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articles/ai-foundry/how-to/develop/ai-template-get-started.md

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1. Go to [Azure AI Foundry portal](https://ai.azure.com).
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1. Open your project in Azure AI Foundry portal.
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1. On the left menu, select **Code** (preview).
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1. On the left menu, select **Samples** (preview).
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1. Find the solution template you want to use.
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1. Select **Open in Github** to view the entire sample application.
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1. Or, clone the repository to your local machine with the provided command.

articles/ai-foundry/how-to/develop/vscode.md

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1. Go to [Azure AI Foundry](https://ai.azure.com).
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1. Open your project in Azure AI Foundry portal.
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1. On the left menu, select **Code**.
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1. On the left menu, select **Templates**.
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1. Select **VS Code container**.
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1. For **Compute**, select an existing compute instance or create a new one.
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* Select a compute instance to use. If it's stopped, select **Start compute** and wait for it to switch to **Running**. You'll see a **Ready** status when the compute is ready for use.

articles/ai-foundry/includes/use-blocklists.md

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## Create a blocklist
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1. Go to [Azure AI Foundry](https://ai.azure.com/) and navigate to your project/hub. Then select the **Safety+ Security** page on the left nav and select the **Blocklists** tab.
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1. Go to [Azure AI Foundry](https://ai.azure.com/) and navigate to your project. Then select the **Safety+ Security** page on the left nav and select the **Blocklists** tab.
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:::image type="content" source="../media/content-safety/content-filter/select-blocklists.png" lightbox="../media/content-safety/content-filter/select-blocklists.png" alt-text="Screenshot of the Blocklists page tab.":::
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1. On the **Input filter** and **Output filter** screens, toggle the **Blocklist** button on. You can then select a blocklist from the list.
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There are two types of blocklists: the custom blocklists you created, and prebuilt blocklists that Microsoft provides—in this case a Profanity blocklist (English).
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1. You can now decide which of the available blocklists you want to include in your content filtering configuration. The last step is to review and finish the content filtering configuration by selecting **Next**. You can always go back and edit your configuration. Once it’s ready, select a **Create content filter**. The new configuration that includes your blocklists can now be applied to a deployment.
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1. You can now decide which of the available blocklists you want to include in your content filtering configuration. The last step is to review and finish the content filtering configuration by selecting **Next**. You can always go back and edit your configuration. Once it’s ready, select a **Create content filter**. The new configuration that includes your blocklists can now be applied to a deployment.

articles/ai-foundry/model-inference/how-to/use-blocklists.md

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* An Azure AI services resource. For more information, see [Create an Azure AI Services resource](../../../ai-services/multi-service-resource.md?context=/azure/ai-services/model-inference/context/context).
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* An Azure AI Foundry project and Azure AI Foundry Hub [connected to your Azure AI services resource](configure-project-connection.md).
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* An Azure AI Foundry project [connected to your Azure AI services resource](configure-project-connection.md).
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* A model deployment. See [Add and configure models to Azure AI services](create-model-deployments.md) for adding models to your resource.
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## Next steps
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* [Configure content filtering](configure-content-filters.md)
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* [Configure content filtering](configure-content-filters.md)

articles/ai-services/.openpublishing.redirection.ai-services.json

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},
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{
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"source_path_from_root": "/articles/ai-services/plan-manage-costs.md",
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"redirect_url": "/azure/ai-studio/how-to/costs-plan-manage",
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"redirect_document_id": true
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"redirect_url": "/azure/ai-foundry/how-to/costs-plan-manage",
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"redirect_document_id": false
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},
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{
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"source_path_from_root": "/articles/ai-services/cognitive-services-and-machine-learning.md",

articles/ai-services/agents/how-to/tools/azure-functions.md

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## Prerequisites
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* [Azure Functions Core Tools v4.x](/azure/azure-functions/functions-run-local)
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* [Azure AI Agent Service](../../../../ai-studio/how-to/develop/sdk-overview.md?tabs=sync&pivots=programming-language-python#azure-ai-agent-service)
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* [Azure AI Agent Service](../../../../ai-foundry/how-to/develop/sdk-overview.md?tabs=sync&pivots=programming-language-python#azure-ai-agent-service)
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* [Azurite](https://github.com/Azure/Azurite)
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## Prepare your local environment

articles/ai-services/agents/how-to/virtual-networks.md

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1. An Azure subscription - [Create one for free](https://azure.microsoft.com/free/cognitive-services).
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2. [Python 3.8 or later](https://www.python.org/)
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3. Ensure that the individual deploying the template has the [Azure AI Developer role](/azure/ai-studio/concepts/rbac-ai-studio) assigned at the resource group level where the template is being deployed.
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3. Ensure that the individual deploying the template has the [Azure AI Developer role](/azure/ai-foundry/concepts/rbac-ai-foundry) assigned at the resource group level where the template is being deployed.
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4. Additionally, to deploy the template, you need to have the preset [Role Based Access Administrator](/azure/role-based-access-control/built-in-roles/privileged#role-based-access-control-administrator) role at the subscription level.
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* The **Owner** role at the subscription level satisfies this requirement.
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* The specific admin role that is needed is `Microsoft.Authorization/roleAssignments/write`
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5. Ensure that each team member who wants to use the Agent Playground or SDK to create or edit agents has been assigned the built-in **Azure AI Developer** [RBAC role](../../../ai-studio/concepts/rbac-ai-studio.md) for the project.
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5. Ensure that each team member who wants to use the Agent Playground or SDK to create or edit agents has been assigned the built-in **Azure AI Developer** [RBAC role](../../../ai-foundry/concepts/rbac-ai-foundry.md) for the project.
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* Note: assign these roles after the template has been deployed
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* The minimum set of permissions required is: **agents/*/read**, **agents/*/action**, **agents/*/delete**
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5. Install [the Azure CLI and the machine learning extension](/azure/machine-learning/how-to-configure-cli). If you have the CLI already installed, make sure it's updated to the latest version.

articles/ai-services/agents/includes/bicep-setup.md

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The following section shows you how to set up the required resources for getting started with Azure AI Agent Service:
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1. Creating an [Azure AI Hub](../../../ai-studio/quickstarts/get-started-playground.md) to set up your app environment and Azure resources.
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1. Creating an [Azure AI Hub](../../../ai-foundry/quickstarts/get-started-playground.md) to set up your app environment and Azure resources.
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1. Creating an Azure AI project under your Hub creates an endpoint for your app to call, and sets up app services to access to resources in your tenant.
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articles/ai-services/agents/includes/quickstart-csharp.md

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* Additionally, to deploy the template, you need to have the preset **Role Based Access Administrator** role at the subscription level.
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* The **Owner** role at the subscription level satisfies this requirement.
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* The specific admin role that is needed is `Microsoft.Authorization/roleAssignments/write`
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* Ensure that each team member who wants to use the Agent Playground or SDK to create or edit agents has been assigned the built-in **Azure AI Developer** [RBAC role](../../../ai-studio/concepts/rbac-ai-studio.md) for the project.
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* Ensure that each team member who wants to use the Agent Playground or SDK to create or edit agents has been assigned the built-in **Azure AI Developer** [RBAC role](../../../ai-foundry/concepts/rbac-ai-foundry.md) for the project.
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* Note: assign these roles after the template has been deployed
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* The minimum set of permissions required is: **agents/*/read**, **agents/*/action**, **agents/*/delete**
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* Install [the Azure CLI and the machine learning extension](/azure/machine-learning/how-to-configure-cli). If you have the CLI already installed, make sure it's updated to the latest version.

articles/ai-services/agents/includes/quickstart-javascript.md

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* Additionally, to deploy the template, you need to have the preset **Role Based Access Administrator** role at the subscription level.
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* The **Owner** role at the subscription level satisfies this requirement.
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* The specific admin role that is needed is `Microsoft.Authorization/roleAssignments/write`
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* Ensure that each team member who wants to use the Agent Playground or Agent SDK to create or edit agents has been assigned the built-in **Azure AI Developer** [RBAC role](../../../ai-studio/concepts/rbac-ai-studio.md) for the project.
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* Ensure that each team member who wants to use the Agent Playground or Agent SDK to create or edit agents has been assigned the built-in **Azure AI Developer** [RBAC role](../../../ai-foundry/concepts/rbac-ai-foundry.md) for the project.
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* Note: assign these roles after the template has been deployed
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* The minimum set of permissions required is: **agents/*/read**, **agents/*/action**, **agents/*/delete**
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* Install [the Azure CLI and the machine learning extension](/azure/machine-learning/how-to-configure-cli). If you have the CLI already installed, make sure it's updated to the latest version.

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