Merge branch 'main' of https://github.com/MicrosoftDocs/azure-docs-pr into samples-auth

Author: pauljewellmsft

articles/active-directory-b2c/oauth2-error-technical-profile.md

@@ -9,7 +9,7 @@ manager: CelesteDG
 ms.service: active-directory
 
 ms.topic: reference
-ms.date: 01/11/2024
+ms.date: 05/07/2024
 ms.author: kengaderdus
 ms.subservice: B2C
 
@@ -73,6 +73,43 @@ The following example shows a technical profile for `ReturnOAuth2Error`:
 </ClaimsProviders> -->
 ```
 
+## Define claims transformation to generate custom values of error code and error message
+
+Use these steps to generate custom values of error code and error message:
+
+1. Locate the `ClaimsTransformations` element, then add the following code inside it
+
+    ```xml
+    <!--
+     <ClaimsTransformations> -->
+    <ClaimsTransformation Id="GenerateErrorCode" TransformationMethod="CreateStringClaim">
+            <InputParameters>
+              <InputParameter Id="value" DataType="string" Value="Error_001" />
+            </InputParameters>
+            <OutputClaims>
+              <OutputClaim ClaimTypeReferenceId="errorCode" TransformationClaimType="createdClaim" />
+            </OutputClaims>
+          </ClaimsTransformation>
+          <ClaimsTransformation Id="GenerateErrorMessage" TransformationMethod="CreateStringClaim">
+            <InputParameters>
+              <InputParameter Id="value" DataType="string" Value="Insert error description." />
+            </InputParameters>
+            <OutputClaims>
+              <OutputClaim ClaimTypeReferenceId="errorMessage" TransformationClaimType="createdClaim" />
+            </OutputClaims>
+          </ClaimsTransformation>
+    <!--
+    </ClaimsTransformations> -->
+    ```
+
+1. Add the two claims transformations in the `OutputClaimsTransformations` element of any technical profile before Oauth2 technical that you define:
+
+    ```xml
+        <OutputClaimsTransformations>
+          <OutputClaimsTransformation ReferenceId="generateErrorCode" />
+          <OutputClaimsTransformation ReferenceId="generateErrorMessage" />
+        </OutputClaimsTransformations>
+    ```
 ## Input claims
 
 The **InputClaims** element contains a list of claims required to return OAuth2 error. 
@@ -123,6 +160,20 @@ In the following example:
 </UserJourney>
 ```
 
+Optionally, you can use preconditions to manipulate the Oauth2 error technical profile. For example, if there is no email claim, you can set to call Oauth2 error technical profile:
+
+```xml
+<OrchestrationStep Order="3" Type="SendClaims" CpimIssuerTechnicalProfileReferenceId="ReturnOAuth2Error">
+      <Preconditions>
+        <Precondition Type="ClaimsExist" ExecuteActionsIf="false">
+          <Value>email</Value>
+          <Action>SkipThisOrchestrationStep</Action>
+        </Precondition>
+      </Preconditions>
+    </OrchestrationStep>
+```
+
+
 ## Next steps
 
 Learn about [UserJourneys](userjourneys.md)

articles/active-directory-b2c/partner-saviynt.md

@@ -70,6 +70,9 @@ The following architecture diagram illustrates the implementation.
 2. Create delegated administration policies.
 3. Assign users the delegated administrator role.
 
+>[!NOTE]
+>User administrator role will be required for a Service Principal Name (SPN) to integrate with Saviynt EIC system. 
+
 ## Configure Azure AD B2C with Saviynt
 
 Use the following instructions to create an application, delete users, and more. 

articles/ai-services/computer-vision/how-to/find-similar-faces.md

@@ -46,17 +46,6 @@ The following code uses the above method to get face data from a series of image
 [!code-csharp[](~/cognitive-services-quickstart-code/dotnet/Face/FaceQuickstart.cs?name=snippet_loadfaces)]
 
 
-#### [JavaScript](#tab/javascript)
-
-The following face detection method is optimized for comparison operations. It doesn't extract detailed face attributes, and it uses an optimized recognition model.
-
-:::code language="js" source="~/cognitive-services-quickstart-code/javascript/Face/sdk_quickstart.js" id="recognize":::
-
-The following code uses the above method to get face data from a series of images.
-
-:::code language="js" source="~/cognitive-services-quickstart-code/javascript/Face/sdk_quickstart.js" id="snippet_loadfaces":::
-
-
 #### [REST API](#tab/rest)
 
 Copy the following cURL command and insert your key and endpoint where appropriate. Then run the command to detect one of the target faces.
@@ -89,12 +78,6 @@ The following code prints the match details to the console:
 
 [!code-csharp[](~/cognitive-services-quickstart-code/dotnet/Face/FaceQuickstart.cs?name=snippet_find_similar_print)]
 
-#### [JavaScript](#tab/javascript)
-
-The following method takes a set of target faces and a single source face. Then, it compares them and finds all the target faces that are similar to the source face. Finally, it prints the match details to the console.
-
-:::code language="js" source="~/cognitive-services-quickstart-code/javascript/Face/sdk_quickstart.js" id="find_similar":::
-
 
 #### [REST API](#tab/rest)
 

articles/ai-services/computer-vision/includes/quickstarts-sdk/identity-javascript-sdk.md

@@ -15,7 +15,7 @@ ms.author: pafarley
 
 Get started with facial recognition using the Face client library for JavaScript. Follow these steps to install the package and try out the example code for basic tasks. The Face service provides you with access to advanced algorithms for detecting and recognizing human faces in images. Follow these steps to install the package and try out the example code for basic face identification using remote images.
 
-[Reference documentation](/javascript/api/overview/azure/cognitiveservices-face-readme) | [Package (npm)](https://www.npmjs.com/package/@azure/cognitiveservices-face) | [Samples](/samples/browse/?products=azure&term=face&languages=javascript)
+[Reference documentation](https://aka.ms/azsdk-javascript-face-ref) | [Library source code](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/face/ai-vision-face-rest) | [Package (npm)](https://www.npmjs.com/package/@azure-rest/ai-vision-face) | [Samples](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/face/ai-vision-face-rest/samples)
 
 ## Prerequisites
 
@@ -47,10 +47,10 @@ Get started with facial recognition using the Face client library for JavaScript
     npm init
     ```
 
-1. Install the `ms-rest-azure` and `azure-cognitiveservices-face` npm packages:
+1. Install the `@azure-rest/ai-vision-face` npm packages:
 
     ```console
-    npm install @azure/cognitiveservices-face @azure/ms-rest-js uuid
+    npm install @azure-rest/ai-vision-face
     ```
 
     Your app's `package.json` file is updated with the dependencies.
@@ -96,12 +96,18 @@ Add face to the person group person: (Family2-Lady) from image: Family2-Lady1.jp
 Done adding faces to person group.
 
 Training person group: c08484e0-044b-4610-8b7e-c957584e5d2d.
-Waiting 10 seconds...
 Training status: succeeded.
-
+No persons identified for face with ID 259dd648-be70-499c-9942-3512594e21eb
 Person: Family1-Mom is identified for face in: identification1.jpg with ID: b7f7f542-c338-4a40-ad52-e61772bc6e14. Confidence: 0.96921.
 Person: Family1-Son is identified for face in: identification1.jpg with ID: 600dc1b4-b2c4-4516-87de-edbbdd8d7632. Confidence: 0.92886.
 Person: Family1-Dad is identified for face in: identification1.jpg with ID: e83b494f-9ad2-473f-9d86-3de79c01e345. Confidence: 0.96725.
+Verification result between face bb7f7f542-c338-4a40-ad52-e61772bc6e14 and person de1d7dea-a393-4f69-9062-10cb66d4cf17: true with confidence: 0.96921
+Verification result between face 600dc1b4-b2c4-4516-87de-edbbdd8d7632 and person 05fd84e4-41b0-4716-b767-4376e33fa207: true with confidence: 0.92886
+Verification result between face e83b494f-9ad2-473f-9d86-3de79c01e345 and person c5124fe2-39dd-47ba-9163-1ed2998fdeb2: true with confidence: 0.96725
+
+Deleting person group: c08484e0-044b-4610-8b7e-c957584e5d2d
+
+Done.
 ```
 
 
@@ -120,4 +126,4 @@ In this quickstart, you learned how to use the Face client library for JavaScrip
 > [Specify a face detection model version](../../how-to/specify-detection-model.md)
 
 * [What is the Face service?](../../overview-identity.md)
-* More extensive sample code can be found on [GitHub](https://github.com/Azure-Samples/cognitive-services-quickstart-code/blob/master/javascript/Face/sdk_quickstart.js).
+* More extensive sample code can be found on [GitHub](https://github.com/Azure/azure-sdk-for-js/tree/main/sdk/face/ai-vision-face-rest/samples).

articles/ai-services/openai/concepts/model-retirements.md

@@ -66,9 +66,9 @@ These models are currently available for use in Azure OpenAI Service.
 | `gpt-35-turbo` | 0125 | No earlier than Feb 22, 2025 |
 | `gpt-4`<br>`gpt-4-32k` | 0314 | No earlier than July 13, 2024 |
 | `gpt-4`<br>`gpt-4-32k` | 0613 | No earlier than Sep 30, 2024 |
-| `gpt-4` | 1106-preview | To be upgraded to `gpt-4` Version: `turbo-2024-04-09`, starting on June 10, 2024, or later **<sup>1</sup>** |
-| `gpt-4` | 0125-preview |To be upgraded to `gpt-4` Version: `turbo-2024-04-09`, starting on June 10, 2024, or later  **<sup>1</sup>**  |
-| `gpt-4` | vision-preview | To be upgraded to `gpt-4` Version: `turbo-2024-04-09`, starting on June 10, 2024, or later  **<sup>1</sup>** |
+| `gpt-4` | 1106-preview | To be upgraded to `gpt-4` Version: `turbo-2024-04-09`, starting on July 15, 2024, or later **<sup>1</sup>** |
+| `gpt-4` | 0125-preview |To be upgraded to `gpt-4` Version: `turbo-2024-04-09`, starting on July 15, 2024, or later  **<sup>1</sup>**  |
+| `gpt-4` | vision-preview | To be upgraded to `gpt-4` Version: `turbo-2024-04-09`, starting on July 15, 2024, or later  **<sup>1</sup>** |
 | `gpt-3.5-turbo-instruct` | 0914 | No earlier than Sep 14, 2025 |
 | `text-embedding-ada-002` | 2 | No earlier than April 3, 2025 |
 | `text-embedding-ada-002` | 1 | No earlier than April 3, 2025 |

articles/ai-services/openai/concepts/use-your-data.md

@@ -78,7 +78,9 @@ You might want to consider using an Azure AI Search index when you either want t
 * Reuse an index created before by ingesting data from other data sources.
 
 > [!NOTE]
-> To use an existing index, it must have at least one searchable field.
+> * To use an existing index, it must have at least one searchable field.
+> * Set the CORS **Allow Origin Type** option to `all` and the **Allowed origins** option to `*`. 
+
 
 ### Search types
 
@@ -135,6 +137,7 @@ If you want to implement additional value-based criteria for query execution, yo
 
 [!INCLUDE [ai-search-ingestion](../includes/ai-search-ingestion.md)]
 
+[!INCLUDE [authentication](../includes/on-your-data-authentication.md)]
 
 # [Vector Database in Azure Cosmos DB for MongoDB](#tab/mongo-db)
 
@@ -202,6 +205,8 @@ To modify the schedule, you can use the [Azure portal](https://portal.azure.com/
 
 [!INCLUDE [ai-search-ingestion](../includes/ai-search-ingestion.md)]
 
+[!INCLUDE [authentication](../includes/on-your-data-authentication.md)]
+
 # [Upload files (preview)](#tab/file-upload)
 
 Using Azure OpenAI Studio, you can upload files from your machine to try Azure OpenAI On Your Data. You also have the option to create a new Azure Blob Storage account and Azure AI Search resource. The service then stores the files to an Azure storage container and performs ingestion from the container. You can use the [quickstart](../use-your-data-quickstart.md) article to learn how to use this data source option.
@@ -210,6 +215,8 @@ Using Azure OpenAI Studio, you can upload files from your machine to try Azure O
 
 [!INCLUDE [ai-search-ingestion](../includes/ai-search-ingestion.md)]
 
+[!INCLUDE [authentication](../includes/on-your-data-authentication.md)]
+
 # [URL/Web address (preview)](#tab/web-pages)
 
 You can paste URLs and the service will store the webpage content, using it when generating responses from the model. The content in URLs/web addresses that you use need to have the following characteristics to be properly ingested:
@@ -224,6 +231,10 @@ You can paste URLs and the service will store the webpage content, using it when
 
 Once you have added the URL/web address for data ingestion, the web pages from your URL are fetched and saved to Azure Blob Storage with a container name: `webpage-<index name>`. Each URL will be saved into a different container within the account. Then the files are indexed into an Azure AI Search index, which is used for retrieval when you’re chatting with the model.
 
+[!INCLUDE [ai-search-ingestion](../includes/ai-search-ingestion.md)]
+
+[!INCLUDE [authentication](../includes/on-your-data-authentication.md)]
+
 # [Elasticsearch (preview)](#tab/elasticsearch)
 
 You can connect to your [Elasticsearch vector database](https://www.elastic.co/guide/en/elasticsearch/reference/current/elasticsearch-intro.html) and chat with your data.

articles/ai-services/openai/faq.yml

@@ -248,6 +248,10 @@ sections:
           Can I bring my own data store to use with Assistants? 
         answer: |
           No. Currently Assistants supports only local files uploaded to the Assistants-managed storage. You cannot use your private storage account with Assistants. 
+      - question: | 
+          Does Assistants support customer-managed key encryption (CMK)?
+        answer: |
+          Today we support CMK for Threads and Files in Assistants. See the [What's new page](./whats-new.md#customer-managed-key-cmk-support-for-assistants) for available regions for this feature.
       - question: |
           Is my data used by Microsoft for training models? 
         answer: |
@@ -259,9 +263,9 @@ sections:
       - question: |
           How am I charged for Assistants?
         answer: |
-          Currently, when you use Assistants API, you're billed for the following: 
-          - Inference cost (input and output) of the base model you're using for each Assistant (for example gpt-4-0125). If you've created multiple Assistants, you will be charged for the base model attached to each Assistant. 
-          - If you've enabled the Code Interpreter tool. For example if your assistant calls Code Interpreter simultaneously in two different threads, this would create two Code Interpreter sessions, each of which would be charged. Each session is active by default for one hour, which means that you would only pay this fee once if your user keeps giving instructions to Code Interpreter in the same thread for up to one hour. 
+          * Inference cost (input and output) of the base model you're using for each Assistant (for example gpt-4-0125). If you've created multiple Assistants, you will be charged for the base model attached to each Assistant.
+          * If you've enabled the Code Interpreter tool. For example if your assistant calls Code Interpreter simultaneously in two different threads, this would create two Code Interpreter sessions, each of which would be charged. Each session is active by default for one hour, which means that you would only pay this fee once if your user keeps giving instructions to Code Interpreter in the same thread for up to one hour.
+          * File search is currently not billed. 
 
           For more information, see the [pricing page](https://azure.microsoft.com/pricing/details/cognitive-services/openai-service/).
       - question: |

articles/ai-services/openai/includes/assistants-ai-studio.md

@@ -12,7 +12,7 @@ ms.author: mbullwin
 author: mrbullwinkle
 ---
 
-[!INCLUDE [Feature preview](../../../ai-studio/includes/feature-preview.md)]
+[!INCLUDE [Feature preview](~/reusable-content/ce-skilling/azure/includes/ai-studio/includes/feature-preview.md)]
 
 ## Prerequisites
 

articles/ai-services/openai/includes/fine-tuning-openai-in-ai-studio.md

@@ -9,7 +9,7 @@
 ms.custom: include, build-2024
 ---
 
-[!INCLUDE [Feature preview](../../../ai-studio/includes/feature-preview.md)]
+[!INCLUDE [Feature preview](~/reusable-content/ce-skilling/azure/includes/ai-studio/includes/feature-preview.md)]
 
 ## Prerequisites
 

articles/ai-services/openai/includes/on-your-data-authentication.md

@@ -0,0 +1,20 @@
+---
+manager: nitinme
+author: aahill
+ms.author: aahi
+ms.service: azure-ai-openai
+ms.topic: include
+ms.date: 03/27/2024
+---
+
+## Data connection
+
+You need to select how you want to authenticate the connection from Azure OpenAI, Azure AI Search, and Azure blob storage. You can choose a *System assigned managed identity* or an *API key*. By selecting *API key* as the authentication type, the system will automatically populate the API key for you to connect with your Azure AI Search, Azure OpenAI, and Azure Blob Storage resources. By selecting *System assigned managed identity*, the authentication will be based on the [role assignment](../how-to/use-your-data-securely.md#role-assignments) you have. *System assigned managed identity* is selected by default for security. 
+
+
+:::image type="content" source="../media/use-your-data/data-connection-authentication.png" alt-text="A screenshot showing the managed identity option in Azure OpenAI Studio." lightbox="../media/use-your-data/data-connection-authentication.png":::
+
+Once you select the **next** button, it will automatically validate your setup to use the selected authentication method. If you encounter an error, see the [role assignments article](../how-to/use-your-data-securely.md#role-assignments) to update your setup.
+
+Once you have fixed the setup, select **next** again to validate and proceed. API users can also [configure authentication](../references/azure-search.md#api-key-authentication-options) with assigned managed identity and API keys.
+