Hi all, I am getting different embeddings for the same texts. Using the following script: import time import numpy as np import openai openai.api_key = ... model = 'text-embedding-ada-002' def test(): def get_openai_embeddings(texts, model): result = openai.Embedding.create( …

[image] thiboeri: "The Lake Street Transfer station was a rapid transit station on the Chicago \"L\" that linked its Lake Street Elevated with the Logan Square branch of its Metropolitan West Side Elevated Railroad from 1913 to 1951.", Hi @thiboeri I ran your text (the first example) 10 tim…

Yes. The OpenAI python library will return many more decimal places; essentially noise. I believe it’s something to do with the conversion to base64? Can’t remember exactly. Regardless, the similarity scores will be the same.

We just faced the same issues for the first time here when using the openai-python package. We did some tests and around 11% of them were considerably different, even being near in the vector space. UPDATE: For anyone facing this issue, the embeddings’ endpoint is deterministic. The reason to this…

hi, faced same issue with python here. :smiling_face_with_tear: In my dataset, Im getting only 2 decimal precision. did you fix the prob? I’ve read all the instructions and guide but still don’t know what to do. Is it the only way not to use python? :smiling_face_with_tear:

I think it’s worth to separate the python precision issue discussed in Discrepancy in embeddings precision - #7 by RonaldGRuckus from the issue of the OpenAI API returning slightly different embeddings for the same exact input. Instead of using python, let’s use curl directly: curl https://api.open…

Non-deterministic embedding results using text-embedding-ada-002

API

curt.kennedy March 6, 2023, 8:44pm 5

See this post for more discussion on embedding decimal places Discrepancy in embeddings precision - #8 by curt.kennedy

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Non-deterministic embedding results using text-embedding-ada-002

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