You have a SQL database in Microsoft Fabric named Sales BD that contains a table...

The first correct selection is embedding because a vector index must be created on the vector column , not on a scalar distance column or a text column such as product_name. Microsoft’s CREATE VECTOR INDEX documentation shows that the index is created directly on the vector-valued column, for example ON product_embeddings(embedding).

The second correct selection is VECTOR_SEARCH because the requirement is to use a supplied natural language query vector and search against the indexed embeddings. Microsoft documents that VECTOR_SEARCH is the Transact-SQL function for approximate nearest neighbor vector retrieval and that it applies to SQL database in Microsoft Fabric as well as other supported SQL platforms.

This also matches the shown code pattern:

declare a vector variable such as @query_vector VECTOR(1536),

create a vector index on dbo.Products(embedding),

query with VECTOR_SEARCH(... SIMILAR_TO = @query_vector, METRIC = ' cosine ' , TOP_N = 10).