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Azure AI Document Intelligence automatically encrypts your data when persisting it to the cloud. Document Intelligence encryption protects your data to help you to meet your organizational security and compliance commitments.
> Customer-managed keys are only available resources created after 11 May, 2020. To use CMK with Document Intelligence, you will need to create a new Document Intelligence resource. Once the resource is created, you can use Azure Key Vault to set up your managed identity.
Copy file name to clipboardExpand all lines: articles/ai-services/document-intelligence/how-to-guides/disaster-recovery.md
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manager: nitinme
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ms.service: azure-ai-document-intelligence
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ms.topic: how-to
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ms.date: 08/07/2024
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ms.date: 10/15/2024
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ms.author: lajanuar
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---
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# Disaster recovery
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::: moniker range="doc-intel-4.0.0"
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[!INCLUDE [applies to v4.0](includes/applies-to-v40.md)]
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[!INCLUDE [applies to v4.0](../includes/applies-to-v40.md)]
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::: moniker-end
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::: moniker range="doc-intel-3.1.0"
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[!INCLUDE [applies to v3.1](includes/applies-to-v31.md)]
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[!INCLUDE [applies to v3.1](../includes/applies-to-v31.md)]
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::: moniker-end
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::: moniker range="doc-intel-3.0.0"
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[!INCLUDE [applies to v3.0](includes/applies-to-v30.md)]
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[!INCLUDE [applies to v3.0](../includes/applies-to-v30.md)]
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::: moniker-end
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::: moniker range="doc-intel-2.1.0"
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[!INCLUDE [applies to v2.1](includes/applies-to-v21.md)]
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[!INCLUDE [applies to v2.1](../includes/applies-to-v21.md)]
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::: moniker-end
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::: moniker range=">= doc-intel-2.1.0"
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The Copy API enables this scenario by allowing you to copy custom models and classifiers from one Document Intelligence account or into others, which can exist in any supported geographical region. This guide shows you how to use the Copy REST API with cURL for custom models. You can also use an HTTP request service to issue the requests.
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> [!NOTE]
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> Starting with the `2024-07-31-preview` API, custom clasification models also support the Copy API. This guide specifically uses custom models to copy models. For classifier model copy, follow this [guide](train/custom-classifier.md#copy-a-model).
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> Starting with the `2024-07-31-preview` API, custom clasification models also support the Copy API. This guide specifically uses custom models to copy models. For classifier model copy, follow this [guide](../train/custom-classifier.md#copy-a-model).
Copy file name to clipboardExpand all lines: articles/ai-services/document-intelligence/tutorial/azure-function.md
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Document Intelligence can be used as part of an automated data processing pipeline built with Azure Functions. This guide will show you how to use Azure Functions to process documents that are uploaded to an Azure blob storage container. This workflow extracts table data from stored documents using the Document Intelligence layout model and saves the table data in a .csv file in Azure. You can then display the data using Microsoft Power BI (not covered here).
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:::image type="content" source="media/tutorial-azure-function/workflow-diagram.png" alt-text="Screenshot of Azure Service workflow diagram":::
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:::image type="content" source="../media/tutorial-azure-function/workflow-diagram.png" alt-text="Screenshot of Azure Service workflow diagram":::
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In this tutorial, you learn how to:
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* After your resource deploys, select **Go to resource**. You need the key and endpoint from the resource you create to connect your application to the Document Intelligence API. You'll paste your key and endpoint into the code below later in the tutorial:
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:::image type="content" source="media/containers/keys-and-endpoint.png" alt-text="Screenshot of keys and endpoint location in the Azure portal.":::
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:::image type="content" source="../media/containers/keys-and-endpoint.png" alt-text="Screenshot of keys and endpoint location in the Azure portal.":::
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*[**Python 3.6.x, 3.7.x, 3.8.x or 3.9.x**](https://www.python.org/downloads/) (Python 3.10.x isn't supported for this project).
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* Select the Azure subscription that you're using for this project and below you should see the Azure Function App.
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:::image type="content" source="media/tutorial-azure-function/azure-extensions-visual-studio-code.png" alt-text="Screenshot of a list showing your Azure resources in a single, unified view.":::
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:::image type="content" source="../media/tutorial-azure-function/azure-extensions-visual-studio-code.png" alt-text="Screenshot of a list showing your Azure resources in a single, unified view.":::
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1. Select the Workspace (Local) section located below your listed resources. Select the plus symbol and choose the **Create Function** button.
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:::image type="content" source="media/tutorial-azure-function/workspace-create-function.png" alt-text="Screenshot showing where to begin creating an Azure function.":::
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:::image type="content" source="../media/tutorial-azure-function/workspace-create-function.png" alt-text="Screenshot showing where to begin creating an Azure function.":::
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1. When prompted, choose **Create new project** and navigate to the **function-app** directory. Choose **Select**.
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1. Open Azure Storage Explorer and upload the sample PDF document to the **input** container. Then check the VS Code terminal. The script should log that it was triggered by the PDF upload.
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:::image type="content" source="media/tutorial-azure-function/visual-studio-code-terminal-test.png" alt-text="Screenshot of the VS Code terminal after uploading a new document.":::
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:::image type="content" source="../media/tutorial-azure-function/visual-studio-code-terminal-test.png" alt-text="Screenshot of the VS Code terminal after uploading a new document.":::
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1. Stop the script before continuing.
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## Add document processing code
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Next, you'll add your own code to the Python script to call the Document Intelligence service and parse the uploaded documents using the Document Intelligence [layout model](prebuilt/layout.md).
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Next, you'll add your own code to the Python script to call the Document Intelligence service and parse the uploaded documents using the Document Intelligence [layout model](../prebuilt/layout.md).
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1. In VS Code, navigate to the function's *requirements.txt* file. This file defines the dependencies for your script. Add the following Python packages to the file:
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```
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> [!IMPORTANT]
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> Remember to remove the key from your code when you're done, and never post it publicly. For production, use a secure way of storing and accessing your credentials like [Azure Key Vault](/azure/key-vault/general/overview). For more information, *see* Azure AI services [security](../../ai-services/security-features.md).
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> Remember to remove the key from your code when you're done, and never post it publicly. For production, use a secure way of storing and accessing your credentials like [Azure Key Vault](/azure/key-vault/general/overview). For more information, *see* Azure AI services [security](../../../ai-services/security-features.md).
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1. Next, add code to query the service and get the returned data.
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> [!div class="nextstepaction"]
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> [Microsoft Power BI](https://powerbi.microsoft.com/integrations/azure-table-storage/)
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* [What is Document Intelligence?](overview.md)
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* Learn more about the [layout model](prebuilt/layout.md)
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* [What is Document Intelligence?](../overview.md)
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* Learn more about the [layout model](../prebuilt/layout.md)
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1. Return to the Logic App designer tab and select the **Run trigger** button and select **Run** from the drop-down menu.
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:::image type="content" source="media/logic-apps-tutorial/trigger-run.png" alt-text="Screenshot of Run trigger and Run buttons.":::
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:::image type="content" source="../media/logic-apps-tutorial/trigger-run.png" alt-text="Screenshot of Run trigger and Run buttons.":::
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1. You see a message in the upper=right corner indicating that the trigger was successful:
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:::image type="content" source="media/logic-apps-tutorial/trigger-successful.png" alt-text="Screenshot of Successful trigger message.":::
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:::image type="content" source="../media/logic-apps-tutorial/trigger-successful.png" alt-text="Screenshot of Successful trigger message.":::
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1. Navigate to your Logic App overview page by selecting your app name link in the upper-left corner.
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:::image type="content" source="media/logic-apps-tutorial/navigate-overview.png" alt-text="Screenshot of navigate to overview page link.":::
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:::image type="content" source="../media/logic-apps-tutorial/navigate-overview.png" alt-text="Screenshot of navigate to overview page link.":::
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1. Check the status, to see if the run succeeded or failed. You can select the status indicator to check which steps were successful.
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:::image border="true" type="content" source="media/logic-apps-tutorial/succeeded-failed-indicator.png" alt-text="Screenshot of Succeeded or Failed status.":::
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:::image border="true" type="content" source="../media/logic-apps-tutorial/succeeded-failed-indicator.png" alt-text="Screenshot of Succeeded or Failed status.":::
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1. If your run failed, check the failed step to ensure that you entered the correct information.
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:::image type="content" source="media/logic-apps-tutorial/failed-run-step.png" alt-text="Screenshot of failed step.":::
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:::image type="content" source="../media/logic-apps-tutorial/failed-run-step.png" alt-text="Screenshot of failed step.":::
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1. After a workflow run succeeds, check your email. There's a new email with the information we specified.
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:::image type="content" source="media/logic-apps-tutorial/invoice-received.png" alt-text="Screenshot of received email message.":::
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:::image type="content" source="../media/logic-apps-tutorial/invoice-received.png" alt-text="Screenshot of received email message.":::
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1. After you're done, [disable or delete your logic app](/azure/logic-apps/manage-logic-apps-with-azure-portal?tabs=consumption#disable-enable-logic-apps) so that usage stops.
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:::image type="content" source="media/logic-apps-tutorial/disable-delete.png" alt-text="Screenshot of disable and delete buttons.":::
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:::image type="content" source="../media/logic-apps-tutorial/disable-delete.png" alt-text="Screenshot of disable and delete buttons.":::
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Congratulations! You completed this tutorial.
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## Next steps
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> [!div class="nextstepaction"]
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> [Learn more about Document Intelligence models](model-overview.md)
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> [Learn more about Document Intelligence models](../model-overview.md)
Copy file name to clipboardExpand all lines: articles/ai-services/document-intelligence/versioning/changelog-release-history.md
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This reference article provides a version-based description of Document Intelligence feature and capability releases, changes, updates, and enhancements.
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