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I packed-up a full-text paper scraper, vector database, and LLM into a CLI to answer questions from only highly-cited peer-reviewed papers. Feels unreal to be able instantly get answers by an LLM "reading" dozens of papers. 1/2

525,414 views • 3 years ago •via X (Twitter)

9 Comments

Andrew White 🐦‍⬛'s profile picture
Andrew White 🐦‍⬛3 years ago

Made with @LangChainAI, @OpenAI, textualize, FAISS, @SemanticScholar. Final frame (sorry no alt) 2/2

Andrew White 🐦‍⬛'s profile picture
Andrew White 🐦‍⬛3 years ago

@OpenAI @SemanticScholar Most of the code (except the interface) is already open source -

Karel Krápník Berka's profile picture
Karel Krápník Berka3 years ago

Can you ask it a question that bothers me about birds? Why are birds moving their heads in quick succession of interrupted rapid movements?

Teresa Kubacka's profile picture
Teresa Kubacka3 years ago

Cool! how did you come up with a decision to cut off lower cited papers and what threshold did you choose?

Andrew White 🐦‍⬛'s profile picture
Andrew White 🐦‍⬛3 years ago

It's a sort from influential citations and cut to 5 papers per search. No citation threshold.

Abdullah Al Nahid's profile picture
Abdullah Al Nahid3 years ago

Can the code be open-sourced Professor? I want to try too

ashish (@acgt01@genomic.social)'s profile picture
ashish (@[email protected])3 years ago

Is it open sourced ? If not, can you try to open source it ?

Barrett Davis's profile picture
Barrett Davis3 years ago

I’m new to this stuff. Is there a way to do something similar by reading 10 websites ? Or do 10 websites need to be converted into text and then read

Andrew White 🐦‍⬛'s profile picture
Andrew White 🐦‍⬛3 years ago

Definitely possible

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