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Changes default cache embedding model #326

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Merged
merged 2 commits into from
Apr 24, 2025

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justin-cechmanek
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Changes the default semantic cache embedding model to our fine tuned model.

@tylerhutcherson tylerhutcherson added the enhancement New feature or request label Apr 23, 2025
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LGTM! one comment pending

@@ -111,8 +111,19 @@ def __init__(
if dtype:
vectorizer_kwargs.update(dtype=dtype)

# 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.

@justin-cechmanek justin-cechmanek merged commit b44ac7b into 0.6.0 Apr 24, 2025
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@justin-cechmanek justin-cechmanek deleted the feat/RAAE-736/new-embed-model branch April 24, 2025 22:21
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2 participants