Roll out prepare models for other tutorils + integrate search endpoint info into set up rest client

Author: HeidiSteen

articles/search/tutorial-document-extraction-image-verbalization.md

@@ -83,18 +83,28 @@ The following instructions apply to Azure Storage which provides the sample data
       }
       ```
 
-### Copy a search service URL and API key
+## Prepare models
 
-For this tutorial, your local REST client connection to Azure AI Search requires an endpoint and an API key. You can get these values from the Azure portal. For alternative connection methods, see [Connect to a search service](search-get-started-rbac.md).
+This tutorial assumes you have an existing Azure OpenAI resource through which the skills call the text embedding model and chat completion models. The search service connects to the models during skillset processing and during query execution using its managed identity. This section gives you guidance and links for assigning roles for authorized access.
 
-1. Sign in to the [Azure portal](https://portal.azure.com), navigate to the search service **Overview** page, and copy the URL. An example endpoint might look like `https://mydemo.search.windows.net`.
+1. Sign in to the Azure portal (not the Foundry portal) and find the Azure OpenAI resource.
 
-1. Under **Settings** > **Keys**, copy an admin key. Admin keys are used to add, modify, and delete objects. There are two interchangeable admin keys. Copy either one.
+1. Select **Access control (IAM)**.
 
-   :::image type="content" source="media/search-get-started-rest/get-url-key.png" alt-text="Screenshot of the URL and API keys in the Azure portal.":::
+1. Select **Add** and then **Add role assignment**.
+
+1. Search for **Cognitive Services OpenAI User** and then select it.
+
+1. Choose **Managed identity** and then assign your [search service managed identity](search-howto-managed-identities-data-sources.md).
+
+For more information, see [Role-based access control for Azure OpenAI in Azure AI Foundry Models](/azure/ai-foundry/openai/how-to/role-based-access-control).
 
 ## Set up your REST file
 
+For this tutorial, your local REST client connection to Azure AI Search requires an endpoint and an API key. You can get these values from the Azure portal. For alternative connection methods, see [Connect to a search service](search-get-started-rbac.md).
+
+For other authenticated connections, the search service uses the role assignments you previously defined.
+
 1. Start Visual Studio Code and create a new file.
 
 1. Provide values for variables used in the request.
@@ -110,9 +120,15 @@ For this tutorial, your local REST client connection to Azure AI Search requires
    @imageProjectionContainer=PUT-YOUR-IMAGE-PROJECTION-CONTAINER-HERE (Azure AI Search creates this container for you during skills processing)
    ```
 
-1. Save the file using a `.rest` or `.http` file extension.
+1. Save the file using a `.rest` or `.http` file extension. For help with the REST client, see [Quickstart: Full-text search using REST](search-get-started-text.md).
+
+To get the Azure AI Search endpoint and API key:
+
+1. Sign in to the [Azure portal](https://portal.azure.com), navigate to the search service **Overview** page, and copy the URL. An example endpoint might look like `https://mydemo.search.windows.net`.
+
+1. Under **Settings** > **Keys**, copy an admin key. Admin keys are used to add, modify, and delete objects. There are two interchangeable admin keys. Copy either one.
 
-For help with the REST client, see [Quickstart: Full-text search using REST](search-get-started-text.md).
+   :::image type="content" source="media/search-get-started-rest/get-url-key.png" alt-text="Screenshot of the URL and API keys in the Azure portal.":::
 
 ## Create a data source
 

articles/search/tutorial-document-extraction-multimodal-embeddings.md

@@ -101,7 +101,7 @@ This tutorial assumes you have an existing Azure AI multiservice account through
 
 For this tutorial, your local REST client connection to Azure AI Search requires an endpoint and an API key. You can get these values from the Azure portal. For alternative connection methods, see [Connect to a search service](search-get-started-rbac.md).
 
-For other connections, the search service uses the role assignments you previously defined.
+For other authenticated connections, the search service uses the role assignments you previously defined.
 
 1. Start Visual Studio Code and create a new file.
 

articles/search/tutorial-document-layout-image-verbalization.md

@@ -82,22 +82,31 @@ The following instructions apply to Azure Storage which provides the sample data
       }
       ```
 
-### Copy a search service URL and API key
+## Prepare models
 
-For this tutorial, your local REST client connection to Azure AI Search requires an endpoint and an API key. You can get these values from the Azure portal. For alternative connection methods, see [Connect to a search service](search-get-started-rbac.md).
+This tutorial assumes you have an existing Azure OpenAI resource through which the skills call the text embedding model and chat completion models. The search service connects to the models during skillset processing and during query execution using its managed identity. This section gives you guidance and links for assigning roles for authorized access.
 
-1. Sign in to the [Azure portal](https://portal.azure.com), navigate to the search service **Overview** page, and copy the URL. An example endpoint might look like `https://mydemo.search.windows.net`.
+1. Sign in to the Azure portal (not the Foundry portal) and find the Azure OpenAI resource.
 
-1. Under **Settings** > **Keys**, copy an admin key. Admin keys are used to add, modify, and delete objects. There are two interchangeable admin keys. Copy either one.
+1. Select **Access control (IAM)**.
 
-   :::image type="content" source="media/search-get-started-rest/get-url-key.png" alt-text="Screenshot of the URL and API keys in the Azure portal.":::
+1. Select **Add** and then **Add role assignment**.
+
+1. Search for **Cognitive Services OpenAI User** and then select it.
+
+1. Choose **Managed identity** and then assign your [search service managed identity](search-howto-managed-identities-data-sources.md).
+
+For more information, see [Role-based access control for Azure OpenAI in Azure AI Foundry Models](/azure/ai-foundry/openai/how-to/role-based-access-control).
 
 ## Set up your REST file
 
+For this tutorial, your local REST client connection to Azure AI Search requires an endpoint and an API key. You can get these values from the Azure portal. For alternative connection methods, see [Connect to a search service](search-get-started-rbac.md).
+
+For other authenticated connections, the search service uses the role assignments you previously defined.
+
 1. Start Visual Studio Code and create a new file.
 
 1. Provide values for variables used in the request.
-
    ```http
    @searchUrl = PUT-YOUR-SEARCH-SERVICE-ENDPOINT-HERE
    @searchApiKey = PUT-YOUR-ADMIN-API-KEY-HERE
@@ -109,9 +118,15 @@ For this tutorial, your local REST client connection to Azure AI Search requires
    @imageProjectionContainer=PUT-YOUR-IMAGE-PROJECTION-CONTAINER-HERE (Azure AI Search creates this container for you during skills processing)
    ```
 
-1. Save the file using a `.rest` or `.http` file extension.
+1. Save the file using a `.rest` or `.http` file extension. For help with the REST client, see [Quickstart: Full-text search using REST](search-get-started-text.md).
+
+To get the Azure AI Search endpoint and API key:
+
+1. Sign in to the [Azure portal](https://portal.azure.com), navigate to the search service **Overview** page, and copy the URL. An example endpoint might look like `https://mydemo.search.windows.net`.
+
+1. Under **Settings** > **Keys**, copy an admin key. Admin keys are used to add, modify, and delete objects. There are two interchangeable admin keys. Copy either one.
 
-For help with the REST client, see [Quickstart: Full-text search using REST](search-get-started-text.md).
+   :::image type="content" source="media/search-get-started-rest/get-url-key.png" alt-text="Screenshot of the URL and API keys in the Azure portal.":::
 
 ## Create a data source
 

articles/search/tutorial-document-layout-multimodal-embeddings.md

@@ -80,18 +80,26 @@ The following instructions apply to Azure Storage which provides the sample data
       }
       ```
 
-### Copy a search service URL and API key
+## Prepare models
 
-For this tutorial, your local REST client connection to Azure AI Search requires an endpoint and an API key. You can get these values from the Azure portal. For alternative connection methods, see [Connect to a search service](search-get-started-rbac.md).
+This tutorial assumes you have an existing Azure AI multiservice account through which the skill calls the Azure AI Vision multimodal 4.0 embedding model. The search service connects to the model during skillset processing using its managed identity. This section gives you guidance and links for assigning roles for authorized access.
 
-1. Sign in to the [Azure portal](https://portal.azure.com), navigate to the search service **Overview** page, and copy the URL. An example endpoint might look like `https://mydemo.search.windows.net`.
+1. Sign in to the Azure portal (not the Foundry portal) and find the Azure AI multiservice account. Make sure it's in a region that provides the [multimodal 4.0 API](/azure/ai-services/computer-vision/overview-image-analysis#region-availability).
 
-1. Under **Settings** > **Keys**, copy an admin key. Admin keys are used to add, modify, and delete objects. There are two interchangeable admin keys. Copy either one.
+1. Select **Access control (IAM)**.
 
-   :::image type="content" source="media/search-get-started-rest/get-url-key.png" alt-text="Screenshot of the URL and API keys in the Azure portal.":::
+1. Select **Add** and then **Add role assignment**.
+
+1. Search for **Cognitive Services User** and then select it.
+
+1. Choose **Managed identity** and then assign your [search service managed identity](search-howto-managed-identities-data-sources.md).
 
 ## Set up your REST file
 
+For this tutorial, your local REST client connection to Azure AI Search requires an endpoint and an API key. You can get these values from the Azure portal. For alternative connection methods, see [Connect to a search service](search-get-started-rbac.md).
+
+For other authenticated connections, the search service uses the role assignments you previously defined.
+
 1. Start Visual Studio Code and create a new file.
 
 1. Provide values for variables used in the request.
@@ -106,9 +114,15 @@ For this tutorial, your local REST client connection to Azure AI Search requires
    @imageProjectionContainer=PUT-YOUR-IMAGE-PROJECTION-CONTAINER-HERE (Azure AI Search creates this container for you during skills processing)
    ```
 
-1. Save the file using a `.rest` or `.http` file extension.
+1. Save the file using a `.rest` or `.http` file extension. For help with the REST client, see [Quickstart: Full-text search using REST](search-get-started-text.md).
+
+To get the Azure AI Search endpoint and API key:
+
+1. Sign in to the [Azure portal](https://portal.azure.com), navigate to the search service **Overview** page, and copy the URL. An example endpoint might look like `https://mydemo.search.windows.net`.
 
-For help with the REST client, see [Quickstart: Full-text search using REST](search-get-started-text.md).
+1. Under **Settings** > **Keys**, copy an admin key. Admin keys are used to add, modify, and delete objects. There are two interchangeable admin keys. Copy either one.
+
+   :::image type="content" source="media/search-get-started-rest/get-url-key.png" alt-text="Screenshot of the URL and API keys in the Azure portal.":::
 
 ## Create a data source