VS Code updates

Author: HeidiSteen

articles/search/cognitive-search-tutorial-blob-dotnet.md

@@ -53,7 +53,7 @@ Once content is extracted, the [skillset](cognitive-search-working-with-skillset
 + [Sample data files (mixed media)](https://github.com/Azure-Samples/azure-search-sample-data/tree/main/ai-enrichment-mixed-media)
 
 > [!NOTE]
-> You can use the free search service for this tutorial. A free search service limits you to three indexes, three indexers, and three data sources. This tutorial creates one of each. Before starting, make sure you have room on your service to accept the new resources.
+> You can use a free search service for this tutorial. The free tier limits you to three indexes, three indexers, and three data sources. This tutorial creates one of each. Before starting, make sure you have room on your service to accept the new resources.
 
 ### Upload sample data to Azure Storage
 

articles/search/cognitive-search-tutorial-blob.md

@@ -44,21 +44,21 @@ Once content is extracted, the [skillset](cognitive-search-working-with-skillset
 
 + [Azure AI Search](search-create-app-portal.md)
 
-+ [Sample data files (mixed media)](https://github.com/Azure-Samples/azure-search-sample-data/tree/main/ai-enrichment-mixed-media)
+> [!NOTE]
+> You can use a free search service for this tutorial. The free tier limits you to three indexes, three indexers, and three data sources. This tutorial creates one of each. Before starting, make sure you have room on your service to accept the new resources.
 
-+ [Sample REST file](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/skillset-tutorial)
+### Download files
 
-> [!NOTE]
-> You can use the free service for this tutorial. A free search service limits you to three indexes, three indexers, and three data sources. This tutorial creates one of each. Before starting, make sure you have room on your service to accept the new resources.
++ [Sample data files (mixed media)](https://github.com/Azure-Samples/azure-search-sample-data/tree/main/ai-enrichment-mixed-media). Download a zip file of the sample data repository and extract the contents.
+
++ [Sample REST file](https://github.com/Azure-Samples/azure-search-rest-samples/tree/main/skillset-tutorial)
 
 ### Upload sample data to Azure Storage
 
 1. In Azure Storage, create a new container and name it *cog-search-demo*.
 
 1. [Upload the sample data files](/azure/storage/blobs/storage-quickstart-blobs-portal).
 
-   :::image type="content" source="media/cognitive-search-tutorial-blob/sample-files.png" alt-text="Screenshot of the files in File Explorer." border="true":::
-
 1. Get a storage connection string so that you can formulate a connection in Azure AI Search.
 
    1. On the left, select **Access keys**.

articles/search/search-get-started-rest.md

@@ -56,7 +56,7 @@ If you're not familiar with the REST client for Visual Studio Code, this section
 1. Paste in the following example. Replace the base URL and API key with the values you copied earlier.
 
    ```http
-   @baseUrl = https://PUT-YOUR-SERVICE-NAME-HERE.search.windows.net
+   @baseUrl = PUT-YOUR-SEARCH-SERVICE-ENDPOINT-HERE
    @apiKey = PUT-YOUR-API-KEY-HERE
     
     ### List existing indexes by name
@@ -322,7 +322,14 @@ When you're working in your own subscription, it's a good idea at the end of a p
 
 You can find and manage resources in the portal, using the **All resources** or **Resource groups** link in the left-navigation pane.
 
-On a free service, remember the limitation of three indexes, indexers, and data sources. You can delete individual items in the portal to stay under the limit.
+You can also try this DELETE command:
+
+```http
+### Delete an index
+DELETE  {{baseUrl}}/indexes/hotels-quickstart?api-version=2023-11-01 HTTP/1.1
+    Content-Type: application/json
+    api-key: {{apiKey}}
+```
 
 ## Next steps
 

articles/search/search-get-started-vector.md

@@ -805,7 +805,18 @@ Here's the last query in the collection: a hybrid query, with semantic ranking,
 
 ## Clean up
 
-Azure AI Search is a billable resource. If it's no longer needed, delete it from your subscription to avoid charges.
+When you're working in your own subscription, it's a good idea at the end of a project to identify whether you still need the resources you created. Resources left running can cost you money. You can delete resources individually or delete the resource group to delete the entire set of resources.
+
+You can find and manage resources in the portal, using the **All resources** or **Resource groups** link in the left-navigation pane.
+
+You can also try this DELETE command:
+
+```http
+### Delete an index
+DELETE  {{baseUrl}}/indexes/hotels-vector-quickstart?api-version=2023-11-01 HTTP/1.1
+    Content-Type: application/json
+    api-key: {{apiKey}}
+```
 
 ## Next steps
 

articles/search/search-indexer-tutorial.md

@@ -33,10 +33,10 @@ If you don't have an Azure subscription, create a [free account](https://azure.m
 
 * [Azure SQL Database](https://azure.microsoft.com/services/sql-database/) using SQL Server authentication
 * [Visual Studio](https://visualstudio.microsoft.com/downloads/)
-* [Create](search-create-service-portal.md) or [find an existing search service](https://portal.azure.com/#blade/HubsExtension/BrowseResourceBlade/resourceType/Microsoft.Search%2FsearchServices) 
+* [Azure AI Search](search-what-is-azure-search.md). [Create](search-create-service-portal.md) or [find an existing search service](https://portal.azure.com/#blade/HubsExtension/BrowseResourceBlade/resourceType/Microsoft.Search%2FsearchServices) 
 
 > [!NOTE]
-> You can use the free service for this tutorial. A free search service limits you to three indexes, three indexers, and three data sources. This tutorial creates one of each. Before starting, make sure you have room on your service to accept the new resources.
+> You can use a free search service for this tutorial. The free tier limits you to three indexes, three indexers, and three data sources. This tutorial creates one of each. Before starting, make sure you have room on your service to accept the new resources.
 
 ## Download files
 

articles/search/search-query-partial-matching.md

@@ -54,9 +54,6 @@ The approach looks like this:
 1. Assign the analyzer to the field
 1. Build and test the index
 
-> [!TIP]
-> Evaluating analyzers is an iterative process that requires frequent index rebuilds. You can make this step easier by using Postman, the REST APIs for [Create Index](/rest/api/searchservice/create-index), [Delete Index](/rest/api/searchservice/delete-index),[Load Documents](/rest/api/searchservice/addupdate-or-delete-documents), and [Search Documents](/rest/api/searchservice/search-documents). For Load Documents, the request body should contain a small representative data set that you want to test (for example, a field with phone numbers or product codes). With these APIs in the same Postman collection, you can cycle through these steps quickly.
-
 ## 1 - Create a dedicated field
 
 Analyzers determine how terms are tokenized in an index. Since analyzers are assigned on a per-field basis, you can create fields in your index to optimize for different scenarios. For example, you might define "featureCode" and "featureCodeRegex" to support regular full text search on the first, and advanced pattern matching on the second. The analyzers assigned to each field determine how the contents of each field are tokenized in the index.  
@@ -91,7 +88,7 @@ When choosing an analyzer that produces whole-term tokens, the following analyze
 | [whitespace](https://lucene.apache.org/core/6_6_1/analyzers-common/org/apache/lucene/analysis/core/WhitespaceAnalyzer.html) | Separates on white spaces only. Terms that include dashes or other characters are treated as a single token. |
 | [custom analyzer](index-add-custom-analyzers.md) | (recommended) Creating a custom analyzer lets you specify both the tokenizer and token filter. The previous analyzers must be used as-is. A custom analyzer lets you pick which tokenizers and token filters to use. <br><br>A recommended combination is the [keyword tokenizer](https://lucene.apache.org/core/6_6_1/analyzers-common/org/apache/lucene/analysis/core/KeywordTokenizer.html) with a [lower-case token filter](https://lucene.apache.org/core/6_6_1/analyzers-common/org/apache/lucene/analysis/core/LowerCaseFilter.html). By itself, the built-in [keyword analyzer](https://lucene.apache.org/core/6_6_1/analyzers-common/org/apache/lucene/analysis/core/KeywordAnalyzer.html) doesn't lower-case any upper-case text, which can cause queries to fail. A custom analyzer gives you a mechanism for adding the lower-case token filter. |
 
-If you're using a web API test tool like Postman, you can add the [Test Analyzer REST call](/rest/api/searchservice/test-analyzer) to inspect tokenized output.
+Using a REST client, you can add the [Test Analyzer REST call](/rest/api/searchservice/test-analyzer) to inspect tokenized output.
 
 The index must exist on the search service, but it can be empty. Given an existing index and a field containing dashes or partial terms, you can try various analyzers over specific terms to see what tokens are emitted.  
 
@@ -231,7 +228,7 @@ Once you've defined an index with analyzers and field definitions that support y
 
 If you're familiar with Postman and REST APIs, [download the query examples collection](https://github.com/Azure-Samples/azure-search-rest-samples/) to query partial terms and special characters described in this article. The collection includes REST API requests for index creation and deletion, sample documents and an upload documents request, a test analyzer request, and queries. 
 
-The previous sections explained the logic. This section steps through each API you should call when testing your solution. As previously noted, if you use an interactive web test tool such as Postman, you can step through these tasks quickly.
+The previous sections explained the logic. This section steps through each API you should call when testing your solution. 
 
 + [Delete Index](/rest/api/searchservice/delete-index) removes an existing index of the same name so that you can recreate it.