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To implement vector research in Azure Cognitive Search, there are several methods that should be adopted for facts ingestion and at query time.
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When the consumer submits the question during the consumer application, call the exact same Azure OpenAI embedding design (or other embedding design) applied to build the vector embeddings that were saved in the beginning from the index.
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In the same way your Alternative will have to comprise calls to an embedding model to build the embeddings prior to deciding to help save them to an index, you must also call a similar embedding product to vectorize your quest query prior to sending it to Cognitive Search.
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