Changes default cache embedding model #326
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tylerhutcherson
approved these changes
Apr 23, 2025
| @@ -111,8 +111,19 @@ def __init__( | |||
| if dtype: | |||
| vectorizer_kwargs.update(dtype=dtype) | |||
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| # raise a warning to inform users we changed the default model | |||
| # remove this warning in future releases | |||
| logger.warning( | |||
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With the warning below in the case of pre-existing index AND overwrite=True, I don't think we actually need this one here right?
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You're right that a mismatch won't happen in that case, but there still is a behavior change when we switch default models. It's why I had to update the tests because the embedding distances changed.
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If someone goes from 0.5 to 0.6 and never specifies a vectorizer, and runs the same script start to finish - writes/reads/clears - they may get different results.
abrookins
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that referenced
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May 1, 2025
Changes the default semantic cache embedding model to our fine tuned model.
abrookins
pushed a commit
that referenced
this pull request
May 1, 2025
Changes the default semantic cache embedding model to our fine tuned model.
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Changes the default semantic cache embedding model to our fine tuned model.