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articles/ai-foundry/agents/concepts/model-region-support.md

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Azure AI Foundry Agent Service supports the following Azure OpenAI models in the listed regions.
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> [!NOTE]
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> * [Hub based projects](../../what-is-azure-ai-foundry.md#project-types) are limited to the following models: gpt-4o, gpt-4o-mini, gpt-4, gpt-35-turbo
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> * [Hub-based projects](../../what-is-azure-ai-foundry.md#project-types) are limited to the following models: gpt-4o, gpt-4o-mini, gpt-4, gpt-35-turbo
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> * For information on class A subnet support, see the setup guide on [GitHub](https://github.com/azure-ai-foundry/foundry-samples/tree/main/samples/microsoft/infrastructure-setup/15-private-network-standard-agent-setup).
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> * The [file search tool](../how-to/tools/file-search.md) is currently unavailable in the following regions:
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> * Italy north

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

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Now that you know when to use fine-tuning for your use case, you can go to Azure AI Foundry to find models available to fine-tune.
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**To fine-tune an AI Foundry model using Serverless** you must have a hub/project in the region where the model is available for fine tuning. See [Region availability for models in serverless API deployment](../how-to/deploy-models-serverless-availability.md) for detailed information on model and region availability, and [How to Create a Hub based project](../how-to/create-projects.md) to create your project.
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**To fine-tune an AI Foundry model using Serverless** you must have a hub/project in the region where the model is available for fine tuning. See [Region availability for models in serverless API deployment](../how-to/deploy-models-serverless-availability.md) for detailed information on model and region availability, and [How to Create a Hub-based project](../how-to/create-projects.md) to create your project.
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**To fine-tune an OpenAI model** you can use an Azure OpenAI Resource, a Foundry resource or default project, or a hub/project. GPT 4.1, 4.1-mini and 4.1-nano are available in all regions with Global Training. For regional availability, see [Regional Availability and Limits for Azure OpenAI Fine Tuning](../openai/concepts/models.md). See [Create a project for Azure AI Foundry](../how-to/create-projects.md) for instructions on creating a new project.
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**To fine-tune a model using Managed Compute** you must have a hub/project and available VM quota for training and inferencing. See [Fine-tune models using managed compute (preview)](../how-to/fine-tune-managed-compute.md) for more details on how to use managed compute fine tuning, and [How to Create a Hub based project](../how-to/create-projects.md) to create your project.
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**To fine-tune a model using Managed Compute** you must have a hub/project and available VM quota for training and inferencing. See [Fine-tune models using managed compute (preview)](../how-to/fine-tune-managed-compute.md) for more details on how to use managed compute fine tuning, and [How to Create a Hub-based project](../how-to/create-projects.md) to create your project.
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## Related content

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

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For more information, see [Create a [!INCLUDE [fdp-project-name](../includes/fdp-project-name.md)]](../how-to/create-projects.md?pivots=fdp-project)
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### Manage Azure AI Foundry hubs and hub based projects
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### Manage Azure AI Foundry hubs and hub-based projects
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You can also manage [!INCLUDE [hub](../includes/hub-project-name.md)]s from the management center. They're listed in the __All resources__ section, and when selected are displayed in the left menu.
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articles/ai-foundry/how-to/azure-policy.md

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|---|---|---|
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| Azure AI Foundry App | cb2ff863-7f30-4ced-ab89-a00194bcf6d9 | Use to control access to the Azure AI Foundry portal. |
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| Azure Machine Learning Web App | d7304df8-741f-47d3-9bc2-df0e24e2071f | Use to control access to Azure Machine Learning studio. |
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| Azure Machine Learning | 0736f41a-0425-bdb5-1563eff02385 | Use to control direct access to the Azure Machine Learning API. For example, when using the SDK or REST API. Azure AI Foundry hub based projects rely on the Azure Machine Learning API. |
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| Azure Machine Learning | 0736f41a-0425-bdb5-1563eff02385 | Use to control direct access to the Azure Machine Learning API. For example, when using the SDK or REST API. Azure AI Foundry hub-based projects rely on the Azure Machine Learning API. |
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## Configure built-in policies
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articles/ai-foundry/how-to/connections-add.md

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title: Add a new connection to your project
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titleSuffix: Azure AI Foundry
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description: Learn how to add a new connection to your hub based or Foundry project.
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description: Learn how to add a new connection to your hub-based or Foundry project.
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ms.service: azure-ai-foundry
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ms.custom:
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- ignite-2023

articles/ai-foundry/how-to/data-add.md

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[!INCLUDE [tip-left-pane](../includes/tip-left-pane.md)]
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These steps explain how to add an existing file, folder, or table data resource from Azure Storage to your hub based project workspace in the Azure AI Foundry portal:
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These steps explain how to add an existing file, folder, or table data resource from Azure Storage to your hub-based project workspace 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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1. Select the hub based project where you want to add 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 **My assets** menu on the left, select **Data + indexes**, then select **New data** as shown in this screenshot:
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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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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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### Delete data
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articles/ai-foundry/how-to/evaluation-azure-devops.md

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```
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# [Hub based project](#tab/hub-project)
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# [Hub-based project](#tab/hub-project)
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```yaml
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articles/ai-foundry/how-to/evaluation-github-action.md

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- `azure-ai-project-endpoint`: The endpoint of the Azure AI project. This is used to connect to your AI project to simulate conversations with each agent, and to connect to the Azure AI evaluation SDK to perform the evaluation.
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# [Hub based project](#tab/hub-project)
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# [Hub-based project](#tab/hub-project)
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- `azure-aiproject-connection-string`: The connection string of the Azure AI project. This is used to connect to your AI project to simulate conversations with each agent, and to connect to the Azure AI evaluation SDK to perform the evaluation.
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```
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# [Hub based project](#tab/hub-project)
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# [Hub-based project](#tab/hub-project)
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```YAML
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name: "AI Agent Evaluation"

articles/ai-foundry/how-to/evaluations-storage-account.md

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# How to create and configure your storage account for use in Azure AI Foundry Projects
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> [!IMPORTANT]
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> This guidance only applies to the new Foundry resource based projects, not hub based projects. These steps aren't required for hub based projects.
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> This guidance only applies to the new Foundry resource based projects, not hub-based projects. These steps aren't required for hub-based projects.
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When running evaluations with user provided datasets, users must connect a Storage Account to their Azure AI Foundry Resource. This is the storage account that is used to store these datasets. However, providing this connection isn't enough, the project must also be given contributor access to the blob storage to allow read and write access to the storage account. These instructions walk you through how to create the storage account, connect it to your project, and give resource permission.
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articles/ai-foundry/how-to/migrate-project.md

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title: Migrate From Hub based to Foundry Projects
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title: Migrate From Hub-based to Foundry Projects
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description: Learn how to migrate from existing hub-based projects to new Azure AI Foundry projects to access the latest platform capabilities, unified workflows, and enhanced governance features.
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# Migrate from hub based to Foundry projects
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# Migrate from hub-based to Foundry projects
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This guide helps existing customers with [!INCLUDE [hub-project-name](../includes/hub-project-name.md)]s migrate to the new [!INCLUDE [fdp-project-name](../includes/fdp-project-name.md)]s to access the latest platform capabilities.
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You'll create new [!INCLUDE [fdp-project-name](../includes/fdp-project-name.md)]s in the AI Foundry models resource from your [!INCLUDE [hub-project-name](../includes/hub-project-name.md)]. This process allows the new projects to access work originally done in the [!INCLUDE [hub-project-name](../includes/hub-project-name.md)].
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:::image type="content" source="../media/migrate-project/upgrade.svg" alt-text="Screenshot shows the upgrade path from hub based to Foundry project types.":::
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:::image type="content" source="../media/migrate-project/upgrade.svg" alt-text="Screenshot shows the upgrade path from hub-based to Foundry project types.":::
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What can you take forward to the new project type?
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See the [SDK migration guide](https://github.com/Azure/azure-sdk-for-python/blob/main/sdk/ai/azure-ai-projects/AGENTS_MIGRATION_GUIDE.md) on how to update your existing code.
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## (Optional) Clean up hub based projects
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## (Optional) Clean up hub-based projects
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If you no longer require access to your [!INCLUDE [hub-project-name](../includes/hub-project-name.md)]s, delete them from your Azure subscription.
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