Merge pull request #302582 from MicrosoftDocs/main

Auto Publish – main to live - 2025-07-11 11:00 UTC

Author: learn-build-service-prod[bot]

articles/azure-app-configuration/concept-ai-configuration.md

@@ -46,6 +46,8 @@ Chat completion is an AI capability that produces human-like dialogue responses
 | Anthropic      | Claude 3.7 Sonnet     |
 | Google         | Gemini 2.5 Pro        |
 | DeepSeek       | DeepSeek-R1           |
+| xAI            | Grok-3                |
+| xAI            | Grok-3 Mini           |
 
 Azure OpenAI Service supports a diverse set of models from OpenAI. For more information, see [Azure OpenAI Service models](/azure/ai-services/openai/concepts/models). To learn more about models from Anthropic, refer to the [Claude models documentation](https://docs.anthropic.com/docs/about-claude/models/overview).  
 For more details about models provided by Google, see the [Gemini models documentation](https://ai.google.dev/gemini-api/docs/models).

articles/azure-app-configuration/howto-chat-completion-config.md

@@ -26,12 +26,9 @@ In this section, you create a chat completion configuration in Azure portal usin
  1. In Azure portal, navigate to your App configuration store. From the **Operations** menu, select **Configuration explorer** > **Create**, and then select **AI configuration**.
 
  1. Specify the following values:
-    - **Key**: Type **ChatApp:Model**.
+    - **Key**: Type **ChatApp:ChatCompletion**.
     - **Label**: Leave this value blank.
     - **Model**: Select **gpt-4o**.
-    - **Message**: Add a new message.
-        - **Role**: Select **user**
-        - **Content**: Type "What is the capital of France?"
 
     > [!div class="mx-imgBorder"]
     > ![Screenshot shows the create new AI configuration form.](./media/create-ai-chat-completion-config.png)
@@ -40,13 +37,13 @@ In this section, you create a chat completion configuration in Azure portal usin
 
 ## Add model connection configuration
 
-You successfully added your chat completion configuration named **ChatApp:Model** in the previous section. In this section, you add the connection details for your model, including the endpoint and deployment name. If required by your authentication method, you can also specify an API key using a Key Vault reference.
+You successfully added your chat completion configuration named **ChatApp:ChatCompletion** in the previous section. In this section, you add the connection details for your model, including the endpoint and deployment name. If required by your authentication method, you can also specify an API key using a Key Vault reference.
 
 > [!NOTE]
 > This tutorial demonstrates how to use chat completion configuration with an Azure OpenAI model. However, the chat completion configuration demonstrated in the tutorial can be applied to any AI model you choose to work with in your application.
 >
 
-1. Follow the [Get started with Azure OpenAI Service](/azure/ai-services/openai/overview#get-started-with-azure-openai-service) to create and deploy an Azure OpenAI service resource with a **gpt-4o** model. Note down the deployment name for later use.
+1. Follow the [Get started with Azure OpenAI Service](/azure/ai-foundry/openai/how-to/create-resource) to create and deploy an Azure OpenAI service resource with a **gpt-4o** model. Note down the deployment name for later use.
 
 1. In your Azure OpenAI resource, from the **Resource Management** menu, select **Keys and Endpoint** and copy the Azure OpenAI resource endpoint. It should follow the format: `https://<open-ai-resource-name>.openai.azure.com`. If using the API key for authentication, copy the API key as well.
 

articles/azure-app-configuration/media/create-ai-chat-completion-config.png

@@ -17,7 +17,9 @@ ms.collection: ce-skilling-ai-copilot
 
 # Use chat completion configuration in a .NET console app
 
-In this guide, you build an AI chat application and iterate on the prompt using chat completion configuration dynamically loaded from Azure App Configuration.
+In this guide, you build an AI chat application and iterate on the prompt using chat completion configuration dynamically loaded from Azure App Configuration. 
+
+The full sample source code is available in the [Azure App Configuration GitHub repository](https://github.com/Azure/AppConfiguration/tree/main/examples/DotNetCore/ChatApp).
 
 ## Prerequisites
 
@@ -112,10 +114,10 @@ In this guide, you build an AI chat application and iterate on the prompt using
     });
     ```
 
-1. Define the `ModelConfiguration` class in _Program.cs_ file:
+1. Define the `ChatCompletionConfiguration` class in _Program.cs_ file:
 
     ```csharp
-    internal class ModelConfiguration
+    internal class ChatCompletionConfiguration
     {
         [ConfigurationKeyName("model")]
         public string? Model { get; set; }
@@ -146,10 +148,10 @@ In this guide, you build an AI chat application and iterate on the prompt using
 1. Update the _Program.cs_ file to add a helper method `GetChatMessages` to process chat messages:
 
     ```csharp
-    // Helper method to convert configuration messages to chat API format
-    static IEnumerable<ChatMessage> GetChatMessages(ModelConfiguration modelConfiguration)
+    // Helper method to convert configuration messages to ChatMessage objects
+    static IEnumerable<ChatMessage> GetChatMessages(ChatCompletionConfiguration chatCompletionConfiguration)
     {
-        return modelConfiguration.Messages.Select<Message, ChatMessage>(message => message.Role switch
+        return chatCompletionConfiguration.Messages.Select<Message, ChatMessage>(message => message.Role switch
         {
             "system" => ChatMessage.CreateSystemMessage(message.Content),
             "user" => ChatMessage.CreateUserMessage(message.Content),
@@ -162,31 +164,50 @@ In this guide, you build an AI chat application and iterate on the prompt using
 1. Next, update the existing code in the _Program.cs_ file to refresh the configuration from Azure App Configuration, apply the latest AI configuration values to the chat completion settings, and retrieve a response from the AI model.
 
     ```csharp
+    // Initialize chat conversation
+    var chatConversation = new List<ChatMessage>();
+    Console.WriteLine("Chat started! What's on your mind?");
+
     while (true)
     {
+        // Get user input
+        Console.Write("You: ");
+        string? userInput = Console.ReadLine();
+
+        // Exit if user input is empty
+        if (string.IsNullOrEmpty(userInput))
+        {
+            Console.WriteLine("Exiting chat. Goodbye!");
+            break;
+        }
+
+        chatConversation.Add(ChatMessage.CreateUserMessage(userInput));
+
         // Refresh the configuration from Azure App Configuration
         await refresher.RefreshAsync();
 
         // Configure chat completion with AI configuration
-        var modelConfiguration = configuration.GetSection("ChatApp:Model").Get<ModelConfiguration>();
+        var chatCompletionConfiguration = configuration.GetSection("ChatApp:ChatCompletion").Get<ChatCompletionConfiguration>();
+
         var requestOptions = new ChatCompletionOptions()
         {
-            MaxOutputTokenCount = modelConfiguration.MaxTokens,
-            Temperature = modelConfiguration.Temperature,
-            TopP = modelConfiguration.TopP
+            MaxOutputTokenCount = chatCompletionConfiguration.MaxTokens,
+            Temperature = chatCompletionConfiguration.Temperature,
+            TopP = chatCompletionConfiguration.TopP
         };
 
-        foreach (var message in modelConfiguration.Messages)
-        {
-            Console.WriteLine($"{message.Role}: {message.Content}");
-        }
+        // Get latest system message from AI configuration
+        var chatMessages = new List<ChatMessage>(GetChatMessages(chatCompletionConfiguration));
+        chatMessages.AddRange(chatConversation);
+
+        // Get AI response and add it to chat conversation
+        var response = await chatClient.CompleteChatAsync(chatMessages, requestOptions);
+        string aiResponse = response.Value.Content[0].Text;
 
-        // Get chat response from AI
-        var response = await chatClient.CompleteChatAsync(GetChatMessages(modelConfiguration), requestOptions);
-        Console.WriteLine($"AI response: {response.Value.Content[0].Text}");
+        Console.WriteLine($"AI: {aiResponse}");
+        chatConversation.Add(ChatMessage.CreateAssistantMessage(aiResponse));
 
-        Console.WriteLine("Press Enter to continue...");
-        Console.ReadLine();
+        Console.WriteLine();
     }
     ```
 
@@ -231,37 +252,55 @@ In this guide, you build an AI chat application and iterate on the prompt using
     AzureOpenAIClient azureClient = new(openaiEndpoint, credential);
     ChatClient chatClient = azureClient.GetChatClient(deploymentName);
 
+    // Initialize chat conversation
+    var chatConversation = new List<ChatMessage>();
+    Console.WriteLine("Chat started! What's on your mind?");
+
     while (true)
     {
+        // Get user input
+        Console.Write("You: ");
+        string? userInput = Console.ReadLine();
+
+        // Exit if user input is empty
+        if (string.IsNullOrEmpty(userInput))
+        {
+            Console.WriteLine("Exiting chat. Goodbye!");
+            break;
+        }
+
+        chatConversation.Add(ChatMessage.CreateUserMessage(userInput));
+
         // Refresh the configuration from Azure App Configuration
         await refresher.RefreshAsync();
 
         // Configure chat completion with AI configuration
-        var modelConfiguration = configuration.GetSection("ChatApp:Model").Get<ModelConfiguration>();
+        var chatCompletionConfiguration = configuration.GetSection("ChatApp:ChatCompletion").Get<ChatCompletionConfiguration>();
         var requestOptions = new ChatCompletionOptions()
         {
-            MaxOutputTokenCount = modelConfiguration.MaxTokens,
-            Temperature = modelConfiguration.Temperature,
-            TopP = modelConfiguration.TopP
+            MaxOutputTokenCount = chatCompletionConfiguration.MaxTokens,
+            Temperature = chatCompletionConfiguration.Temperature,
+            TopP = chatCompletionConfiguration.TopP
         };
 
-        foreach (var message in modelConfiguration.Messages)
-        {
-            Console.WriteLine($"{message.Role}: {message.Content}");
-        }
+        // Get latest system message from AI configuration
+        var chatMessages = new List<ChatMessage>(GetChatMessages(chatCompletionConfiguration));
+        chatMessages.AddRange(chatConversation);
+
+        // Get AI response and add it to chat conversation
+        var response = await chatClient.CompleteChatAsync(chatMessages, requestOptions);
+        string aiResponse = response.Value.Content[0].Text;
 
-        // Get chat response from AI
-        var response = await chatClient.CompleteChatAsync(GetChatMessages(modelConfiguration), requestOptions);
-        Console.WriteLine($"AI response: {response.Value.Content[0].Text}");
+        Console.WriteLine($"AI: {aiResponse}");
+        chatConversation.Add(ChatMessage.CreateAssistantMessage(aiResponse));
 
-        Console.WriteLine("Press Enter to continue...");
-        Console.ReadLine();
-        
+        Console.WriteLine();
     }
 
-    static IEnumerable<ChatMessage> GetChatMessages(ModelConfiguration modelConfiguration)
+    // Helper method to convert configuration messages to ChatMessage objects
+    static IEnumerable<ChatMessage> GetChatMessages(ChatCompletionConfiguration chatCompletionConfiguration)
     {
-        return modelConfiguration.Messages.Select<Message, ChatMessage>(message => message.Role switch
+        return chatCompletionConfiguration.Messages.Select<Message, ChatMessage>(message => message.Role switch
         {
             "system" => ChatMessage.CreateSystemMessage(message.Content),
             "user" => ChatMessage.CreateUserMessage(message.Content),
@@ -270,7 +309,7 @@ In this guide, you build an AI chat application and iterate on the prompt using
         });
     }
 
-    internal class ModelConfiguration
+    internal class ChatCompletionConfiguration
     {
         [ConfigurationKeyName("model")]
         public string? Model { get; set; }
@@ -323,29 +362,29 @@ In this guide, you build an AI chat application and iterate on the prompt using
     dotnet run
     ```
 
-    You should see the following output:
 
-    ```Output
-    system: You are a helpful assistant.
-    user: What is the capital of France ?
-    AI response: The capital of France is **Paris**.
-    Press Enter to continue...
+1. Type the message "What is your name?" when prompted with "You:" and then press the Enter key.
 
+    ```Output
+    Chat started! What's on your mind?
+    You: What is your name ?
+    AI: I’m your helpful assistant! I don’t have a personal name, but you can call me whatever you’d like. 
+    😊 Do you have a name in mind?
     ```
 
-1. In Azure portal, select the App Configuration store instance that you created. From the **Operations** menu, select **Configuration explorer** and select the **ChatApp:Model** key. Update the value of the Messages property:
+1. In Azure portal, select the App Configuration store instance that you created. From the **Operations** menu, select **Configuration explorer** and select the **ChatApp:ChatCompletion** key. Update the value of the Messages property:
     - Role: **system**
-    - Content: "You are a cheerful tour guide".
+    - Content: "You are a pirate and your name is Eddy."
 
-1. Wait a few moments for the refresh interval to elapse, and then press the Enter key to see the updated AI response in the output.
+1. Type the same message when prompted with "You:". Be sure to wait a few moments for the refresh interval to elapse, and then press the Enter key to see the updated AI response in the output.
 
     ```Output
-    system: You are a cheerful tour guide
-    user: What is the capital of France ?
-    AI response: Oh là là! The capital of France is the magnificent **Paris**!
-    Known as the "City of Light" (*La Ville Lumière*), it's famous for its romantic ambiance,
-    iconic landmarks like the Eiffel Tower, the Louvre Museum, and Notre-Dame Cathedral,
-    as well as its delicious pastries and charming cafés.
-    Have you ever been, or is it on your travel bucket list? 😊✨
-    Press Enter to continue...
+    Chat started! What's on your mind?
+    You: What is your name ?
+    AI: I’m your helpful assistant! I don’t have a personal name, but you can call me whatever you’d like. 
+    😊 Do you have a name in mind?
+
+    You: What is your name ?
+    AI: Arrr, matey! Me name be Eddy, the most fearsome pirate to ever sail the seven seas!
+    What be yer name, landlubber? 
     ```

articles/azure-app-configuration/quickstart-chat-completion-dotnet.md

@@ -2,7 +2,7 @@
 title: Configure and manage backup for Azure Blobs using Azure Backup
 description: Learn how to configure and manage operational and vaulted backups for Azure Blobs.
 ms.topic: how-to
-ms.date: 06/18/2025
+ms.date: 07/11/2025
 ms.service: azure-backup
 author: jyothisuri
 ms.author: jsuri
@@ -169,7 +169,7 @@ For more information, see [Overview of Azure Business Continuity Center](../busi
 You can stop operational backup for your storage account according to your requirement.
 
 >[!NOTE]
->When you remove backups, the **object replication policy** isn't removed from the source. So, you need to remove the policy separately. Stopping protection only dissociates the storage account from the Backup vault (and the backup tools, such as Backup center), and doesn’t disable blob point-in-time restore, versioning, and change feed that were configured.
+>When you remove backups, Azure Backup automatically deletes the **object replication policy** from the source. If custom locks exist, remove the policy manually. If you stop protection, it disconnects only the storage account from the Backup vault and tools (such as Backup center). This action doesn't disable blob point-in-time restore, versioning, or change feed settings.
 
 To stop backup for a storage account, follow these steps:
 

articles/backup/blob-backup-configure-manage.md

@@ -2,7 +2,7 @@
 title: Support matrix for Azure Blobs backup
 description: Provides a summary of support settings and limitations when backing up Azure Blobs.
 ms.topic: reference
-ms.date: 07/02/2025
+ms.date: 07/11/2025
 ms.custom: references_regions, engagement-fy24
 ms.service: azure-backup
 author: jyothisuri
@@ -66,6 +66,8 @@ Operational backup of blobs uses blob point-in-time restore, blob versioning, so
 - The storage accounts to be backed up must contain *a minimum of one container*. If the storage account doesn't contain any containers or if no containers are selected, an error may appear when you configure backup.
 - Only `$web` and `$root` system containers are supported for vaulted backup.
 - If you stop protection (vaulted backup) on a storage account, it doesn't delete the object replication policy created on the storage account. In these scenarios, you need to manually delete the *OR policies*.
+- You can avoid disruption to Azure Blob vaulted backups during a storage account failover by following a specific sequence - pause the backup, remove the object replication policy at the storage account level, complete the failover, and then resume the backup. This process doesn't impact existing recovery points. However, it triggers a full re-replication of blobs during the next backup operation. The object replication policy is automatically recreated in the next backup cycle.
+- When you remove backups, Azure Backup automatically deletes the **object replication policy** from the source. If custom locks exist, remove the policy manually. If you stop protection, it disconnects only the storage account from the Backup vault and tools (such as Backup center). This action doesn't disable blob point-in-time restore, versioning, or change feed settings.
 - Archive tier blob backup isn't supported. Cool and cold tier blobs are restored in hot tier. 
 - The backup operation isn't supported for blobs that are uploaded by using [Data Lake Storage APIs](/rest/api/storageservices/data-lake-storage-gen2).
 - When you delete and recreate a storage account with the same name, **Object Replication** doesn't recognize the change. As a result, future Recovery Points continue to include the older blobs and their versions.