dotnet · dotnet-policy-service · May 10, 2025 · May 9, 2025 · May 9, 2025 · May 9, 2025
diff --git a/docs/ai/quickstarts/build-chat-app.md b/docs/ai/quickstarts/build-chat-app.md
@@ -1,6 +1,6 @@
 ---
 title: Quickstart - Build an AI chat app with .NET
-description: Create a simple AI powered chat app using Semantic Kernel SDK for .NET and the OpenAI or Azure OpenAI SDKs
+description: Create a simple AI powered chat app using Microsoft.Extensions.AI and the OpenAI or Azure OpenAI SDKs
 ms.date: 04/09/2025
 ms.topic: quickstart
 ms.custom: devx-track-dotnet, devx-track-dotnet-ai
@@ -31,8 +31,6 @@ In this quickstart, you learn how to create a conversational .NET console chat a
 
 [!INCLUDE [semantic-kernel](includes/semantic-kernel.md)]
 
-[!INCLUDE [clone-sample-repo](includes/clone-sample-repo.md)]
-
 ## Create the app
 
 Complete the following steps to create a .NET console app to connect to an AI model.
@@ -104,13 +102,13 @@ Complete the following steps to create a .NET console app to connect to an AI mo
 
 ## Add the app code
 
-The app uses the [`Microsoft.Extensions.AI`](https://www.nuget.org/packages/Microsoft.Extensions.AI/) package to send and receive requests to the AI model and is designed to provide users with information about hiking trails.
+This app uses the [`Microsoft.Extensions.AI`](https://www.nuget.org/packages/Microsoft.Extensions.AI/) package to send and receive requests to the AI model. The app provides users with information about hiking trails.
 
-1. In the **Program.cs** file, add the following code to connect and authenticate to the AI model.
+1. In the `Program.cs` file, add the following code to connect and authenticate to the AI model.
 
     :::zone target="docs" pivot="azure-openai"
 
-    :::code language="csharp" source="snippets/build-chat-app/azure-openai/program.cs" range="1-12":::
+    :::code language="csharp" source="snippets/build-chat-app/azure-openai/program.cs" id="GetChatClient":::
 
     > [!NOTE]
     > <xref:Azure.Identity.DefaultAzureCredential> searches for authentication credentials from your local tooling. If you aren't using the `azd` template to provision the Azure OpenAI resource, you'll need to assign the `Azure AI Developer` role to the account you used to sign in to Visual Studio or the Azure CLI. For more information, see [Authenticate to Azure AI services with .NET](../azure-ai-services-authentication.md).
@@ -119,17 +117,17 @@ The app uses the [`Microsoft.Extensions.AI`](https://www.nuget.org/packages/Micr
 
     :::zone target="docs" pivot="openai"
 
-    :::code language="csharp" source="snippets/build-chat-app/openai/program.cs" range="1-11":::
+    :::code language="csharp" source="snippets/build-chat-app/openai/program.cs" id="GetChatClient":::
 
     :::zone-end
 
 1. Create a system prompt to provide the AI model with initial role context and instructions about hiking recommendations:
 
-    :::code language="csharp" source="snippets/build-chat-app/openai/program.cs" range="13-30":::
+    :::code language="csharp" source="snippets/build-chat-app/openai/program.cs" id="FirstMessage":::
 
 1. Create a conversational loop that accepts an input prompt from the user, sends the prompt to the model, and prints the response completion:
 
-    :::code language="csharp" source="snippets/build-chat-app/openai/program.cs" range="32-51":::
+    :::code language="csharp" source="snippets/build-chat-app/openai/program.cs" id="ChatLoop":::
 
 1. Use the `dotnet run` command to run the app:
 
@@ -143,11 +141,10 @@ The app uses the [`Microsoft.Extensions.AI`](https://www.nuget.org/packages/Micr
 
 ## Clean up resources
 
-When you no longer need the sample application or resources, remove the corresponding deployment and all resources.
+If you no longer need them, delete the Azure OpenAI resource and GPT-4 model deployment.
 
-```azdeveloper
-azd down
-```
+1. In the [Azure Portal](https://aka.ms/azureportal), navigate to the Azure OpenAI resource.
+1. Select the Azure OpenAI resource, and then select **Delete**.
 
 :::zone-end
 

diff --git a/docs/ai/quickstarts/build-vector-search-app.md b/docs/ai/quickstarts/build-vector-search-app.md
@@ -26,8 +26,6 @@ In this quickstart, you create a .NET console app to perform semantic search on
 
 :::zone-end
 
-[!INCLUDE [clone-sample-repo](includes/clone-sample-repo.md)]
-
 ## Interact with your data using vector stores
 
 Vector stores or vector databases are essential for tasks like semantic search, Retrieval Augmented Generation (RAG), and other scenarios that require grounding generative AI responses. While relational databases and document databases are optimized for structured and semi-structured data, vector databases are built to efficiently store, index, and manage data represented as embedding vectors. As a result, the indexing and search algorithms used by vector databases are optimized to efficiently retrieve data that can be used downstream in your applications.
@@ -171,7 +169,7 @@ Complete the following steps to create a .NET console app that can:
 
     :::zone target="docs" pivot="openai"
 
-    :::code language="csharp" source="snippets/chat-with-data/openai/program.cs" range="49-57":::
+    :::code language="csharp" source="snippets/chat-with-data/openai/program.cs" id="EmbeddingGenerator":::
 
     :::zone-end
 
@@ -197,11 +195,10 @@ Complete the following steps to create a .NET console app that can:
 
 ## Clean up resources
 
-When you no longer need the sample application or resources, remove the corresponding deployment and all resources.
+If you no longer need them, delete the Azure OpenAI resource and GPT-4 model deployment.
 
-```azdeveloper
-azd down
-```
+1. In the [Azure Portal](https://aka.ms/azureportal), navigate to the Azure OpenAI resource.
+1. Select the Azure OpenAI resource, and then select **Delete**.
 
 :::zone-end
 

diff --git a/docs/ai/quickstarts/chat-local-model.md b/docs/ai/quickstarts/chat-local-model.md
@@ -84,12 +84,12 @@ The Semantic Kernel SDK provides many services and features to connect to AI mod
 
     The preceding code accomplishes the following:
 
-    - Creates an `OllamaChatClient` that implements the `IChatClient` interface.
-        - This interface provides a loosely coupled abstraction you can use to chat with AI Models.
-        - You can later change the underlying chat client implementation to another model, such as Azure OpenAI, without changing any other code.
-    - Creates a `ChatHistory` object to store the messages between the user and the AI model.
-    - Retrieves a prompt from the user and stores it in the `ChatHistory`.
-    - Sends the chat data to the AI model to generate a response.
+    * Creates an `OllamaChatClient` that implements the `IChatClient` interface.
+        * This interface provides a loosely coupled abstraction you can use to chat with AI Models.
+        * You can later change the underlying chat client implementation to another model, such as Azure OpenAI, without changing any other code.
+    * Creates a `ChatHistory` object to store the messages between the user and the AI model.
+    * Retrieves a prompt from the user and stores it in the `ChatHistory`.
+    * Sends the chat data to the AI model to generate a response.
 
     > [!NOTE]
     > Ollama runs on port 11434 by default, which is why the AI model endpoint is set to `http://localhost:11434`.
@@ -146,4 +146,4 @@ The Semantic Kernel SDK provides many services and features to connect to AI mod
 
 ## Next steps
 
-- [Generate text and conversations with .NET and Azure OpenAI Completions](/training/modules/open-ai-dotnet-text-completions/)
+* [Generate text and conversations with .NET and Azure OpenAI Completions](/training/modules/open-ai-dotnet-text-completions/)
diff --git a/docs/ai/quickstarts/create-assistant.md b/docs/ai/quickstarts/create-assistant.md
@@ -107,27 +107,27 @@ Complete the following steps to create a .NET console app and add the package ne
 
 ## Create the AI assistant client
 
-1. Open the _Program.cs_ file and replace the contents of the file with the following code to create the required clients:
+1. Open the `Program.cs` file and replace the contents of the file with the following code to create the required clients:
 
-    :::code language="csharp" source="snippets/assistants/program.cs" range="0-17" :::
+    :::code language="csharp" source="snippets/assistants/program.cs" id="CreateClient" :::
 
 1. Create an in-memory sample document and upload it to the `OpenAIFileClient`:
 
-    :::code language="csharp" source="snippets/assistants/program.cs" range="19-53" :::
+    :::code language="csharp" source="snippets/assistants/program.cs" id="CreateDocument" :::
 
 1. Enable file search and code interpreter tooling capabilities via the `AssistantCreationOptions`:
 
-    :::code language="csharp" source="snippets/assistants/program.cs" range="55-78" :::
+    :::code language="csharp" source="snippets/assistants/program.cs" id="EnableTools" :::
 
 1. Create the `Assistant` and a thread to manage interactions between the user and the assistant:
 
-    :::code language="csharp" source="snippets/assistants/program.cs" range="80-105" :::
+    :::code language="csharp" source="snippets/assistants/program.cs" id="CreateAssistant" :::
 
 1. Print the messages and save the generated image from the conversation with the assistant:
 
-    :::code language="csharp" source="snippets/assistants/program.cs" range="107-147" :::
+    :::code language="csharp" source="snippets/assistants/program.cs" id="ProcessMessages" :::
 
-    Locate and open the saved image in the app *bin* directory, which should resemble the following:
+    Locate and open the saved image in the app `bin` directory, which should resemble the following:
 
     :::image type="content" source="../media/assistants/generated-sales-graph.png" alt-text="A graph showing the visualization generated by the AI model.":::
 

diff --git a/docs/ai/quickstarts/evaluate-ai-response.md b/docs/ai/quickstarts/evaluate-ai-response.md
@@ -96,6 +96,13 @@ Complete the following steps to create an MSTest project that connects to the `g
 
 Run the test using your preferred test workflow, for example, by using the CLI command `dotnet test` or through [Test Explorer](/visualstudio/test/run-unit-tests-with-test-explorer).
 
+## Clean up resources
+
+If you no longer need them, delete the Azure OpenAI resource and GPT-4 model deployment.
+
+1. In the [Azure Portal](https://aka.ms/azureportal), navigate to the Azure OpenAI resource.
+1. Select the Azure OpenAI resource, and then select **Delete**.
+
 ## Next steps
 
 - Evaluate the responses from different OpenAI models.

diff --git a/docs/ai/quickstarts/generate-images.md b/docs/ai/quickstarts/generate-images.md
@@ -28,8 +28,6 @@ In this quickstart, you learn how to create a .NET console app to generate image
 
 [!INCLUDE [semantic-kernel](includes/semantic-kernel.md)]
 
-[!INCLUDE [clone-sample-repo](includes/clone-sample-repo.md)]
-
 ## Create the app
 
 Complete the following steps to create a .NET console app to connect to an AI model.
@@ -134,11 +132,10 @@ Complete the following steps to create a .NET console app to connect to an AI mo
 
 ## Clean up resources
 
-When you no longer need the sample application or resources, remove the corresponding deployment and all resources.
+If you no longer need them, delete the Azure OpenAI resource and GPT-4 model deployment.
 
-```azdeveloper
-azd down
-```
+1. In the [Azure Portal](https://aka.ms/azureportal), navigate to the Azure OpenAI resource.
+1. Select the Azure OpenAI resource, and then select **Delete**.
 
 :::zone-end
 

diff --git a/docs/ai/quickstarts/includes/clone-sample-repo.md b/docs/ai/quickstarts/includes/clone-sample-repo.md
diff --git a/docs/ai/quickstarts/includes/create-ai-service.md b/docs/ai/quickstarts/includes/create-ai-service.md
@@ -1,7 +1,5 @@
 ## Create the AI service
 
-# [Azure Portal or Azure CLI](#tab/azure-cli)
-
 1. To provision an Azure OpenAI service and model, complete the steps in the [Create and deploy an Azure OpenAI Service resource](/azure/ai-services/openai/how-to/create-resource) article.
 
 1. From a terminal or command prompt, navigate to the root of your project directory.
@@ -13,9 +11,3 @@
     dotnet user-secrets set AZURE_OPENAI_ENDPOINT <your-azure-openai-endpoint>
     dotnet user-secrets set AZURE_OPENAI_GPT_NAME <your-azure-openai-model-name>
     ```
-
-# [Azure Developer CLI](#tab/azd)
-
-[!INCLUDE [deploy-azd](deploy-azd.md)]
-
----
diff --git a/docs/ai/quickstarts/includes/deploy-azd.md b/docs/ai/quickstarts/includes/deploy-azd.md
diff --git a/docs/ai/quickstarts/prompt-model.md b/docs/ai/quickstarts/prompt-model.md
@@ -31,8 +31,6 @@ In this quickstart, you learn how to create a .NET console chat app to connect t
 
 [!INCLUDE [semantic-kernel](includes/semantic-kernel.md)]
 
-[!INCLUDE [clone-sample-repo](includes/clone-sample-repo.md)]
-
 ## Create the app
 
 Complete the following steps to create a .NET console app to connect to an AI model.
@@ -141,11 +139,10 @@ The app uses the [`Microsoft.Extensions.AI`](https://www.nuget.org/packages/Micr
 
 ## Clean up resources
 
-When you no longer need the sample application or resources, remove the corresponding deployment and all resources.
+If you no longer need them, delete the Azure OpenAI resource and GPT-4 model deployment.
 
-```azdeveloper
-azd down
-```
+1. In the [Azure Portal](https://aka.ms/azureportal), navigate to the Azure OpenAI resource.
+1. Select the Azure OpenAI resource, and then select **Delete**.
 
 :::zone-end
 

diff --git a/docs/ai/quickstarts/snippets/assistants/Program.cs b/docs/ai/quickstarts/snippets/assistants/Program.cs
@@ -1,4 +1,5 @@
-using OpenAI;
+// <SnippetCreateClient>
+using OpenAI;
 using OpenAI.Assistants;
 using OpenAI.Files;
 using Azure.AI.OpenAI;
@@ -15,7 +16,9 @@
 #pragma warning disable OPENAI001
 AssistantClient assistantClient = openAIClient.GetAssistantClient();
 OpenAIFileClient fileClient = openAIClient.GetOpenAIFileClient();
+// </SnippetCreateClient>
 
+// <SnippetCreateDocument>
 // Create an in-memory document to upload to the file client
 using Stream document = BinaryData.FromBytes("""
     {
@@ -51,7 +54,9 @@
     document,
     "monthly_sales.json",
     FileUploadPurpose.Assistants);
+// </SnippetCreateDocument>
 
+// <SnippetEnableTools>
 // Configure the assistant options
 AssistantCreationOptions assistantOptions = new()
 {
@@ -76,7 +81,9 @@
         }
     },
 };
+// </SnippetEnableTools>
 
+// <SnippetCreateAssistant>
 // Create the assistant
 Assistant assistant = assistantClient.CreateAssistant("gpt-4o", assistantOptions);
 
@@ -100,10 +107,13 @@
 var messages = assistantClient.GetMessagesAsync(
     threadRun.ThreadId,
     new MessageCollectionOptions()
-    { 
+    {
         Order = MessageCollectionOrder.Ascending
     });
+// </SnippetCreateAssistant>
 
+// <SnippetProcessMessages>
+// Process the messages from the assistant
 await foreach (ThreadMessage message in messages)
 {
     // Print out the messages from the assistant
@@ -144,4 +154,5 @@
         }
     }
     Console.WriteLine();
-}
+}
+// </SnippetProcessMessages>
diff --git a/docs/ai/quickstarts/snippets/build-chat-app/azure-openai/Program.cs b/docs/ai/quickstarts/snippets/build-chat-app/azure-openai/Program.cs
@@ -3,6 +3,7 @@
 using Azure.AI.OpenAI;
 using Azure.Identity;
 
+// <SnippetGetChatClient>
 IConfigurationRoot config = new ConfigurationBuilder().AddUserSecrets<Program>().Build();
 string endpoint = config["AZURE_OPENAI_ENDPOINT"];
 string deployment = config["AZURE_OPENAI_GPT_NAME"];
@@ -11,7 +12,9 @@
     new AzureOpenAIClient(new Uri(endpoint), new DefaultAzureCredential())
     .GetChatClient(deployment)
     .AsIChatClient();
+// </SnippetGetChatClient>
 
+// <SnippetFirstMessage>
 // Start the conversation with context for the AI model
 List<ChatMessage> chatHistory =
     [
@@ -30,7 +33,9 @@ the local nature on the hikes when making a recommendation. At the end of your
             response, ask if there is anything else you can help with.
         """)
     ];
+// </SnippetFirstMessage>
 
+// <SnippetChatLoop>
 while (true)
 {
     // Get user prompt and add to chat history
@@ -50,3 +55,4 @@ the local nature on the hikes when making a recommendation. At the end of your
     chatHistory.Add(new ChatMessage(ChatRole.Assistant, response));
     Console.WriteLine();
 }
+// </SnippetChatLoop>