Merge pull request #4336 from MicrosoftDocs/main

4/25/2025 PM Publish

Author: Albertyang0

articles/ai-foundry/how-to/costs-plan-manage.md

@@ -9,7 +9,7 @@ ms.custom:
   - build-2024
   - ignite-2024
 ms.topic: conceptual
-ms.date: 02/19/2025
+ms.date: 04/25/2025
 ms.reviewer: siarora
 ms.author: larryfr
 author: Blackmist
@@ -73,10 +73,12 @@ Before you delete a hub in the Azure portal or with Azure CLI, the following sub
 - Azure Virtual Network
 - Bandwidth
 
-Each VM is billed per hour it's running. Cost depends on VM specifications. VMs that are running but not actively working on a dataset are still charged via the load balancer. For each compute instance, one load balancer is billed per day. Every 50 nodes of a compute cluster have one standard load balancer billed. Each load balancer is billed around $0.33/day. To avoid load balancer costs on stopped compute instances and compute clusters, delete the compute resource.
+Each VM is billed per hour it's running. Cost depends on VM specifications. VMs that are running but not actively working on a dataset are still charged via the load balancer. For each compute instance, one load balancer is billed per day. Every 50 nodes of a compute cluster have one standard load balancer billed. To avoid load balancer costs on stopped compute instances and compute clusters, delete the compute resource.
 
 Compute instances also incur P10 disk costs even in stopped state. This cost is because any user content saved to disk is persisted across the stopped state similar to Azure VMs. We're working on making the OS disk size/ type configurable to better control costs. For Azure Virtual Networks, one virtual network is billed per subscription and per region. Virtual networks can't span regions or subscriptions. Setting up private endpoints in virtual network setups might also incur charges. If your virtual network uses an Azure Firewall, the firewall might also incur charges. Bandwidth usage is charged; the more data transferred, the more you're charged. 
 
+For more information, see the [Azure pricing calculator](https://azure.microsoft.com/pricing/calculator/).
+
 > [!TIP]
 > Using a managed virtual network is free. However some features of the managed network rely on Azure Private Link (for private endpoints) and Azure Firewall (for FQDN rules) and will incur charges. For more information, see [Managed virtual network isolation](configure-managed-network.md#pricing).
 
@@ -127,9 +129,9 @@ Here's an example of how to monitor costs for a project. The costs are used as a
 
     In this example:
     - The resource group name is **rg-contosoairesource**.
-    - The total cost for all resources and services in the resource group is **$222.97**. In this example, $222.97 is the total cost for your application or solution that you're building with Azure AI Foundry. Again, this example assumes that all Azure AI Foundry resources are in the same resource group. But you can have resources in different resource groups.
+    - The total cost for all resources and services in the example resource group is **$222.97**. In this example, $222.97 is the total cost for your application or solution that you're building with Azure AI Foundry. Again, this example assumes that all Azure AI Foundry resources are in the same resource group. But you can have resources in different resource groups.
     - The project name is **contoso-outdoor-proj**.
-    - The costs that are limited to resources and services in the [project](../concepts/ai-resources.md#organize-work-in-projects-for-customization) total **$212.06**. 
+    - The costs that are limited to resources and services in the example [project](../concepts/ai-resources.md#organize-work-in-projects-for-customization) total **$212.06**. 
 
 1. Expand **contoso-outdoor-proj** to see the costs for services underlying the [project](../concepts/ai-resources.md#organize-work-in-projects-for-customization) resource. 
 

articles/ai-foundry/how-to/develop/get-started-projects-vs-code.md

@@ -1,17 +1,17 @@
 ---
 title: Work with the Azure AI Foundry for Visual Studio Code extension
 titleSuffix: Azure AI Foundry
-description: Use this article to learn how to deploy Large Language Models and develop AI agents using Azure AI Foundry capabilities directly in VS Code.
+description: Use this article to learn how to deploy Large Language Models using Azure AI Foundry capabilities directly in VS Code.
 manager: mcleans
 ms.service: azure-ai-foundry
 content_well_notification: 
   - AI-contribution
 ms.topic: how-to
-ms.date: 04/03/2025
+ms.date: 04/21/2025
 ms.reviewer: erichen
 ms.author: johalexander
 author: ms-johnalex
-# customer intent: As an AI app developer, I want to learn how to use the Azure AI Foundry for Visual Studio Code extension so that I can deploy Large Language Models and develop AI agents using Azure AI Foundry capabilities directly in VS Code.
+# customer intent: As an AI app developer, I want to learn how to use the Azure AI Foundry for Visual Studio Code extension so that I can deploy Large Language Models using Azure AI Foundry capabilities directly in VS Code.
 ---
 
 # Work with the Azure AI Foundry for Visual Studio Code extension (Preview)
@@ -85,22 +85,46 @@ Sign in to your Azure subscription to access your resources with the following s
 
 1. Under the "Resources" section, select your Azure Subscription and Resource Group. 
 
-1. Select **Azure AI Foundry** and open your project.
+1. Select **Azure AI Foundry** and right-click your project.
 
-1. The **Agents** and **Models** sections are listed under your project. 
+1. Select **Open in Azure AI Foundry Extension**.
 
+    :::image type="content" source="../../media/how-to/get-started-projects-vs-code/open-azure-ai-foundry-extension.png" alt-text="A screenshot of the Open in Azure AI Foundry Extension option." lightbox="../../media/how-to/get-started-projects-vs-code/open-azure-ai-foundry-extension.png":::
 
-### Set the default Azure AI Foundry Project
 
- Set your default Azure AI Foundry Project with the following steps:
+### Explore the Azure AI Foundry Extension
 
-1. Open a new Visual Studio Code window.
+The Azure AI Foundry Extension opens in its own view, with the Azure AI Foundry Icon now displayed on the VS Code Navbar. The extension has three main sections: **Resources**, **Tools**, and **Help and Feedback**.
 
-1. Select <kbd>F1</kbd> to open the command palette.
 
-1. Enter **Azure AI Foundry: Select Default Project** and press Enter.
+:::image type="content" source="../../media/how-to/get-started-projects-vs-code/initial-view.png" alt-text="A screenshot of the Azure AI Foundry Extension with highlighted sections.":::
+
+- **Resources**: This section contains the resources you have access to in your Azure AI Foundry project. The **Resources** section is the main view for interacting with your Azure AI Foundry resources. It contains the following subsections:
+  - **Models**: This section contains the models you can use to build and deploy your AI applications. The **Models** view is where you can find your deployed models in your Azure AI Foundry project.  
+  - **Agents**: This section contains your deployed agents in your Azure AI Foundry project.
+  - **Threads**: This section contains the threads and runs from a deployed agent in your Azure AI Foundry project.
+
+- **Tools**: This section contains the tools you can use to build and deploy your AI applications. The **Tools** view is where you can find the tools available to deploy and then work with your deployed models and agents. It contains the following subsections:
+    - **Model Catalog**: The link to the model catalog you can use to discover and deploy models. 
+    - **Model Playground**: The link to the model playground for interacting with your deployed models in your Azure AI Foundry project.
+    - **Agent Playground**: The link to the agent playground for interacting with your deployed agents in your Azure AI Foundry project.
+
+- **Help and Feedback**: This section contains links to the Azure AI Foundry documentation, feedback, and support. It contains the following subsections:
+    - **Documentation**: The link to the Azure AI Foundry Extension documentation.
+    - **GitHub**: The link to the Azure AI Foundry extension GitHub repository.
+
+>[!NOTE]
+> To learn more about working with Agents and Threads in the Azure AI Foundry Extension, see the [Work with Azure AI Agent Service in Visual Studio Code](./vs-code-agents.md) article. 
+
+### The default Azure AI Foundry Project
 
-1. Select the Azure AI Foundry Project you want to use from the list of available projects and press Enter.
+When you open a project in the Azure AI Foundry Extension, that project is set as your default project. 
+
+Switch your default project by following these steps:
+
+1. Right-click on your deployed model and select the **Switch Default Project in Azure Extension** option. 
+
+1. In the top center, select the Azure AI Foundry Project you want to use from the list of available projects and press Enter.
 
 Your selected project will now display **Default** after the project name.
 
@@ -115,7 +139,14 @@ The Azure AI Foundry for Visual Studio Code extension enables you to create, int
 
 The [model catalog](/azure/ai-foundry/how-to/model-catalog-overview) in Azure AI Foundry portal is the hub to discover and use a wide range of models for building generative AI applications.
 
- Access the model catalog from the command palette to explore and deploy a curated selection of models available in Azure AI Foundry, right from inside VS Code.
+ Access the model catalog from several different ways:
+- The **Azure AI Foundry: Open Model Catalog** command palette command.
+- Select the **plus** icon next to **Models** in the **Resources** section of the Azure AI Foundry Extension view.
+- Select the **Model Catalog** link in the **Tools** section of the Azure AI Foundry Extension view.
+
+#### Open the model catalog from the command palette
+
+Access the model catalog from the command palette to explore and deploy a curated selection of models available in Azure AI Foundry, right from inside VS Code.
 
 1. Select <kbd>F1</kbd> to open the command palette.
 
@@ -130,8 +161,22 @@ The [model catalog](/azure/ai-foundry/how-to/model-catalog-overview) in Azure AI
 
 1. Search for a specific model using the search bar at the top-center of the page.
 
+#### Open the model catalog from the Resources section
 
-#### Deploy a model from the model catalog
+The **Model Catalog** is also available in the **Resources** section of the Azure AI Foundry Extension view. 
+
+In the Azure AI Foundry Extension view, select the **plus** icon next to **Models** to open the Model Catalog.
+
+:::image type="content" source="../../media/how-to/get-started-projects-vs-code/select-model-plus-expanded.png" alt-text="Screenshot of the plus sign next to models with the list of models expanded." lightbox="../../media/how-to/get-started-projects-vs-code/select-model-plus-expanded.png":::
+
+> [!TIP] 
+> You can also right-click on **Models** and select the **Deploy new AI model** option to open the Model Catalog to start the deployment process. 
+
+#### Open the model catalog from the Tools section
+
+The **Model Catalog** is also available in the **Tools** section of the Azure AI Foundry Extension view. Double-click on the **Model Catalog** link to open the Model Catalog.
+
+### Deploy a model from the model catalog
 
 Deploy a selected model in the model catalog using the following steps:
 
@@ -163,48 +208,7 @@ Deploy a selected model in the model catalog using the following steps:
 
     :::image type="content" source="../../media/how-to/get-started-projects-vs-code/deployed-model.png" alt-text="Screenshot of the newly deployed model under the Models section." lightbox="../../media/how-to/get-started-projects-vs-code/deployed-model.png":::
 
-### Deploy, view, and update models
-
-#### Deploy a model
-
-You can also deploy a model directly from your Azure AI Foundry project. 
-
-1. In the Azure Resources Extension view, select the **plus** icon next to **Models** to start the deployment process.
-
-    :::image type="content" source="../../media/how-to/get-started-projects-vs-code/select-model-plus-expanded.png" alt-text="Screenshot of the plus sign next to models with the list of models expanded." lightbox="../../media/how-to/get-started-projects-vs-code/select-model-plus-expanded.png":::
-
-    > [!TIP] 
-    > You can also right-click on **Models** and select the **Deploy new AI model** option to start the deployment process. 
-
-1. In the top center, select the AI service to use in the **Choose an AI service** dropdown and press Enter.
-
-    :::image type="content" source="../../media/how-to/get-started-projects-vs-code/choose-ai-service.png" alt-text="Screenshot of the Choose AI service dropdown for model deployment." lightbox="../../media/how-to/get-started-projects-vs-code/choose-ai-service.png":::
-
-1. In the top center, select the model to deploy in the **Choose a model to deploy** dropdown and press Enter.
-
-    :::image type="content" source="../../media/how-to/get-started-projects-vs-code/select-deployment-model.png" alt-text="Screenshot of the Choose a model to deploy dropdown." lightbox="../../media/how-to/get-started-projects-vs-code/select-deployment-model.png":::
-
-1. In the top center, select the model version to use in the **Choose model version** dropdown and press Enter.
-
-    :::image type="content" source="../../media/how-to/get-started-projects-vs-code/select-model-version-2.png" alt-text="Screenshot of the Choose model version dropdown for model deployment." lightbox="../../media/how-to/get-started-projects-vs-code/select-model-version-2.png":::
-
-1. In the top center, select the deployment type to use in the **Choose deployment type** dropdown and press Enter.
-
-    :::image type="content" source="../../media/how-to/get-started-projects-vs-code/select-deployment-type.png" alt-text="Screenshot of the Choose deployment type dropdown for model deployment." lightbox="../../media/how-to/get-started-projects-vs-code/select-deployment-type.png":::
-
-1. In the top center, enter the model deployment name to use in the **Enter deployment name** textbox and press Enter.
-
-    :::image type="content" source="../../media/how-to/get-started-projects-vs-code/enter-deployment-name-2.png" alt-text="Screenshot of the Enter deployment name textbox for model deployment." lightbox="../../media/how-to/get-started-projects-vs-code/enter-deployment-name-2.png":::
-
-1. A confirmation dialog box appears. Select the **Deploy** button to deploy the model to your project.
-
-    :::image type="content" source="../../media/how-to/get-started-projects-vs-code/deploy-model-popup-2.png" alt-text="Screenshot of the model deployment confirmation dialog box with the Deploy button highlighted." lightbox="../../media/how-to/get-started-projects-vs-code/deploy-model-popup-2.png":::
-
-1. After a successful deployment, your model will be listed with your other deployed models under the **Models** section in your project.  
-
-    :::image type="content" source="../../media/how-to/get-started-projects-vs-code/deployed-model-2.png" alt-text="Screenshot of the deployed model under the Models section." lightbox="../../media/how-to/get-started-projects-vs-code/deployed-model-2.png":::
-
-#### View deployed models
+### View deployed models
 
 In the Azure Resources Extension view, select the **caret** icon in front of the **Models** section to view the list of deployed models.
 
@@ -271,7 +275,9 @@ This Python sample code file that demonstrates a basic call to the chat completi
 
 Chat interactively with the model, change settings, and system instructions using the **Model Playground**.
 
-Open the model playground using the following steps:
+The **Model Playground** is available in the **Tools** section of the Azure AI Foundry Extension view. Double-click on the **Model Playground** link to open the Model Playground.
+
+You can also open the model playground using the following steps:
 
 1. Right-click on your deployed model and select the **Open in playground** option. 
 
@@ -294,13 +300,15 @@ The Azure resources that you created in this article are billed to your Azure su
 
 ### Delete your agents
 
-Delete the deployed agent in the [online AI Foundry portal](https://ai.azure.com). Select **Agents** from the navigation menu on the left, select your agent, then select the **Delete** button.
+1. In the VS Code navbar, refresh the **Azure AI Foundry Extension**. In the **Resources** section, expand the **Agents** subsection to display the list of deployed agents.
+
+1. Right-click on your deployed agent to delete and select the **Delete** option.
 
 :::image type="content" source="../../media/how-to/get-started-projects-vs-code/delete-agent.png" alt-text="Screenshot of the AI Foundry portal with 'Agents' from the navigation menu on the left and the **Delete** button highlighted." lightbox="../../media/how-to/get-started-projects-vs-code/delete-agent.png":::
 
 ### Delete your models
 
-1. In the VS Code navbar, refresh the **Azure Resources** view. Expand the **Models** subsection to display the list of deployed models.
+1. In the VS Code navbar, refresh the **Azure AI Foundry Extension**. In the **Resources** section, expand the **Models** subsection to display the list of deployed models.
 
 1. Right-click on your deployed model to delete and select the **Delete** option.