Updated vector content

Author: haileytap

articles/search/vector-search-how-to-create-index.md

@@ -97,14 +97,14 @@ A vector configuration includes:
 
 ### [**2024-07-01**](#tab/config-2024-07-01)
 
-[**2024-07-01**](/rest/api/searchservice/search-service-api-versions#2024-07-01) is generally available. It supports a vector configuration having:
-
-+ Hierarchical navigable small world (HNSW) algorithm
-+ Exhaustive k-nearest neighbor (KNN) algorithm
-+ Scalar compression
-+ Binary compression (available in 2024-07-01 only and in newer Azure SDK packages)
-+ Oversampling
-+ Reranking with original vectors
+[**2024-07-01**](/rest/api/searchservice/search-service-api-versions#2024-07-01) is generally available. It supports a vector configuration that has:
+
++ The hierarchical navigable small world (HNSW) algorithm.
++ The exhaustive k-nearest neighbor (KNN) algorithm.
++ Scalar compression.
++ Binary compression, which is available in 2024-07-01 only and in newer Azure SDK packages.
++ Oversampling.
++ Reranking with original vectors.
 
 If you choose HNSW on a field, you can opt for exhaustive KNN at query time. However, the opposite doesn’t work. If you choose exhaustive for indexing, you can’t later request HNSW search because the extra data structures that enable approximate search don’t exist.
 

articles/search/vector-search-how-to-query.md

@@ -39,7 +39,7 @@ You can also use [Search Explorer](search-explorer.md) in the Azure portal.
 
 ## Convert a query string input into a vector
 
-To query a vector field, the query itself must be a vector. 
+To query a vector field, the query itself must be a vector.
 
 One approach for converting a user's text query string into its vector representation is to call an embedding library or API in your application code. As a best practice, *always use the same embedding models used to generate embeddings in the source documents*. You can find code samples showing [how to generate embeddings](vector-search-how-to-generate-embeddings.md) in the [azure-search-vector-samples](https://github.com/Azure/azure-search-vector-samples) repo.