Merge branch 'release-azure-agents' of https://github.com/MicrosoftDocs/azure-ai-docs-pr into agents

Author: aahill

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

@@ -790,6 +790,21 @@
       "redirect_url": "/azure/ai-services/language-service/question-answering/overview",
       "redirect_document_id": true
     },
+    {
+      "source_path_from_root": "/articles/ai-services/document-intelligence/quickstarts/try-document-intelligence-studio.md",
+      "redirect_url": "/azure/ai-services/document-intelligence/quickstarts/studio-custom-project",
+      "redirect_document_id": true
+    },
+    {
+      "source_path_from_root": "/articles/ai-services/document-intelligence/train/custom-generative-extraction.md",
+      "redirect_url": "/azure/ai-services/document-intelligence/train/custom-model",
+      "redirect_document_id": false
+    },
+    {
+      "source_path_from_root": "/articles/ai-services/document-intelligence/how-to-guides/build-train-custom-generative-model.md",
+      "redirect_url": "/azure/ai-services/document-intelligence/how-to-guides/build-a-custom-model",
+      "redirect_document_id": true
+    },
     {
       "source_path_from_root": "/articles/ai-services/openai/how-to/integrate-synapseml.md",
       "redirect_url": "/azure/ai-services/openai/overview",

articles/ai-services/agents/how-to/tools/bing-grounding.md

@@ -33,6 +33,19 @@ Developers and end users don't have access to raw content returned from Groundin
 > [!NOTE]
 > Grounding with Bing Search only works with the following Azure OpenAI models: `gpt-3.5-turbo-0125`, `gpt-4-0125-preview`, `gpt-4-turbo-2024-04-09`, `gpt-4o-0513`
 
+In one click, you can start creating a **new Azure AI Foundry project and Grounding with Bing Search resource** with the available [deployment template](../../quickstart.md#choose-basic-or-standard-agent-setup). After the deployment, you can find your resources including: an AI hub, project, Grounding with Bing Search resource and more created in your resource group. You can find your Grounding with Bing Search connection in the **connected resources** for your project in Azure AI Foundry portal.
+ 
+:::image type="content" source="../../media/tools/bing/connected-resources.png" alt-text="A screenshot showing the connected resources for a project in the Azure AI Foundry portal." lightbox="../../media/tools/bing/connected-resources.png":::
+ 
+1. If you already have a Grounding with Bing Search resource, you can provide your resource ID in the bicep file. Your resource ID should be in this format `/subscriptions/{subscription ID}/resourceGroups/{resource group name}/providers/Microsoft.Bing/accounts/{resource name}`. Replace the following empty string with your resource ID:
+    ```bicep
+    @description('The full ARM Bing Resource ID. This is an optional field, and if not provided, the resource will be created.')
+    param bingSearchResourceID string = ''
+    ```
+ 
+ 
+Alternatively, you can also follow the step-by-step guide below:
+
 1. Create a standard Azure AI Agent by following the steps in the [quickstart](../../quickstart.md).
 
 1. Register the Bing Search provider.

articles/ai-services/agents/how-to/tools/openapi-spec.md

@@ -50,7 +50,19 @@ work together, generate client code, create tests, apply design standards, and m
       - value: YOUR_API_KEY
       - Connection name: `YOUR_CONNECTION_NAME` (You will use this connection name in the sample code below.)
       - Access: you can choose either *this project only* or *shared to all projects*. Just make sure in the sample code below, the project you entered connection string for has access to this connection.
-        
+     
+    1. Update your OpenAPI Spec with the following:
+    ```json
+        "components": {
+        "securitySchemes": {
+          "cosoLocationApiLambdaAuthorizer": {
+            "type": "apiKey",
+            "name": "key",
+            "in": "query"
+          }
+        }
+      }
+    ```
 ::: zone-end
 
 ::: zone pivot="code-example"

articles/ai-services/content-understanding/media/overview/overview-flow.png

@@ -1,17 +1,19 @@
 ---
 title: What is Azure AI Content Understanding?
 titleSuffix: Azure AI services
-description: Learn about Azure AI Content Understanding solutions
+description: Learn about Azure AI Content Understanding solutions, processes, workflows, use-cases, and field extractions.
 author: laujan
 ms.author: lajanuar
 manager: nitinme
 ms.service: azure-ai-content-understanding
 ms.topic: overview
 ms.date: 11/19/2024
 ms.custom: ignite-2024-understanding-release
+
+#customer intent: As a user, I want to learn more about Content Understanding solutions.
 ---
 
-# What is Azure AI Content Understanding?
+# What is Azure AI Content Understanding (preview)?
 
 > [!IMPORTANT]
 >
@@ -23,7 +25,7 @@ Azure AI Content Understanding is a new Generative AI based [**Azure AI Service*
 
 Content Understanding offers a streamlined process to reason over large amounts of unstructured data, accelerating time-to-value by generating an output that can be integrated into automation and analytical workflows.
 
-:::image type="content" source="media/overview/content-understanding-overview.png" alt-text="Screenshot of Content Understanding overview.":::
+:::image type="content" source="media/overview/overview-flow.png" alt-text="Screenshot of Content Understanding overview, process, and workflow.":::
 
 ## Why process with Content Understanding?
 
@@ -42,6 +44,7 @@ Content Understanding offers a streamlined process to reason over large amounts
 * **Analytics and reporting**: Content Understanding's extracted field outputs enhance analytics and reporting, allowing businesses to gain valuable insights, conduct deeper analysis, and make informed decisions based on accurate reports.
 
 ## Applications
+
 Common applications for Content Understanding include:
 
 |Application|Description|Quickstart|

articles/ai-services/content-understanding/media/overview/content-understanding-overview.png renamed to articles/ai-services/content-understanding/media/quickstarts/ai-foundry-overview.png

@@ -13,6 +13,8 @@ ms.custom: ignite-2024-understanding-release
 # Use Content Understanding in Azure AI Foundry
 [Azure AI Foundry](https://ai.azure.com/) is a comprehensive platform for developing and deploying generative AI applications and APIs responsibly. This guide shows you how to use Content Understanding and build an analyzer, either by creating your own schema from scratch or by using a suggested analyzer template.
 
+  :::image type="content" source="../media/quickstarts/ai-foundry-overview.png" alt-text="Screenshot of the Content Understanding workflow in the Azure AI Foundry.":::
+
 ## Steps to create a Content Understanding analyzer
 
 Azure AI Foundry enables you to build a Content Understanding analyzer tailored to your specific needs. An analyzer can extract data from your content based on your scenario.

articles/ai-services/content-understanding/overview.md

@@ -48,7 +48,7 @@ Content extraction for video includes transcription, shot detection, key frame e
 * **Shot detection**: Identifies segments of the video aligned with shot boundaries where possible, allowing for precise editing and repackaging of content with breaks exactly on shot boundaries.
 * **Key frame extraction**: Extracts key frames from videos to represent each shot completely, ensuring each shot has enough key frames to enable Field Extraction to work effectively.
 * **Face grouping**: Grouped faces appearing in a video to extract one representative face image for each person and provides segments where each one is present. The grouped face data is available as metadata and can be used to generate customized metadata fields.
-  * This feature is limited access and involves face identification and grouping; customers need to register for access at [Face Recognition](https://aka.ms/facerecognition).
+* This feature is limited access and involves face identification and grouping; customers need to register for access at [Face Recognition](https://aka.ms/facerecognition).
 
 ### Field extraction 
 

articles/ai-services/content-understanding/quickstart/use-ai-foundry.md

@@ -5,7 +5,7 @@ ms.topic: how-to
 author: laujan
 manager: nitinme
 ms.service: azure-ai-document-intelligence
-ms.date: 07/11/2024
+ms.date: 11/19/2024
 ms.author: lajanuar
 ---
 
@@ -16,7 +16,7 @@ ms.author: lajanuar
  [!INCLUDE [applies to v4.0 v3.1 v3.0 v2.1](../includes/applies-to-v40-v31-v30-v21.md)]
 ::: moniker-end
 
-In this article, learn how to create user delegation, shared access signature (SAS) tokens, using the Azure portal or Azure Storage Explorer. User delegation SAS tokens are secured with Microsoft Entra credentials. SAS tokens provide secure, delegated access to resources in your Azure storage account.
+In this article, learn how to create user delegation, shared access signature (SAS) tokens, using either the Azure portal or Azure Storage Explorer. User delegation SAS tokens are secured with Microsoft Entra credentials. SAS tokens provide secure, delegated access to resources in your Azure storage account.
 
   :::image type="content" source="../media/sas-tokens/sas-url-token.png" alt-text="Screenshot of storage URI with SAS token appended.":::
 
@@ -81,7 +81,10 @@ To get started, you need:
    > [!NOTE]
    > By default, the REST API uses documents located at the root of your container. You can also use data organized in subfolders if specified in the API call. For more information, see [Organize your data in subfolders](../how-to-guides/build-a-custom-model.md?view=doc-intel-2.1.0&preserve-view=true#organize-your-data-in-subfolders-optional).
 
-## Use the Azure portal
+## Generating SAS tokens
+Once the prerequisites are met and you upload your documents, you can now generate SAS tokens. There are two paths you can take from here; one using the Azure portal and the other using the Azure storage explorer. Select between the two following tabs for more information.
+
+### [**Azure Portal**](#tab/azure-portal)
 
 The Azure portal is a web-based console that enables you to manage your Azure subscription and resources using a graphical user interface (GUI).
 
@@ -128,17 +131,17 @@ The Azure portal is a web-based console that enables you to manage your Azure su
 
 1. To [construct a SAS URL](#use-your-sas-url-to-grant-access), append the SAS token (URI) to the URL for a storage service.
 
-## Use Azure Storage Explorer
+### [**Azure Storage Explorer**](#tab/azure-storage-explorer)
 
 Azure Storage Explorer is a free standalone app that enables you to easily manage your Azure cloud storage resources from your desktop.
 
-### Get started
+#### Get started
 
 * You need the [**Azure Storage Explorer**](/azure/vs-azure-tools-storage-manage-with-storage-explorer) app installed in your Windows, macOS, or Linux development environment.
 
 * After the Azure Storage Explorer app is installed, [connect it the storage account](/azure/vs-azure-tools-storage-manage-with-storage-explorer?tabs=windows#connect-to-a-storage-account-or-service) you're using for Document Intelligence.
 
-### Create your SAS tokens
+#### Create your SAS tokens
 
 1. Open the Azure Storage Explorer app on your local machine and navigate to your connected **Storage Accounts**.
 1. Expand the Storage Accounts node and select **Blob Containers**.

articles/ai-services/content-understanding/video/overview.md

@@ -6,7 +6,7 @@ author: erindormier
 manager: venkyv
 ms.service: azure-ai-document-intelligence
 ms.topic: conceptual
-ms.date: 11/15/2023
+ms.date: 11/19/2024
 monikerRange: '<=doc-intel-4.0.0'
 ---