Crucial Exams

Microsoft Azure AI Engineer Associate AI-102 Practice Question

You manage an Azure AI Search index that contains a 1536-dimension field named productVector and a semantic configuration called product-semantic. You need to return the five most relevant documents by combining BM25 keyword ranking, semantic re-ranking, and vector similarity in a single request. Which set of request parameters should you include in the body of a POST /indexes//docs/search call to meet the requirement?

  • queryType set to "full" with semanticConfiguration set to "product-semantic" together with a vectorQueries clause

  • searchMode set to "all" together with scoringProfile set to "vectorBoost" and a vectorQueries clause

  • queryType set to "semantic" and searchMode set to "any" (no vectorQueries clause)

  • queryType set to "semantic", semanticConfiguration set to "product-semantic", and a vectorQueries clause that supplies the embedding, the productVector field, and k = 5

Microsoft Azure AI Engineer Associate AI-102
Implement knowledge mining and information extraction solutions
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