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Add Search embedding sample for reduced embedding dimensions #34940

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@alzimmermsft

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@alzimmermsft

Add a sample for reducing embedding dimensions. Provide cases for scenarios where embeddings are being indexed client-side and with the vectorizer skill.

Additionally, give some overview on the reduced dimensions when the embedding is or is not normalized. This is a case where the vector search algorithm metric may change when searching (dot product when normalized and cosine when not normalized).

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ClientThis issue points to a problem in the data-plane of the library.DocsSearch

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