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articles/ai-foundry/agents/includes/quickstart-foundry.md

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## Prerequisites
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- An Azure subscription - <a href="https://azure.microsoft.com/free/cognitive-services" target="_blank">Create one for free</a>.
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- Ensure that the individual creating the account and project has the **Azure AI Account Owner** role at the subscription scope
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* Alternatively, having the **Contributor** or **Cognitive Services Contributor** role at the subscription level also satisfies this requirement.
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- Ensure that the individual creating the account and project has the **Azure AI Account Owner** role at the subscription scope, which will grant the necessary permissions for creating the project
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* Alternatively, having the **Contributor** or **Cognitive Services Contributor** role at the subscription level will allow the creation of the project
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- Once the project is created, ensure that the individual creating the agent within the project has the **Azure AI User** role at the project level
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> [!IMPORTANT]

articles/ai-foundry/foundry-models/how-to/configure-deployment-policies.md

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title: Control model deployment with custom policies
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titleSuffix: Azure AI Foundry
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description: "Learn how to use custom Azure Policies to control Azure AI Foundry and Azure OpenAI in Foundry Models deployment with Azure AI Foundry."
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manager: scottpolly
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manager: mcleans
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ms.service: azure-ai-foundry
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ms.topic: how-to #Don't change
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ms.date: 05/05/2025
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ms.date: 07/31/2025
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author: jonburchel
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ms.reviewer: fasantia
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reviewer: aashishb_microsoft
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---
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# Control model deployment with custom policies

articles/ai-foundry/how-to/access-on-premises-resources.md

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title: How to access on-premises resources
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titleSuffix: Azure AI Foundry
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description: Learn how to configure an Azure AI Foundry managed network to securely allow access to your on-premises resources.
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manager: scottpolly
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manager: mcleans
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ms.service: azure-ai-foundry
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ms.topic: how-to
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ms.date: 05/08/2025
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ms.date: 07/31/2025
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articles/ai-foundry/how-to/azure-policy.md

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description: Learn how to use Azure Policy with Azure AI Foundry to make sure your hubs and projects are compliant with your requirements.
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ms.author: jburchel
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ms.date: 05/01/2025
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ms.date: 07/31/2025
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reviewer: aashishb_microsoft
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# Customer Intent: As an admin, I want to understand how I can use Azure Policy to audit and govern Azure AI Foundry Services so that I can ensure compliance with my organization's requirements.
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articles/ai-foundry/how-to/built-in-policy-model-deployment.md

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#customer intent: As an admin, I want control what Managed AI Services (serverless API deployment) and Model-as-a-Platform (MaaP) AI models can be deployed by my developers.
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articles/ai-foundry/how-to/configure-private-link.md

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title: How to configure a private link for an Azure AI Foundry hub
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titleSuffix: Azure AI Foundry
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description: Learn how to configure a private link for Azure AI Foundry hubs. A private link is used to secure communication with the Azure AI Foundry hub.
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manager: mcleans
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articles/ai-foundry/how-to/data-add.md

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title: How to add and manage data in your Azure AI Foundry project
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titleSuffix: Azure AI Foundry
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description: Learn how to add and manage data in your Azure AI Foundry project.
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[!INCLUDE [hub-only-prereq](../includes/hub-only-prereq.md)]
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## Create data
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## Add new data
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You are charged for the storage used by your data. To help estimate the cost, you can use the [Azure Pricing Calculator](https://azure.microsoft.com/pricing/calculator/). The data is stored in a container called `workspaceblobstore` in your project's Azure Storage account.
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|Type |**Canonical Scenarios**|
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|---------|---------|
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|**`file`**<br>Reference a single file | Read a single file on Azure Storage (the file can have any format). |
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|**`folder`**<br> Reference a folder | Read a folder of parquet/CSV files into Pandas/Spark.<br><br>Read unstructured data (for example: images, text, or audio) located in a folder. |
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|**`folder`**<br>Reference a folder | Read a folder of parquet/CSV files into Pandas/Spark.<br><br>Read unstructured data (for example: images, text, or audio) located in a folder. |
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|**`table`**<br>Reference a table | Read a table on Azure Storage. |
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Azure AI Foundry shows the supported source paths. You can create a data from a folder or file:
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- If you select **folder type**, you can choose the folder URL format. Azure AI Foundry shows the supported folder URL formats. You can create a data resource as shown:
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- If you select **Folder** for the data source **Type**, you can choose the folder URL format. Azure AI Foundry shows the supported folder URL formats. You can create a data resource as shown:
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:::image type="content" source="../media/data-add/studio-url-folder.png" alt-text="Screenshot of folder URL format.":::
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- If you select **file type**, you can choose the file URL format. The supported file URL formats are shown in Azure AI Foundry portal. You can create a data resource as shown:
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- If you select **File** for the data source **Type**, you can choose the file URL format. The supported file URL formats are shown in Azure AI Foundry portal. You can create a data resource as shown:
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:::image type="content" source="../media/data-add/studio-url-file.png" alt-text="Screenshot of file URL format.":::
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### Create data: File type
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- If you select **Table** for the data source **Type**, you can choose the table URL format. The supported file URL formats are shown in Azure AI Foundry portal. You can create a data resource as shown:
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:::image type="content" source="../media/data-add/studio-url-table.png" alt-text="Screenshot of table URL format.":::
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A file (`uri_file`) data resource type points to a *single file* on storage (for example, a CSV file).
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[!INCLUDE [tip-left-pane](../includes/tip-left-pane.md)]
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### Upload files and folders
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These steps explain how to create a File typed data resource in the Azure AI Foundry portal:
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1. Navigate to the [Azure AI Foundry](https://ai.azure.com/?cid=learnDocs).
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You can upload files or folders directly to your workspace storage account by selecting **Upload files/folders** in the **Data source** field as shown:
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1. Select the project where you want to create the data.
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1. From the collapsible **My assets** menu on the left, select **Data + indexes**, then select **New data** as shown in this screenshot:
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:::image type="content" source="../media/data-add/add-data.png" alt-text="Screenshot highlighting New Data in the Data tab.":::
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:::image type="content" source="../media/data-add/upload-file-folder.png" alt-text="This screenshot shows how to upload a file.":::
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1. Choose your **Data source**. To choose a data source, you have two options.
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- You can select **Get data with storage URL** if you have a direct URL to a storage account or a public accessible HTTPS server.
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- You can select **Upload files/folders** to upload a folder from your local drive.
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When you upload files or folders, they are uploaded to the default `workspaceblobstore` connection. The files and folders are uploaded to the root of the storage container.
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- **Get data with Storage URL**: You can choose the "File" as the **Type**, and then provide a URL based on the supported URL formats listed on that page, as shown in this screenshot:
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:::image type="content" source="../media/data-add/file-url.png" alt-text="This screenshot shows the provisioning of a URL that points to a file.":::
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### Add file, folder, and table data from Azure Storage
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- **Upload files/folders**: You can select **Upload files/folders**, select **Upload files**, and choose the local file to upload. The file uploads into the default "workspaceblobstore" connection.
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:::image type="content" source="../media/data-add/upload-file.png" alt-text="This screenshot shows how to upload a file.":::
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You can add file, folder, and table data from Azure Storage to your Azure AI Foundry workspace.
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1. Select **Next** after you choose the data source.
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A file (`uri_file`) data resource type points to a *single file* on storage (for example, a CSV file).
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1. Enter a custom name for your data, and then select **Create**.
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A Folder (`uri_folder`) data source type points to a *folder* on a storage resource (for example, a folder containing several subfolders of images).
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:::image type="content" source="../media/data-add/data-add-finish.png" alt-text="This screenshot shows the naming step for the data source." lightbox="../media/data-connections/data-add-finish.png":::
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A Table (`uri_table`) data source type points to a *table* on a storage resource (for example, a folder that contains tabular data).
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### Create data: Folder type
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[!INCLUDE [tip-left-pane](../includes/tip-left-pane.md)]
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A Folder (`uri_folder`) data source type points to a *folder* on a storage resource (for example, a folder containing several subfolders of images). Use these steps to create a Folder type data resource in Azure AI Foundry portal:
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1. Navigate to [Azure AI Foundry](https://ai.azure.com/?cid=learnDocs)
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1. Navigate to the [Azure AI Foundry](https://ai.azure.com/?cid=learnDocs).
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1. Select the project where you want to create the data.
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1. Select the hub based project where you want to add the data.
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1. From the collapsible **Components** menu on the left, select **Data**.
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1. From the collapsible **My assets** menu on the left, select **Data + indexes**, then select **New data** as shown in this screenshot:
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:::image type="content" source="../media/data-add/add-data.png" alt-text="Screenshot highlighting New Data in the Data tab.":::
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1. Choose your **Data source**. To choose a data source, you have two options.
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1. Select **Get data with Storage URL** if you have a direct URL to a storage account or a public accessible HTTPS server
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1. Select **Upload files/folders** to upload a folder from your local drive
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:::image type="content" source="../media/data-add/folder-url.png" alt-text="This screenshot shows the step to provide a URL that points to a folder.":::
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:::image type="content" source="../media/data-add/upload-folder.png" alt-text="This screenshot shows how to upload a folder.":::
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1. Select **Get data with storage URL** as your **Data source**.
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1. Then choose the *File*, *Folder*, or *Table* as the data **Type**, and then provide a URL based on the supported URL formats listed on that page.
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:::image type="content" source="../media/data-connections/data-add-finish.png" alt-text="Screenshot of naming the data." lightbox="../media/data-connections/data-add-finish.png":::
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:::image type="content" source="../media/data-add/data-add-finish.png" alt-text="This screenshot shows the naming step for the data source." lightbox="../media/data-connections/data-add-finish.png":::
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## Manage data
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After you add data to your hub based project, you can you can delete, archive, restore, tag, archive, and preview the data in the Azure AI Foundry.
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> [!IMPORTANT]
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|The **name** is incorrect | [Archive the data](#archive-data) |
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|The team **no longer uses** the data | [Archive the data](#archive-data) |
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|It **clutters the data listing** | [Archive the data](#archive-data) |
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|The **path** is incorrect | Create a *new version* of the data (same name) with the correct path. For more information, visit [Create data](#create-data). |
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|It has an incorrect **type** | Currently, Azure AI doesn't allow the creation of a new version with a *different* type compared to the initial version.<br>(1) [Archive the data](#archive-data)<br>(2) [Create a new data](#create-data) under a different name with the correct type. |
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|The **path** is incorrect | Create a *new version* of the data (same name) with the correct path. For more information, visit [Add new data](#add-new-data). |
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|It has an incorrect **type** | Currently, Azure AI doesn't allow the creation of a new version with a *different* type compared to the initial version.<br>(1) [Archive the data](#archive-data)<br>(2) [Add new data](#add-new-data) under a different name with the correct type. |
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articles/ai-foundry/how-to/index-add.md

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