Merge pull request #5362 from msakande/fix-conflict-with-main

AI services  Dirty PR for release branch merge conflict with upstream main

Author: v-ccolin

articles/ai-foundry/ai-services/content-safety-overview.md

@@ -14,7 +14,7 @@ author: PatrickFarley
 
 # Content Safety in the Azure AI Foundry portal
 
-Azure AI Content Safety is an AI service that detects harmful user-generated and AI-generated content in applications and services. Azure AI Content Safety includes APIs that allow you to detect and prevent the output of harmful content. The interactive Content Safety **try it out** page in [Azure AI Foundry portal](https://ai.azure.com) allows you to view, explore, and try out sample code for detecting harmful content across different modalities. 
+Azure AI Content Safety is an AI service that detects harmful user-generated and AI-generated content in applications and services. Azure AI Content Safety includes APIs that allow you to detect and prevent the output of harmful content. The interactive Content Safety **try it out** page in [Azure AI Foundry portal](https://ai.azure.com/?cid=learnDocs) allows you to view, explore, and try out sample code for detecting harmful content across different modalities. 
 
 ## Features
 
@@ -46,4 +46,4 @@ Refer to the [Content Safety overview](/azure/ai-services/content-safety/overvie
 
 ## Next step
 
-Get started using Azure AI Content Safety in [Azure AI Foundry portal](https://ai.azure.com) by following the [How-to guide](/azure/ai-services/content-safety/how-to/foundry).
+Get started using Azure AI Content Safety in [Azure AI Foundry portal](https://ai.azure.com/?cid=learnDocs) by following the [How-to guide](/azure/ai-services/content-safety/how-to/foundry).

articles/ai-foundry/concepts/ai-resources.md

@@ -25,7 +25,7 @@ ms.custom:
 
 Azure AI Hub is a resource type that is used in combination with Azure AI Foundry resource type, and is only required for selected use cases. Hub resources provides access to open-source model hosting and finetuning capabilities, as well as Azure Machine Learning capabilities, next to capabilities supported by its associated AI Foundry resource.
 
-When you create an AI Hub, an Azure AI Foundry resource is automatically provisioned. Hub resources can be used in [Azure AI Foundry](https://ai.azure.com) and [Azure Machine Learning studio](https://ml.azure.com).
+When you create an AI Hub, an Azure AI Foundry resource is automatically provisioned. Hub resources can be used in [Azure AI Foundry](https://ai.azure.com/?cid=learnDocs) and [Azure Machine Learning studio](https://ml.azure.com).
 
 Hubs have their own project types that support a differentiated feature set from Foundry projects. See [project types](../what-is-azure-ai-foundry.md#which-type-of-project-do-i-need) for an overview of supported features.
 
@@ -37,7 +37,7 @@ Hubs group one or more projects together with common settings including data acc
 
 ## Create a hub-based project
 
-To start developing, [create a project](../how-to/create-projects.md). Hub-projects can be accessed in [AI Foundry Portal](https://ai.azure.com) to build with generative AI tools, and [ML Studio](https://ml.azure.com) to build with tools designed for custom machine learning model training.
+To start developing, [create a project](../how-to/create-projects.md). Hub-projects can be accessed in [AI Foundry Portal](https://ai.azure.com/?cid=learnDocs) to build with generative AI tools, and [ML Studio](https://ml.azure.com) to build with tools designed for custom machine learning model training.
 
 ## Project concepts
 

articles/ai-foundry/concepts/content-filtering.md

@@ -17,7 +17,7 @@ author: PatrickFarley
 
 # Content filtering in Azure AI Foundry portal
 
-[Azure AI Foundry](https://ai.azure.com) includes a content filtering system that works alongside core models and image generation models.
+[Azure AI Foundry](https://ai.azure.com/?cid=learnDocs) includes a content filtering system that works alongside core models and image generation models.
 
 > [!IMPORTANT]
 > The content filtering system isn't applied to prompts and completions processed by the Whisper model in Azure OpenAI in Azure AI Foundry Models. Learn more about the [Whisper model in Azure OpenAI](../../ai-services/openai/concepts/models.md).

articles/ai-foundry/concepts/encryption-keys-portal.md

@@ -18,7 +18,7 @@ zone_pivot_groups: project-type
 
 # Customer-managed keys for encryption with Azure AI Foundry
 
-Customer-managed keys (CMKs) in [Azure AI Foundry portal](https://ai.azure.com/) provide enhanced control over the encryption of your data. By using CMKs, you can manage your own encryption keys to add an extra layer of protection and meet compliance requirements more effectively.
+Customer-managed keys (CMKs) in [Azure AI Foundry portal](https://ai.azure.com/?cid=learnDocs) provide enhanced control over the encryption of your data. By using CMKs, you can manage your own encryption keys to add an extra layer of protection and meet compliance requirements more effectively.
 
 ## About encryption in Azure AI Foundry
 
@@ -68,7 +68,7 @@ Two architecture options are available when using customer-managed keys:
   |-----|-----|-----|
   |Azure Cosmos DB|Stores metadata for your Azure AI projects and tools|Index names, tags; Flow creation timestamps; deployment tags; evaluation metrics|
   |Azure AI Search|Stores indices that are used to help query your Azure AI Foundry content.|An index based off your model deployment names|
-  |Azure Storage Account|Stores instructions for how customization tasks are orchestrated|JSON representation of flows you create in [Azure AI Foundry portal](https://ai.azure.com/)|
+  |Azure Storage Account|Stores instructions for how customization tasks are orchestrated|JSON representation of flows you create in [Azure AI Foundry portal](https://ai.azure.com/?cid=learnDocs)|
 
 
 ::: zone-end

articles/ai-foundry/concepts/fine-tuning-overview.md

@@ -27,7 +27,7 @@ Consider fine-tuning GenAI models to:
 - Save time and resources with faster and more precise results
 - Get more relevant and context-aware outcomes as models are fine-tuned for specific use cases
 
-[Azure AI Foundry](https://ai.azure.com) offers several models across model providers enabling you to get access to the latest and greatest in the market. [View this list for more details](#supported-models-for-fine-tuning). 
+[Azure AI Foundry](https://ai.azure.com/?cid=learnDocs) offers several models across model providers enabling you to get access to the latest and greatest in the market. [View this list for more details](#supported-models-for-fine-tuning). 
 
 :::image type="content" source="../media/concepts/model-catalog-fine-tuning.png" alt-text="Screenshot of Azure AI Foundry model catalog and filtering by Fine-tuning tasks." lightbox="../media/concepts/model-catalog-fine-tuning.png":::
 

articles/ai-foundry/concepts/foundry-models-overview.md

@@ -129,7 +129,7 @@ Network isolation | [Configure managed networks for Azure AI Foundry hubs](../ho
 
 For Azure OpenAI models, see [Azure OpenAI](../../ai-services/openai/concepts/models.md).
 
-To view a list of supported models for standard deployment or Managed Compute, go to the home page of the model catalog in [Azure AI Foundry](https://ai.azure.com). Use the **Deployment options** filter to select either **Standard deployment** or **Managed Compute**. 
+To view a list of supported models for standard deployment or Managed Compute, go to the home page of the model catalog in [Azure AI Foundry](https://ai.azure.com/?cid=learnDocs). Use the **Deployment options** filter to select either **Standard deployment** or **Managed Compute**. 
 
 :::image type="content" source="../media/how-to/model-catalog-overview/catalog-filter.png" alt-text="A screenshot showing how to filter by managed compute models in the catalog." lightbox="../media/how-to/model-catalog-overview/catalog-filter.png":::  
 

articles/ai-foundry/concepts/management-center.md

@@ -25,7 +25,7 @@ The management center is a part of the Azure AI Foundry portal that streamlines
 
 - User management and role assignment
 
-To access the management center, sign in to [Azure AI Foundry](https://ai.azure.com), select a project, and then select **Management center** from the bottom of left menu.
+To access the management center, sign in to [Azure AI Foundry](https://ai.azure.com/?cid=learnDocs), select a project, and then select **Management center** from the bottom of left menu.
 
 :::image type="content" source="../media/management-center/management-center.png" alt-text="Screenshot of the left menu of Azure AI Foundry with the management center selected." lightbox="../media/management-center/management-center.png":::
 

articles/ai-foundry/concepts/prompt-flow.md

@@ -23,7 +23,7 @@ ms.update-cycle: 180-days
 
 Prompt flow is a development tool designed to streamline the entire development cycle of AI applications powered by Large Language Models (LLMs). Prompt flow provides a comprehensive solution that simplifies the process of prototyping, experimenting, iterating, and deploying your AI applications.
 
-Prompt flow is available independently as an open-source project on [GitHub](https://github.com/microsoft/promptflow), with its own SDK and [VS Code extension](https://marketplace.visualstudio.com/items?itemName=prompt-flow.prompt-flow). Prompt flow is also available and recommended to use as a feature within both [Azure AI Foundry](https://ai.azure.com) and [Azure Machine Learning studio](https://ml.azure.com). This set of documentation focuses on prompt flow in Azure AI Foundry portal.
+Prompt flow is available independently as an open-source project on [GitHub](https://github.com/microsoft/promptflow), with its own SDK and [VS Code extension](https://marketplace.visualstudio.com/items?itemName=prompt-flow.prompt-flow). Prompt flow is also available and recommended to use as a feature within both [Azure AI Foundry](https://ai.azure.com/?cid=learnDocs) and [Azure Machine Learning studio](https://ml.azure.com). This set of documentation focuses on prompt flow in Azure AI Foundry portal.
 
 Definitions:
 

articles/ai-foundry/concepts/rbac-azure-ai-foundry.md

@@ -9,7 +9,7 @@ ms.custom:
   - build-2024
   - ignite-2024
 ms.topic: conceptual
-ms.date: 03/04/2025
+ms.date: 06/04/2025
 ms.reviewer: deeikele
 ms.author: larryfr
 author: Blackmist
@@ -18,7 +18,7 @@ zone_pivot_groups: project-type
 
 # Role-based access control in Azure AI Foundry portal
 
-In this article, you learn how to manage access (authorization) to your [Azure AI Foundry](https://ai.azure.com) resources. Azure role-based access control (Azure RBAC) is used to manage access to Azure resources, such as the ability to create new resources or use existing ones. Users in your Microsoft Entra ID are assigned specific roles, which grant access to resources. Azure provides both built-in roles and the ability to create custom roles.
+In this article, you learn how to manage access (authorization) to your [Azure AI Foundry](https://ai.azure.com/?cid=learnDocs) resources. Azure role-based access control (Azure RBAC) is used to manage access to Azure resources, such as the ability to create new resources or use existing ones. Users in your Microsoft Entra ID are assigned specific roles, which grant access to resources. Azure provides both built-in roles and the ability to create custom roles.
 
 Azure AI Foundry supports two types of projects: a **[!INCLUDE [fdp](../includes/fdp-project-name.md)]** and a **[!INCLUDE [hub](../includes/hub-project-name.md)]**. For more information about the differences between these two project types, see [Types of projects](../what-is-azure-ai-foundry.md#project-types). Use the selector at the top of this article to switch between the two project types.
 
@@ -220,12 +220,12 @@ For example, if you're trying to consume a new Blob storage, you need to ensure
 
 ## Manage access with roles
 
-If you're an owner of a Foundry account resource, you can add and remove roles for Azure AI Foundry. From the **Home** page in [Azure AI Foundry](https://ai.azure.com), select your Foundry resource. Then select **Users** to add and remove users for the hub. You can also manage permissions from the [Azure portal](https://portal.azure.com) under **Access Control (IAM)** or through the Azure CLI.
+If you're an owner of a Foundry account resource, you can add and remove roles for Azure AI Foundry. From the **Home** page in [Azure AI Foundry](https://ai.azure.com/?cid=learnDocs), select your Foundry resource. Then select **Users** to add and remove users for the hub. You can also manage permissions from the [Azure portal](https://portal.azure.com) under **Access Control (IAM)** or through the Azure CLI.
 
-For example, use the Azure CLI to assign the Azure AI User role to `[email protected]` for resource group `this-rg` with the following command:
+For example, the following command assigns Azure AI User role to `[email protected]` for resource group `this-rg` in the subscription with an ID of `00000000-0000-0000-0000-000000000000`:
 
 ```azurecli
-az role assignment create --role "Azure AI User" --assignee "[email protected]" --resource-group this-rg 
+az role assignment create --role "Azure AI User" --assignee "[email protected]" --scope /subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/this-rg 
 ```
 
 ## Create custom roles
@@ -461,10 +461,10 @@ For example, if you're trying to consume a new Blob storage, you need to ensure
 
 ## Manage access with roles 
 
-If you're an owner of a hub, you can add and remove roles for Azure AI Foundry. Go to the **Home** page in [Azure AI Foundry](https://ai.azure.com) and select your hub. Then select **Users** to add and remove users for the hub. You can also manage permissions from the Azure portal under **Access Control (IAM)** or through the Azure CLI. For example, use the [Azure CLI](/cli/azure/) to assign the Azure AI Developer role to "[email protected]" for resource group "this-rg" with the following command: 
+If you're an owner of a hub, you can add and remove roles for Azure AI Foundry. Go to the **Home** page in [Azure AI Foundry](https://ai.azure.com/?cid=learnDocs) and select your hub. Then select **Users** to add and remove users for the hub. You can also manage permissions from the Azure portal under **Access Control (IAM)** or through the Azure CLI. For example, to assign the Azure AI Developer role to "[email protected]" for resource group "this-rg" in the subscription with an ID of `00000000-0000-0000-0000-000000000000`, you can use the following Azure CLI command: 
  
 ```azurecli-interactive
-az role assignment create --role "Azure AI Developer" --assignee "[email protected]" --resource-group this-rg 
+az role assignment create --role "Azure AI Developer" --assignee "[email protected]" --scope /subscriptions/00000000-0000-0000-0000-000000000000/resourceGroups/this-rg 
 ```
 
 ## Create custom roles

articles/ai-foundry/concepts/vulnerability-management.md

@@ -20,7 +20,7 @@ author: Blackmist
 
 Vulnerability management involves detecting, assessing, mitigating, and reporting on any security vulnerabilities that exist in an organization's systems and software. Vulnerability management is a shared responsibility between you and Microsoft.
 
-This article discusses these responsibilities and outlines the vulnerability management controls that [Azure AI Foundry](https://ai.azure.com) provides. You learn how to keep your service instance and applications up to date with the latest security updates, and how to minimize the window of opportunity for attackers.
+This article discusses these responsibilities and outlines the vulnerability management controls that [Azure AI Foundry](https://ai.azure.com/?cid=learnDocs) provides. You learn how to keep your service instance and applications up to date with the latest security updates, and how to minimize the window of opportunity for attackers.
 
 ## Microsoft-managed VM images