@@ -46,7 +46,9 @@ In this tutorial, you:
 
 + The [Azure CLI](/cli/azure/install-azure-cli) for keyless authentication with Microsoft Entra ID.
 
-+ [Visual Studio Code](https://code.visualstudio.com/download) with the [Python extension](https://marketplace.visualstudio.com/items?itemName=ms-python.python) and [Jupyter package](https://pypi.org/project/jupyter/).
+- The latest version of [Python](https://www.python.org/downloads/).
+
+- [Visual Studio Code](https://code.visualstudio.com/download) with the [Python](https://marketplace.visualstudio.com/items?itemName=ms-python.python) and [Jupyter](https://marketplace.visualstudio.com/items?itemName=ms-toolsai.jupyter) extensions.
 
 ## Understand the solution
 
@@ -532,9 +534,7 @@ response.to_dict()
 
 ### Clean up resources
 
-When you work in your own subscription, it's a good idea to finish a project by determining whether you still need the resources you created. Resources that are left running can cost you money.
-
-In the Azure portal, you can manage your Azure AI Search and Microsoft Foundry resources by selecting **All resources** or **Resource groups** from the left pane.
+[!INCLUDE [clean up resources (paid)](includes/resource-cleanup-paid.md)]
 
 You can also run the following code to delete individual objects:
 

@@ -275,9 +275,7 @@ To review the auto-generated objects:
 
 ## Clean up resources
 
-When you work in your own subscription, it's a good idea to finish a project by determining whether you still need the resources you created. Resources that are left running can cost you money.
-
-In the Azure portal, you can manage your Azure AI Search, Azure Blob Storage, and Foundry resources by selecting **All resources** or **Resource groups** from the left pane.
+[!INCLUDE [clean up resources (paid)](includes/resource-cleanup-paid.md)]
 
 You can also delete the knowledge source and knowledge base on their respective portal pages. When you delete the knowledge source, the portal prompts you to delete the associated data source, skillset, index, and indexer.
 

@@ -844,9 +844,7 @@ foreach (var reference in retrievalResult.Value.References)
 
 ## Clean up resources
 
-When you work in your own subscription, it's a good idea to finish a project by determining whether you still need the resources you created. Resources that are left running can cost you money.
-
-In the Azure portal, you can manage your Azure AI Search and Microsoft Foundry resources by selecting **All resources** or **Resource groups** from the left pane.
+[!INCLUDE [clean up resources (paid)](../resource-cleanup-paid.md)]
 
 Otherwise, the following code from `Program.cs` deleted the objects you created in this quickstart.
 

@@ -1385,9 +1385,9 @@ messages.add(userMessage);
 
 ## Clean up resources
 
-When working in your own subscription, it's a good idea to finish a project by determining whether you still need the resources you created. Resources that are left running can cost you money. You can delete resources individually, or you can delete the resource group to delete the entire set of resources.
+[!INCLUDE [clean up resources (paid)](../resource-cleanup-paid.md)]
 
-In the Azure portal, you can find and manage resources by selecting **All resources** or **Resource groups** from the left pane. You can also run the following code to delete the objects you created in this quickstart.
+You can also run the following code to delete the objects you created in this quickstart.
 
 ### Delete the knowledge agent
 

@@ -937,9 +937,7 @@ if (result2.references) {
 
 ## Clean up resources
 
-When you work in your own subscription, it's a good idea to finish a project by determining whether you still need the resources you created. Resources that are left running can cost you money.
-
-In the [Azure portal](https://portal.azure.com/), you can manage your Azure AI Search and Microsoft Foundry resources by selecting **All resources** or **Resource groups** from the left pane.
+[!INCLUDE [clean up resources (paid)](../resource-cleanup-paid.md)]
 
 Otherwise, the following code from `index.js` deleted the objects you created in this quickstart.
 

@@ -30,7 +30,9 @@ Although you can provide your own data, this quickstart uses [sample JSON docume
 
 + The [Azure CLI](/cli/azure/install-azure-cli) for keyless authentication with Microsoft Entra ID.
 
-+ [Visual Studio Code](https://code.visualstudio.com/download) and the latest version of [Python](https://www.python.org/downloads/).
++ The latest version of [Python](https://www.python.org/downloads/).
+
++ [Visual Studio Code](https://code.visualstudio.com/download) with the [Python extension](https://marketplace.visualstudio.com/items?itemName=ms-python.python).
 
 [!INCLUDE [Setup](./agentic-retrieval-setup.md)]
 
@@ -779,9 +781,7 @@ print("references_content:\n", references_content)
 
 ## Clean up resources
 
-When you work in your own subscription, it's a good idea to finish a project by determining whether you still need the resources you created. Resources that are left running can cost you money.
-
-In the [Azure portal](https://portal.azure.com/), you can manage your Azure AI Search and Microsoft Foundry resources by selecting **All resources** or **Resource groups** from the left pane.
+[!INCLUDE [clean up resources (paid)](../resource-cleanup-paid.md)]
 
 Otherwise, the following code from `agentic-retrieval.py` deleted the objects you created in this quickstart.
 

@@ -627,16 +627,10 @@ The output should contain the following components:
 
 ## Clean up resources
 
-When you work in your own subscription, it's a good idea to finish a project by determining whether you still need the resources you created. Resources that are left running can cost you money.
-
-In the [Azure portal](https://portal.azure.com/), you can manage your Azure AI Search and Microsoft Foundry resources by selecting **All resources** or **Resource groups** from the left pane.
+[!INCLUDE [clean up resources (paid)](../resource-cleanup-paid.md)]
 
 Otherwise, the following requests from `agentic-retrieval.rest` deleted the objects you created in this quickstart.
 
-<!-- You can delete resources individually or delete the entire resource group.
-
-In the Azure portal, you can find and manage resources by selecting **All resources** or **Resource groups** from the left pane. -->
-
 ### Delete the knowledge base
 
 ```HTTP

@@ -998,9 +998,7 @@ console.log("\n✅ Quickstart completed successfully!");
 
 ## Clean up resources
 
-When you work in your own subscription, it's a good idea to finish a project by determining whether you still need the resources you created. Resources that are left running can cost you money.
-
-In the [Azure portal](https://portal.azure.com/), you can manage your Azure AI Search and Microsoft Foundry resources by selecting **All resources** or **Resource groups** from the left pane.
+[!INCLUDE [clean up resources (paid)](../resource-cleanup-paid.md)]
 
 Otherwise, the following code from `index.ts` deleted the objects you created in this quickstart.
 

@@ -4,669 +4,193 @@ author: haileytap
 ms.author: haileytapia
 ms.service: azure-ai-search
 ms.topic: include
-ms.date: 11/20/2025
+ms.date: 02/02/2026
 ---
 
-[!INCLUDE [Full text introduction](full-text-intro.md)]
+In this quickstart, you use the [Azure AI Search client library for .NET](/dotnet/api/overview/azure/search) to create, load, and query a search index for [full-text search](../../search-lucene-query-architecture.md), also known as keyword search.
+
+Full-text search uses Apache Lucene for indexing and queries and the BM25 ranking algorithm for scoring results. This quickstart uses fictional hotel data from the [azure-search-sample-data](https://github.com/Azure-Samples/azure-search-sample-data/tree/main/hotels/hotel-json-documents) GitHub repository to populate the index.
 
 > [!TIP]
-> You can download the [source code](https://github.com/Azure-Samples/azure-search-dotnet-samples/tree/main/quickstart-keyword-search) to start with a finished project or follow these steps to create your own.
+> Want to get started right away? Download the [source code](https://github.com/Azure-Samples/azure-search-dotnet-samples/tree/main/quickstart-keyword-search) on GitHub.
 
 ## Prerequisites
 
 - An Azure account with an active subscription. [Create an account for free](https://azure.microsoft.com/pricing/purchase-options/azure-account?cid=msft_learn).
 
-- An Azure AI Search service. [Create a service](../../search-create-service-portal.md) if you don't have one. For this quickstart, you can use a free service.
+- An [Azure AI Search service](../../search-create-service-portal.md). You can use a free service for this quickstart.
 
-## Microsoft Entra ID prerequisites
+- The latest version of the [.NET SDK](https://dotnet.microsoft.com/download).
 
-For the recommended keyless authentication with Microsoft Entra ID, you must:
+- [Visual Studio Code](https://code.visualstudio.com/download).
 
-- Install the [Azure CLI](/cli/azure/install-azure-cli).
+- [Git](https://git-scm.com/downloads) to clone the sample repository.
 
-- Assign the `Search Service Contributor` and `Search Index Data Contributor` roles to your user account. You can assign roles in the Azure portal under **Access control (IAM)** > **Add role assignment**. For more information, see [Connect to Azure AI Search using roles](../../search-security-rbac.md).
+- The [Azure CLI](/cli/azure/install-azure-cli) for keyless authentication with Microsoft Entra ID.
 
-## Get service information
+## Configure access
 
 [!INCLUDE [resource authentication](../resource-authentication.md)]
 
-## Set up
+## Get endpoint
 
-1. Create a new folder `full-text-quickstart` to contain the application and open Visual Studio Code in that folder with the following command:
+[!INCLUDE [resource endpoint](../resource-endpoint.md)]
 
-    ```shell
-    mkdir full-text-quickstart && cd full-text-quickstart
-    ```
+## Set up the environment
 
-1. Create a new console application with the following command:
+1. Use Git to clone the sample repository.
 
-    ```shell
-    dotnet new console
-    ```
+   ```console
+   git clone https://github.com/Azure-Samples/azure-search-dotnet-samples
+   ```
 
-1. Install the Azure AI Search client library ([Azure.Search.Documents](/dotnet/api/overview/azure/search.documents-readme)) for .NET with:
+1. Open the `azure-search-dotnet-samples/quickstart-keyword-search/AzureSearchQuickstart` folder in Visual Studio Code.
 
-    ```console
-    dotnet add package Azure.Search.Documents
-    ```
+1. Open the `Program.cs` file.
 
-1. For the **recommended** keyless authentication with Microsoft Entra ID, install the [Azure.Identity](https://www.nuget.org/packages/Azure.Identity) package with:
+1. Replace the placeholder value for `serviceEndpoint` with the URL you obtained in [Get endpoint](#get-endpoint).
 
-    ```console
-    dotnet add package Azure.Identity
-    ```
+1. Install the dependencies from the `AzureSearchQuickstart.csproj` file.
+
+   ```console
+   dotnet restore
+   ```
 
-1. For the **recommended** keyless authentication with Microsoft Entra ID, sign in to Azure with the following command:
+1. For keyless authentication with Microsoft Entra ID, sign in to your Azure account. If you have multiple subscriptions, select the one that contains your Azure AI Search service.
 
-    ```console
+    ```azurecli
     az login
     ```
 
-## Create, load, and query a search index
+## Run the code
 
-In the prior [set up](#set-up) section, you created a new console application and installed the Azure AI Search client library. 
+Build and run the application.
 
-In this section, you add code to create a search index, load it with documents, and run queries. You run the program to see the results in the console. For a detailed explanation of the code, see the [Explaining the code](#explaining-the-code) section.
+```console
+dotnet run
+```
 
-The sample code in this quickstart uses Microsoft Entra ID for the recommended keyless authentication. If you prefer to use an API key, you can replace the `DefaultAzureCredential` object with a `AzureKeyCredential` object. 
+### Output
 
-#### [Microsoft Entra ID](#tab/keyless)
+The output should be similar to the following:
 
-```csharp
-Uri serviceEndpoint = new Uri($"https://<Put your search service NAME here>.search.windows.net/");
-DefaultAzureCredential credential = new();
 ```
+Deleting index...
 
-#### [API key](#tab/api-key)
+Creating index...
 
-```csharp
-Uri serviceEndpoint = new Uri($"https://<Put your search service NAME here>.search.windows.net/");
-AzureKeyCredential credential = new AzureKeyCredential("<Your search service admin key>");
-```
----
+Uploading documents...
 
-1. In *Program.cs*, paste the following code. Edit the `serviceName` and `apiKey` variables with your search service name and admin API key.
+Waiting for indexing...
 
-    ```csharp
-    using System;
-    using Azure;
-    using Azure.Identity;
-    using Azure.Search.Documents;
-    using Azure.Search.Documents.Indexes;
-    using Azure.Search.Documents.Indexes.Models;
-    using Azure.Search.Documents.Models;
-    
-    namespace AzureSearch.Quickstart
-    
-    {
-        class Program
-        {
-            static void Main(string[] args)
-            {    
-                // Your search service endpoint
-                Uri serviceEndpoint = new Uri($"https://<Put your search service NAME here>.search.windows.net/");
-    
-                // Use the recommended keyless credential instead of the AzureKeyCredential credential.
-                DefaultAzureCredential credential = new();
-                //AzureKeyCredential credential = new AzureKeyCredential("Your search service admin key");
-    
-                // Create a SearchIndexClient to send create/delete index commands
-                SearchIndexClient searchIndexClient = new SearchIndexClient(serviceEndpoint, credential);
-    
-                // Create a SearchClient to load and query documents
-                string indexName = "hotels-quickstart";
-                SearchClient searchClient = new SearchClient(serviceEndpoint, indexName, credential);
-    
-                // Delete index if it exists
-                Console.WriteLine("{0}", "Deleting index...\n");
-                DeleteIndexIfExists(indexName, searchIndexClient);
-    
-                // Create index
-                Console.WriteLine("{0}", "Creating index...\n");
-                CreateIndex(indexName, searchIndexClient);
-    
-                SearchClient ingesterClient = searchIndexClient.GetSearchClient(indexName);
-    
-                // Load documents
-                Console.WriteLine("{0}", "Uploading documents...\n");
-                UploadDocuments(ingesterClient);
-    
-                // Wait 2 secondsfor indexing to complete before starting queries (for demo and console-app purposes only)
-                Console.WriteLine("Waiting for indexing...\n");
-                System.Threading.Thread.Sleep(2000);
-    
-                // Call the RunQueries method to invoke a series of queries
-                Console.WriteLine("Starting queries...\n");
-                RunQueries(searchClient);
-    
-                // End the program
-                Console.WriteLine("{0}", "Complete. Press any key to end this program...\n");
-                Console.ReadKey();
-            }
-    
-            // Delete the hotels-quickstart index to reuse its name
-            private static void DeleteIndexIfExists(string indexName, SearchIndexClient searchIndexClient)
-            {
-                searchIndexClient.GetIndexNames();
-                {
-                    searchIndexClient.DeleteIndex(indexName);
-                }
-            }
-            // Create hotels-quickstart index
-            private static void CreateIndex(string indexName, SearchIndexClient searchIndexClient)
-            {
-                FieldBuilder fieldBuilder = new FieldBuilder();
-                var searchFields = fieldBuilder.Build(typeof(Hotel));
-    
-                var definition = new SearchIndex(indexName, searchFields);
-    
-                var suggester = new SearchSuggester("sg", new[] { "HotelName", "Category", "Address/City", "Address/StateProvince" });
-                definition.Suggesters.Add(suggester);
-    
-                searchIndexClient.CreateOrUpdateIndex(definition);
-            }
-    
-            // Upload documents in a single Upload request.
-            private static void UploadDocuments(SearchClient searchClient)
-            {
-                IndexDocumentsBatch<Hotel> batch = IndexDocumentsBatch.Create(
-                    IndexDocumentsAction.Upload(
-                        new Hotel()
-                        {
-                            HotelId = "1",
-                            HotelName = "Stay-Kay City Hotel",
-                            Description = "This classic hotel is fully-refurbished and ideally located on the main commercial artery of the city in the heart of New York. A few minutes away is Times Square and the historic centre of the city, as well as other places of interest that make New York one of America's most attractive and cosmopolitan cities.",
-                            Category = "Boutique",
-                            Tags = new[] { "view", "air conditioning", "concierge" },
-                            ParkingIncluded = false,
-                            LastRenovationDate = new DateTimeOffset(2022, 1, 18, 0, 0, 0, TimeSpan.Zero),
-                            Rating = 3.6,
-                            Address = new Address()
-                            {
-                                StreetAddress = "677 5th Ave",
-                                City = "New York",
-                                StateProvince = "NY",
-                                PostalCode = "10022",
-                                Country = "USA"
-                            }
-                        }),
-                    IndexDocumentsAction.Upload(
-                        new Hotel()
-                        {
-                            HotelId = "2",
-                            HotelName = "Old Century Hotel",
-                            Description = "The hotel is situated in a nineteenth century plaza, which has been expanded and renovated to the highest architectural standards to create a modern, functional and first-class hotel in which art and unique historical elements coexist with the most modern comforts. The hotel also regularly hosts events like wine tastings, beer dinners, and live music.",
-                            Category = "Boutique",
-                            Tags = new[] { "pool", "free wifi", "concierge" },
-                            ParkingIncluded = false,
-                            LastRenovationDate = new DateTimeOffset(2019, 2, 18, 0, 0, 0, TimeSpan.Zero),
-                            Rating = 3.60,
-                            Address = new Address()
-                            {
-                                StreetAddress = "140 University Town Center Dr",
-                                City = "Sarasota",
-                                StateProvince = "FL",
-                                PostalCode = "34243",
-                                Country = "USA"
-                            }
-                        }),
-                    IndexDocumentsAction.Upload(
-                        new Hotel()
-                        {
-                            HotelId = "3",
-                            HotelName = "Gastronomic Landscape Hotel",
-                            Description = "The Gastronomic Hotel stands out for its culinary excellence under the management of William Dough, who advises on and oversees all of the Hotel’s restaurant services.",
-                            Category = "Suite",
-                            Tags = new[] { "restaurant", "bar", "continental breakfast" },
-                            ParkingIncluded = true,
-                            LastRenovationDate = new DateTimeOffset(2015, 9, 20, 0, 0, 0, TimeSpan.Zero),
-                            Rating = 4.80,
-                            Address = new Address()
-                            {
-                                StreetAddress = "3393 Peachtree Rd",
-                                City = "Atlanta",
-                                StateProvince = "GA",
-                                PostalCode = "30326",
-                                Country = "USA"
-                            }
-                        }),
-                    IndexDocumentsAction.Upload(
-                        new Hotel()
-                        {
-                            HotelId = "4",
-                            HotelName = "Sublime Palace Hotel",
-                            Description = "Sublime Palace Hotel is located in the heart of the historic center of Sublime in an extremely vibrant and lively area within short walking distance to the sites and landmarks of the city and is surrounded by the extraordinary beauty of churches, buildings, shops and monuments. Sublime Cliff is part of a lovingly restored 19th century resort, updated for every modern convenience.",
-                            Category = "Boutique",
-                            Tags = new[] { "concierge", "view", "air conditioning" },
-                            ParkingIncluded = true,
-                            LastRenovationDate = new DateTimeOffset(2020, 2, 06, 0, 0, 0, TimeSpan.Zero),
-                            Rating = 4.60,
-                            Address = new Address()
-                            {
-                                StreetAddress = "7400 San Pedro Ave",
-                                City = "San Antonio",
-                                StateProvince = "TX",
-                                PostalCode = "78216",
-                                Country = "USA"
-                            }
-                        })
-                    );
-    
-                try
-                {
-                    IndexDocumentsResult result = searchClient.IndexDocuments(batch);
-                }
-                catch (Exception)
-                {
-                    // If for some reason any documents are dropped during indexing, you can compensate by delaying and
-                    // retrying. This simple demo just logs the failed document keys and continues.
-                    Console.WriteLine("Failed to index some of the documents: {0}");
-                }
-            }
-    
-            // Run queries, use WriteDocuments to print output
-            private static void RunQueries(SearchClient searchClient)
-            {
-                SearchOptions options;
-                SearchResults<Hotel> response;
-    
-                // Query 1
-                Console.WriteLine("Query #1: Search on empty term '*' to return all documents, showing a subset of fields...\n");
-    
-                options = new SearchOptions()
-                {
-                    IncludeTotalCount = true,
-                    Filter = "",
-                    OrderBy = { "" }
-                };
-    
-                options.Select.Add("HotelId");
-                options.Select.Add("HotelName");
-                options.Select.Add("Rating");
-    
-                response = searchClient.Search<Hotel>("*", options);
-                WriteDocuments(response);
-    
-                // Query 2
-                Console.WriteLine("Query #2: Search on 'hotels', filter on 'Rating gt 4', sort by Rating in descending order...\n");
-    
-                options = new SearchOptions()
-                {
-                    Filter = "Rating gt 4",
-                    OrderBy = { "Rating desc" }
-                };
-    
-                options.Select.Add("HotelId");
-                options.Select.Add("HotelName");
-                options.Select.Add("Rating");
-    
-                response = searchClient.Search<Hotel>("hotels", options);
-                WriteDocuments(response);
-    
-                // Query 3
-                Console.WriteLine("Query #3: Limit search to specific fields (pool in Tags field)...\n");
-    
-                options = new SearchOptions()
-                {
-                    SearchFields = { "Tags" }
-                };
-    
-                options.Select.Add("HotelId");
-                options.Select.Add("HotelName");
-                options.Select.Add("Tags");
-    
-                response = searchClient.Search<Hotel>("pool", options);
-                WriteDocuments(response);
-    
-                // Query 4 - Use Facets to return a faceted navigation structure for a given query
-                // Filters are typically used with facets to narrow results on OnClick events
-                Console.WriteLine("Query #4: Facet on 'Category'...\n");
-    
-                options = new SearchOptions()
-                {
-                    Filter = ""
-                };
-    
-                options.Facets.Add("Category");
-    
-                options.Select.Add("HotelId");
-                options.Select.Add("HotelName");
-                options.Select.Add("Category");
-    
-                response = searchClient.Search<Hotel>("*", options);
-                WriteDocuments(response);
-    
-                // Query 5
-                Console.WriteLine("Query #5: Look up a specific document...\n");
-    
-                Response<Hotel> lookupResponse;
-                lookupResponse = searchClient.GetDocument<Hotel>("3");
-    
-                Console.WriteLine(lookupResponse.Value.HotelId);
-    
-    
-                // Query 6
-                Console.WriteLine("Query #6: Call Autocomplete on HotelName...\n");
-    
-                var autoresponse = searchClient.Autocomplete("sa", "sg");
-                WriteDocuments(autoresponse);
-    
-            }
-    
-            // Write search results to console
-            private static void WriteDocuments(SearchResults<Hotel> searchResults)
-            {
-                foreach (SearchResult<Hotel> result in searchResults.GetResults())
-                {
-                    Console.WriteLine(result.Document);
-                }
-    
-                Console.WriteLine();
-            }
-    
-            private static void WriteDocuments(AutocompleteResults autoResults)
-            {
-                foreach (AutocompleteItem result in autoResults.Results)
-                {
-                    Console.WriteLine(result.Text);
-                }
-    
-                Console.WriteLine();
-            }
-        }
-    }
-    ```
+Starting queries...
 
-1. In the same folder, create a new file named *Hotel.cs* and paste the following code. This code defines the structure of a hotel document. 
+Query #1: Search on empty term '*' to return all documents, showing a subset of fields...
 
-    ```csharp
-    using System;
-    using System.Text.Json.Serialization;
-    using Azure.Search.Documents.Indexes;
-    using Azure.Search.Documents.Indexes.Models;
-    
-    namespace AzureSearch.Quickstart
-    {
-        public partial class Hotel
-        {
-            [SimpleField(IsKey = true, IsFilterable = true)]
-            public string HotelId { get; set; }
-    
-            [SearchableField(IsSortable = true)]
-            public string HotelName { get; set; }
-    
-            [SearchableField(AnalyzerName = LexicalAnalyzerName.Values.EnLucene)]
-            public string Description { get; set; }
-    
-            [SearchableField(IsFilterable = true, IsSortable = true, IsFacetable = true)]
-            public string Category { get; set; }
-    
-            [SearchableField(IsFilterable = true, IsFacetable = true)]
-            public string[] Tags { get; set; }
-    
-            [SimpleField(IsFilterable = true, IsSortable = true, IsFacetable = true)]
-            public bool? ParkingIncluded { get; set; }
-    
-            [SimpleField(IsFilterable = true, IsSortable = true, IsFacetable = true)]
-            public DateTimeOffset? LastRenovationDate { get; set; }
-    
-            [SimpleField(IsFilterable = true, IsSortable = true, IsFacetable = true)]
-            public double? Rating { get; set; }
-    
-            [SearchableField]
-            public Address Address { get; set; }
-        }
-    }
-    ```
+HotelId: 3
+Name: Gastronomic Landscape Hotel
+Rating: 4.8
 
-1. Create a new file named *Hotel.cs* and paste the following code to define the structure of a hotel document. Attributes on the field determine how it's used in an application. For example, the `IsFilterable` attribute must be assigned to every field that supports a filter expression.
+HotelId: 2
+Name: Old Century Hotel
+Rating: 3.6
 
-    ```csharp
-    using System;
-    using System.Text.Json.Serialization;
-    using Azure.Search.Documents.Indexes;
-    using Azure.Search.Documents.Indexes.Models;
-    
-    namespace AzureSearch.Quickstart
-    {
-        public partial class Hotel
-        {
-            [SimpleField(IsKey = true, IsFilterable = true)]
-            public string HotelId { get; set; }
-    
-            [SearchableField(IsSortable = true)]
-            public string HotelName { get; set; }
-    
-            [SearchableField(AnalyzerName = LexicalAnalyzerName.Values.EnLucene)]
-            public string Description { get; set; }
-    
-            [SearchableField(IsFilterable = true, IsSortable = true, IsFacetable = true)]
-            public string Category { get; set; }
-    
-            [SearchableField(IsFilterable = true, IsFacetable = true)]
-            public string[] Tags { get; set; }
-    
-            [SimpleField(IsFilterable = true, IsSortable = true, IsFacetable = true)]
-            public bool? ParkingIncluded { get; set; }
-    
-            [SimpleField(IsFilterable = true, IsSortable = true, IsFacetable = true)]
-            public DateTimeOffset? LastRenovationDate { get; set; }
-    
-            [SimpleField(IsFilterable = true, IsSortable = true, IsFacetable = true)]
-            public double? Rating { get; set; }
-    
-            [SearchableField]
-            public Address Address { get; set; }
-        }
-    }
-    ```
+HotelId: 4
+Name: Sublime Palace Hotel
+Rating: 4.6
 
-1. Create a new file named *Address.cs* and paste the following code to define the structure of an address document.
+HotelId: 1
+Name: Stay-Kay City Hotel
+Rating: 3.6
 
-    ```csharp
-    using Azure.Search.Documents.Indexes;
-    
-    namespace AzureSearch.Quickstart
-    {
-        public partial class Address
-        {
-            [SearchableField(IsFilterable = true)]
-            public string StreetAddress { get; set; }
-    
-            [SearchableField(IsFilterable = true, IsSortable = true, IsFacetable = true)]
-            public string City { get; set; }
-    
-            [SearchableField(IsFilterable = true, IsSortable = true, IsFacetable = true)]
-            public string StateProvince { get; set; }
-    
-            [SearchableField(IsFilterable = true, IsSortable = true, IsFacetable = true)]
-            public string PostalCode { get; set; }
-    
-            [SearchableField(IsFilterable = true, IsSortable = true, IsFacetable = true)]
-            public string Country { get; set; }
-        }
-    }
-    ```
 
-1. Create a new file named *Hotel.Methods.cs* and paste the following code to define a `ToString()` override for the `Hotel` class. 
+Query #2: Search on 'hotels', filter on 'Rating gt 4', sort by Rating in descending order...
 
-    ```csharp
-    using System;
-    using System.Text;
-    
-    namespace AzureSearch.Quickstart
-    {
-        public partial class Hotel
-        {
-            public override string ToString()
-            {
-                var builder = new StringBuilder();
-    
-                if (!String.IsNullOrEmpty(HotelId))
-                {
-                    builder.AppendFormat("HotelId: {0}\n", HotelId);
-                }
-    
-                if (!String.IsNullOrEmpty(HotelName))
-                {
-                    builder.AppendFormat("Name: {0}\n", HotelName);
-                }
-    
-                if (!String.IsNullOrEmpty(Description))
-                {
-                    builder.AppendFormat("Description: {0}\n", Description);
-                }
-    
-                if (!String.IsNullOrEmpty(Category))
-                {
-                    builder.AppendFormat("Category: {0}\n", Category);
-                }
-    
-                if (Tags != null && Tags.Length > 0)
-                {
-                    builder.AppendFormat("Tags: [ {0} ]\n", String.Join(", ", Tags));
-                }
-    
-                if (ParkingIncluded.HasValue)
-                {
-                    builder.AppendFormat("Parking included: {0}\n", ParkingIncluded.Value ? "yes" : "no");
-                }
-    
-                if (LastRenovationDate.HasValue)
-                {
-                    builder.AppendFormat("Last renovated on: {0}\n", LastRenovationDate);
-                }
-    
-                if (Rating.HasValue)
-                {
-                    builder.AppendFormat("Rating: {0}\n", Rating);
-                }
-    
-                if (Address != null && !Address.IsEmpty)
-                {
-                    builder.AppendFormat("Address: \n{0}\n", Address.ToString());
-                }
-    
-                return builder.ToString();
-            }
-        }
-    }
-    ```
+HotelId: 3
+Name: Gastronomic Landscape Hotel
+Rating: 4.8
 
-1. Create a new file named *Address.Methods.cs* and paste the following code to define a `ToString()` override for the `Address` class.
+HotelId: 4
+Name: Sublime Palace Hotel
+Rating: 4.6
 
-    ```csharp
-    using System;
-    using System.Text;
-    using System.Text.Json.Serialization;
-    
-    namespace AzureSearch.Quickstart
-    {
-        public partial class Address
-        {
-            public override string ToString()
-            {
-                var builder = new StringBuilder();
-    
-                if (!IsEmpty)
-                {
-                    builder.AppendFormat("{0}\n{1}, {2} {3}\n{4}", StreetAddress, City, StateProvince, PostalCode, Country);
-                }
-    
-                return builder.ToString();
-            }
-    
-            [JsonIgnore]
-            public bool IsEmpty => String.IsNullOrEmpty(StreetAddress) &&
-                                   String.IsNullOrEmpty(City) &&
-                                   String.IsNullOrEmpty(StateProvince) &&
-                                   String.IsNullOrEmpty(PostalCode) &&
-                                   String.IsNullOrEmpty(Country);
-        }
-    }
-    ```
 
-1. Build and run the application with the following command:
+Query #3: Limit search to specific fields (pool in Tags field)...
 
-    ```shell
-    dotnet run
-    ```
+HotelId: 2
+Name: Old Century Hotel
+Tags: [ pool, free wifi, concierge ]
 
-Output includes messages from [Console.WriteLine](/dotnet/api/system.console.writeline), with the addition of query information and results.
 
-## Explaining the code
+Query #4: Facet on 'Category'...
 
-In the previous sections, you created a new console application and installed the Azure AI Search client library. You added code to create a search index, load it with documents, and run queries. You ran the program to see the results in the console. 
+HotelId: 3
+Name: Gastronomic Landscape Hotel
+Category: Suite
 
-In this section, we explain the code you added to the console application.
+HotelId: 2
+Name: Old Century Hotel
+Category: Boutique
 
-### Create a search client
+HotelId: 4
+Name: Sublime Palace Hotel
+Category: Boutique
 
-In *Program.cs*, you created two clients:
-- [SearchIndexClient](/dotnet/api/azure.search.documents.indexes.searchindexclient) creates the index.
-- [SearchClient](/dotnet/api/azure.search.documents.searchclient) loads and queries an existing index. 
+HotelId: 1
+Name: Stay-Kay City Hotel
+Category: Boutique
 
-Both clients need the search service endpoint and credentials described previously in the [Get service information](#get-service-information) section.
 
-The sample code in this quickstart uses Microsoft Entra ID for the recommended keyless authentication. If you prefer to use an API key, you can replace the `DefaultAzureCredential` object with a `AzureKeyCredential` object. 
+Query #5: Look up a specific document...
 
-#### [Microsoft Entra ID](#tab/keyless)
+3
+Query #6: Call Autocomplete on HotelName...
 
-```csharp
-Uri serviceEndpoint = new Uri($"https://<Put your search service NAME here>.search.windows.net/");
-DefaultAzureCredential credential = new();
+san
+sarasota
+
+Complete. Press any key to end this program...
 ```
 
-#### [API key](#tab/api-key)
+## Understand the code
 
-```csharp
-Uri serviceEndpoint = new Uri($"https://<Put your search service NAME here>.search.windows.net/");
-AzureKeyCredential credential = new AzureKeyCredential("<Your search service admin key>");
-```
----
+Now that you've run the code, let's break down the key steps:
 
-```csharp
-static void Main(string[] args)
-{
-    // Your search service endpoint
-    Uri serviceEndpoint = new Uri($"https://<Put your search service NAME here>.search.windows.net/");
+1. [Create a search client](#create-a-search-client)
+1. [Create a search index](#create-a-search-index)
+1. [Upload documents to the index](#upload-documents-to-the-index)
+1. [Query the index](#query-the-index)
 
-    // Use the recommended keyless credential instead of the AzureKeyCredential credential.
-    DefaultAzureCredential credential = new();
-    //AzureKeyCredential credential = new AzureKeyCredential("Your search service admin key");
+### Create a search client
 
-    // Create a SearchIndexClient to send create/delete index commands
-    SearchIndexClient searchIndexClient = new SearchIndexClient(serviceEndpoint, credential);
+In `Program.cs`, you create two clients:
 
-    // Create a SearchClient to load and query documents
-    string indexName = "hotels-quickstart";
-    SearchClient searchClient = new SearchClient(serviceEndpoint, indexName, credential);
-    
-    // REDACTED FOR BREVITY . . . 
-}
-```
+- [SearchIndexClient](/dotnet/api/azure.search.documents.indexes.searchindexclient) creates the index.
+- [SearchClient](/dotnet/api/azure.search.documents.searchclient) loads and queries an existing index.
 
-### Create an index
+Both clients require the service endpoint and a credential for authentication. In this quickstart, you use [DefaultAzureCredential](/dotnet/api/azure.identity.defaultazurecredential) for keyless authentication with Microsoft Entra ID.
 
-This quickstart builds a Hotels index that you load with hotel data and execute queries against. In this step, you define the fields in the index. Each field definition includes a name, data type, and attributes that determine how the field is used.
+### Create a search index
 
-In this example, synchronous methods of the *Azure.Search.Documents* library are used for simplicity and readability. However, for production scenarios, you should use asynchronous methods to keep your app scalable and responsive. For example, you would use [CreateIndexAsync](/dotnet/api/azure.search.documents.indexes.searchindexclient.createindexasync) instead of [CreateIndex](/dotnet/api/azure.search.documents.indexes.searchindexclient.createindex).
+This quickstart builds a hotels index that you load with hotel data and execute queries against. In this step, you define the fields in the index. Each field definition includes a name, data type, and attributes that determine how the field is used.
+
+This example uses synchronous methods of the [SearchIndexClient](/dotnet/api/azure.search.documents.indexes.searchindexclient) class for simplicity and readability. However, for production scenarios, use asynchronous methods to keep your app scalable and responsive. For example, use [CreateIndexAsync](/dotnet/api/azure.search.documents.indexes.searchindexclient.createindexasync) instead of [CreateIndex](/dotnet/api/azure.search.documents.indexes.searchindexclient.createindex).
 
 #### Define the structures
 
-You created two helper classes, *Hotel.cs* and *Address.cs*, to define the structure of a hotel document and its address. The `Hotel` class includes fields for a hotel ID, name, description, category, tags, parking, renovation date, rating, and address. The `Address` class includes fields for street address, city, state/province, postal code, and country/region.
+You create two helper classes, `Hotel.cs` and `Address.cs`, to define the structure of a hotel document and its address. The `Hotel` class includes fields for a hotel ID, name, description, category, tags, parking, renovation date, rating, and address. The `Address` class includes fields for street address, city, state/province, postal code, and country/region.
 
-In the *Azure.Search.Documents* client library, you can use [SearchableField](/dotnet/api/azure.search.documents.indexes.models.searchablefield) and [SimpleField](/dotnet/api/azure.search.documents.indexes.models.simplefield) to streamline field definitions. Both are derivatives of a [SearchField](/dotnet/api/azure.search.documents.indexes.models.searchfield) and can potentially simplify your code:
+In the Azure.Search.Documents client library, you can use [SearchableField](/dotnet/api/azure.search.documents.indexes.models.searchablefield) and [SimpleField](/dotnet/api/azure.search.documents.indexes.models.simplefield) to streamline field definitions. Both are helper classes that generate a [SearchField](/dotnet/api/azure.search.documents.indexes.models.searchfield) and can potentially simplify your code:
 
-+ `SimpleField` can be any data type, is always non-searchable (ignored for full text search queries), and is retrievable (not hidden). Other attributes are off by default, but can be enabled. You might use a `SimpleField` for document IDs or fields used only in filters, facets, or scoring profiles. If so, be sure to apply any attributes that are necessary for the scenario, such as `IsKey = true` for a document ID. For more information, see [SimpleFieldAttribute.cs](https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/search/Azure.Search.Documents/src/Indexes/SimpleFieldAttribute.cs) in source code.
++ `SimpleField` can be any data type, is always nonsearchable (ignored for full-text search queries), and is retrievable (not hidden). Other attributes are off by default, but can be enabled. You might use a `SimpleField` for document IDs or fields used only in filters, facets, or scoring profiles. If so, apply any attributes that are necessary for the scenario, such as `IsKey = true` for a document ID.
 
-+ `SearchableField` must be a string, and is always searchable and retrievable. Other attributes are off by default, but can be enabled. Because this field type is searchable, it supports synonyms and the full complement of analyzer properties. For more information, see the [SearchableFieldAttribute.cs](https://github.com/Azure/azure-sdk-for-net/blob/main/sdk/search/Azure.Search.Documents/src/Indexes/SearchableFieldAttribute.cs) in source code.
++ `SearchableField` must be a string, and is always searchable and retrievable. Other attributes are off by default, but can be enabled. Because this field type is searchable, it supports synonyms and the full complement of analyzer properties.
 
 Whether you use the basic `SearchField` API or either one of the helper models, you must explicitly enable filter, facet, and sort attributes. For example, [IsFilterable](/dotnet/api/azure.search.documents.indexes.models.searchfield.isfilterable), [IsSortable](/dotnet/api/azure.search.documents.indexes.models.searchfield.issortable), and [IsFacetable](/dotnet/api/azure.search.documents.indexes.models.searchfield.isfacetable) must be explicitly attributed, as shown in the previous sample.
 
 #### Create the search index
 
-In *Program.cs*, you create a [SearchIndex](/dotnet/api/azure.search.documents.indexes.models.searchindex) object, and then call the [CreateIndex](/dotnet/api/azure.search.documents.indexes.searchindexclient.createindex) method to express the index in your search service. The index also includes a [SearchSuggester](/dotnet/api/azure.search.documents.indexes.models.searchsuggester) to enable autocomplete on the specified fields.
+In `Program.cs`, you create a [SearchIndex](/dotnet/api/azure.search.documents.indexes.models.searchindex) object, and then call the [CreateOrUpdateIndex](/dotnet/api/azure.search.documents.indexes.searchindexclient.createorupdateindex) method to express the index in your search service. The index also includes a [SearchSuggester](/dotnet/api/azure.search.documents.indexes.models.searchsuggester) to enable autocomplete on the specified fields.
 
 ```csharp
 // Create hotels-quickstart index
@@ -684,15 +208,15 @@ private static void CreateIndex(string indexName, SearchIndexClient searchIndexC
 }
 ```
 
-### Load documents
+### Upload documents to the index
 
 Azure AI Search searches over content stored in the service. In this step, you load JSON documents that conform to the hotel index you created.
 
-In Azure AI Search, search documents are data structures that are both inputs to indexing and outputs from queries. As obtained from an external data source, document inputs might be rows in a database, blobs in Blob storage, or JSON documents on disk. In this example, we're taking a shortcut and embedding JSON documents for four hotels in the code itself.
+In Azure AI Search, search documents are data structures that are both inputs to indexing and outputs from queries. As obtained from an external data source, document inputs might be rows in a database, blobs in Azure Blob Storage, or JSON documents on disk. In this example, you take a shortcut and embed JSON documents for four hotels directly.
 
 When uploading documents, you must use an [IndexDocumentsBatch](/dotnet/api/azure.search.documents.models.indexdocumentsbatch-1) object. An `IndexDocumentsBatch` object contains a collection of [Actions](/dotnet/api/azure.search.documents.models.indexdocumentsbatch-1.actions), each of which contains a document and a property telling Azure AI Search what action to perform ([upload, merge, delete, and mergeOrUpload](/azure/search/search-what-is-data-import#indexing-actions)).
 
-In *Program.cs*, you create an array of documents and index actions, and then pass the array to `IndexDocumentsBatch`. The following documents conform to the hotels-quickstart index, as defined by the hotel class.
+In `Program.cs`, you create an array of documents and index actions, and then pass the array to `IndexDocumentsBatch`. The following documents conform to the hotels-quickstart index, as defined by the hotel class.
 
 ```csharp
 // Upload documents in a single Upload request.
@@ -723,9 +247,7 @@ private static void UploadDocuments(SearchClient searchClient)
 }
 ```
 
-Once you initialize the [IndexDocumentsBatch](/dotnet/api/azure.search.documents.models.indexdocumentsbatch-1) object, you can send it to the index by calling [IndexDocuments](/dotnet/api/azure.search.documents.searchclient.indexdocuments) on your [SearchClient](/dotnet/api/azure.search.documents.searchclient) object.
-
-You load documents using SearchClient in `Main()`, but the operation also requires admin rights on the service, which is typically associated with SearchIndexClient. One way to set up this operation is to get SearchClient through `SearchIndexClient` (`searchIndexClient` in this example).
+The `UploadDocuments` method creates an [IndexDocumentsBatch](/dotnet/api/azure.search.documents.models.indexdocumentsbatch-1) and calls [IndexDocuments](/dotnet/api/azure.search.documents.searchclient.indexdocuments) on a [SearchClient](/dotnet/api/azure.search.documents.searchclient) to upload the documents. This quickstart obtains `SearchClient` from `SearchIndexClient` using [GetSearchClient](/dotnet/api/azure.search.documents.indexes.searchindexclient.getsearchclient), which reuses the same credentials.
 
 ```csharp
 SearchClient ingesterClient = searchIndexClient.GetSearchClient(indexName);
@@ -735,25 +257,25 @@ Console.WriteLine("{0}", "Uploading documents...\n");
 UploadDocuments(ingesterClient);
 ```
 
-Because we have a console app that runs all commands sequentially, we add a 2-second wait time between indexing and queries.
+Because this console app runs all commands sequentially, the code adds a two-second wait time between indexing and queries.
 
 ```csharp
 // Wait 2 seconds for indexing to complete before starting queries (for demo and console-app purposes only)
 Console.WriteLine("Waiting for indexing...\n");
 System.Threading.Thread.Sleep(2000);
 ```
 
-The 2-second delay compensates for indexing, which is asynchronous, so that all documents can be indexed before the queries are executed. Coding in a delay is typically only necessary in demos, tests, and sample applications.
+The two-second delay compensates for indexing, which is asynchronous, so that all documents can be indexed before the queries are executed. Coding in a delay is typically only necessary in demos, tests, and sample applications.
 
-### Search an index
+### Query the index
 
 You can get query results as soon as the first document is indexed, but actual testing of your index should wait until all documents are indexed.
 
-This section adds two pieces of functionality: query logic, and results. For queries, use the [Search](/dotnet/api/azure.search.documents.searchclient.search) method. This method takes search text (the query string) and other [options](/dotnet/api/azure.search.documents.searchoptions).
+This section adds two pieces of functionality: query logic and results. For queries, use the [Search](/dotnet/api/azure.search.documents.searchclient.search) method. This method takes search text (the query string) and other [options](/dotnet/api/azure.search.documents.searchoptions).
 
 The [SearchResults](/dotnet/api/azure.search.documents.models.searchresults-1) class represents the results.
 
-In *Program.cs*, the `WriteDocuments` method prints search results to the console.
+In `Program.cs`, the `WriteDocuments` method prints search results to the console.
 
 ```csharp
 // Write search results to console
@@ -801,7 +323,7 @@ private static void RunQueries(SearchClient searchClient)
 
     options.Select.Add("HotelId");
     options.Select.Add("HotelName");
-    options.Select.Add("Address/City");
+    options.Select.Add("Rating");
 
     response = searchClient.Search<Hotel>("*", options);
     WriteDocuments(response);
@@ -811,7 +333,7 @@ private static void RunQueries(SearchClient searchClient)
 
 #### Query example 2
 
-In the second query, search on a term, add a filter that selects documents where *Rating* is greater than 4, and then sort by Rating in descending order. Filter is a boolean expression that is evaluated over [IsFilterable](/dotnet/api/azure.search.documents.indexes.models.searchfield.isfilterable) fields in an index. Filter queries either include or exclude values. As such, there's no relevance score associated with a filter query.
+In the second query, search on a term, add a filter that selects documents where `Rating` is greater than 4, and then sort by `Rating` in descending order. A filter is a boolean expression evaluated over [IsFilterable](/dotnet/api/azure.search.documents.indexes.models.searchfield.isfilterable) fields in an index. Filter queries either include or exclude values. As such, there's no relevance score associated with a filter query.
 
 ```csharp
 // Query 2
@@ -833,7 +355,7 @@ WriteDocuments(response);
 
 #### Query example 3
 
-The third query demonstrates `searchFields`, used to scope a full text search operation to specific fields.
+The third query demonstrates `searchFields`, used to scope a full-text search operation to specific fields.
 
 ```csharp
 // Query 3
@@ -877,7 +399,7 @@ WriteDocuments(response);
 
 #### Query example 5
 
-In the fifth query, return a specific document. A document lookup is a typical response to `OnClick` event in a result set.
+In the fifth query, return a specific document. A document lookup is a typical response to an `OnClick` event in a result set.
 
 ```csharp
 // Query 5
@@ -891,11 +413,11 @@ Console.WriteLine(lookupResponse.Value.HotelId);
 
 #### Query example 6
 
-The last query shows the syntax for autocomplete, simulating a partial user input of *sa* that resolves to two possible matches in the sourceFields associated with the suggester you defined in the index.
+The last query shows the syntax for autocomplete, simulating a partial user input of *sa* that resolves to two possible matches in the `sourceFields` associated with the suggester you defined in the index.
 
 ```csharp
 // Query 6
-Console.WriteLine("Query #6: Call Autocomplete on HotelName that starts with 'sa'...\n");
+Console.WriteLine("Query #6: Call Autocomplete on HotelName...\n");
 
 var autoresponse = searchClient.Autocomplete("sa", "sg");
 WriteDocuments(autoresponse);
@@ -905,5 +427,5 @@ WriteDocuments(autoresponse);
 
 The previous queries show multiple [ways of matching terms in a query](/azure/search/search-query-overview#types-of-queries): full-text search, filters, and autocomplete.
 
-Full text search and filters are performed using the [SearchClient.Search](/dotnet/api/azure.search.documents.searchclient.search) method. A search query can be passed in the `searchText` string, while a filter expression can be passed in the [Filter](/dotnet/api/azure.search.documents.searchoptions.filter) property of the [SearchOptions](/dotnet/api/azure.search.documents.searchoptions) class. To filter without searching, just pass `"*"` for the `searchText` parameter of the [Search](/dotnet/api/azure.search.documents.searchclient.search) method. To search without filtering, leave the `Filter` property unset, or don't pass in a `SearchOptions` instance at all.
+The [SearchClient.Search](/dotnet/api/azure.search.documents.searchclient.search) method performs full-text search and filters. You can pass a search query in the `searchText` string, while you pass a filter expression in the [Filter](/dotnet/api/azure.search.documents.searchoptions.filter) property of the [SearchOptions](/dotnet/api/azure.search.documents.searchoptions) class. To filter without searching, just pass `"*"` for the `searchText` parameter of the [Search](/dotnet/api/azure.search.documents.searchclient.search) method. To search without filtering, leave the `Filter` property unset, or don't pass in a `SearchOptions` instance at all.
 

@@ -1,12 +0,0 @@
----
-manager: nitinme
-author: haileytap
-ms.author: haileytapia
-ms.service: azure-ai-search
-ms.topic: include
-ms.date: 06/26/2025
----
-
-In this quickstart, you use the Azure.Search.Documents client library to create, load, and query a search index with sample data for [full-text search](../../search-lucene-query-architecture.md). Full-text search uses Apache Lucene for indexing and queries and the BM25 ranking algorithm for scoring results.
-
-This quickstart uses fictional hotel data from the [azure-search-sample-data](https://github.com/Azure-Samples/azure-search-sample-data/tree/main/hotels/hotel-json-documents) repo to populate the index.
\ No newline at end of file

@@ -4,604 +4,155 @@ author: haileytap
 ms.author: haileytapia
 ms.service: azure-ai-search
 ms.topic: include
-ms.date: 11/20/2025
+ms.date: 02/02/2026
 ---
 
-[!INCLUDE [Full text introduction](full-text-intro.md)]
+In this quickstart, you use the [Azure AI Search client library for Java](/java/api/overview/azure/search-documents-readme) to create, load, and query a search index for [full-text search](../../search-lucene-query-architecture.md), also known as keyword search.
+
+Full-text search uses Apache Lucene for indexing and queries and the BM25 ranking algorithm for scoring results. This quickstart uses fictional hotel data from the [azure-search-sample-data](https://github.com/Azure-Samples/azure-search-sample-data/tree/main/hotels/hotel-json-documents) GitHub repository to populate the index.
 
 > [!TIP]
-> You can download the [source code](https://github.com/Azure-Samples/azure-search-java-samples/tree/main/quickstart-keyword-search) to start with a finished project or follow these steps to create your own.
+> Want to get started right away? Download the [source code](https://github.com/Azure-Samples/azure-search-java-samples/tree/main/quickstart-keyword-search) on GitHub.
 
 ## Prerequisites
 
 - An Azure account with an active subscription. [Create an account for free](https://azure.microsoft.com/pricing/purchase-options/azure-account?cid=msft_learn).
 
-- An Azure AI Search service. [Create a service](../../search-create-service-portal.md) if you don't have one. For this quickstart, you can use a free service.
+- An [Azure AI Search service](../../search-create-service-portal.md). You can use a free service for this quickstart.
 
-## Microsoft Entra ID prerequisites
+- [Java 21 (LTS)](/java/openjdk/install) and [Maven](https://maven.apache.org/download.cgi).
 
-For the recommended keyless authentication with Microsoft Entra ID, you must:
+- [Visual Studio Code](https://code.visualstudio.com/download).
 
-- Install the [Azure CLI](/cli/azure/install-azure-cli).
+- [Git](https://git-scm.com/downloads) to clone the sample repository.
 
-- Assign the `Search Service Contributor` and `Search Index Data Contributor` roles to your user account. You can assign roles in the Azure portal under **Access control (IAM)** > **Add role assignment**. For more information, see [Connect to Azure AI Search using roles](../../search-security-rbac.md).
+- The [Azure CLI](/cli/azure/install-azure-cli) for keyless authentication with Microsoft Entra ID.
 
-## Get service information
+## Configure access
 
 [!INCLUDE [resource authentication](../resource-authentication.md)]
 
-## Set up
-
-The sample in this quickstart works with the Java Runtime. Install a Java Development Kit such as [Azul Zulu OpenJDK](https://www.azul.com/downloads/?package=jdk). The [Microsoft Build of OpenJDK](https://www.microsoft.com/openjdk) or your preferred JDK should also work.
-
-1. Install [Apache Maven](https://maven.apache.org/install.html). Then run `mvn -v` to confirm successful installation.
-1. Create a new `pom.xml` file in the root of your project, and copy the following code into it:
-
-    ```xml
-    <project xmlns="http://maven.apache.org/POM/4.0.0" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance" xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
-        <modelVersion>4.0.0</modelVersion>
-        <groupId>azure.search.sample</groupId>
-        <artifactId>azuresearchquickstart</artifactId>
-        <version>1.0.0-SNAPSHOT</version>
-        <build>
-            <sourceDirectory>src</sourceDirectory>
-            <plugins>
-            <plugin>
-                <artifactId>maven-compiler-plugin</artifactId>
-                <version>3.7.0</version>
-                <configuration>
-                <source>1.8</source>
-                <target>1.8</target>
-                </configuration>
-            </plugin>
-            </plugins>
-        </build>
-        <dependencies>
-            <dependency>
-                <groupId>junit</groupId>
-                <artifactId>junit</artifactId>
-                <version>4.11</version>
-                <scope>test</scope>
-            </dependency>
-            <dependency>
-                <groupId>com.azure</groupId>
-                <artifactId>azure-search-documents</artifactId>
-                <version>11.7.3</version>
-            </dependency>
-            <dependency>
-                <groupId>com.azure</groupId>
-                <artifactId>azure-core</artifactId>
-                <version>1.53.0</version>
-            </dependency>
-            <dependency>
-                <groupId>com.azure</groupId>
-                <artifactId>azure-identity</artifactId>
-                <version>1.15.1</version>
-            </dependency>
-        </dependencies>
-    </project>
-    ```
+## Get endpoint
+
+[!INCLUDE [resource endpoint](../resource-endpoint.md)]
 
-1. Install the dependencies including the Azure AI Search client library ([Azure.Search.Documents](/java/api/overview/azure/search)) for Java and [Azure Identity client library for Java](https://mvnrepository.com/artifact/com.azure/azure-identity) with:
+## Set up the environment
+
+1. Use Git to clone the sample repository.
 
    ```console
-   mvn clean dependency:copy-dependencies
+   git clone https://github.com/Azure-Samples/azure-search-java-samples
    ```
 
-1. For the **recommended** keyless authentication with Microsoft Entra ID, sign in to Azure with the following command:
+1. Open the `azure-search-java-samples/quickstart-keyword-search` folder in Visual Studio Code.
 
-    ```console
-    az login
-    ```
+1. Open the `App.java` file in the `src/main/java/azure/search/sample` folder.
 
-## Create, load, and query a search index
+1. Replace the placeholder value for `searchServiceEndpoint` with the URL you obtained in [Get endpoint](#get-endpoint).
 
-In the prior [set up](#set-up) section, you installed the Azure AI Search client library and other dependencies. 
+1. Use a terminal in Visual Studio Code to install the dependencies.
 
-In this section, you add code to create a search index, load it with documents, and run queries. You run the program to see the results in the console. For a detailed explanation of the code, see the [Explaining the code](#explaining-the-code) section.
+   ```console
+   mvn clean dependency:copy-dependencies
+   ```
 
-The sample code in this quickstart uses Microsoft Entra ID for the recommended keyless authentication. If you prefer to use an API key, you can replace the `DefaultAzureCredential` object with a `AzureKeyCredential` object. 
+1. For keyless authentication with Microsoft Entra ID, sign in to your Azure account. If you have multiple subscriptions, select the one that contains your Azure AI Search service.
 
-#### [Microsoft Entra ID](#tab/keyless)
+    ```azurecli
+    az login
+    ```
 
-```java
-String searchServiceEndpoint = "https://<Put your search service NAME here>.search.windows.net/";
-DefaultAzureCredential credential = new DefaultAzureCredentialBuilder().build();
-```
+## Run the code
 
-#### [API key](#tab/api-key)
+Compile and run the application.
 
-```java
-String searchServiceEndpoint = "https://<Put your search service NAME here>.search.windows.net/";
-AzureKeyCredential credential = new AzureKeyCredential("<Your search service admin key>");
+```console
+javac -d target/classes -cp "target/dependency/*" src/main/java/azure/search/sample/*.java
+java -cp "target/classes;target/dependency/*" azure.search.sample.App
 ```
----
-
-1. Create a new file named *App.java* and paste the following code into *App.java*:
-
-    ```java
-    import java.util.Arrays;
-    import java.util.ArrayList;
-    import java.time.OffsetDateTime;
-    import java.time.ZoneOffset;
-    import java.time.LocalDateTime;
-    import java.time.LocalDate;
-    import java.time.LocalTime;
-    import com.azure.core.util.Configuration;
-    import com.azure.core.util.Context;
-    import com.azure.identity.DefaultAzureCredential;
-    import com.azure.identity.DefaultAzureCredentialBuilder;
-    import com.azure.search.documents.SearchClient;
-    import com.azure.search.documents.SearchClientBuilder;
-    import com.azure.search.documents.indexes.SearchIndexClient;
-    import com.azure.search.documents.indexes.SearchIndexClientBuilder;
-    import com.azure.search.documents.indexes.models.IndexDocumentsBatch;
-    import com.azure.search.documents.models.SearchOptions;
-    import com.azure.search.documents.indexes.models.SearchIndex;
-    import com.azure.search.documents.indexes.models.SearchSuggester;
-    import com.azure.search.documents.util.AutocompletePagedIterable;
-    import com.azure.search.documents.util.SearchPagedIterable;
-    
-    public class App {
-    
-        public static void main(String[] args) {
-            // Your search service endpoint
-            "https://<Put your search service NAME here>.search.windows.net/";
-    
-            // Use the recommended keyless credential instead of the AzureKeyCredential credential.
-            DefaultAzureCredential credential = new DefaultAzureCredentialBuilder().build();
-            //AzureKeyCredential credential = new AzureKeyCredential("<Your search service admin key>");
-    
-            // Create a SearchIndexClient to send create/delete index commands
-            SearchIndexClient searchIndexClient = new SearchIndexClientBuilder()
-                .endpoint(searchServiceEndpoint)
-                .credential(credential)
-                .buildClient();
-            
-            // Create a SearchClient to load and query documents
-            String indexName = "hotels-quickstart-java";
-            SearchClient searchClient = new SearchClientBuilder()
-                .endpoint(searchServiceEndpoint)
-                .credential(credential)
-                .indexName(indexName)
-                .buildClient();
-    
-            // Create Search Index for Hotel model
-            searchIndexClient.createOrUpdateIndex(
-                new SearchIndex(indexName, SearchIndexClient.buildSearchFields(Hotel.class, null))
-                .setSuggesters(new SearchSuggester("sg", Arrays.asList("HotelName"))));
-    
-            // Upload sample hotel documents to the Search Index
-            uploadDocuments(searchClient);
-    
-            // Wait 2 seconds for indexing to complete before starting queries (for demo and console-app purposes only)
-            System.out.println("Waiting for indexing...\n");
-            try
-            {
-                Thread.sleep(2000);
-            }
-            catch (InterruptedException e)
-            {
-            }
-    
-            // Call the RunQueries method to invoke a series of queries
-            System.out.println("Starting queries...\n");
-            RunQueries(searchClient);
-    
-            // End the program
-            System.out.println("Complete.\n");
-        }
-    
-        // Upload documents in a single Upload request.
-        private static void uploadDocuments(SearchClient searchClient)
-        {
-            var hotelList = new ArrayList<Hotel>();
-    
-            var hotel = new Hotel();
-            hotel.hotelId = "1";
-            hotel.hotelName = "Stay-Kay City Hotel";
-            hotel.description = "This classic hotel is fully-refurbished and ideally located on the main commercial artery of the city in the heart of New York. A few minutes away is Times Square and the historic centre of the city, as well as other places of interest that make New York one of America's most attractive and cosmopolitan cities.";
-            hotel.category = "Boutique";
-            hotel.tags = new String[] { "view", "air conditioning", "concierge" };
-            hotel.parkingIncluded = false;
-            hotel.lastRenovationDate = OffsetDateTime.of(LocalDateTime.of(LocalDate.of(2022, 1, 18), LocalTime.of(0, 0)), ZoneOffset.UTC);
-            hotel.rating = 3.6;
-            hotel.address = new Address();
-            hotel.address.streetAddress = "677 5th Ave";
-            hotel.address.city = "New York";
-            hotel.address.stateProvince = "NY";
-            hotel.address.postalCode = "10022";
-            hotel.address.country = "USA";
-            hotelList.add(hotel);
-    
-            hotel = new Hotel();
-            hotel.hotelId = "2";
-            hotel.hotelName = "Old Century Hotel";
-            hotel.description = "The hotel is situated in a nineteenth century plaza, which has been expanded and renovated to the highest architectural standards to create a modern, functional and first-class hotel in which art and unique historical elements coexist with the most modern comforts. The hotel also regularly hosts events like wine tastings, beer dinners, and live music.",
-            hotel.category = "Boutique";
-            hotel.tags = new String[] { "pool", "free wifi", "concierge" };
-            hotel.parkingIncluded = false;
-            hotel.lastRenovationDate = OffsetDateTime.of(LocalDateTime.of(LocalDate.of(2019, 2, 18), LocalTime.of(0, 0)), ZoneOffset.UTC);
-            hotel.rating = 3.60;
-            hotel.address = new Address();
-            hotel.address.streetAddress = "140 University Town Center Dr";
-            hotel.address.city = "Sarasota";
-            hotel.address.stateProvince = "FL";
-            hotel.address.postalCode = "34243";
-            hotel.address.country = "USA";
-            hotelList.add(hotel);
-    
-            hotel = new Hotel();
-            hotel.hotelId = "3";
-            hotel.hotelName = "Gastronomic Landscape Hotel";
-            hotel.description = "The Gastronomic Hotel stands out for its culinary excellence under the management of William Dough, who advises on and oversees all of the Hotel’s restaurant services.";
-            hotel.category = "Suite";
-            hotel.tags = new String[] { "restaurant", "bar", "continental breakfast" };
-            hotel.parkingIncluded = true;
-            hotel.lastRenovationDate = OffsetDateTime.of(LocalDateTime.of(LocalDate.of(2015, 9, 20), LocalTime.of(0, 0)), ZoneOffset.UTC);
-            hotel.rating = 4.80;
-            hotel.address = new Address();
-            hotel.address.streetAddress = "3393 Peachtree Rd";
-            hotel.address.city = "Atlanta";
-            hotel.address.stateProvince = "GA";
-            hotel.address.postalCode = "30326";
-            hotel.address.country = "USA";
-            hotelList.add(hotel);
-    
-            hotel = new Hotel();
-            hotel.hotelId = "4";
-            hotel.hotelName = "Sublime Palace Hotel";
-            hotel.description = "Sublime Palace Hotel is located in the heart of the historic center of Sublime in an extremely vibrant and lively area within short walking distance to the sites and landmarks of the city and is surrounded by the extraordinary beauty of churches, buildings, shops and monuments. Sublime Cliff is part of a lovingly restored 19th century resort, updated for every modern convenience.";
-            hotel.category = "Boutique";
-            hotel.tags = new String[] { "concierge", "view", "air conditioning" };
-            hotel.parkingIncluded = true;
-            hotel.lastRenovationDate = OffsetDateTime.of(LocalDateTime.of(LocalDate.of(2020, 2, 06), LocalTime.of(0, 0)), ZoneOffset.UTC);
-            hotel.rating = 4.60;
-            hotel.address = new Address();
-            hotel.address.streetAddress = "7400 San Pedro Ave";
-            hotel.address.city = "San Antonio";
-            hotel.address.stateProvince = "TX";
-            hotel.address.postalCode = "78216";
-            hotel.address.country = "USA";
-            hotelList.add(hotel);
-    
-            var batch = new IndexDocumentsBatch<Hotel>();
-            batch.addMergeOrUploadActions(hotelList);
-            try
-            {
-                searchClient.indexDocuments(batch);
-            }
-            catch (Exception e)
-            {
-                e.printStackTrace();
-                // If for some reason any documents are dropped during indexing, you can compensate by delaying and
-                // retrying. This simple demo just logs failure and continues
-                System.err.println("Failed to index some of the documents");
-            }
-        }
-    
-        // Write search results to console
-        private static void WriteSearchResults(SearchPagedIterable searchResults)
-        {
-            searchResults.iterator().forEachRemaining(result ->
-            {
-                Hotel hotel = result.getDocument(Hotel.class);
-                System.out.println(hotel);
-            });
-    
-            System.out.println();
-        }
-    
-        // Write autocomplete results to console
-        private static void WriteAutocompleteResults(AutocompletePagedIterable autocompleteResults)
-        {
-            autocompleteResults.iterator().forEachRemaining(result ->
-            {
-                String text = result.getText();
-                System.out.println(text);
-            });
-    
-            System.out.println();
-        }
-    
-        // Run queries, use WriteDocuments to print output
-        private static void RunQueries(SearchClient searchClient)
-        {
-            // Query 1
-            System.out.println("Query #1: Search on empty term '*' to return all documents, showing a subset of fields...\n");
-    
-            SearchOptions options = new SearchOptions();
-            options.setIncludeTotalCount(true);
-            options.setFilter("");
-            options.setOrderBy("");
-            options.setSelect("HotelId", "HotelName", "Address/City");
-    
-            WriteSearchResults(searchClient.search("*", options, Context.NONE));
-    
-            // Query 2
-            System.out.println("Query #2: Search on 'hotels', filter on 'Rating gt 4', sort by Rating in descending order...\n");
-    
-            options = new SearchOptions();
-            options.setFilter("Rating gt 4");
-            options.setOrderBy("Rating desc");
-            options.setSelect("HotelId", "HotelName", "Rating");
-    
-            WriteSearchResults(searchClient.search("hotels", options, Context.NONE));
-    
-            // Query 3
-            System.out.println("Query #3: Limit search to specific fields (pool in Tags field)...\n");
-    
-            options = new SearchOptions();
-            options.setSearchFields("Tags");
-    
-            options.setSelect("HotelId", "HotelName", "Tags");
-    
-            WriteSearchResults(searchClient.search("pool", options, Context.NONE));
-    
-            // Query 4
-            System.out.println("Query #4: Facet on 'Category'...\n");
-    
-            options = new SearchOptions();
-            options.setFilter("");
-            options.setFacets("Category");
-            options.setSelect("HotelId", "HotelName", "Category");
-    
-            WriteSearchResults(searchClient.search("*", options, Context.NONE));
-    
-            // Query 5
-            System.out.println("Query #5: Look up a specific document...\n");
-    
-            Hotel lookupResponse = searchClient.getDocument("3", Hotel.class);
-            System.out.println(lookupResponse.hotelId);
-            System.out.println();
-    
-             // Query 6
-            System.out.println("Query #6: Call Autocomplete on HotelName that starts with 's'...\n");
-    
-            WriteAutocompleteResults(searchClient.autocomplete("s", "sg"));
-        }
-    }
-    ```
 
-1. Create a new file named *Hotel.java* and paste the following code into *Hotel.java*:
+### Output
 
-    ```java
-    import com.azure.search.documents.indexes.SearchableField;
-    import com.azure.search.documents.indexes.SimpleField;
-    import com.fasterxml.jackson.annotation.JsonInclude;
-    import com.fasterxml.jackson.annotation.JsonProperty;
-    import com.fasterxml.jackson.core.JsonProcessingException;
-    import com.fasterxml.jackson.databind.ObjectMapper;
-    import com.fasterxml.jackson.annotation.JsonInclude.Include;
-    
-    import java.time.OffsetDateTime;
-    
-    /**
-     * Model class representing a hotel.
-     */
-    @JsonInclude(Include.NON_NULL)
-    public class Hotel {
-        /**
-         * Hotel ID
-         */
-        @JsonProperty("HotelId")
-        @SimpleField(isKey = true)
-        public String hotelId;
-    
-        /**
-         * Hotel name
-         */
-        @JsonProperty("HotelName")
-        @SearchableField(isSortable = true)
-        public String hotelName;
-    
-        /**
-         * Description
-         */
-        @JsonProperty("Description")
-        @SearchableField(analyzerName = "en.microsoft")
-        public String description;
-    
-        /**
-         * Category
-         */
-        @JsonProperty("Category")
-        @SearchableField(isFilterable = true, isSortable = true, isFacetable = true)
-        public String category;
-    
-        /**
-         * Tags
-         */
-        @JsonProperty("Tags")
-        @SearchableField(isFilterable = true, isFacetable = true)
-        public String[] tags;
-    
-        /**
-         * Whether parking is included
-         */
-        @JsonProperty("ParkingIncluded")
-        @SimpleField(isFilterable = true, isSortable = true, isFacetable = true)
-        public Boolean parkingIncluded;
-    
-        /**
-         * Last renovation time
-         */
-        @JsonProperty("LastRenovationDate")
-        @SimpleField(isFilterable = true, isSortable = true, isFacetable = true)
-        public OffsetDateTime lastRenovationDate;
-    
-        /**
-         * Rating
-         */
-        @JsonProperty("Rating")
-        @SimpleField(isFilterable = true, isSortable = true, isFacetable = true)
-        public Double rating;
-    
-        /**
-         * Address
-         */
-        @JsonProperty("Address")
-        public Address address;
-    
-        @Override
-        public String toString()
-        {
-            try
-            {
-                return new ObjectMapper().writeValueAsString(this);
-            }
-            catch (JsonProcessingException e)
-            {
-                e.printStackTrace();
-                return "";
-            }
-        }
-    }
-    ```
+The output should be similar to the following:
 
-1. Create a new file named *Address.java* and paste the following code into *Address.java*:
+```
+Waiting for indexing...
 
-    ```java
-    import com.azure.search.documents.indexes.SearchableField;
-    import com.fasterxml.jackson.annotation.JsonInclude;
-    import com.fasterxml.jackson.annotation.JsonProperty;
-    import com.fasterxml.jackson.annotation.JsonInclude.Include;
-    
-    /**
-     * Model class representing an address.
-     */
-    @JsonInclude(Include.NON_NULL)
-    public class Address {
-        /**
-         * Street address
-         */
-        @JsonProperty("StreetAddress")
-        @SearchableField
-        public String streetAddress;
-    
-        /**
-         * City
-         */
-        @JsonProperty("City")
-        @SearchableField(isFilterable = true, isSortable = true, isFacetable = true)
-        public String city;
-    
-        /**
-         * State or province
-         */
-        @JsonProperty("StateProvince")
-        @SearchableField(isFilterable = true, isSortable = true, isFacetable = true)
-        public String stateProvince;
-    
-        /**
-         * Postal code
-         */
-        @JsonProperty("PostalCode")
-        @SearchableField(isFilterable = true, isSortable = true, isFacetable = true)
-        public String postalCode;
-    
-        /**
-         * Country
-         */
-        @JsonProperty("Country")
-        @SearchableField(isFilterable = true, isSortable = true, isFacetable = true)
-        public String country;
-    }
-    ```
+Starting queries...
 
+Query #1: Search on empty term '*' to return all documents, showing a subset of fields...
 
-1. Run your new console application:
+{"HotelId":"3","HotelName":"Gastronomic Landscape Hotel","Address":{"City":"Atlanta"}}
+{"HotelId":"2","HotelName":"Old Century Hotel","Address":{"City":"Sarasota"}}
+{"HotelId":"4","HotelName":"Sublime Palace Hotel","Address":{"City":"San Antonio"}}
+{"HotelId":"1","HotelName":"Stay-Kay City Hotel","Address":{"City":"New York"}}
 
-    ```console
-    javac Address.java App.java Hotel.java -cp ".;target\dependency\*"
-    java -cp ".;target\dependency\*" App
-    ```
+Query #2: Search on 'hotels', filter on 'Rating gt 4', sort by Rating in descending order...
 
-## Explaining the code
+{"HotelId":"3","HotelName":"Gastronomic Landscape Hotel","Rating":4.8}
+{"HotelId":"4","HotelName":"Sublime Palace Hotel","Rating":4.6}
 
-In the previous sections, you created a new console application and installed the Azure AI Search client library. You added code to create a search index, load it with documents, and run queries. You ran the program to see the results in the console. 
+Query #3: Limit search to specific fields (pool in Tags field)...
 
-In this section, we explain the code you added to the console application.
+{"HotelId":"2","HotelName":"Old Century Hotel","Tags":["pool","free wifi","concierge"]}
 
-### Create a search client
+Query #4: Facet on 'Category'...
 
-In *App.java* you created two clients:
+{"HotelId":"3","HotelName":"Gastronomic Landscape Hotel","Category":"Suite"}
+{"HotelId":"2","HotelName":"Old Century Hotel","Category":"Boutique"}
+{"HotelId":"4","HotelName":"Sublime Palace Hotel","Category":"Boutique"}
+{"HotelId":"1","HotelName":"Stay-Kay City Hotel","Category":"Boutique"}
 
-- SearchIndexClient creates the index.
-- SearchClient loads and queries an existing index.
+Query #5: Look up a specific document...
 
-Both clients need the search service endpoint and credentials described previously in the resource information section.
+3
 
-The sample code in this quickstart uses Microsoft Entra ID for the recommended keyless authentication. If you prefer to use an API key, you can replace the `DefaultAzureCredential` object with a `AzureKeyCredential` object. 
+Query #6: Call Autocomplete on HotelName that starts with 's'...
 
-#### [Microsoft Entra ID](#tab/keyless)
+stay
+sublime
 
-```java
-String searchServiceEndpoint = "https://<Put your search service NAME here>.search.windows.net/";
-DefaultAzureCredential credential = new DefaultAzureCredentialBuilder().build();
+Complete.
 ```
 
-#### [API key](#tab/api-key)
+## Understand the code
 
-```java
-String searchServiceEndpoint = "https://<Put your search service NAME here>.search.windows.net/";
-AzureKeyCredential credential = new AzureKeyCredential("<Your search service admin key>");
-```
----
+Now that you've run the code, let's break down the key steps:
 
-```java
-public static void main(String[] args) {
-    // Your search service endpoint
-    String searchServiceEndpoint = "https://<Put your search service NAME here>.search.windows.net/";
-
-    // Use the recommended keyless credential instead of the AzureKeyCredential credential.
-    DefaultAzureCredential credential = new DefaultAzureCredentialBuilder().build();
-    //AzureKeyCredential credential = new AzureKeyCredential("Your search service admin key");
-
-    // Create a SearchIndexClient to send create/delete index commands
-    SearchIndexClient searchIndexClient = new SearchIndexClientBuilder()
-        .endpoint(searchServiceEndpoint)
-        .credential(credential)
-        .buildClient();
-    
-    // Create a SearchClient to load and query documents
-    String indexName = "hotels-quickstart-java";
-    SearchClient searchClient = new SearchClientBuilder()
-        .endpoint(searchServiceEndpoint)
-        .credential(credential)
-        .indexName(indexName)
-        .buildClient();
-
-    // Create Search Index for Hotel model
-    searchIndexClient.createOrUpdateIndex(
-        new SearchIndex(indexName, SearchIndexClient.buildSearchFields(Hotel.class, null))
-        .setSuggesters(new SearchSuggester("sg", Arrays.asList("HotelName"))));
-
-    // REDACTED FOR BREVITY . . . 
-}
-```
+1. [Create a search client](#create-a-search-client)
+1. [Create a search index](#create-a-search-index)
+1. [Upload documents to the index](#upload-documents-to-the-index)
+1. [Query the index](#query-the-index)
 
+### Create a search client
 
-### Create an index
+In `App.java`, you create two clients:
 
-This quickstart builds a Hotels index that you load with hotel data and execute queries against. In this step, you define the fields in the index. Each field definition includes a name, data type, and attributes that determine how the field is used.
+- [SearchIndexClient](/java/api/com.azure.search.documents.indexes.searchindexclient) creates the index.
+- [SearchClient](/java/api/com.azure.search.documents.searchclient) loads and queries an existing index.
 
-In this example, synchronous methods of the *Azure.Search.Documents* library are used for simplicity and readability. However, for production scenarios, you should use asynchronous methods to keep your app scalable and responsive. For example, you would use [CreateIndexAsync](/dotnet/api/azure.search.documents.indexes.searchindexclient.createindexasync) instead of [CreateIndex](/dotnet/api/azure.search.documents.indexes.searchindexclient.createindex).
+Both clients require the service endpoint and a credential for authentication. In this quickstart, you use [DefaultAzureCredential](/java/api/com.azure.identity.defaultazurecredential) for keyless authentication with Microsoft Entra ID.
+
+### Create a search index
+
+This quickstart builds a hotels index that you load with hotel data and execute queries against. In this step, you define the fields in the index. Each field definition includes a name, data type, and attributes that determine how the field is used.
+
+This example uses synchronous methods of the [SearchIndexClient](/java/api/com.azure.search.documents.indexes.searchindexclient) class for simplicity and readability. However, for production scenarios, use the [SearchIndexAsyncClient](/java/api/com.azure.search.documents.indexes.searchindexasyncclient) class to keep your app scalable and responsive.
 
 #### Define the structures
 
-You created two helper classes, *Hotel.java* and *Address.java*, to define the structure of a hotel document and its address. The Hotel class includes fields for a hotel ID, name, description, category, tags, parking, renovation date, rating, and address. The Address class includes fields for street address, city, state/province, postal code, and country/region.
+You create two helper classes, `Hotel.java` and `Address.java`, to define the structure of a hotel document and its address. The `Hotel` class includes fields for a hotel ID, name, description, category, tags, parking, renovation date, rating, and address. The `Address` class includes fields for street address, city, state/province, postal code, and country/region.
 
-In the Azure.Search.Documents client library, you can use [SearchableField](/java/api/com.azure.search.documents.indexes.searchablefield) and [SimpleField](/java/api/com.azure.search.documents.indexes.simplefield) to streamline field definitions.
+In the azure-search-documents client library, you can use [SearchableField](/java/api/com.azure.search.documents.indexes.searchablefield) and [SimpleField](/java/api/com.azure.search.documents.indexes.simplefield) to streamline field definitions. Both are annotations that you can apply to fields or methods to generate a [SearchField](/java/api/com.azure.search.documents.indexes.models.searchfield):
 
-* `SimpleField` can be any data type, is always non-searchable (ignored for full text search queries), and is retrievable (not hidden). Other attributes are off by default, but can be enabled. You might use a SimpleField for document IDs or fields used only in filters, facets, or scoring profiles. If so, be sure to apply any attributes that are necessary for the scenario, such as IsKey = true for a document ID.
-* `SearchableField` must be a string, and is always searchable and retrievable. Other attributes are off by default, but can be enabled. Because this field type is searchable, it supports synonyms and the full complement of analyzer properties.
++ `SimpleField` can be any data type, is always nonsearchable (ignored for full-text search queries), and is retrievable (not hidden). Other attributes are off by default, but can be enabled. You might use a `SimpleField` for document IDs or fields used only in filters, facets, or scoring profiles. If so, apply any attributes that are necessary for the scenario, such as `isKey = true` for a document ID.
++ `SearchableField` must be a string, and is always searchable and retrievable. Other attributes are off by default, but can be enabled. Because this field type is searchable, it supports synonyms and the full complement of analyzer properties.
 
-Whether you use the basic `SearchField` API or either one of the helper models, you must explicitly enable filter, facet, and sort attributes. For example, `isFilterable`, `isSortable`, and `isFacetable` must be explicitly attributed, as shown in the previous sample.
+Whether you use the basic `SearchField` API or either one of the helper models, you must explicitly enable filter, facet, and sort attributes. For example, [isFilterable](/java/api/com.azure.search.documents.indexes.models.searchfield), [isSortable](/java/api/com.azure.search.documents.indexes.models.searchfield), and [isFacetable](/java/api/com.azure.search.documents.indexes.models.searchfield) must be explicitly attributed, as shown in the previous sample.
 
 #### Create the search index
 
-In `App.java`, you create a `SearchIndex` object in the `main` method, and then call the `createOrUpdateIndex` method to create the index in your search service. The index also includes a `SearchSuggester` to enable autocomplete on the specified fields.
+In `App.java`, you create a [SearchIndex](/java/api/com.azure.search.documents.indexes.models.searchindex) object, and then call the [createOrUpdateIndex](/java/api/com.azure.search.documents.indexes.searchindexclient) method to express the index in your search service. The index also includes a [SearchSuggester](/java/api/com.azure.search.documents.indexes.models.searchsuggester) to enable autocomplete on the specified fields.
 
 ```java
 // Create Search Index for Hotel model
@@ -610,15 +161,15 @@ searchIndexClient.createOrUpdateIndex(
     .setSuggesters(new SearchSuggester("sg", Arrays.asList("HotelName"))));
 ```
 
-### Load documents
+### Upload documents to the index
 
 Azure AI Search searches over content stored in the service. In this step, you load JSON documents that conform to the hotel index you created.
 
-In Azure AI Search, search documents are data structures that are both inputs to indexing and outputs from queries. As obtained from an external data source, document inputs might be rows in a database, blobs in Blob storage, or JSON documents on disk. In this example, we're taking a shortcut and embedding JSON documents for four hotels in the code itself.
+In Azure AI Search, search documents are data structures that are both inputs to indexing and outputs from queries. As obtained from an external data source, document inputs might be rows in a database, blobs in Azure Blob Storage, or JSON documents on disk. In this example, you take a shortcut and embed JSON documents for four hotels directly.
 
-When uploading documents, you must use an [IndexDocumentsBatch](/java/api/com.azure.search.documents.indexes.models.indexdocumentsbatch) object. An `IndexDocumentsBatch` object contains a collection of [IndexActions](/java/api/com.azure.search.documents.models.indexaction), each of which contains a document and a property telling Azure AI Search what action to perform (upload, merge, delete, and mergeOrUpload).
+When uploading documents, you must use an [IndexDocumentsBatch](/java/api/com.azure.search.documents.indexes.models.indexdocumentsbatch) object. An `IndexDocumentsBatch` object contains a collection of [IndexActions](/java/api/com.azure.search.documents.models.indexaction), each of which contains a document and a property telling Azure AI Search what action to perform ([upload, merge, delete, and mergeOrUpload](/azure/search/search-what-is-data-import#indexing-actions)).
 
-In `App.java`, you create documents and index actions, and then pass them to `IndexDocumentsBatch`. The following documents conform to the hotels-quickstart index, as defined by the hotel class.
+In `App.java`, you create an array of documents and index actions, and then pass the array to `IndexDocumentsBatch`. The following documents conform to the hotels-quickstart index, as defined by the hotel class.
 
 ```java
 private static void uploadDocuments(SearchClient searchClient)
@@ -660,15 +211,13 @@ private static void uploadDocuments(SearchClient searchClient)
 }
 ```
 
-Once you initialize the `IndexDocumentsBatch` object, you can send it to the index by calling [indexDocuments](/java/api/com.azure.search.documents.searchclient#com-azure-search-documents-searchclient-indexdocuments(com-azure-search-documents-indexes-models-indexdocumentsbatch(-))) on your `SearchClient` object.
-
-You load documents using SearchClient in `main()`, but the operation also requires admin rights on the service, which is typically associated with SearchIndexClient. One way to set up this operation is to get SearchClient through `SearchIndexClient` (`searchIndexClient` in this example).
+The `uploadDocuments` method creates an [IndexDocumentsBatch](/java/api/com.azure.search.documents.indexes.models.indexdocumentsbatch) and calls [indexDocuments](/java/api/com.azure.search.documents.searchclient) on a [SearchClient](/java/api/com.azure.search.documents.searchclient) to upload the documents. This quickstart creates `SearchClient` independently using [SearchClientBuilder](/java/api/com.azure.search.documents.searchclientbuilder), which requires configuring the endpoint and credentials separately.
 
 ```java
 uploadDocuments(searchClient);
 ```
 
-Because we have a console app that runs all commands sequentially, we add a 2-second wait time between indexing and queries.
+Because this console app runs all commands sequentially, the code adds a two-second wait time between indexing and queries.
 
 ```java
 // Wait 2 seconds for indexing to complete before starting queries (for demo and console-app purposes only)
@@ -682,13 +231,15 @@ catch (InterruptedException e)
 }
 ```
 
-The 2-second delay compensates for indexing, which is asynchronous, so that all documents can be indexed before the queries are executed. Coding in a delay is typically only necessary in demos, tests, and sample applications.
+The two-second delay compensates for indexing, which is asynchronous, so that all documents can be indexed before the queries are executed. Coding in a delay is typically only necessary in demos, tests, and sample applications.
 
-### Search an index
+### Query the index
 
 You can get query results as soon as the first document is indexed, but actual testing of your index should wait until all documents are indexed.
 
-This section adds two pieces of functionality: query logic and results. For queries, use the Search method. This method takes search text (the query string) and other options.
+This section adds two pieces of functionality: query logic and results. For queries, use the [search](/java/api/com.azure.search.documents.searchclient) method. This method takes search text (the query string) and other [options](/java/api/com.azure.search.documents.models.searchoptions).
+
+The [SearchPagedIterable](/java/api/com.azure.search.documents.util.searchpagediterable) class represents the results.
 
 In `App.java`, the `WriteDocuments` method prints search results to the console.
 
@@ -741,7 +292,7 @@ private static void RunQueries(SearchClient searchClient)
 
 #### Query example 2
 
-In the second query, search on a term, add a filter that selects documents where Rating is greater than 4, and then sort by *Rating* in descending order. Filter is a boolean expression that is evaluated over `isFilterable` fields in an index. Filter queries either include or exclude values. As such, there's no relevance score associated with a filter query.
+In the second query, search on a term, add a filter that selects documents where `Rating` is greater than 4, and then sort by `Rating` in descending order. A filter is a boolean expression evaluated over [isFilterable](/java/api/com.azure.search.documents.indexes.models.searchfield) fields in an index. Filter queries either include or exclude values. As such, there's no relevance score associated with a filter query.
 
 ```java
 // Query 2
@@ -757,7 +308,7 @@ WriteSearchResults(searchClient.search("hotels", options, Context.NONE));
 
 #### Query example 3
 
-The third query demonstrates `searchFields`, used to scope a full text search operation to specific fields.
+The third query demonstrates `searchFields`, used to scope a full-text search operation to specific fields.
 
 ```java
 // Query 3
@@ -789,7 +340,7 @@ WriteSearchResults(searchClient.search("*", options, Context.NONE));
 
 #### Query example 5
 
-In the fifth query, return a specific document.
+In the fifth query, return a specific document. A document lookup is a typical response to an `OnClick` event in a result set.
 
 ```java
 // Query 5
@@ -813,7 +364,7 @@ WriteAutocompleteResults(searchClient.autocomplete("s", "sg"));
 
 #### Summary of queries
 
-The previous queries show multiple ways of matching terms in a query: full-text search, filters, and autocomplete.
+The previous queries show multiple [ways of matching terms in a query](/azure/search/search-query-overview#types-of-queries): full-text search, filters, and autocomplete.
 
-Full text search and filters are performed using the [SearchClient.search](/java/api/com.azure.search.documents.searchclient#com-azure-search-documents-searchclient-search(java-lang-string)) method. A search query can be passed in the `searchText` string, while a filter expression can be passed in the `filter` property of the [SearchOptions](/java/api/com.azure.search.documents.models.searchoptions) class. To filter without searching, just pass "*" for the `searchText` parameter of the `search` method. To search without filtering, leave the `filter` property unset, or don't pass in a `SearchOptions` instance at all.
+The [SearchClient.search](/java/api/com.azure.search.documents.searchclient) method performs full-text search and filters. You can pass a search query in the `searchText` string, while you pass a filter expression in the [filter](/java/api/com.azure.search.documents.models.searchoptions) property of the [SearchOptions](/java/api/com.azure.search.documents.models.searchoptions) class. To filter without searching, just pass `"*"` for the `searchText` parameter of the [search](/java/api/com.azure.search.documents.searchclient) method. To search without filtering, leave the `filter` property unset, or don't pass in a `SearchOptions` instance at all.
 

@@ -4,553 +4,145 @@ author: haileytap
 ms.author: haileytapia
 ms.service: azure-ai-search
 ms.topic: include
-ms.date: 11/20/2025
+ms.date: 02/02/2026
 ---
 
-[!INCLUDE [Full text introduction](full-text-intro.md)]
+In this quickstart, you use the [Azure AI Search client library for JavaScript](/javascript/api/overview/azure/search-documents-readme) to create, load, and query a search index for [full-text search](../../search-lucene-query-architecture.md), also known as keyword search.
+
+Full-text search uses Apache Lucene for indexing and queries and the BM25 ranking algorithm for scoring results. This quickstart uses fictional hotel data from the [azure-search-sample-data](https://github.com/Azure-Samples/azure-search-sample-data/tree/main/hotels/hotel-json-documents) GitHub repository to populate the index.
 
 > [!TIP]
-> You can download the [source code](https://github.com/Azure-Samples/azure-search-javascript-samples/tree/main/quickstart-keyword-search) to start with a finished project or follow these steps to create your own.
+> Want to get started right away? Download the [source code](https://github.com/Azure-Samples/azure-search-javascript-samples/tree/main/quickstart-keyword-search) on GitHub.
 
 ## Prerequisites
 
 - An Azure account with an active subscription. [Create an account for free](https://azure.microsoft.com/pricing/purchase-options/azure-account?cid=msft_learn).
 
-- An Azure AI Search service. [Create a service](../../search-create-service-portal.md) if you don't have one. For this quickstart, you can use a free service.
+- An [Azure AI Search service](../../search-create-service-portal.md). You can use a free service for this quickstart.
 
-## Microsoft Entra ID prerequisites
+- The latest LTS version of [Node.js](https://nodejs.org/en/download/).
 
-For the recommended keyless authentication with Microsoft Entra ID, you must:
+- [Visual Studio Code](https://code.visualstudio.com/download).
 
-- Install the [Azure CLI](/cli/azure/install-azure-cli).
+- [Git](https://git-scm.com/downloads) to clone the sample repository.
 
-- Assign the `Search Service Contributor` and `Search Index Data Contributor` roles to your user account. You can assign roles in the Azure portal under **Access control (IAM)** > **Add role assignment**. For more information, see [Connect to Azure AI Search using roles](../../search-security-rbac.md).
+- The [Azure CLI](/cli/azure/install-azure-cli) for keyless authentication with Microsoft Entra ID.
 
-## Get service information
+## Configure access
 
 [!INCLUDE [resource authentication](../resource-authentication.md)]
 
-## Set up
+## Get endpoint
 
-1. Create a new folder `full-text-quickstart` to contain the application and open Visual Studio Code in that folder with the following command:
+[!INCLUDE [resource endpoint](../resource-endpoint.md)]
 
-    ```shell
-    mkdir full-text-quickstart && cd full-text-quickstart
-    ```
+## Set up the environment
 
-1. Create the `package.json` with the following command:
+1. Use Git to clone the sample repository.
 
-    ```shell
-    npm init -y
-    ```
+   ```console
+   git clone https://github.com/Azure-Samples/azure-search-javascript-samples
+   ```
 
-1. Install the Azure AI Search client library ([Azure.Search.Documents](/javascript/api/overview/azure/search-documents-readme)) for JavaScript with:
+1. Open the `azure-search-javascript-samples/quickstart-keyword-search` folder in Visual Studio Code.
 
-    ```console
-    npm install @azure/search-documents
-    ```
+1. Rename the `sample.env` file to `.env`, and then open the file.
 
-1. For the **recommended** passwordless authentication, install the Azure Identity client library with:
+1. Replace the placeholder value for `SEARCH_API_ENDPOINT` with the URL you obtained in [Get endpoint](#get-endpoint).
+
+1. Use a terminal in Visual Studio Code to install the dependencies.
 
     ```console
-    npm install @azure/identity
+    npm install
     ```
 
+1. For keyless authentication with Microsoft Entra ID, sign in to your Azure account. If you have multiple subscriptions, select the one that contains your Azure AI Search service.
 
+    ```azurecli
+    az login
+    ```
 
-## Create, load, and query a search index
+## Run the code
 
-In the prior [set up](#set-up) section, you installed the Azure AI Search client library and other dependencies. 
+Run the application.
 
-In this section, you add code to create a search index, load it with documents, and run queries. You run the program to see the results in the console. For a detailed explanation of the code, see the [Explaining the code](#explaining-the-code) section.
+```console
+node index.js
+```
 
-The sample code in this quickstart uses Microsoft Entra ID for the recommended keyless authentication. If you prefer to use an API key, you can replace the `DefaultAzureCredential` object with a `AzureKeyCredential` object. 
+### Output
 
-#### [Microsoft Entra ID](#tab/keyless)
+The output should be similar to the following:
 
-```java
-String searchServiceEndpoint = "https://<Put your search service NAME here>.search.windows.net/";
-DefaultAzureCredential credential = new DefaultAzureCredentialBuilder().build();
 ```
-
-#### [API key](#tab/api-key)
-
-```java
-String searchServiceEndpoint = "https://<Put your search service NAME here>.search.windows.net/";
-AzureKeyCredential credential = new AzureKeyCredential("<Your search service admin key>");
+Running Azure AI Search Javascript quickstart...
+Checking if index exists...
+Deleting index...
+Creating index...
+Index named hotels-quickstart-js has been created.
+Uploading documents...
+Index operations succeeded: true
+Querying the index...
+
+Query #1 - search everything:
+{"HotelId":"3","HotelName":"Gastronomic Landscape Hotel","Rating":4.8}
+{"HotelId":"2","HotelName":"Old Century Hotel","Rating":3.6}
+{"HotelId":"4","HotelName":"Sublime Palace Hotel","Rating":4.6}
+{"HotelId":"1","HotelName":"Stay-Kay City Hotel","Rating":3.6}
+Result count: 4
+
+Query #2 - search with filter, orderBy, and select:
+{"HotelId":"2","HotelName":"Old Century Hotel","Rating":3.6}
+
+Query #3 - limit searchFields:
+{"HotelId":"4","HotelName":"Sublime Palace Hotel","Rating":4.6}
+
+Query #4 - limit searchFields and use facets:
+{"HotelId":"3","HotelName":"Gastronomic Landscape Hotel","Rating":4.8}
+{"HotelId":"2","HotelName":"Old Century Hotel","Rating":3.6}
+{"HotelId":"4","HotelName":"Sublime Palace Hotel","Rating":4.6}
+{"HotelId":"1","HotelName":"Stay-Kay City Hotel","Rating":3.6}
+
+Query #5 - Lookup document:
+HotelId: 3; HotelName: Gastronomic Landscape Hotel
 ```
----
-
-1. Create a new file named *index.js* and paste the following code into *index.js*:
-
-    ```javascript
-    // Import from the @azure/search-documents library
-    import { SearchIndexClient, odata } from "@azure/search-documents";
-    // Import from the Azure Identity library
-    import { DefaultAzureCredential } from "@azure/identity";
-    // Importing the hotels sample data
-    import hotelData from './hotels.json' assert { type: "json" };
-    // Load the .env file if it exists
-    import * as dotenv from "dotenv";
-    dotenv.config();
-    // Defining the index definition
-    const indexDefinition = {
-        "name": "hotels-quickstart",
-        "fields": [
-            {
-                "name": "HotelId",
-                "type": "Edm.String",
-                "key": true,
-                "filterable": true
-            },
-            {
-                "name": "HotelName",
-                "type": "Edm.String",
-                "searchable": true,
-                "filterable": false,
-                "sortable": true,
-                "facetable": false
-            },
-            {
-                "name": "Description",
-                "type": "Edm.String",
-                "searchable": true,
-                "filterable": false,
-                "sortable": false,
-                "facetable": false,
-                "analyzerName": "en.lucene"
-            },
-            {
-                "name": "Description_fr",
-                "type": "Edm.String",
-                "searchable": true,
-                "filterable": false,
-                "sortable": false,
-                "facetable": false,
-                "analyzerName": "fr.lucene"
-            },
-            {
-                "name": "Category",
-                "type": "Edm.String",
-                "searchable": true,
-                "filterable": true,
-                "sortable": true,
-                "facetable": true
-            },
-            {
-                "name": "Tags",
-                "type": "Collection(Edm.String)",
-                "searchable": true,
-                "filterable": true,
-                "sortable": false,
-                "facetable": true
-            },
-            {
-                "name": "ParkingIncluded",
-                "type": "Edm.Boolean",
-                "filterable": true,
-                "sortable": true,
-                "facetable": true
-            },
-            {
-                "name": "LastRenovationDate",
-                "type": "Edm.DateTimeOffset",
-                "filterable": true,
-                "sortable": true,
-                "facetable": true
-            },
-            {
-                "name": "Rating",
-                "type": "Edm.Double",
-                "filterable": true,
-                "sortable": true,
-                "facetable": true
-            },
-            {
-                "name": "Address",
-                "type": "Edm.ComplexType",
-                "fields": [
-                    {
-                        "name": "StreetAddress",
-                        "type": "Edm.String",
-                        "filterable": false,
-                        "sortable": false,
-                        "facetable": false,
-                        "searchable": true
-                    },
-                    {
-                        "name": "City",
-                        "type": "Edm.String",
-                        "searchable": true,
-                        "filterable": true,
-                        "sortable": true,
-                        "facetable": true
-                    },
-                    {
-                        "name": "StateProvince",
-                        "type": "Edm.String",
-                        "searchable": true,
-                        "filterable": true,
-                        "sortable": true,
-                        "facetable": true
-                    },
-                    {
-                        "name": "PostalCode",
-                        "type": "Edm.String",
-                        "searchable": true,
-                        "filterable": true,
-                        "sortable": true,
-                        "facetable": true
-                    },
-                    {
-                        "name": "Country",
-                        "type": "Edm.String",
-                        "searchable": true,
-                        "filterable": true,
-                        "sortable": true,
-                        "facetable": true
-                    }
-                ]
-            }
-        ],
-        "suggesters": [
-            {
-                "name": "sg",
-                "searchMode": "analyzingInfixMatching",
-                "sourceFields": [
-                    "HotelName"
-                ]
-            }
-        ]
-    };
-    async function main() {
-        // Your search service endpoint
-        const searchServiceEndpoint = "https://<Put your search service NAME here>.search.windows.net/";
-        // Use the recommended keyless credential instead of the AzureKeyCredential credential.
-        const credential = new DefaultAzureCredential();
-        //const credential = new AzureKeyCredential(Your search service admin key);
-        // Create a SearchIndexClient to send create/delete index commands
-        const searchIndexClient = new SearchIndexClient(searchServiceEndpoint, credential);
-        // Creating a search client to upload documents and issue queries
-        const indexName = "hotels-quickstart";
-        const searchClient = searchIndexClient.getSearchClient(indexName);
-        console.log('Checking if index exists...');
-        await deleteIndexIfExists(searchIndexClient, indexName);
-        console.log('Creating index...');
-        let index = await searchIndexClient.createIndex(indexDefinition);
-        console.log(`Index named ${index.name} has been created.`);
-        console.log('Uploading documents...');
-        let indexDocumentsResult = await searchClient.mergeOrUploadDocuments(hotelData['value']);
-        console.log(`Index operations succeeded: ${JSON.stringify(indexDocumentsResult.results[0].succeeded)} `);
-        // waiting one second for indexing to complete (for demo purposes only)
-        sleep(1000);
-        console.log('Querying the index...');
-        console.log();
-        await sendQueries(searchClient);
-    }
-    async function deleteIndexIfExists(searchIndexClient, indexName) {
-        try {
-            await searchIndexClient.deleteIndex(indexName);
-            console.log('Deleting index...');
-        }
-        catch {
-            console.log('Index does not exist yet.');
-        }
-    }
-    async function sendQueries(searchClient) {
-        // Query 1
-        console.log('Query #1 - search everything:');
-        let searchOptions = {
-            includeTotalCount: true,
-            select: ["HotelId", "HotelName", "Rating"]
-        };
-        let searchResults = await searchClient.search("*", searchOptions);
-        for await (const result of searchResults.results) {
-            console.log(`${JSON.stringify(result.document)}`);
-        }
-        console.log(`Result count: ${searchResults.count}`);
-        console.log();
-        // Query 2
-        console.log('Query #2 - search with filter, orderBy, and select:');
-        let state = 'FL';
-        searchOptions = {
-            filter: odata `Address/StateProvince eq ${state}`,
-            orderBy: ["Rating desc"],
-            select: ["HotelId", "HotelName", "Rating"]
-        };
-        searchResults = await searchClient.search("wifi", searchOptions);
-        for await (const result of searchResults.results) {
-            console.log(`${JSON.stringify(result.document)}`);
-        }
-        console.log();
-        // Query 3
-        console.log('Query #3 - limit searchFields:');
-        searchOptions = {
-            select: ["HotelId", "HotelName", "Rating"],
-            searchFields: ["HotelName"]
-        };
-        searchResults = await searchClient.search("sublime palace", searchOptions);
-        for await (const result of searchResults.results) {
-            console.log(`${JSON.stringify(result.document)}`);
-        }
-        console.log();
-        // Query 4
-        console.log('Query #4 - limit searchFields and use facets:');
-        searchOptions = {
-            facets: ["Category"],
-            select: ["HotelId", "HotelName", "Rating"],
-            searchFields: ["HotelName"]
-        };
-        searchResults = await searchClient.search("*", searchOptions);
-        for await (const result of searchResults.results) {
-            console.log(`${JSON.stringify(result.document)}`);
-        }
-        console.log();
-        // Query 5
-        console.log('Query #5 - Lookup document:');
-        let documentResult = await searchClient.getDocument('3');
-        console.log(`HotelId: ${documentResult.HotelId}; HotelName: ${documentResult.HotelName}`);
-        console.log();
-    }
-    function sleep(ms) {
-        return new Promise(resolve => setTimeout(resolve, ms));
-    }
-    main().catch((err) => {
-        console.error("The sample encountered an error:", err);
-    });
-    ```
 
-1. Create a file named *hotels.json* and paste the following code into *hotels.json*:
-
-    ```json
-    {
-        "value": [
-            {
-                "HotelId": "1",
-                "HotelName": "Stay-Kay City Hotel",
-                "Description": "This classic hotel is fully-refurbished and ideally located on the main commercial artery of the city in the heart of New York. A few minutes away is Times Square and the historic centre of the city, as well as other places of interest that make New York one of America's most attractive and cosmopolitan cities.",
-                "Category": "Boutique",
-                "Tags": ["view", "air conditioning", "concierge"],
-                "ParkingIncluded": false,
-                "LastRenovationDate": "2022-01-18T00:00:00Z",
-                "Rating": 3.6,
-                "Address": {
-                    "StreetAddress": "677 5th Ave",
-                    "City": "New York",
-                    "StateProvince": "NY",
-                    "PostalCode": "10022"
-                }
-            },
-            {
-                "HotelId": "2",
-                "HotelName": "Old Century Hotel",
-                "Description": "The hotel is situated in a nineteenth century plaza, which has been expanded and renovated to the highest architectural standards to create a modern, functional and first-class hotel in which art and unique historical elements coexist with the most modern comforts. The hotel also regularly hosts events like wine tastings, beer dinners, and live music.",
-                "Category": "Boutique",
-                "Tags": ["pool", "free wifi", "concierge"],
-                "ParkingIncluded": "false",
-                "LastRenovationDate": "2019-02-18T00:00:00Z",
-                "Rating": 3.6,
-                "Address": {
-                    "StreetAddress": "140 University Town Center Dr",
-                    "City": "Sarasota",
-                    "StateProvince": "FL",
-                    "PostalCode": "34243"
-                }
-            },
-            {
-                "HotelId": "3",
-                "HotelName": "Gastronomic Landscape Hotel",
-                "Description": "The Gastronomic Hotel stands out for its culinary excellence under the management of William Dough, who advises on and oversees all of the Hotel’s restaurant services.",
-                "Category": "Suite",
-                "Tags": ["restaurant", "bar", "continental breakfast"],
-                "ParkingIncluded": "true",
-                "LastRenovationDate": "2015-09-20T00:00:00Z",
-                "Rating": 4.8,
-                "Address": {
-                    "StreetAddress": "3393 Peachtree Rd",
-                    "City": "Atlanta",
-                    "StateProvince": "GA",
-                    "PostalCode": "30326"
-                }
-            },
-            {
-                "HotelId": "4",
-                "HotelName": "Sublime Palace Hotel",
-                "Description": "Sublime Palace Hotel is located in the heart of the historic center of Sublime in an extremely vibrant and lively area within short walking distance to the sites and landmarks of the city and is surrounded by the extraordinary beauty of churches, buildings, shops and monuments. Sublime Cliff is part of a lovingly restored 19th century resort, updated for every modern convenience.",
-                "Category": "Boutique",
-                "Tags": ["concierge", "view", "air conditioning"],
-                "ParkingIncluded": true,
-                "LastRenovationDate": "2020-02-06T00:00:00Z",
-                "Rating": 4.6,
-                "Address": {
-                    "StreetAddress": "7400 San Pedro Ave",
-                    "City": "San Antonio",
-                    "StateProvince": "TX",
-                    "PostalCode": "78216"
-                }
-            }
-        ]
-    }
-    ```
+## Understand the code
 
-1. Create a file named *hotels_quickstart_index.json* and paste the following code into *hotels_quickstart_index.json*:
-
-    ```json
-    {
-    	"name": "hotels-quickstart",
-    	"fields": [
-    		{
-    			"name": "HotelId",
-    			"type": "Edm.String",
-    			"key": true,
-    			"filterable": true
-    		},
-    		{
-    			"name": "HotelName",
-    			"type": "Edm.String",
-    			"searchable": true,
-    			"filterable": false,
-    			"sortable": true,
-    			"facetable": false
-    		},
-    		{
-    			"name": "Description",
-    			"type": "Edm.String",
-    			"searchable": true,
-    			"filterable": false,
-    			"sortable": false,
-    			"facetable": false,
-    			"analyzerName": "en.lucene"
-    		},
-    		{
-    			"name": "Category",
-    			"type": "Edm.String",
-    			"searchable": true,
-    			"filterable": true,
-    			"sortable": true,
-    			"facetable": true
-    		},
-    		{
-    			"name": "Tags",
-    			"type": "Collection(Edm.String)",
-    			"searchable": true,
-    			"filterable": true,
-    			"sortable": false,
-    			"facetable": true
-    		},
-    		{
-    			"name": "ParkingIncluded",
-    			"type": "Edm.Boolean",
-    			"filterable": true,
-    			"sortable": true,
-    			"facetable": true
-    		},
-    		{
-    			"name": "LastRenovationDate",
-    			"type": "Edm.DateTimeOffset",
-    			"filterable": true,
-    			"sortable": true,
-    			"facetable": true
-    		},
-    		{
-    			"name": "Rating",
-    			"type": "Edm.Double",
-    			"filterable": true,
-    			"sortable": true,
-    			"facetable": true
-    		},
-    		{
-    			"name": "Address",
-    			"type": "Edm.ComplexType",
-    			"fields": [
-    				{
-    					"name": "StreetAddress",
-    					"type": "Edm.String",
-    					"filterable": false,
-    					"sortable": false,
-    					"facetable": false,
-    					"searchable": true
-    				},
-    				{
-    					"name": "City",
-    					"type": "Edm.String",
-    					"searchable": true,
-    					"filterable": true,
-    					"sortable": true,
-    					"facetable": true
-    				},
-    				{
-    					"name": "StateProvince",
-    					"type": "Edm.String",
-    					"searchable": true,
-    					"filterable": true,
-    					"sortable": true,
-    					"facetable": true
-    				},
-    				{
-    					"name": "PostalCode",
-    					"type": "Edm.String",
-    					"searchable": true,
-    					"filterable": true,
-    					"sortable": true,
-    					"facetable": true
-    				},
-    				{
-    					"name": "Country",
-    					"type": "Edm.String",
-    					"searchable": true,
-    					"filterable": true,
-    					"sortable": true,
-    					"facetable": true
-    				}
-    			]
-    		}
-    	],
-    	"suggesters": [
-    		{
-    			"name": "sg",
-    			"searchMode": "analyzingInfixMatching",
-    			"sourceFields": [
-    				"HotelName"
-    			]
-    		}
-    	]
-    }
-    ```
+Now that you've run the code, let's break down the key steps:
 
-1. Sign in to Azure with the following command:
+1. [Create a search client](#create-a-search-client)
+1. [Create a search index](#create-a-search-index)
+1. [Upload documents to the index](#upload-documents-to-the-index)
+1. [Query the index](#query-the-index)
 
-    ```shell
-    az login
-    ```
+### Create a search client
 
-1. Run the JavaScript code with the following command:
+In `index.js`, you create two clients:
 
-    ```shell
-    node index.js
-    ```
+- [SearchIndexClient](/javascript/api/@azure/search-documents/searchindexclient) creates the index.
+- [SearchClient](/javascript/api/@azure/search-documents/searchclient) loads and queries an existing index.
 
-## Explaining the code
+Both clients require the service endpoint and a credential for authentication. In this quickstart, you use [DefaultAzureCredential](/javascript/api/@azure/identity/defaultazurecredential) for keyless authentication with Microsoft Entra ID.
 
-### Create index
+```javascript
+const credential = new DefaultAzureCredential();
+const indexClient = new SearchIndexClient(endpoint, credential);
+```
 
-The *hotels_quickstart_index.json* file defines how Azure AI Search works with the documents you load in the next step. Each field is identified by a `name` and has a specified `type`. Each field also has a series of index attributes that specify whether Azure AI Search can search, filter, sort, and facet upon the field. Most of the fields are simple data types, but some, like `AddressType` are complex types that allow you to create rich data structures in your index. You can read more about [supported data types](/rest/api/searchservice/supported-data-types) and index attributes described in [Create Index (REST)](/rest/api/searchservice/indexes/create). 
+### Create a search index
 
-With our index definition in place, we want to import *hotels_quickstart_index.json* at the top of *index.js* so the main function can access the index definition.
+This quickstart builds a hotels index that you load with hotel data and execute queries against. In this step, you import an index definition from a JSON file and create the index on your search service.
 
-```javascript
-const indexDefinition = require('./hotels_quickstart_index.json');
-```
+The `hotels_quickstart_index.json` file defines the index schema, including the fields and their attributes. Each field is identified by a `name` and has a specified `type`. Each field also has a series of index attributes that specify whether Azure AI Search can search, filter, sort, and facet upon the field. Most of the fields are simple data types, but some, like `Address`, are complex types that allow you to create rich data structures in your index. You can read more about [supported data types](/rest/api/searchservice/supported-data-types) and index attributes described in [Create Index (REST)](/rest/api/searchservice/indexes/create).
 
-Within the main function, we then create a `SearchIndexClient`, which is used to create and manage indexes for Azure AI Search. 
+The following code imports `hotels_quickstart_index.json` at the top of `index.js` so the main function can access the index definition.
 
 ```javascript
-const indexClient = new SearchIndexClient(endpoint, new AzureKeyCredential(apiKey));
+const indexDefinition = require('./hotels_quickstart_index.json');
 ```
 
-Next, we want to delete the index if it already exists. This operation is a common practice for test/demo code.
-
-We do this by defining a simple function that tries to delete the index.
+This quickstart deletes the index if it already exists, which is a common practice for test/demo code. The following function tries to delete the index.
 
 ```javascript
 async function deleteIndexIfExists(indexClient, indexName) {
@@ -563,7 +155,7 @@ async function deleteIndexIfExists(indexClient, indexName) {
 }
 ```
 
-To run the function, we extract the index name from the index definition and pass the `indexName` along with the `indexClient` to the `deleteIndexIfExists()` function.
+The following code extracts the index name from the index definition and passes the `indexName` along with the `indexClient` to the `deleteIndexIfExists()` function.
 
 ```javascript
 const indexName = indexDefinition["name"];
@@ -572,7 +164,7 @@ console.log('Checking if index exists...');
 await deleteIndexIfExists(indexClient, indexName);
 ```
 
-After that, we're ready to create the index with the `createIndex()` method.
+After that, you create the index with the `createIndex()` method.
 
 ```javascript
 console.log('Creating index...');
@@ -581,31 +173,25 @@ let index = await indexClient.createIndex(indexDefinition);
 console.log(`Index named ${index.name} has been created.`);
 ```
 
-### Load documents 
+### Upload documents to the index
 
-In Azure AI Search, documents are data structures that are both inputs to indexing and outputs from queries. You can push such data to the index or use an [indexer](/azure/search/search-indexer-overview). In this case, we'll programmatically push the documents to the index.
+In Azure AI Search, documents are data structures that are both inputs to indexing and outputs from queries. You can push such data to the index or use an [indexer](/azure/search/search-indexer-overview). In this quickstart, you programmatically push the documents to the index.
 
-Document inputs might be rows in a database, blobs in Blob storage, or, as in this sample, JSON documents on disk. Similar to what we did with the `indexDefinition`, we also need to import `hotels.json` at the top of *index.js* so that the data can be accessed in our main function.
+Document inputs might be rows in a database, blobs in Azure Blob Storage, or JSON documents on disk, as in this quickstart. Similar to the `indexDefinition`, you import `hotels.json` at the top of `index.js` so that the data can be accessed in the main function.
 
 ```javascript
 const hotelData = require('./hotels.json');
 ```
 
-To index data into the search index, we now need to create a `SearchClient`. While the `SearchIndexClient` is used to create and manage an index, the `SearchClient` is used to upload documents and query the index.
+To index data into the search index, you create a [SearchClient](/javascript/api/@azure/search-documents/searchclient). While `SearchIndexClient` creates and manages an index, `SearchClient` uploads documents and queries the index.
 
-There are two ways to create a `SearchClient`. The first option is to create a `SearchClient` from scratch:
-
-```javascript
- const searchClient = new SearchClient(endpoint, indexName, new AzureKeyCredential(apiKey));
-```
-
-Alternatively, you can use the `getSearchClient()` method of the `SearchIndexClient` to create the `SearchClient`:
+This quickstart obtains `SearchClient` from `SearchIndexClient` using [getSearchClient](/javascript/api/@azure/search-documents/searchindexclient#@azure-search-documents-searchindexclient-getsearchclient), which reuses the same credentials.
 
 ```javascript
 const searchClient = indexClient.getSearchClient(indexName);
 ```
 
-Now that the client is defined, upload the documents into the search index. In this case, we use the `mergeOrUploadDocuments()` method, which uploads the documents or merges them with an existing document if a document with the same key already exists.
+The following code uploads the documents into the search index using the `mergeOrUploadDocuments()` method, which uploads the documents or merges them with an existing document if a document with the same key already exists.
 
 ```javascript
 console.log('Uploading documents...');
@@ -614,17 +200,17 @@ let indexDocumentsResult = await searchClient.mergeOrUploadDocuments(hotelData['
 console.log(`Index operations succeeded: ${JSON.stringify(indexDocumentsResult.results[0].succeeded)}`);
 ```
 
-### Search an index
+### Query the index
 
-With an index created and documents uploaded, you're ready to send queries to the index. In this section, we send five different queries to the search index to demonstrate different pieces of query functionality available to you.
+With an index created and documents uploaded, you're ready to send queries to the index. This section sends five different queries to the search index to demonstrate different pieces of query functionality available to you.
 
-The queries are written in a `sendQueries()` function that we call in the main function as follows:
+The queries are written in a `sendQueries()` function called in the main function as follows:
 
 ```javascript
 await sendQueries(searchClient);
 ```
 
-Queries are sent using the `search()` method of `searchClient`. The first parameter is the search text and the second parameter specifies search options.
+The `search()` method of `searchClient` sends queries. The first parameter is the search text and the second parameter specifies search options.
 
 #### Query example 1
 
@@ -654,7 +240,7 @@ The remaining queries outlined below should also be added to the `sendQueries()`
 
 #### Query example 2
 
-In the next query, we specify the search term `"wifi"` and also include a filter to only return results where the state is equal to `'FL'`. Results are also ordered by the Hotel's `Rating`.
+The next query specifies the search term `"wifi"` and includes a filter to only return results where the state is equal to `'FL'`. Results are also ordered by the Hotel's `Rating`. A filter is a boolean expression evaluated over filterable fields in an index. Filter queries either include or exclude values. As such, there's no relevance score associated with a filter query.
 
 ```javascript
 console.log('Query #2 - Search with filter, orderBy, and select:');
@@ -673,7 +259,7 @@ for await (const result of searchResults.results) {
 
 #### Query example 3
 
-Next, the search is limited to a single searchable field using the `searchFields` parameter. This approach is a great option to make your query more efficient if you know you're only interested in matches in certain fields. 
+The third query limits the search to a single searchable field using the `searchFields` parameter. This approach is a great option to make your query more efficient if you know you're only interested in matches in certain fields.
 
 ```javascript
 console.log('Query #3 - Limit searchFields:');
@@ -682,20 +268,18 @@ searchOptions = {
     searchFields: ["HotelName"]
 };
 
-searchResults = await searchClient.search("Sublime Palace", searchOptions);
+searchResults = await searchClient.search("sublime cliff", searchOptions);
 for await (const result of searchResults.results) {
     console.log(`${JSON.stringify(result.document)}`);
 }
-console.log();
 ```
 
-
 #### Query example 4
 
-Another common option to include in a query is `facets`. Facets allow you to build out filters on your UI to make it easy for users to know what values they can filter down to.
+Another common option to include in a query is `facets`. Facets allow you to build out filters on your UI to make it easy for users to know what values they can filter down to. This query also limits the search to the `HotelName` field.
 
 ```javascript
-console.log('Query #4 - Use facets:');
+console.log('Query #4 - limit searchFields and use facets:');
 searchOptions = {
     facets: ["Category"],
     select: ["HotelId", "HotelName", "Rating"],
@@ -710,7 +294,7 @@ for await (const result of searchResults.results) {
 
 #### Query example 5
 
-The final query uses the `getDocument()` method of the `searchClient`. This allows you to efficiently retrieve a document by its key. 
+The final query uses the `getDocument()` method of the `searchClient`. This allows you to efficiently retrieve a document by its key.
 
 ```javascript
 console.log('Query #5 - Lookup document:');
@@ -720,6 +304,6 @@ console.log(`HotelId: ${documentResult.HotelId}; HotelName: ${documentResult.Hot
 
 #### Summary of queries
 
-The previous queries show multiple ways of matching terms in a query: full-text search, filters, and autocomplete.
+The previous queries show multiple ways of matching terms in a query: full-text search, filters, and document lookup.
 
-Full text search and filters are performed using the `searchClient.search` method. A search query can be passed in the `searchText` string, while a filter expression can be passed in the `filter` property of the `SearchOptions` class. To filter without searching, just pass "*" for the `searchText` parameter of the `search` method. To search without filtering, leave the `filter` property unset, or don't pass in a `SearchOptions` instance at all.
+The `searchClient.search` method performs full-text search and filters. You can pass a search query in the `searchText` string, while you pass a filter expression in the `filter` property of the `SearchOptions` class. To filter without searching, just pass `"*"` for the `searchText` parameter of the `search` method. To search without filtering, leave the `filter` property unset, or don't pass in a `SearchOptions` instance at all.

@@ -4,360 +4,237 @@ author: haileytap
 ms.author: haileytapia
 ms.service: azure-ai-search
 ms.topic: include
-ms.date: 06/30/2025
+ms.date: 02/02/2026
 ---
 
-In this quickstart, you use PowerShell and the [Azure AI Search REST APIs](/rest/api/searchservice/) to create, load, and query a search index for [full-text search](../../search-lucene-query-architecture.md). Full-text search uses Apache Lucene for indexing and queries and the BM25 ranking algorithm for scoring results.
+In this quickstart, you use PowerShell and the [Azure AI Search REST APIs](/rest/api/searchservice/) to create, load, and query a search index for [full-text search](../../search-lucene-query-architecture.md), also known as keyword search.
 
-This quickstart uses fictional hotel data from the [azure-search-sample-data](https://github.com/Azure-Samples/azure-search-sample-data/tree/main/hotels/hotel-json-documents) repo to populate the index.
+Full-text search uses Apache Lucene for indexing and queries and the BM25 ranking algorithm for scoring results. This quickstart uses fictional hotel data from the [azure-search-sample-data](https://github.com/Azure-Samples/azure-search-sample-data/tree/main/hotels/hotel-json-documents) GitHub repository to populate the index.
 
 > [!TIP]
-> You can download the [source code](https://github.com/Azure-Samples/azure-search-powershell-samples/tree/main/Quickstart) to start with a finished project or follow these steps to create your own.
+> Want to get started right away? Download the [source code](https://github.com/Azure-Samples/azure-search-powershell-samples/tree/main/Quickstart) on GitHub.
 
 ## Prerequisites
 
-+ An Azure account with an active subscription. [Create an account for free](https://azure.microsoft.com/pricing/purchase-options/azure-account?cid=msft_learn).
+- An Azure account with an active subscription. [Create an account for free](https://azure.microsoft.com/pricing/purchase-options/azure-account?cid=msft_learn).
 
-+ An Azure AI Search service. [Create a service](../../search-create-service-portal.md) or [find an existing service](https://portal.azure.com/#blade/HubsExtension/BrowseResourceBlade/resourceType/Microsoft.Search%2FsearchServices) in your current subscription. For this quickstart, you can use a free service.
+- An [Azure AI Search service](../../search-create-service-portal.md). You can use a free service for this quickstart.
 
-+ The [Azure CLI](/cli/azure/install-azure-cli) for keyless authentication with Microsoft Entra ID.
+- The latest version of [PowerShell](https://github.com/PowerShell/PowerShell).
 
-+ [PowerShell 7.3](https://github.com/PowerShell/PowerShell) or later. This quickstart uses [Invoke-RestMethod](/powershell/module/Microsoft.PowerShell.Utility/Invoke-RestMethod) to make REST API calls.
+- [Git](https://git-scm.com/downloads) to clone the sample repository.
 
-## Configure access
-
-You can connect to your Azure AI Search service using API keys or Microsoft Entra ID with role assignments. Keys are easier to start with, but roles are more secure.
-
-To configure the recommended role-based access:
-
-1. Sign in to the [Azure portal](https://portal.azure.com/) and select your search service.
-
-1. From the left pane, select **Settings** > **Keys**.
-
-1. Under **API Access control**, select **Both**.
-
-   This option enables both key-based and keyless authentication. After you assign roles, you can return to this step and select **Role-based access control**.
+- The [Azure CLI](/cli/azure/install-azure-cli) for keyless authentication with Microsoft Entra ID.
 
-1. From the left pane, select **Access control (IAM)**.
-
-1. Select **Add** > **Add role assignment**.
-
-1. Assign the **Search Service Contributor** and **Search Index Data Contributor** roles to your user account.
+## Configure access
 
-For more information, see [Connect to Azure AI Search using roles](../../search-security-rbac.md).
+[!INCLUDE [resource authentication](../resource-authentication.md)]
 
 ## Get endpoint
 
-In the next section, you specify the following endpoint to establish a connection to your Azure AI Search service. These steps assume that you [configured role-based access](#configure-access).
-
-To get your service endpoint:
-
-1. Sign in to the [Azure portal](https://portal.azure.com/) and select your search service.
-
-1. From the left pane, select **Overview**.
-
-1. Make a note of the URL, which should be similar to `https://my-service.search.windows.net`.
+[!INCLUDE [resource endpoint](../resource-endpoint.md)]
 
-## Connect to Azure AI Search
+## Set up the environment
 
-Before you can make REST API calls to your Azure AI Search service, you must authenticate and connect to the service. You perform the following steps in PowerShell, which supports the Azure CLI commands used in steps two and three.
+1. Use Git to clone the sample repository.
 
-To connect to your search service:
+   ```powershell
+   git clone https://github.com/Azure-Samples/azure-search-powershell-samples
+   ```
 
-1. On your local system, open PowerShell.
+1. Navigate to the `Quickstart` folder.
 
-1. Sign in to your Azure subscription. If you have multiple subscriptions, select the one that contains your search service.
+   ```powershell
+   cd azure-search-powershell-samples/Quickstart
+   ```
 
-    ```azurecli
-    az login
-    ```
+1. For keyless authentication with Microsoft Entra ID, sign in to your Azure account. If you have multiple subscriptions, select the one that contains your Azure AI Search service.
 
-1. Create a `$token` object to store your access token.
+   ```azurecli
+   az login
+   ```
 
-    ```azurecli
-    $token = az account get-access-token --resource https://search.azure.com/ --query accessToken --output tsv
-    ```
+1. Open the `azure-search-powershell-samples/Quickstart/azure-search-quickstart.ps1` file in a text editor.
 
-1. Create a `$headers` object to store your token and content type.
+1. Replace the placeholder value for `$baseUrl` with the URL you obtained in [Get endpoint](#get-endpoint).
 
-    ```powershell
-    $headers = @{
-    'Authorization' = "Bearer $token"
-    'Content-Type' = 'application/json' 
-    'Accept' = 'application/json' }
-    ```
+## Run the code
 
-    You only need to set the header once per session, but you must add it to each request.
+In the same terminal, run the following PowerShell script to execute this quickstart.
 
-1. Create a `$url` object that targets the indexes collection on your search service. Replace `<YOUR-SEARCH-SERVICE>` with the value you obtained in [Get endpoint](#get-endpoint).
-
-    ```powershell
-    $url = "<YOUR-SEARCH-SERVICE>/indexes?api-version=2025-09-01&`$select=name"
-    ```
-
-1. Run `Invoke-RestMethod` to send a GET request to your search service. Include `ConvertTo-Json` to view responses from the service.
+```powershell
+.\azure-search-quickstart.ps1
+```
 
-    ```powershell
-    Invoke-RestMethod -Uri $url -Headers $headers | ConvertTo-Json
-    ```
+### Output
 
-   If your service is empty and has no indexes, the response is similar to the following example. Otherwise, you see a JSON representation of index definitions.
+The script deletes any existing index, creates a new index, uploads documents, and runs multiple full-text search queries. The output shows the full HTTP requests and responses for each operation. The following example shows the response when searching for "restaurant wifi".
 
-    ```json
+```json
+{
+  "value": [
     {
-        "@odata.context":  "https://my-service.search.windows.net/$metadata#indexes",
-        "value":  [
-
-                  ]
+      "@search.score": 0.6931472,
+      "HotelName": "Old Century Hotel",
+      "Description": "The hotel is situated in a nineteenth century plaza, which has been expanded and renovated to the highest architectural standards to create a modern, functional and first-class hotel in which art and unique historical elements coexist with the most modern comforts. The hotel also regularly hosts events like wine tastings, beer dinners, and live music.",
+      "Tags": ["pool", "free wifi", "concierge"]
+    },
+    {
+      "@search.score": 0.5575875,
+      "HotelName": "Gastronomic Landscape Hotel",
+      "Description": "The Gastronomic Hotel stands out for its culinary excellence under the management of William Dough, who advises on and oversees all of the Hotel's restaurant services.",
+      "Tags": ["restaurant", "bar", "continental breakfast"]
     }
-    ```
-
-## Create a search index
-
-Before you add content to Azure AI Search, you must create an index to define how the content is stored and structured. An index is conceptually similar to a table in a relational database, but it's specifically designed for search operations, such as full-text search.
-
-Run the following commands in the same PowerShell session you started in the previous section.
+  ]
+}
+```
 
-To create an index:
+## Understand the code
 
-1. Create a `$body` object to define the index schema.
+Now that you've run the code, let's break down the key steps:
 
-    ```powershell
-    $body = @"
-    {
-        "name": "hotels-quickstart",  
-        "fields": [
-            {"name": "HotelId", "type": "Edm.String", "key": true, "filterable": true},
-            {"name": "HotelName", "type": "Edm.String", "searchable": true, "filterable": false, "sortable": true, "facetable": false},
-            {"name": "Description", "type": "Edm.String", "searchable": true, "filterable": false, "sortable": false, "facetable": false, "analyzer": "en.lucene"},
-            {"name": "Category", "type": "Edm.String", "searchable": true, "filterable": true, "sortable": true, "facetable": true},
-            {"name": "Tags", "type": "Collection(Edm.String)", "searchable": true, "filterable": true, "sortable": false, "facetable": true},
-            {"name": "ParkingIncluded", "type": "Edm.Boolean", "filterable": true, "sortable": true, "facetable": true},
-            {"name": "LastRenovationDate", "type": "Edm.DateTimeOffset", "filterable": true, "sortable": true, "facetable": true},
-            {"name": "Rating", "type": "Edm.Double", "filterable": true, "sortable": true, "facetable": true},
-            {"name": "Address", "type": "Edm.ComplexType", 
-                "fields": [
-                {"name": "StreetAddress", "type": "Edm.String", "filterable": false, "sortable": false, "facetable": false, "searchable": true},
-                {"name": "City", "type": "Edm.String", "searchable": true, "filterable": true, "sortable": true, "facetable": true},
-                {"name": "StateProvince", "type": "Edm.String", "searchable": true, "filterable": true, "sortable": true, "facetable": true},
-                {"name": "PostalCode", "type": "Edm.String", "searchable": true, "filterable": true, "sortable": true, "facetable": true},
-                {"name": "Country", "type": "Edm.String", "searchable": true, "filterable": true, "sortable": true, "facetable": true}
-            ]
-         }
-      ]
-    }
-    "@
-    ```
+1. [Create a search index](#create-a-search-index)
+1. [Upload documents to the index](#upload-documents-to-the-index)
+1. [Query the index](#query-the-index)
 
-2. Update the `$url` object to target the new index. Replace `<YOUR-SEARCH-SERVICE>` with the value you obtained in [Get endpoint](#get-endpoint).
+### Create a search index
 
-    ```powershell
-    $url = "<YOUR-SEARCH-SERVICE>/indexes/hotels-quickstart?api-version=2025-09-01"
-    ```
-
-3. Run `Invoke-RestMethod` to create the index on your search service.
+Before you add content to Azure AI Search, you must create an index to define how the content is stored and structured. An index is conceptually similar to a table in a relational database, but it's specifically designed for search operations, such as full-text search.
 
-    ```powershell
-    Invoke-RestMethod -Uri $url -Headers $headers -Method Put -Body $body | ConvertTo-Json
-    ```
+This quickstart first deletes any existing index with the same name, which is a common practice for test/demo code that runs repeatedly.
 
-    The response should contain the JSON representation of the index schema.
+```powershell
+Send-Request DELETE "$baseUrl/indexes/hotels-quickstart?api-version=2025-09-01" $headers
+```
 
-### About the create index request
+This quickstart then calls [Indexes - Create (REST API)](/rest/api/searchservice/indexes/create) to build a search index named `hotels-quickstart` and its physical data structures on your search service.
 
-This quickstart calls [Indexes - Create (REST API)](/rest/api/searchservice/indexes/create) to build a search index named `hotels-quickstart` and its physical data structures on your search service.
+```powershell
+$body = @"
+{
+    "name": "hotels-quickstart",
+    "fields": [
+        {"name": "HotelId", "type": "Edm.String", "key": true, "filterable": true},
+        {"name": "HotelName", "type": "Edm.String", "searchable": true, "filterable": false, "sortable": true, "facetable": false},
+        {"name": "Description", "type": "Edm.String", "searchable": true, "filterable": false, "sortable": false, "facetable": false, "analyzer": "en.lucene"},
+        ...
+    ]
+}
+"@
+
+Send-RequestWithBody POST "$baseUrl/indexes?api-version=2025-09-01" $headers $body
+```
 
 Within the index schema, the `fields` collection defines the structure of hotel documents. Each field has a `name`, data `type`, and attributes that determine its behavior during indexing and queries. The `HotelId` field is marked as the key, which Azure AI Search requires to uniquely identify each document in an index.
 
 Key points about the index schema:
 
 + Use string fields (`Edm.String`) to make numeric data full-text searchable. Other [supported data types](/rest/api/searchservice/supported-data-types), such as `Edm.Int32`, are filterable, sortable, facetable, and retrievable but aren't searchable.
 
-+ Most of our fields are simple data types, but you can define complex types to represent nested data, such as the `Address` field.
++ Most of the fields are simple data types, but you can define complex types to represent nested data, such as the `Address` field.
 
 + Field attributes determine allowed actions. The REST APIs allow [many actions by default](/rest/api/searchservice/indexes/create#request-body). For example, all strings are searchable and retrievable. With the REST APIs, you might only use attributes if you need to disable a behavior.
 
-## Load the index
+### Upload documents to the index
 
 Newly created indexes are empty. To populate an index and make it searchable, you must upload JSON documents that conform to the index schema.
 
 In Azure AI Search, documents serve as both inputs for indexing and outputs for queries. For simplicity, this quickstart provides sample hotel documents as inline JSON. In production scenarios, however, content is often pulled from connected data sources and transformed into JSON using [indexers](../../search-indexer-overview.md).
 
-To upload documents to your index:
-
-1. Create a `$body` object to store the JSON payload of four sample documents.
+This quickstart calls [Documents - Index (REST API)](/rest/api/searchservice/documents/) to add four sample hotel documents to your index. Compared to the previous request, the URI is extended to include the `docs` collection and `index` operation.
 
-    ```powershell
-    $body = @"
+```powershell
+$body = @"
+{
+    "value": [
         {
-            "value": [
-            {
             "@search.action": "upload",
             "HotelId": "1",
             "HotelName": "Stay-Kay City Hotel",
-            "Description": "This classic hotel is fully-refurbished and ideally located on the main commercial artery of the city in the heart of New York. A few minutes away is Times Square and the historic centre of the city, as well as other places of interest that make New York one of America's most attractive and cosmopolitan cities.",
-            "Category": "Boutique",
-            "Tags": [ "view", "air conditioning", "concierge" ],
-            "ParkingIncluded": false,
-            "LastRenovationDate": "2022-01-18T00:00:00Z",
-            "Rating": 3.60,
-            "Address": 
-                {
-                "StreetAddress": "677 5th Ave",
-                "City": "New York",
-                "StateProvince": "NY",
-                "PostalCode": "10022",
-                "Country": "USA"
-                } 
-            },
-            {
-            "@search.action": "upload",
-            "HotelId": "2",
-            "HotelName": "Old Century Hotel",
-            "Description": "The hotel is situated in a nineteenth century plaza, which has been expanded and renovated to the highest architectural standards to create a modern, functional and first-class hotel in which art and unique historical elements coexist with the most modern comforts. The hotel also regularly hosts events like wine tastings, beer dinners, and live music.",
-            "Category": "Boutique",
-            "Tags": [ "pool", "free wifi", "concierge" ],
-            "ParkingIncluded": false,
-            "LastRenovationDate": "2019-02-18T00:00:00Z",
-            "Rating": 3.60,
-            "Address": 
-                {
-                "StreetAddress": "140 University Town Center Dr",
-                "City": "Sarasota",
-                "StateProvince": "FL",
-                "PostalCode": "34243",
-                "Country": "USA"
-                } 
-            },
-            {
-            "@search.action": "upload",
-            "HotelId": "3",
-            "HotelName": "Gastronomic Landscape Hotel",
-            "Description": "The Gastronomic Hotel stands out for its culinary excellence under the management of William Dough, who advises on and oversees all of the Hotel’s restaurant services.",
-            "Category": "Suite",
-            "Tags": [ "restaurant", "bar", "continental breakfast" ],
-            "ParkingIncluded": true,
-            "LastRenovationDate": "2015-09-20T00:00:00Z",
-            "Rating": 4.80,
-            "Address": 
-                {
-                "StreetAddress": "3393 Peachtree Rd",
-                "City": "Atlanta",
-                "StateProvince": "GA",
-                "PostalCode": "30326",
-                "Country": "USA"
-                } 
-            },
-            {
-            "@search.action": "upload",
-            "HotelId": "4",
-            "HotelName": "Sublime Palace Hotel",
-            "Description": "Sublime Palace Hotel is located in the heart of the historic center of Sublime in an extremely vibrant and lively area within short walking distance to the sites and landmarks of the city and is surrounded by the extraordinary beauty of churches, buildings, shops and monuments. Sublime Cliff is part of a lovingly restored 19th century resort, updated for every modern convenience.",
-            "Category": "Boutique",
-            "Tags": [ "concierge", "view", "air conditioning" ],
-            "ParkingIncluded": true,
-            "LastRenovationDate": "2020-02-06T00:00:00Z",
-            "Rating": 4.60,
-            "Address": 
-                {
-                "StreetAddress": "7400 San Pedro Ave",
-                "City": "San Antonio",
-                "StateProvince": "TX",
-                "PostalCode": "78216",
-                "Country": "USA"
-                }
-            }
-          ]
-        }
-    "@
-    ```
-
-2. Update the `$url` object to target the indexing endpoint. Replace `<YOUR-SEARCH-SERVICE>` with the value you obtained in [Get endpoint](#get-endpoint).
-
-    ```powershell
-    $url = "<YOUR-SEARCH-SERVICE>/indexes/hotels-quickstart/docs/index?api-version=2025-09-01"
-    ```
-
-3. Run `Invoke-RestMethod` to send the upload request to your search service.
-
-    ```powershell
-    Invoke-RestMethod -Uri $url -Headers $headers -Method Post -Body $body | ConvertTo-Json
-    ```
-
-    The response should contain the key and status of each uploaded document.
-
-### About the upload request
-
-This quickstart calls [Documents - Index (REST API)](/rest/api/searchservice/documents/) to add four sample hotel documents to your index. Compared to the previous request, the URI is extended to include the `docs` collection and `index` operation.
+            "Description": "This classic hotel is...",
+            ...
+        },
+        ...
+    ]
+}
+"@
+
+Send-RequestWithBody POST "$baseUrl/indexes/hotels-quickstart/docs/index?api-version=2025-09-01" $headers $body
+```
 
-Each document in the `value` array represents a hotel and contains fields that match the index schema. The `@search.action` parameter specifies the operation to perform for each document. Our example uses `upload`, which adds the document if it doesn't exist or updates the document if it does exist.
+Each document in the `value` array represents a hotel and contains fields that match the index schema. The `@search.action` parameter specifies the operation to perform for each document. This example uses `upload`, which adds the document if it doesn't exist or updates the document if it does exist.
 
-## Query the index
+### Query the index
 
 Now that documents are loaded into your index, you can use full-text search to find specific terms or phrases within their fields.
 
-To run a full-text query against your index:
+This quickstart calls [Documents - Search Post (REST API)](/rest/api/searchservice/documents/search-post) to find hotel documents that match your search criteria. The URI targets the `/docs/search` operation.
 
-1. Update the `$url` object to specify search parameters. Replace `<YOUR-SEARCH-SERVICE>` with the value you obtained in [Get endpoint](#get-endpoint).
+Full-text search requests include a `search` parameter with the query text, which can contain terms, phrases, or operators. The query searches across all searchable fields in each document. The following examples demonstrate common query patterns.
 
-    ```powershell
-    $url = '<YOUR-SEARCH-SERVICE>/indexes/hotels-quickstart/docs?api-version=2025-09-01&search=attached restaurant&searchFields=Description,Tags&$select=HotelId,HotelName,Tags,Description&$count=true'
-    ```
+#### Query example 1
 
-2. Run `Invoke-RestMethod` to send the query request to your search service.
+The following query searches for the terms "restaurant wifi" across all searchable fields. By default, Azure AI Search returns documents that match any of the search terms.
 
-    ```powershell
-    Invoke-RestMethod -Uri $url -Headers $headers | ConvertTo-Json
-    ```
+```powershell
+$body = @"
+{
+    "search": "restaurant wifi",
+    "select": "HotelName, Description, Tags"
+}
+"@
+
+Send-RequestWithBody POST "$baseUrl/indexes/hotels-quickstart/docs/search?api-version=2025-09-01" $headers $body
+```
 
-    The response should be similar to the following example, which shows one matching hotel document, its relevance score, and its selected fields.
+The `select` parameter limits the fields returned in the response to `HotelName`, `Description`, and `Tags`.
 
-    ```json
-    {
-      "@odata.context": "https://my-service.search.windows.net/indexes('hotels-quickstart')/$metadata#docs(*)",
-      "@odata.count": 1,
-      "value": [
-        {
-          "@search.score": 0.5575875,
-          "HotelId": "3",
-          "HotelName": "Gastronomic Landscape Hotel",
-          "Description": "The Gastronomic Hotel stands out for its culinary excellence under the management of William Dough, who advises on and oversees all of the Hotel's restaurant services.",
-          "Tags": "restaurant bar continental breakfast"
-        }
-      ]
-    }
-    ```
+#### Query example 2
 
-### About the query request
+The following query uses a `filter` expression to return only hotels with a rating greater than 4.
 
-This quickstart calls [Documents - Search Post (REST API)](/rest/api/searchservice/documents/search-post) to find hotel documents that match your search criteria. The URI still targets the `docs` collection but no longer includes the `index` operation.
+```powershell
+$body = @"
+{
+    "search": "*",
+    "filter": "Rating gt 4",
+    "select": "HotelName,Rating"
+}
+"@
+
+Send-RequestWithBody POST "$baseUrl/indexes/hotels-quickstart/docs/search?api-version=2025-09-01" $headers $body
+```
+
+The `search` parameter is set to `*`, which matches all documents. The `filter` parameter applies a Boolean condition to narrow the results.
 
-Full-text search requests always include a `search` parameter that contains the query text. The query text can include one or more terms, phrases, or operators. In addition to `search`, you can specify other parameters to refine the search behavior and results.
+#### Query example 3
 
-Our query searches for the terms "attached restaurant" in the `Description` and `Tags` fields of each hotel document. The `$select` parameter limits the fields returned in the response to `HotelId`, `HotelName`, `Tags`, and `Description`. The `$count` parameter requests the total number of matching documents.
+The following query searches for "boutique" and uses `top` to return only the first two results.
+
+```powershell
+$body = @"
+{
+    "search": "boutique",
+    "select": "HotelName,Category",
+    "top": 2
+}
+"@
+
+Send-RequestWithBody POST "$baseUrl/indexes/hotels-quickstart/docs/search?api-version=2025-09-01" $headers $body
+```
 
-#### Other query examples
+#### Query example 4
 
-Run the following commands to explore the query syntax. You can perform string searches, use `$filter` expressions, limit result sets, select specific fields, and more. Remember to replace `<YOUR-SEARCH-SERVICE>` with the value you obtained in [Get endpoint](#get-endpoint).
+The following query searches for "pool" and uses `orderby` to sort results by `Rating` in descending order.
 
 ```powershell
-# Query example 1
-# Search the index for the terms 'restaurant' and 'wifi'
-# Return only the HotelName, Description, and Tags fields
-$url = '<YOUR-SEARCH-SERVICE>/indexes/hotels-quickstart/docs?api-version=2025-09-01&search=restaurant wifi&$count=true&$select=HotelName,Description,Tags'
-
-# Query example 2 
-# Use a filter to find hotels rated 4 or higher
-# Return only the HotelName and Rating fields
-$url = '<YOUR-SEARCH-SERVICE>/indexes/hotels-quickstart/docs?api-version=2025-09-01&search=*&$filter=Rating gt 4&$select=HotelName,Rating'
-
-# Query example 3
-# Take the top two results
-# Return only the HotelName and Category fields
-$url = '<YOUR-SEARCH-SERVICE>/indexes/hotels-quickstart/docs?api-version=2025-09-01&search=boutique&$top=2&$select=HotelName,Category'
-
-# Query example 4
-# Sort by a specific field (Address/City) in ascending order
-# Return only the HotelName, Address/City, Tags, and Rating fields
-$url = '<YOUR-SEARCH-SERVICE>/indexes/hotels-quickstart/docs?api-version=2025-09-01&search=pool&$orderby=Address/City asc&$select=HotelName, Address/City, Tags, Rating'
+$body = @"
+{
+    "search": "pool",
+    "select": "HotelName,Description,Tags,Rating",
+    "orderby": "Rating desc"
+}
+"@
+
+Send-RequestWithBody POST "$baseUrl/indexes/hotels-quickstart/docs/search?api-version=2025-09-01" $headers $body
 ```