[esafak]

Vector databases aren't for key value retrieval, they're for similarity search. What's that got to do with onnx?

[refulgentis]

ONNX runs the ML model that is f(string) -> vector. The similarity search is done using those vectors, and needs to return the original strings.

[all2]

Onnx allows arbitrary bundling and execution of ML models.. so maybe something to with the "run it local and private"?

[esafak]

Vector databases don't contain ML models. There is nothing that is learned. Here is a typical algorithm: https://www.pinecone.io/learn/series/faiss/hnsw/

It is all about performance; latency and recall.

[refulgentis]

Presumably the output of an ML model, the titular vector, and the chunk of text that created that vector are stored in a vector DB?

(that probably read aggressive, ignore my tone. At length: I run the model locally and store the vector locally, but I'm doing consumer use cases so I have different tradeoffs, so I'm glad to have someone who uses them interlocuting.)