Merge branch 'MicrosoftDocs:main' into l3-network-overlaps-warning

Author: paulopiyo777

.openpublishing.publish.config.json

@@ -1228,6 +1228,7 @@
   "articles/ai-services/.openpublishing.redirection.applied-ai-old.json",
   "articles/ai-services/.openpublishing.redirection.applied-ai-services.json",
   "articles/ai-services/.openpublishing.redirection.cognitive-services.json",
+  "articles/ai-studio/.openpublishing.redirection.ai-studio.json",
   "articles/energy-data-services/.openpublishing.redirection.energy-data-services.json",
   "articles/azure-fluid-relay/.openpublishing.redirection.fluid-relay.json",
   "articles/azure-netapp-files/.openpublishing.redirection.azure-netapp-files.json",

articles/ai-services/openai/includes/use-your-data-dotnet.md

@@ -29,13 +29,14 @@ string searchKey = GetEnvironmentVariable("SearchKey");
 string searchIndex = GetEnvironmentVariable("SearchIndex");
 string deploymentName = GetEnvironmentVariable("AOAIDeploymentId");
 
+
 var client = new OpenAIClient(new Uri(azureOpenAIEndpoint), new AzureKeyCredential(azureOpenAIKey));
 
 var chatCompletionsOptions = new ChatCompletionsOptions()
 {
     Messages =
     {
-        new ChatMessage(ChatRole.User, "What are the differences between Azure Machine Learning and Azure AI services?"),
+        new ChatRequestUserMessage("What are the differences between Azure Machine Learning and Azure AI services?"),
     },
     AzureExtensionsOptions = new AzureChatExtensionsOptions()
     {
@@ -48,12 +49,13 @@ var chatCompletionsOptions = new ChatCompletionsOptions()
                 IndexName = searchIndex,
             },
         }
-    }
+    },
+    DeploymentName = deploymentName
 };
 
-Response<ChatCompletions> response = client.GetChatCompletions(deploymentName, chatCompletionsOptions);
+Response<ChatCompletions> response = client.GetChatCompletions(chatCompletionsOptions);
 
-ChatMessage responseMessage = response.Value.Choices[0].Message;
+ChatResponseMessage responseMessage = response.Value.Choices[0].Message;
 
 Console.WriteLine($"Message from {responseMessage.Role}:");
 Console.WriteLine("===");
@@ -62,7 +64,7 @@ Console.WriteLine("===");
 
 Console.WriteLine($"Context information (e.g. citations) from chat extensions:");
 Console.WriteLine("===");
-foreach (ChatMessage contextMessage in responseMessage.AzureExtensionsContext.Messages)
+foreach (ChatResponseMessage contextMessage in responseMessage.AzureExtensionsContext.Messages)
 {
     string contextContent = contextMessage.Content;
     try
@@ -126,25 +128,22 @@ using Azure.AI.OpenAI;
 using System.Text.Json;
 using static System.Environment;
 
-string endpoint = GetEnvironmentVariable("AOAIEndpoint");
-string key = GetEnvironmentVariable("AOAIKey");
-
-var client = new OpenAIClient(new Uri(endpoint), new AzureKeyCredential(key));
-
 string azureOpenAIEndpoint = GetEnvironmentVariable("AOAIEndpoint");
 string azureOpenAIKey = GetEnvironmentVariable("AOAIKey");
 string searchEndpoint = GetEnvironmentVariable("SearchEndpoint");
 string searchKey = GetEnvironmentVariable("SearchKey");
 string searchIndex = GetEnvironmentVariable("SearchIndex");
 string deploymentName = GetEnvironmentVariable("AOAIDeploymentId");
 
+
 var client = new OpenAIClient(new Uri(azureOpenAIEndpoint), new AzureKeyCredential(azureOpenAIKey));
 
 var chatCompletionsOptions = new ChatCompletionsOptions()
 {
+    DeploymentName = deploymentName,
     Messages =
     {
-        new ChatMessage(ChatRole.User, "What are the differences between Azure Machine Learning and Azure AI services?"),
+        new ChatRequestUserMessage("What are the differences between Azure Machine Learning and Azure AI services?"),
     },
     AzureExtensionsOptions = new AzureChatExtensionsOptions()
     {
@@ -159,44 +158,15 @@ var chatCompletionsOptions = new ChatCompletionsOptions()
         }
     }
 };
-
-Response<StreamingChatCompletions> response = await client.GetChatCompletionsStreamingAsync(
-    deploymentName,
-    chatCompletionsOptions);
-
-using StreamingChatCompletions streamingChatCompletions = response.Value;
-
-await foreach (StreamingChatChoice streamingChatChoice in streamingChatCompletions.GetChoicesStreaming())
+await foreach (StreamingChatCompletionsUpdate chatUpdate in client.GetChatCompletionsStreaming(chatCompletionsOptions))
 {
-    await foreach (ChatMessage chatMessage in streamingChatChoice.GetMessageStreaming())
+    if (chatUpdate.Role.HasValue)
     {
-        if (chatMessage.Role != default)
-        {
-            Console.WriteLine($"Message from {chatMessage.Role}: ");
-        }
-        if (chatMessage.Content != default)
-        {
-            Console.Write(chatMessage.Content);
-        }
-        if (chatMessage.AzureExtensionsContext != default)
-        {
-            Console.WriteLine($"Context information (e.g. citations) from chat extensions:");
-            foreach (var contextMessage in chatMessage.AzureExtensionsContext.Messages)
-            {
-                string contextContent = contextMessage.Content;
-                try
-                {
-                    var contextMessageJson = JsonDocument.Parse(contextMessage.Content);
-                    contextContent = JsonSerializer.Serialize(contextMessageJson, new JsonSerializerOptions()
-                    {
-                        WriteIndented = true,
-                    });
-                }
-                catch (JsonException)
-                {}
-                Console.WriteLine($"{contextMessage.Role}: {contextContent}");
-            }
-        }
+        Console.Write($"{chatUpdate.Role.Value.ToString().ToUpperInvariant()}: ");
+    }
+    if (!string.IsNullOrEmpty(chatUpdate.ContentUpdate))
+    {
+        Console.Write(chatUpdate.ContentUpdate);
     }
 }
 ```

articles/ai-studio/.openpublishing.redirection.ai-studio.json

@@ -0,0 +1,9 @@
+{
+  "redirections": [
+    {
+      "source_path_from_root": "/articles/ai-studio/how-to/vscode-web.md",
+      "redirect_url": "/azure/ai-studio/how-to/develop-in-vscode",
+      "redirect_document_id": true
+    }
+  ]
+}

articles/ai-studio/how-to/cli-install.md

@@ -91,7 +91,7 @@ You can install the Azure AI CLI locally as described previously, or run it usin
 
 ### Option 1: Using VS Code (web) in Azure AI Studio
 
-VS Code (web) in Azure AI Studio creates and runs the development container on a compute instance. To get started with this approach, follow the instructions in [How to work with Azure AI Studio projects in VS Code (Web)](vscode-web.md).
+VS Code (web) in Azure AI Studio creates and runs the development container on a compute instance. To get started with this approach, follow the instructions in [Work with Azure AI projects in VS Code](develop-in-vscode.md).
 
 Our prebuilt development environments are based on a docker container that has the Azure AI SDK generative packages, the Azure AI CLI, the Prompt flow SDK, and other tools. It's configured to run VS Code remotely inside of the container. The docker container is similar to [this Dockerfile](https://github.com/Azure/aistudio-copilot-sample/blob/main/.devcontainer/Dockerfile), and is based on [Microsoft's Python 3.10 Development Container Image](https://mcr.microsoft.com/en-us/product/devcontainers/python/about). 
 
@@ -221,7 +221,7 @@ As mentioned in step 2 above, your flow.dag.yaml should reference connection and
 
 If you're working in your own development environment (including Codespaces), you might need to manually update these fields so that your flow runs connected to Azure resources.
 
-If you launched VS Code from the AI Studio, you are in an Azure-connected custom container experience, and you can work directly with flows stored in the `shared` folder. These flow files are the same underlying files prompt flow references in the Studio, so they should already be configured with your project connections and deployments. To learn more about the folder structure in the VS Code container experience, see [Get started with Azure AI projects in VS Code (Web)](vscode-web.md)
+If you launched VS Code from the AI Studio, you are in an Azure-connected custom container experience, and you can work directly with flows stored in the `shared` folder. These flow files are the same underlying files prompt flow references in the Studio, so they should already be configured with your project connections and deployments. To learn more about the folder structure in the VS Code container experience, see [Work with Azure AI projects in VS Code](develop-in-vscode.md)
 
 ## ai chat
 
@@ -295,7 +295,7 @@ ai help
 
 ## Next steps
 
-- [Try the Azure AI CLI from Azure AI Studio in a browser](vscode-web.md)
+- [Try the Azure AI CLI from Azure AI Studio in a browser](develop-in-vscode.md)
 
 
 

articles/ai-studio/how-to/create-manage-compute.md

@@ -57,7 +57,7 @@ To create a compute instance in Azure AI Studio:
     :::image type="content" source="../media/compute/compute-scheduling.png" alt-text="Screenshot of the option to enable idle shutdown and create a schedule." lightbox="../media/compute/compute-scheduling.png":::
 
     > [!IMPORTANT]
-    > The compute can't be idle if you have [prompt flow runtime](./create-manage-runtime.md) in **Running** status on the compute. You need to delete any active runtime before the compute instance can be eligible for idle shutdown. You also can't have any active [VS Code (Web)](./vscode-web.md) sessions hosted on the compute instance.
+    > The compute can't be idle if you have [prompt flow runtime](./create-manage-runtime.md) in **Running** status on the compute. You need to delete any active runtime before the compute instance can be eligible for idle shutdown. You also can't have any active [VS Code (Web)](./develop-in-vscode.md) sessions hosted on the compute instance.
 
 1. You can update the schedule days and times to meet your needs. You can also add additional schedules. For example, you can create a schedule to start at 9 AM and stop at 6 PM from Monday-Thursday, and a second schedule to start at 9 AM and stop at 4 PM for Friday. You can create a total of four schedules per compute instance.
 
@@ -84,7 +84,7 @@ Note that disabling SSH prevents SSH access from the public internet. But when a
 To avoid getting charged for a compute instance that is switched on but inactive, you can configure when to shut down your compute instance due to inactivity. 
 
 > [!IMPORTANT]
-> The compute can't be idle if you have [prompt flow runtime](./create-manage-runtime.md) in **Running** status on the compute. You need to delete any active runtime before the compute instance can be eligible for idle shutdown. You also can't have any active [VS Code (Web)](./vscode-web.md) sessions hosted on the compute instance.
+> The compute can't be idle if you have [prompt flow runtime](./create-manage-runtime.md) in **Running** status on the compute. You need to delete any active runtime before the compute instance can be eligible for idle shutdown. You also can't have any active [VS Code (Web)](./develop-in-vscode.md) sessions hosted on the compute instance.
 
 The setting can be configured during compute instance creation or for existing compute instances.
 

articles/ai-studio/how-to/vscode-web.md renamed to articles/ai-studio/how-to/develop-in-vscode.md

@@ -1,41 +1,42 @@
 ---
-title: Get started with Azure AI projects in VS Code (Web)
+title: Work with Azure AI projects in VS Code
 titleSuffix: Azure AI Studio
-description: This article provides instructions on how to get started with Azure AI projects in VS Code (Web).
+description: This article provides instructions on how to get started with Azure AI projects in VS Code.
 manager: nitinme
 ms.service: azure-ai-studio
 ms.custom:
   - ignite-2023
 ms.topic: how-to
-ms.date: 11/15/2023
+ms.date: 1/10/2024
 ms.reviewer: eur
 ms.author: eur
 author: eric-urban
 ---
 
-# Get started with Azure AI projects in VS Code (Web)
+# Get started with Azure AI projects in VS Code
 
 [!INCLUDE [Azure AI Studio preview](../includes/preview-ai-studio.md)]
 
-Azure AI Studio supports developing in VS Code for the Web. In this scenario, VS Code is remotely connected to a prebuilt custom container running on a virtual machine, also known as a compute instance. To work in your local environment instead, or to learn more, follow the steps in [Install the Azure AI SDK](sdk-install.md) and [Install the Azure AI CLI](cli-install.md).
+Azure AI Studio supports developing in VS Code - Web and Desktop. In each scenario, your VS Code instance is remotely connected to a prebuilt custom container running on a virtual machine, also known as a compute instance. To work in your local environment instead, or to learn more, follow the steps in [Install the Azure AI SDK](sdk-install.md) and [Install the Azure AI CLI](cli-install.md).
 
-## Launch VS Code (Web) from Azure AI Studio
+## Launch VS Code from Azure AI Studio
 
-1. Go to the Azure AI Studio homepage at [aka.ms/AzureAIStudio](https://aka.ms/AzureAIStudio).
+1. Go to [Azure AI Studio](https://ai.azure.com).
 
-1. Got to **Build** > **Projects** and select or create the project you want to work with.
+1. Go to **Build** > **Projects** and select or create the project you want to work with.
 
-1. At the top-right of any page in the **Build** tab, select **Open project in VS Code (Web)**
+1. At the top-right of any page in the **Build** tab, select **Open project in VS Code (Web)** if you want to work in the browser. If you want to work in your local VS Code instance instead, select the dropdown arrow and choose **Open project in VS Code (Desktop)**.
 
-1. Select or create the compute instance that you want to use. 
+1. Within the dialog that opened following the previous step, select or create the compute instance that you want to use.
 
 1. Once the compute is running, select **Set up** which configures the container on your compute for you. The compute setup might take a few minutes to complete. Once you set up the compute the first time, you can directly launch subsequent times. You might need to authenticate your compute when prompted.
 
     > [!WARNING]
-    > Even if you enable and configure idle shutdown on your compute instance, any computes that host this custom container for VS Code (Web) won't idle shutdown. This is to ensure the compute doesn't shut down unexpectedly while you're working within a container. We are working to improve this experience. Scheduled startup and shutdown should still work as expected.
+    > Even if you [enable and configure idle shutdown on your compute instance](./create-manage-compute.md#configure-idle-shutdown), any computes that host this custom container for VS Code won't idle shutdown. This is to ensure the compute doesn't shut down unexpectedly while you're working within a container.
 
-1. Once the container is ready, select **Launch**. This launches VS Code (Web) in a new browser tab connected to *vscode.dev*. 
+1. Once the container is ready, select **Launch**. This launches your previously selected VS Code experience, remotely connected to a custom development environment running on your compute instance.
 
+    If you selected VS Code (Web), a new browser tab connected to *vscode.dev* opens. If you selected VS Code (Desktop), a new local instance of VS Code opens on your local machine.
 
 ## The custom container folder structure
 
@@ -80,25 +81,30 @@ If you prefer to work interactively, the Azure AI CLI has everything you need to
 
 ### Working with prompt flows
 
-You can use the Azure AI SDK and Azure AI CLI to create, reference and work with the flows.
+You can use the Azure AI SDK and Azure AI CLI to create, reference and work with prompt flows.
 
-Prompt flows already created in the Azure AI Studio can be found at `shared\Users\{user-name}\promptflow`. You can also create new flows in your `code` or `shared` folder using the CLIs and SDKs.
+Prompt flows already created in the Azure AI Studio can be found at `shared\Users\{user-name}\promptflow`. You can also create new flows in your `code` or `shared` folder using the Azure AI CLI and SDK.
 
-- To reference an existing flow using the Azure AI CLI, use `ai flow invoke`.
-- To create a new flow using the Azure AI CLI, use `ai flow new`.
+- To reference an existing flow using the AI CLI, use `ai flow invoke`.
+- To create a new flow using the AI CLI, use `ai flow new`.
 
-For prompt flow specific capabilities that aren't present in the AI SDK and CLI, you can work directly with the Prompt flow CLI or SDK, or the Prompt flow VS Code extension (all preinstalled in this environment). For more information, see [prompt flow capabilities](https://microsoft.github.io/promptflow/reference/index.html).
+Prompt flow will automatically use the Azure AI connections your project has access to when you use the AI CLI or SDK.
+
+You can also work with the prompt flow extension in VS Code, which is preinstalled in this environment. Within this extension, you can set the connection provider to your Azure AI project. See [consume connections from Azure AI](https://microsoft.github.io/promptflow/cloud/azureai/consume-connections-from-azure-ai.html).
+
+For prompt flow specific capabilities that aren't present in the AI SDK and CLI, you can work directly with the prompt flow CLI or SDK. For more information, see [prompt flow capabilities](https://microsoft.github.io/promptflow/reference/index.html).
 
 ## Remarks
 
 If you plan to work across multiple code and data directories, or multiple repositories, you can use the split root file explorer feature in VS Code. To try this feature, follow these steps:
+
 1. Enter *Ctrl+Shift+p* to open the command palette. Search for and select **Workspaces: Add Folder to Workspace**.
 1. Select the repository folder that you want to load. You should see a new section in your file explorer for the folder you opened. If it was a repository, you can now work with source control in VS Code.
 1. If you want to save this configuration for future development sessions, again enter *Ctrl+Shift+p* and select **Workspaces: Save Workspace As**. This action saves a config file to your current folder.
-    
+
 For cross-language compatibility and seamless integration of Azure AI capabilities, explore the Azure AI Hub at [https://aka.ms/azai](https://aka.ms/azai). Discover app templates and SDK samples in your preferred programming language.
 
 ## Next steps
 
 - [Get started with the Azure AI CLI](cli-install.md)
-- [Quickstart: Generate product name ideas in the Azure AI Studio playground](../quickstarts/playground-completions.md)
+- [Quickstart: Generate product name ideas in the Azure AI Studio playground](../quickstarts/playground-completions.md)

articles/ai-studio/how-to/sdk-install.md

@@ -102,7 +102,7 @@ You can install the Azure AI SDK locally as described previously, or run it via
 
 ### Option 1: Using VS Code (web) in Azure AI Studio
 
-VS Code (web) in Azure AI Studio creates and runs the development container on a compute instance. To get started with this approach, follow the instructions in [How to work with Azure AI Studio projects in VS Code (Web)](vscode-web.md).
+VS Code (web) in Azure AI Studio creates and runs the development container on a compute instance. To get started with this approach, follow the instructions in [Work with Azure AI projects in VS Code](develop-in-vscode.md).
 
 Our prebuilt development environments are based on a docker container that has the Azure AI Generative SDK, the Azure AI CLI, the prompt flow SDK, and other tools. It's configured to run VS Code remotely inside of the container. The docker container is defined in [this Dockerfile](https://github.com/Azure/aistudio-copilot-sample/blob/main/.devcontainer/Dockerfile), and is based on [Microsoft's Python 3.10 Development Container Image](https://mcr.microsoft.com/en-us/product/devcontainers/python/about). 
 
@@ -127,5 +127,5 @@ The Azure AI code samples in GitHub Codespaces help you quickly get started with
 ## Next steps
 
 - [Get started building a sample copilot application](https://github.com/azure/aistudio-copilot-sample)
-- [Try the Azure AI CLI from Azure AI Studio in a browser](vscode-web.md)
+- [Try the Azure AI CLI from Azure AI Studio in a browser](develop-in-vscode.md)
 - [Azure SDK for Python reference documentation](/python/api/overview/azure/ai)

articles/ai-studio/index.yml

@@ -64,8 +64,8 @@ landingContent:
             url: how-to/sdk-install.md
           - text: Get started with the Azure AI CLI
             url: how-to/cli-install.md
-          - text: Get started with projects in VS Code (Web)
-            url: how-to/vscode-web.md
+          - text: Work with Azure AI projects in VS Code
+            url: how-to/develop-in-vscode.md
       - linkListType: concept
         links:
           - text: Connections for flows and indexing