Python: Fix: use k instead of k_nearest_neighbors in Azure Search vector …#3333
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corradopignato wants to merge 3 commits intomicrosoft:mainfrom
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Python: Fix: use k instead of k_nearest_neighbors in Azure Search vector …#3333corradopignato wants to merge 3 commits intomicrosoft:mainfrom
k instead of k_nearest_neighbors in Azure Search vector …#3333corradopignato wants to merge 3 commits intomicrosoft:mainfrom
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k instead of k_nearest_neighbors in Azure Search vector …k instead of k_nearest_neighbors in Azure Search vector …
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Pull request overview
This PR fixes incorrect parameter naming in Azure AI Search vector query calls that was causing SDK warnings.
Changes:
- Replaced
k_nearest_neighborsparameter withkin VectorizableTextQuery and VectorizedQuery instantiations to align with the azure-search-documents SDK
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@farzad528 can you doublecheck this? |
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Python Test Coverage Report •
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Thanks for your contribution on this! I'm closing this PR in favor of #4212 which incorporates some of the fixes here along with additional improvements that were needed (EmbeddingGenerator support, async context manager cleanup, richer KB message/reference handling). Really appreciate your work on this! |
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Motivation and Context
calls to VectorizedQuery / VectorizableTextQuery pass k_nearest_neighbors, which is not a recognized attribute of the azure-search-documents SDK. The correct attribute is k.
This causes warnings such as:
k_nearest_neighbors is not a known attribute of class and will be ignored
Description
In the function _semantic_search in _search_provider.py, replace every occurrence of k_nearest_neighbors with k (used by VectorizableTextQuery / VectorizedQuery) to match the azure-search-documents SDK.