does llama-index work with Spotify's `annoy` library?

Please stand by @ryanglambert as I search the knowledge base. We are experiencing especially high traffic right now and might take longer than usual. :wave:

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Hmm, I don't know enough to give you a confident answer yet. The provided extracts do not mention any integration with Spotify's annoy library. You can refer to the LlamaIndex documentation for more information: https://gpt-index.readthedocs.io/en/latest/index.html
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Note: you can ask me a follow up question by @ mentioning me again :speech_balloon:
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Should I thumbs down based on model's ability to get the answer? or more on the UX?

I think the answer is fine. We don't have a integration with that

(not sure what that is haha)

annoy is an ANN library

Interesting. So it could be used to retrieve nodes using embeddings right, instead of raw cosine similarity?

This sounds very interesting ... are there papers that compare ANN and cosine similarity efficiency ?

Not that I can see sadly

https://github.com/spotify/annoy

with small chunks, embeddings are not always very efficient ... wondering if ANN works better ...

That's definitely a good point. But I think with small chunks, the problem is probably more with embeddings themselves? Well, at least that's my impression (the cosine similarity starts to become very similar for small chunks)

Cosine similarity will be the upperbound of performance of ANN on accurate retrieval.

simply put, ANN is always 'trying' to be as accurate as cosine similarity while being wildly faster

ANN/KNN/etc. will always have more efficient retrieval than cosine against all documents' vectors.