https://github.com/jdagdelen/hyperDB/blob/main/hyperdb/galax... This was a great laugh. Also, after the benchmark, it says: > Benchmark Credit: Benim Kıçım "Benim Kıçım" means "my ass" in Turkish.
References "[Submitted on 31 Mar 2023] Programmed but Arbitrary Control Minimization of Amplitude and phase for speckle Nulling (PACMAN)" https://arxiv.org/abs/2303.18231 No idea if that's a joke paper.
A hyper-fast local vector database for use with LLM Agents
21–25 of 25 posts
Re: A hyper-fast local vector database for use with LLM Agents
#22Damn this is good - well played. For those who aren't neck deep in LLM hype - ChromaDB raised $18m at a $75m valuation a couple weeks ago with what's essentially just a thin wrapper around duckdb with a parquet import/export for persistence.
Re: A hyper-fast local vector database for use with LLM Agents
#23aside from making fun of Chroma, this seems to 100% work though? What would be the pros/cons of actually using this instead?
Re: A hyper-fast local vector database for use with LLM Agents
#24It’s a joke, but is it a functional one? I found it crazy to run auto-GPT with an external DB over the internet, how can this be ever fast and efficient? (unless the dataset is humongous)
Re: A hyper-fast local vector database for use with LLM Agents
#25aside from making fun of Chroma, this seems to 100% work though? What would be the pros/cons of actually using this instead?
Author here. Yes, it actually does work. If I’m ever indexing fewer than ~100k documents/paragraphs I would use something like this approach rather than reaching for a vector database.