitely was thinking about something like this for PaperMatch itself. Where anyone can pull a docker image and search through the articles locally! Do you think this idea is worthwhile pursuing?

Absolutely worth doing. Here is interesting related video, local RAG:

https://www.youtube.com/watch?v=bq1Plo2RhYI

I'm not an expert, but I'll do it for learning. Then open source if it works. As far as I understand this approach requires a vector database and LLM which doesn't have to be big. Technically it can be implemented as local web server. Should be easy to use, just type and get a sorted by relevance list.

Perfect!

Although, atm I am only using retrieval without any LLM involved. Might try integrating if it significantly improves UX without compromising speeds.

Try Semantra https://github.com/freedmand/semantra

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