Merge branch 'main' into release-2024-openai-aug-vnext

Author: v-alje

.openpublishing.redirection.api-management.json

@@ -1,5 +1,10 @@
 {
   "redirections": [
+    {
+        "source_path": "articles/api-management/api-management-in-workspace.md",
+        "redirect_url": "/azure/api-management/how-to-create-workspace",
+        "redirect_document_id": false
+      },     
       {
         "source_path": "articles/api-management/set-graphql-resolver-policy.md",
         "redirect_url": "/previous-versions/azure/api-management/set-graphql-resolver-policy",

.openpublishing.redirection.azure-functions.json

@@ -0,0 +1,9 @@
+{
+    "redirections": [
+        {
+            "source_path_from_root": "/articles/azure-functions/durable/durable-functions-configure-durable-functions-with-credentials.md",
+            "redirect_url": "/azure/azure-functions/durable/durable-functions-configure-managed-identity",
+            "redirect_document_id": false
+        }
+    ]
+}

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

@@ -0,0 +1,167 @@
+---
+title: "Face Java client library quickstart"
+description: Use the Face client library for Java to detect faces and identify faces (facial recognition search).
+#services: cognitive-services
+author: PatrickFarley
+manager: nitinme
+ms.service: azure-ai-vision
+ms.subservice: azure-ai-face
+ms.custom:
+  - ignite-2023
+ms.topic: include
+ms.date: 08/08/2024
+ms.author: pafarley
+---
+
+Get started with facial recognition using the Face client library for Java. 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](https://aka.ms/azsdk-java-face-ref) | [Library source code](https://github.com/Azure/azure-sdk-for-java/tree/main/sdk/face/azure-ai-vision-face) | [Package (Maven)](https://central.sonatype.com/artifact/com.azure/azure-ai-vision-face) | [Samples](https://github.com/Azure/azure-sdk-for-java/tree/main/sdk/face/azure-ai-vision-face/src/samples)
+
+## Prerequisites
+
+* Azure subscription - [Create one for free](https://azure.microsoft.com/free/cognitive-services/)
+* The current version of the [Java Development Kit (JDK)](https://www.microsoft.com/openjdk)
+* [Apache Maven](https://maven.apache.org/download.cgi) installed. On Linux, install from the distribution repositories if available.
+* Once you have your Azure subscription, <a href="https://portal.azure.com/#create/Microsoft.CognitiveServicesFace"  title="Create a Face resource"  target="_blank">create a Face resource</a> in the Azure portal to get your key and endpoint. After it deploys, select **Go to resource**.
+    * You'll need the key and endpoint from the resource you create to connect your application to the Face API.
+    * You can use the free pricing tier (`F0`) to try the service, and upgrade later to a paid tier for production.
+
+
+## Create environment variables
+
+[!INCLUDE [create environment variables](../face-environment-variables.md)]
+
+## Identify and verify faces
+
+1. Install the client library
+
+    Open a console window and create a new folder for your quickstart application. Copy the following content to a new file. Save the file as `pom.xml` in your project directory:
+
+    <!-- [!INCLUDE][](https://raw.githubusercontent.com/Azure-Samples/cognitive-services-quickstart-code/master/java/Face/pom.xml)] -->
+    ```xml
+    <project xmlns="http://maven.apache.org/POM/4.0.0"
+        xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
+        xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
+      <modelVersion>4.0.0</modelVersion>
+      <groupId>com.example</groupId>
+      <artifactId>my-application-name</artifactId>
+      <version>1.0.0</version>
+      <dependencies>
+        <!-- https://mvnrepository.com/artifact/com.azure/azure-ai-vision-face -->
+        <dependency>
+          <groupId>com.azure</groupId>
+          <artifactId>azure-ai-vision-face</artifactId>
+          <version>1.0.0-beta.1</version>
+        </dependency>
+        <!-- https://mvnrepository.com/artifact/org.apache.httpcomponents/httpclient -->
+        <dependency>
+          <groupId>org.apache.httpcomponents</groupId>
+          <artifactId>httpclient</artifactId>
+          <version>4.5.13</version>
+        </dependency>
+        <!-- https://mvnrepository.com/artifact/com.google.code.gson/gson -->
+        <dependency>
+          <groupId>com.google.code.gson</groupId>
+          <artifactId>gson</artifactId>
+          <version>2.11.0</version>
+        </dependency>
+      </dependencies>
+    </project>
+    ```
+
+    Install the SDK and dependencies by running the following in the project directory:
+
+    ```console
+    mvn clean dependency:copy-dependencies
+    ```
+
+1. Create a new Java application
+
+    Create a file named `Quickstart.java`, open it in a text editor, and paste in the following code:
+
+    > [!NOTE]
+    > If you haven't received access to the Face service using the [intake form](https://aka.ms/facerecognition), some of these functions won't work.
+
+    [!code-java[](~/cognitive-services-quickstart-code/java/Face/Quickstart.java?name=snippet_single)]
+
+
+1. Run your face recognition app from the application directory with the `javac` and `java` commands.
+
+    #### [Windows](#tab/windows)
+
+    ```console
+    javac -cp target\dependency\* Quickstart.java
+    java -cp .;target\dependency\* Quickstart
+    ```
+
+    #### [Linux](#tab/linux)
+
+    ```console
+    javac -cp target/dependency/* Quickstart.java
+    java -cp .:target/dependency/* Quickstart
+    ```
+
+    ---
+
+
+
+## Output
+
+```console
+========IDENTIFY FACES========
+
+Create a person group (3761e61a-16b2-4503-ad29-ed34c58ba676).
+Create a person group person 'Family1-Dad'.
+Check whether image is of sufficient quality for recognition
+Add face to the person group person(Family1-Dad) from image `Family1-Dad1.jpg`
+Check whether image is of sufficient quality for recognition
+Add face to the person group person(Family1-Dad) from image `Family1-Dad2.jpg`
+Create a person group person 'Family1-Mom'.
+Check whether image is of sufficient quality for recognition
+Add face to the person group person(Family1-Mom) from image `Family1-Mom1.jpg`
+Check whether image is of sufficient quality for recognition
+Add face to the person group person(Family1-Mom) from image `Family1-Mom2.jpg`
+Create a person group person 'Family1-Son'.
+Check whether image is of sufficient quality for recognition
+Add face to the person group person(Family1-Son) from image `Family1-Son1.jpg`
+Check whether image is of sufficient quality for recognition
+Add face to the person group person(Family1-Son) from image `Family1-Son2.jpg`
+
+Train person group 3761e61a-16b2-4503-ad29-ed34c58ba676.
+Training status: succeeded.
+
+Pausing for 60 seconds to avoid triggering rate limit on free account...
+4 face(s) with 4 having sufficient quality for recognition.
+Person 'Family1-Dad' is identified for the face in: identification1.jpg - d7995b34-1b72-47fe-82b6-e9877ed2578d, confidence: 0.96807.
+Verification result: is a match? true. confidence: 0.96807
+Person 'Family1-Mom' is identified for the face in: identification1.jpg - 844da0ed-4890-4bbf-a531-e638797f96fc, confidence: 0.96902.
+Verification result: is a match? true. confidence: 0.96902
+No person is identified for the face in: identification1.jpg - c543159a-57f3-4872-83ce-2d4a733d71c9.
+Person 'Family1-Son' is identified for the face in: identification1.jpg - 414fac6c-7381-4dba-9c8b-fd26d52e879b, confidence: 0.9281.
+Verification result: is a match? true. confidence: 0.9281
+
+========DELETE PERSON GROUP========
+
+Deleted the person group 3761e61a-16b2-4503-ad29-ed34c58ba676.
+
+End of quickstart.
+```
+
+
+
+## Clean up resources
+
+If you want to clean up and remove an Azure AI services subscription, you can delete the resource or resource group. Deleting the resource group also deletes any other resources associated with it.
+
+* [Azure portal](../../../multi-service-resource.md?pivots=azportal#clean-up-resources)
+* [Azure CLI](../../../multi-service-resource.md?pivots=azcli#clean-up-resources)
+
+## Next steps
+
+In this quickstart, you learned how to use the Face client library for Java to do basic face identification. Next, learn about the different face detection models and how to specify the right model for your use case.
+
+> [!div class="nextstepaction"]
+> [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://aka.ms/FaceSamples).

articles/ai-services/computer-vision/quickstarts-sdk/identity-client-library.md

@@ -35,6 +35,11 @@ keywords: face search by image, facial recognition search, facial recognition, f
 
 ::: zone-end
 
+::: zone pivot="programming-language-java"
+
+[!INCLUDE [Java quickstart](../includes/quickstarts-sdk/identity-java-sdk.md)]
+
+::: zone-end
 
 ::: zone pivot="programming-language-javascript"
 

articles/ai-services/content-safety/how-to/encrypt-data-at-rest.md

@@ -20,14 +20,10 @@ Azure AI Content Safety automatically encrypts your data when it's persisted to
 
 Azure AI Content Safety is part of Azure AI services. Azure AI services data is encrypted and decrypted using [FIPS 140-2](https://en.wikipedia.org/wiki/FIPS_140-2) compliant [256-bit AES](https://en.wikipedia.org/wiki/Advanced_Encryption_Standard) encryption. Encryption and decryption are transparent, meaning encryption and access are managed for you. Your data is secure by default and you don't need to modify your code or applications to take advantage of encryption.
 
-
 ## About encryption key management
 
 By default, your subscription uses Microsoft-managed encryption keys. There's also the option to manage your subscription with your own keys called customer-managed keys (CMK). CMK offers greater flexibility to create, rotate, disable, and revoke access controls. You can also audit the encryption keys used to protect your data.
 
-> [!IMPORTANT]
-> For blocklist names, only MMK encryption is applied by default. Using CMK or not will not change this behavior. All the other data will use either MMK or CMK depending on what you've selected.
-
 ## Customer-managed keys with Azure Key Vault
 
 Customer-managed keys (CMK), also known as Bring your own key (BYOK), offer greater flexibility to create, rotate, disable, and revoke access controls. You can also audit the encryption keys used to protect your data.

articles/ai-services/openai/concepts/models.md

@@ -202,6 +202,28 @@ For more information on Provisioned deployments, see our [Provisioned guidance](
 
 - eastus
 
+
+### Global batch model availability
+
+### Region and model support
+
+The following models support global batch:
+
+| Model | Version | Input format |
+|---|---|
+|`gpt-4o` | 2024-05-13 |text + image |
+|`gpt-4` | turbo-2024-04-09 | text |
+|`gpt-4` | 0613 | text |
+| `gpt-35-turbo` | 0125 | text |
+| `gpt-35-turbo` | 1106 | text |
+| `gpt-35-turbo` | 0613 | text |
+
+Global batch is currently supported in the following regions:
+
+- East US
+- West US
+- Sweden Central
+
 ### GPT-4 and GPT-4 Turbo model availability
 
 #### Public cloud regions