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* add configurable deployment settings table
* add azure quick deploy
* add guidance for selecting quota and region
* add guidance for selecting a new region
Copy file name to clipboardExpand all lines: README.md
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@@ -16,9 +16,11 @@ Instructions are provided for deployment through GitHub Codespaces, VS Code Dev
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## Quick Deploy
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|[](https://codespaces.new/Azure-Samples/get-started-with-ai-agents)|[](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/Azure-Samples/get-started-with-ai-agents)||
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|[](https://codespaces.new/Azure-Samples/get-started-with-ai-agents)|[](https://vscode.dev/redirect?url=vscode://ms-vscode-remote.remote-containers/cloneInVolume?url=https://github.com/Azure-Samples/get-started-with-ai-agents)|[](https://portal.azure.com/#create/Microsoft.Template/uri/https%3A%2F%2Fraw.githubusercontent.com%2FAzure-Samples%2Fget-started-with-ai-agents%2Frefs%2Fheads%2Fmain%2Finfra%2Fmain.json)|
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Github Codespaces and Dev Containers both allow you to download and deploy the code for development. Deploy to Azure will create the resources for later deployment. Detailed instructions for options to deploy this solution can be found in [deployment](#deployment).
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## Getting Started
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### Prerequisites
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To deploy this Azure environment successfully, your Azure account (the account you authenticate with) must have the following permissions and prerequisites on the targeted Azure Subscription:
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-**Microsoft.Authorization/roleAssignments/write** permissions at the subscription scope.
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_(typically included if you have [Role Based Access Control Administrator](https://learn.microsoft.com/azure/role-based-access-control/built-in-roles#role-based-access-control-administrator-preview), [User Access Administrator](https://learn.microsoft.com/azure/role-based-access-control/built-in-roles#user-access-administrator), or [Owner](https://learn.microsoft.com/azure/role-based-access-control/built-in-roles#owner)role_
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_(typically included if you have [Role Based Access Control Administrator](https://learn.microsoft.com/azure/role-based-access-control/built-in-roles#role-based-access-control-administrator-preview), [User Access Administrator](https://learn.microsoft.com/azure/role-based-access-control/built-in-roles#user-access-administrator), or [Owner](https://learn.microsoft.com/azure/role-based-access-control/built-in-roles#owner)role)_
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-**Microsoft.Resources/deployments/write** permissions at the subscription scope.
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You can view the permissions for your account and subscription by going to Azure portal, clicking 'Subscriptions' under 'Navigation' and then choosing your subscription from the list. If you try to search for your subscription and it does not come up, make sure no filters are selected. After selecting your subscription, select 'Access control (IAM)' and you can see the roles that are assigned to your account for this subscription. If you want to see more information about the roles, you can go to the 'Role assignments' tab and search by your account name and then click the role you want to view more information about.
At this point you could make changes to the code if required. However, no changes are needed to deploy and test the app as shown in the next step.
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#### Configurable Deployment Settings
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When you start a deployment, most parameters will have default values. You can change the following default settings:
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|**Setting**|**Description**|**Default value**|
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|------------|----------------| ------------|
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|**Azure Region**| Select a region with quota which supports your selected model. ||
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|**Model**| Choose from the [list of models supported by Azure AI Agent Service](https://learn.microsoft.com/azure/ai-services/agents/concepts/model-region-support) for your selected region | gpt-4o-mini |
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|**Model Format**| Choose from OpenAI or Microsoft, depending on your model | OpenAI |
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|**Model Deployment Capacity**| Configure capacity for your model. Recommended value is 100k. | 50k |
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|**Embedding Model**| Choose from text-embedding-3-large, text-embedding-3-small, and text-embedding-ada-002. | text-embedding-3-small |
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|**Embedding Model Capacity**| Configure capacity for your embedding model. | 50k |
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|**Knowledge Retrieval**| Choose from OpenAI's file search or including Azure AI Search Index. | OpenAI's file search |
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For a detailed description of customizable fields and instructions, view the [deployment customization guide](docs/deploy_customization.md).
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#### How to configure Agent model and version
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By default, the template uses model `gpt-4o-mini`, version `2024-07-18` for text generation and `text-embedding-3-small` version `1` for embeddings. If you want to personalize your agent, you can change the default configuration for your agent. Additional details on changing your agent can be found in [customizing model deployments](docs/deploy_customization.md#customizing-model-deployments). For more information on the Azure OpenAI models and non-Microsoft models that can be used in your deployment, view the [list of models supported by Azure AI Agent Service](https://learn.microsoft.com/azure/ai-services/agents/concepts/model-region-support).
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4. You will be prompted to provide an `azd` environment name (like "azureaiapp"), select a subscription from your Azure account, and select a location which has quota for all the resources. Then, it will provision the resources in your account and deploy the latest code.
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* For guidance on selecting a region with quota and model availability, follow the instructions in the [quota recommendations](#quota-recommendations-optional) section and ensure that your model is available in your selected region by checking the [list of models supported by Azure AI Agent Service](https://learn.microsoft.com/azure/ai-services/agents/concepts/model-region-support)
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* This deployment will take 8-12 minutes to provision the resources in your account and set up the solution with sample data.
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* If you get an error or timeout with deployment, changing the location can help, as there may be availability constraints for the resources.
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* If you get an error or timeout with deployment, changing the location can help, as there may be availability constraints for the resources. You can do this by running `azd down` and deleting the `.azure` folder from your code, and then running `azd up` again and selecting a new region.
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**NOTE!** If you get authorization failed and/or permission related errors during the deployment, please refer to the Azure account requirements in the [Prerequisites](#prerequisites) section. If you were recently granted these permissions, it may take a few minutes for the authorization to apply.
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