Merge branch 'main' into release-2025-openai-may-27

Author: v-alje

articles/ai-foundry/how-to/deploy-models-managed.md

@@ -22,6 +22,14 @@ Deployment of a large language model (LLM) makes it available for use in a websi
 
 In this article, you learn how to deploy models using the Azure Machine Learning SDK. The article also covers how to perform inference on the deployed model.
 
+## Prerequisites
+
+- An Azure subscription with a valid payment method. Free or trial Azure subscriptions won't work. If you don't have an Azure subscription, create a [paid Azure account](https://azure.microsoft.com/pricing/purchase-options/pay-as-you-go) to begin.
+
+- If you don't have one, [create a [!INCLUDE [hub-project-name](../includes/hub-project-name.md)]](create-projects.md?pivots=hub-project).
+
+- Marketplace purchases enabled for your Azure subscription. Learn more [here](/azure/cost-management-billing/manage/enable-marketplace-purchases).
+
 ## Get the model ID
 
 You can deploy managed compute models using the Azure Machine Learning SDK, but first, let's browse the model catalog and get the model ID you need for deployment.

articles/ai-foundry/how-to/deploy-models-serverless-availability.md

@@ -28,9 +28,6 @@ Certain models in the model catalog can be deployed as a standard deployment. Th
 
 Standard billing is available only to users whose Azure subscription belongs to a billing account in a country/region where the model provider has made the offer available (see "offer availability region" in the table in the next section). If the offer is available in the relevant region, the user then must have a Hub/Project in the Azure region where the model is available for deployment or fine-tuning, as applicable (see "Hub/Project Region" columns in the following tables).
 
-> [!NOTE]
-> If you plan to access your deployed models in Azure Machine Learning Studio, you must use a **[!INCLUDE [hub](../includes/hub-project-name.md)]**, rather than a **[!INCLUDE [fdp](../includes/fdp-project-name.md)]**. For more information, see [Project types](../what-is-azure-ai-foundry.md#project-types).
-
 
 [!INCLUDE [region-availability-maas](../includes/region-availability-maas.md)]
 

articles/ai-foundry/how-to/deploy-models-serverless-connect.md

@@ -35,7 +35,7 @@ The need to consume a standard deployments endpoint in a different project or hu
 
 - An [Azure AI Foundry hub](create-azure-ai-resource.md), if you're using a **[!INCLUDE [hub](../includes/hub-project-name.md)]**. A **[!INCLUDE [fdp](../includes/fdp-project-name.md)]** does not use a hub. For more information, see [Project types](../what-is-azure-ai-foundry.md#project-types).
 
-- An [Azure AI Foundry project](create-projects.md).
+- If you don't have one, [create a [!INCLUDE [hub](../includes/hub-project-name.md)]](create-projects.md?pivots=hub-project).
 
 - A model [deployed to a standard deployments](deploy-models-serverless.md). This article assumes that you previously deployed the **Meta-Llama-3-8B-Instruct** model. To learn how to deploy this model as a standard deployment, see [Deploy models as standard deployments](deploy-models-serverless.md).
 

articles/ai-foundry/how-to/deploy-models-serverless.md

@@ -27,7 +27,7 @@ This article uses a Meta Llama model deployment for illustration. However, you c
 
 - An Azure subscription with a valid payment method. Free or trial Azure subscriptions won't work. If you don't have an Azure subscription, create a [paid Azure account](https://azure.microsoft.com/pricing/purchase-options/pay-as-you-go) to begin.
 
-- An [Azure AI Foundry project](create-projects.md).
+- If you don't have one, [create a [!INCLUDE [hub](../includes/hub-project-name.md)]](create-projects.md?pivots=hub-project).
 
 - Ensure that the **Deploy models to Azure AI model inference service** feature is turned off in the Azure AI Foundry portal. When this feature is on, standard deployments are not available for deployment when using the portal.
 

articles/ai-foundry/how-to/deploy-nvidia-inference-microservice.md

@@ -25,7 +25,7 @@ NVIDIA inference microservices are containers built by NVIDIA for optimized pret
 
 - An Azure subscription with a valid payment method. Free or trial Azure subscriptions won't work. If you don't have an Azure subscription, create a [paid Azure account](https://azure.microsoft.com/pricing/purchase-options/pay-as-you-go) to begin.
 
-- An [Azure AI Foundry project](create-projects.md).
+- If you don't have one, [create a [!INCLUDE [hub](../includes/hub-project-name.md)]](create-projects.md?pivots=hub-project).
 
 - Marketplace purchases enabled for your Azure subscription. Learn more [here](/azure/cost-management-billing/manage/enable-marketplace-purchases).
 

articles/ai-foundry/how-to/healthcare-ai/deploy-cxrreportgen.md

@@ -37,7 +37,7 @@ The CXRReportGen model combines a radiology-specific image encoder with a large
 
 - An Azure subscription with a valid payment method. Free or trial Azure subscriptions won't work. If you don't have an Azure subscription, create a [paid Azure account](https://azure.microsoft.com/pricing/purchase-options/pay-as-you-go) to begin.
 
-- An [Azure AI Foundry project](../create-projects.md).
+- If you don't have one, [create a [!INCLUDE [hub](../../includes/hub-project-name.md)]](../create-projects.md?pivots=hub-project).
 
 - Azure role-based access controls (Azure RBAC) are used to grant access to operations in Azure AI Foundry portal. To perform the steps in this article, your user account must be assigned the __Azure AI Developer role__ on the resource group. For more information on permissions, see [Role-based access control in Azure AI Foundry portal](../../concepts/rbac-ai-foundry.md).
 

articles/ai-foundry/how-to/healthcare-ai/deploy-medimageinsight.md

@@ -35,7 +35,8 @@ An embedding model is capable of serving as the basis of many different solution
 
 - An Azure subscription with a valid payment method. Free or trial Azure subscriptions won't work. If you don't have an Azure subscription, create a [paid Azure account](https://azure.microsoft.com/pricing/purchase-options/pay-as-you-go) to begin.
 
-- An [Azure AI Foundry project](../create-projects.md).
+- If you don't have one, [create a [!INCLUDE [hub](../../includes/hub-project-name.md)]](../create-projects.md?pivots=hub-project).
+
 
 - Azure role-based access controls (Azure RBAC) are used to grant access to operations in Azure AI Foundry portal. To perform the steps in this article, your user account must be assigned the __Azure AI Developer role__ on the resource group. For more information on permissions, see [Role-based access control in Azure AI Foundry portal](../../concepts/rbac-ai-foundry.md).
 

articles/ai-foundry/how-to/healthcare-ai/deploy-medimageparse.md

@@ -47,7 +47,7 @@ Similar to the MedImageParse model, MedImageParse 3D uses a combination of a tex
 
 - An Azure subscription with a valid payment method. Free or trial Azure subscriptions won't work. If you don't have an Azure subscription, create a [paid Azure account](https://azure.microsoft.com/pricing/purchase-options/pay-as-you-go) to begin.
 
-- An [Azure AI Foundry project](../create-projects.md).
+- If you don't have one, [create a [!INCLUDE [hub](../../includes/hub-project-name.md)]](../create-projects.md?pivots=hub-project).
 
 - Azure role-based access controls (Azure RBAC) are used to grant access to operations in Azure AI Foundry portal. To perform the steps in this article, your user account must be assigned the __Azure AI Developer role__ on the resource group. For more information on permissions, see [Role-based access control in Azure AI Foundry portal](../../concepts/rbac-ai-foundry.md).
 

articles/ai-foundry/includes/find-endpoint.md

@@ -0,0 +1,17 @@
+---
+title: Include file
+description: Include file
+author: sgilley
+ms.author: sgilley
+ms.service: azure-ai-foundry
+ms.topic: include
+ms.date: 05/13/2025
+ms.custom: include file
+---
+
+Copy the **Azure AI Foundry project endpoint** in the **Overview** section of your project. You'll use it in a moment.
+
+:::image type="content" source="../media/how-to/projects/fdp-project-overview.png" alt-text="Screenshot shows the project overview for a Foundry project.":::
+
+> [!TIP]
+> If you don't see the **Azure AI Foundry project endpoint**, you're using a [!INCLUDE [hub-project-name](hub-project-name.md)]. (See [Types of projects](../what-is-azure-ai-foundry.md#project-types)). Switch to a [!INCLUDE [fdp-project-name](fdp-project-name.md)], or use the preceding steps to create one.

articles/ai-foundry/includes/get-started-fdp.md

@@ -45,7 +45,7 @@ The Azure AI Foundry SDK is available in multiple languages, including Python, J
 
 You now have both a project and a model available for your agent.
 
-### Set up your environment  
+## Set up your environment  
 
 # [Azure AI Foundry portal](#tab/azure-ai-foundry)
 
@@ -60,22 +60,24 @@ No installation is necessary to use the Azure AI Foundry portal.
     pip install openai azure-ai-projects azure-identity
     ```
 
+1. [!INCLUDE [find-endpoint](find-endpoint.md)]
 1. Make sure to sign in using the CLI `az login` (or `az login --use-device-code`) command to authenticate before running your Python scripts.
 
-> [!TIP]
+> [!NOTE]
 > All the code in this article is at [GitHub Quickstart](https://github.com/azure-ai-foundry/foundry-samples/tree/main/samples/microsoft/python/mslearn-resources/quickstart).
 
 # [Java (preview)](#tab/java)
 
 1. [Install Java and Azure CLI](../how-to/develop/install-cli-sdk.md?pivots=programming-language-java).
+1. [!INCLUDE [find-endpoint](find-endpoint.md)]
 1. Set these environment variables to use in your scripts:
 
     :::code language="plaintext" source="~/foundry-samples-main/samples/microsoft/java/mslearn-resources/quickstart/.env.template":::
 
 1. Make sure to sign in using the CLI `az login` (or `az login --use-device-code`) command to authenticate before running your Java scripts.
 1. Download [POM.XML](https://github.com/azure-ai-foundry/foundry-samples/blob/main/samples/microsoft/java/mslearn-resources/quickstart/pom.xml) to your Java IDE.
 
-> [!TIP]
+> [!NOTE]
 > All the code in this article is at [GitHub Quickstart](https://github.com/azure-ai-foundry/foundry-samples/blob/main/samples/microsoft/java/mslearn-resources/quickstart).
 
 # [JavaScript (preview)](#tab/javascript)
@@ -84,12 +86,13 @@ No installation is necessary to use the Azure AI Foundry portal.
 1. Make sure to sign in using the CLI `az login` (or `az login --use-device-code`) command to authenticate before running your JavaScript scripts.
 1. Download [package.json](https://github.com/azure-ai-foundry/foundry-samples/blob/main/samples/microsoft/javascript/mslearn-resources/quickstart/package.json).
 1. Install packages with `npm install`
+1. [!INCLUDE [find-endpoint](find-endpoint.md)]
 1. Set these environment variables to use in your scripts:
 
     :::code language="plaintext" source="~/foundry-samples-main/samples/microsoft/javascript/mslearn-resources/quickstart/.env.template":::
 
 
-> [!TIP]
+> [!NOTE]
 > All the code in this article is at [GitHub Quickstart](https://github.com/azure-ai-foundry/foundry-samples/tree/main/samples/microsoft/javascript/mslearn-resources/quickstart).
 
 # [C#](#tab/csharp)
@@ -99,13 +102,15 @@ No installation is necessary to use the Azure AI Foundry portal.
 
     [!INCLUDE [install-csharp-packages](install-csharp-packages.md)]
 
+1. [!INCLUDE [find-endpoint](find-endpoint.md)]
+
 1. Set these environment variables to use in your scripts:
 
     :::code language="plaintext" source="~/foundry-samples-main/samples/microsoft/csharp/mslearn-resources/quickstart/Samples/.env.example":::
 
 1. Make sure to sign in using the CLI `az login` (or `az login --use-device-code`) command to authenticate before running your C# scripts.
 
-> [!TIP]
+> [!NOTE]
 > All the code in this article is at [GitHub Quickstart](https://github.com/azure-ai-foundry/foundry-samples/tree/main/samples/microsoft/csharp/mslearn-resources/quickstart).
 
 # [REST API](#tab/rest)
@@ -120,7 +125,7 @@ No installation is necessary to use the Azure AI Foundry portal.
     
 1. Save the results as the environment variable `AZURE_AI_AUTH_TOKEN`.  
 
-> [!TIP]
+> [!NOTE]
 > All the code in this article is at [GitHub Quickstart](https://github.com/azure-ai-foundry/foundry-samples/tree/main/samples/microsoft/REST/mslearn-resources/quickstart).
 
 
@@ -140,6 +145,8 @@ After the preceding steps, you're now in the agents playground.
 
 # [Python](#tab/python)
 
+Substitute your endpoint for the `endpoint` in this code:
+
 :::code language="python" source="~/foundry-samples-main/samples/microsoft/python/mslearn-resources/quickstart/quickstart.py" id="create_and_run_agent":::
 
 # [Java (preview)](#tab/java)
@@ -183,6 +190,8 @@ Now let's add a file search tool that enables us to do knowledge retrieval.
 
 # [Python](#tab/python)
 
+Substitute your endpoint for the `endpoint` in this code:
+
 :::code language="python" source="~/foundry-samples-main/samples/microsoft/python/mslearn-resources/quickstart/quickstart.py" id="create_filesearch_agent":::
 
 # [Java (preview)](#tab/java)
@@ -219,7 +228,7 @@ Chat completions are the basic building block of AI applications. Using chat com
 
 # [Python](#tab/python)
 
-Substitute your value for the endpoint in this code:
+Substitute your endpoint for the `endpoint` in this code:
 
 :::code language="python" source="~/foundry-samples-main/samples/microsoft/python/mslearn-resources/quickstart/quickstart.py" id="chat_completion":::