Merge pull request #284611 from MicrosoftDocs/main

8/14 11:00 AM IST Publish

Author: PhilKang0704

.openpublishing.redirection.ai-services-from-cog.json

@@ -1670,11 +1670,6 @@
       "redirect_url": "/azure/ai-services/speech-service/how-to-configure-openssl-linux",
       "redirect_document_id": true
     },
-    {
-      "source_path_from_root": "/articles/cognitive-services/speech-service/how-to-configure-rhel-centos-7.md",
-      "redirect_url": "/azure/ai-services/speech-service/how-to-configure-rhel-centos-7",
-      "redirect_document_id": true
-    },
     {
       "source_path_from_root": "/articles/cognitive-services/speech-service/how-to-control-connections.md",
       "redirect_url": "/azure/ai-services/speech-service/how-to-control-connections",

.openpublishing.redirection.json

@@ -5079,6 +5079,11 @@
       "source_path_from_root": "/articles/xplat-cli-install.md",
       "redirect_url": "/cli/azure/install-azure-cli",
       "redirect_document_id": false
+    },
+    {
+      "source_path_from_root": "/articles/virtual-network/template-samples.md",
+      "redirect_url": "/samples/browse/?expanded=azure&products=azure-resource-manager&terms=virtual%20network",
+      "redirect_document_id": false
     }
   ]
 }

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

@@ -384,6 +384,16 @@
             "source_path_from_root": "/articles/ai-services/speech-service/faq-voice-assistants.yml",
             "redirect_url": "/azure/ai-services/speech-service/custom-commands",
             "redirect_document_id": false
+          },
+          {
+            "source_path_from_root": "/articles/cognitive-services/speech-service/how-to-configure-rhel-centos-7.md",
+            "redirect_url": "/azure/ai-services/speech-service/quickstarts/setup-platform",
+            "redirect_document_id": false
+          },
+          {
+            "source_path_from_root": "/articles/ai-services/speech-service/how-to-configure-rhel-centos-7.md",
+            "redirect_url": "/azure/ai-services/speech-service/quickstarts/setup-platform",
+            "redirect_document_id": false
           }
 
     ]

articles/ai-services/computer-vision/how-to/identity-access-token.md

@@ -112,61 +112,51 @@ curl -X POST 'https://<client-endpoint>/face/v1.0/identify' \
 
 #### [C#](#tab/csharp)
 
-The following code snippets show you how to use an access token with the [Face SDK for C#](https://www.nuget.org/packages/Microsoft.Azure.CognitiveServices.Vision.Face).
+The following code snippets show you how to use an access token with the [Face SDK for C#](https://aka.ms/azsdk-csharp-face-pkg).
 
-The following class uses an access token to create a **ServiceClientCredentials** object that can be used to authenticate a Face API client object. It automatically adds the access token as a header in every request that the Face client will make.
+The following class uses an access token to create a **HttpPipelineSynchronousPolicy** object that can be used to authenticate a Face API client object. It automatically adds the access token as a header in every request that the Face client will make.
 
 ```csharp
-public class LimitedAccessTokenWithApiKeyClientCredential : ServiceClientCredentials 
+public class LimitedAccessTokenPolicy : HttpPipelineSynchronousPolicy
 {
-    /// <summary> 
-    /// Creates a new instance of the LimitedAccessTokenWithApiKeyClientCredential class 
-    /// </summary> 
-    /// <param name="apiKey">API Key for the Face API or CognitiveService endpoint</param> 
-    /// <param name="limitedAccessToken">LimitedAccessToken to bypass the limited access program, requires ISV sponsership.</param> 
-
-    public LimitedAccessTokenWithApiKeyClientCredential(string apiKey, string limitedAccessToken) 
-    { 
-        this.ApiKey = apiKey; 
-        this.LimitedAccessToken = limitedAccessToken; 
+    /// <summary>
+    /// Creates a new instance of the LimitedAccessTokenPolicy class
+    /// </summary>
+    /// <param name="limitedAccessToken">LimitedAccessToken to bypass the limited access program, requires ISV sponsership.</param>
+    public LimitedAccessTokenPolicy(string limitedAccessToken)
+    {
+        _limitedAccessToken = limitedAccessToken;
     }
 
-    private readonly string ApiKey; 
-    private readonly string LimitedAccesToken; 
-
-    /// <summary> 
-    /// Add the Basic Authentication Header to each outgoing request 
-    /// </summary> 
-    /// <param name="request">The outgoing request</param>
-    /// <param name="cancellationToken">A token to cancel the operation</param> 
-    public override Task ProcessHttpRequestAsync(HttpRequestMessage request, CancellationToken cancellationToken) 
-    { 
-        if (request == null) 
-            throw new ArgumentNullException("request"); 
-        request.Headers.Add("Ocp-Apim-Subscription-Key", ApiKey); 
-        request.Headers.Add("LimitedAccessToken", $"Bearer {LimitedAccesToken}");
-
-        return Task.FromResult<object>(null); 
-    } 
-} 
+    private readonly string _limitedAccessToken;
+
+    /// <summary>
+    /// Add the authentication header to each outgoing request
+    /// </summary>
+    /// <param name="message">The outgoing message</param>
+    public override void OnSendingRequest(HttpMessage message)
+    {
+        message.Request.Headers.Add("LimitedAccessToken", $"Bearer {_limitedAccessToken}");
+    }
+}
 ```
 
 In the client-side application, the helper class can be used like in this example:
 
 ```csharp
-static void Main(string[] args) 
-{ 
+static void Main(string[] args)
+{
     // create Face client object
-    var faceClient = new FaceClient(new LimitedAccessTokenWithApiKeyClientCredential(apiKey: "<client-face-key>", limitedAccessToken: "<token>")); 
-
-    faceClient.Endpoint = "https://mytest-eastus2.cognitiveservices.azure.com"; 
+    var clientOptions = new AzureAIVisionFaceClientOptions();
+    clientOptions.AddPolicy(new LimitedAccessTokenPolicy("<token>"), HttpPipelinePosition.PerCall);
+    FaceClient faceClient = new FaceClient(new Uri("<client-endpoint>"), new AzureKeyCredential("<client-face-key>"), clientOptions);
 
     // use Face client in an API call
-    using (var stream = File.OpenRead("photo.jpg")) 
+    using (var stream = File.OpenRead("photo.jpg"))
     {
-        var result = faceClient.Face.DetectWithStreamAsync(stream, detectionModel: "Detection_03", recognitionModel: "Recognition_04", returnFaceId: true).Result; 
+        var response = faceClient.Detect(BinaryData.FromStream(stream), FaceDetectionModel.Detection03, FaceRecognitionModel.Recognition04, returnFaceId: true);
 
-        Console.WriteLine(JsonConvert.SerializeObject(result)); 
+        Console.WriteLine(JsonConvert.SerializeObject(response.Value));
     }
 }
 ```

articles/ai-services/computer-vision/how-to/specify-detection-model.md

@@ -73,7 +73,7 @@ var faces = response.Value;
 
 The Face service can extract face data from an image and associate it with a **Person** object through the [Add Person Group Person Face] API. In this API call, you can specify the detection model in the same way as in [Detect].
 
-See the following code example for the .NET client library.
+See the following .NET code example.
 
 ```csharp
 // Create a PersonGroup and add a person with face detected by "detection_03" model
@@ -110,7 +110,7 @@ This code creates a **PersonGroup** with ID `mypersongroupid` and adds a **Perso
 
 ## Add face to FaceList with specified model
 
-You can also specify a detection model when you add a face to an existing **FaceList** object. See the following code example for the .NET client library.
+You can also specify a detection model when you add a face to an existing **FaceList** object. See the following .NET code example.
 
 ```csharp
 using (var content = new ByteArrayContent(Encoding.UTF8.GetBytes(JsonConvert.SerializeObject(new Dictionary<string, object> { ["name"] = "My face collection", ["recognitionModel"] = "recognition_04" }))))
@@ -139,6 +139,7 @@ In this article, you learned how to specify the detection model to use with diff
 
 * [Face .NET SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-csharp%253fpivots%253dprogramming-language-csharp)
 * [Face Python SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-python%253fpivots%253dprogramming-language-python)
+* [Face Java SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-java%253fpivots%253dprogramming-language-java)
 * [Face JavaScript SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-javascript%253fpivots%253dprogramming-language-javascript)
 
 [Detect]: /rest/api/face/face-detection-operations/detect

articles/ai-services/computer-vision/how-to/specify-recognition-model.md

@@ -132,6 +132,7 @@ In this article, you learned how to specify the recognition model to use with di
 
 * [Face .NET SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-csharp%253fpivots%253dprogramming-language-csharp)
 * [Face Python SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-python%253fpivots%253dprogramming-language-python)
+* [Face Java SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-java%253fpivots%253dprogramming-language-java)
 * [Face JavaScript SDK](../quickstarts-sdk/identity-client-library.md?pivots=programming-language-javascript%253fpivots%253dprogramming-language-javascript)
 
 [Detect]: /rest/api/face/face-detection-operations/detect

articles/ai-services/document-intelligence/concept-custom-neural.md

@@ -1,18 +1,22 @@
 ---
 title: Custom neural document model - Document Intelligence (formerly Form Recognizer)
 titleSuffix: Azure AI services
-description: Use the custom neural document model to train a model to extract data from structured, semistructured, and unstructured documents.
+description: Use the custom neural document model to train a model to extract data from structured, semi-structured, and unstructured documents.
 author: laujan
 manager: nitinme
 ms.service: azure-ai-document-intelligence
 ms.topic: conceptual
-ms.date: 08/07/2024
+ms.date: 08/13/2024
 ms.author: lajanuar
 ms.custom:
   - references_regions
 monikerRange: '>=doc-intel-3.0.0'
 ---
 
+<!-- markdownlint-disable MD001 -->
+<!-- markdownlint-disable MD033 -->
+<!-- markdownlint-disable MD051 -->
+<!-- markdownlint-disable MD024 -->
 
 # Document Intelligence custom neural model
 
@@ -212,13 +216,13 @@ Custom neural models are available in the [v3.0 and later models](v3-1-migration
 
 | Document Type | REST API | SDK | Label and Test Models|
 |--|--|--|--|
-| Custom document | [Document Intelligence 3.1](/rest/api/aiservices/document-models/analyze-document?view=rest-aiservices-2023-07-31&preserve-view=true&tabs=HTTP)| [Document Intelligence SDK](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-3.0.0&preserve-view=true)| [Document Intelligence Studio](https://formrecognizer.appliedai.azure.com/studio)
+| Custom document | [Document Intelligence 3.1](/rest/api/aiservices/document-models/analyze-document?view=rest-aiservices-2023-07-31&preserve-view=true&tabs=HTTP)| [Document Intelligence SDK](quickstarts/get-started-sdks-rest-api.md?view=doc-intel-3.0.0&preserve-view=true)| [Document Intelligence Studio](https://formrecognizer.appliedai.azure.com/studio)|
 
 The `Build` operation to train model supports a new ```buildMode``` property, to train a custom neural model, set the ```buildMode``` to ```neural```.
 
 :::moniker range="doc-intel-4.0.0"
 
-```REST
+```bash
 https://{endpoint}/documentintelligence/documentModels:build?api-version=2024-07-31-preview
 
 {
@@ -237,7 +241,7 @@ https://{endpoint}/documentintelligence/documentModels:build?api-version=2024-07
 
 :::moniker range="doc-intel-3.1.0"
 
-```REST
+```bash
 https://{endpoint}/formrecognizer/documentModels:build?api-version=v3.1:2023-07-31
 
 {
@@ -256,7 +260,7 @@ https://{endpoint}/formrecognizer/documentModels:build?api-version=v3.1:2023-07-
 
 :::moniker range="doc-intel-3.0.0"
 
-```REST
+```bash
 https://{endpoint}/formrecognizer/documentModels/{modelId}:copyTo?api-version=2022-08-31
 
 {
@@ -276,8 +280,10 @@ https://{endpoint}/formrecognizer/documentModels/{modelId}:copyTo?api-version=20
 :::moniker range="doc-intel-4.0.0"
 
 ## Billing
- 
-Starting with version `2024-07-31-preview`, you can train your custom neural model for longer durations than 30 minutes. Previous versions have been capped at 30 minutes per training instance, with a total of 20 free training instances per month. Now with `2024-07-31-preview`, you can receive **10 hours** of free model training, and train a model for as long as 10 hours. If you would like to train a model for longer than 10 hours, billing charges are calculated for model trainings that exceed 10 hours. You can choose to spend all of 10 free hours on a single build with a large set of data, or utilize it across multiple builds by adjusting the maximum duration value for the `build` operation by specifying `maxTrainingHours` as below:
+
+Starting with version `2024-07-31-preview`, you can train your custom neural model for longer durations than the standard 30 minutes. Previous versions are limited to 30 minutes per training instance, with a total of 20 free training instances per month. Now with `2024-07-31-preview`, you can receive **10 hours** of **free model training**, and train a model for as long as 10 hours.
+
+You can choose to spend all of 10 free hours on a single model build with a large set of data, or utilize it across multiple builds by adjusting the maximum duration value for the `build` operation by specifying `maxTrainingHours`:
 
 ```bash
 
@@ -288,10 +294,12 @@ POST /documentModels:build
 }
 ```
 
-> [!NOTE]
-> For Document Intelligence versions `v3.1 (2023-07-31)` and `v3.0 (2022-08-31)`, custom neural model's paid training is not enabled. For the two older versions, you will get a maximum of 30 minutes training duration per model. If you would like to train more than 20 model instances, you can request for increase in the training limit.
-
-Each training hour is the amount of compute a single V100 GPU can perform in an hour. As each build takes different amount of time, billing is calculated for the actual time spent (excluding time in queue), with a minimum of 30 minutes per training job. The elapsed time is converted to V100 equivalent training hours and reported as part of the model.
+> [!IMPORTANT]
+>
+> * If you would like to train additional neural models or train models for a longer time period that **exceed 10 hours**, billing charges apply. For details on the billing charges, refer to the [pricing page](https://azure.microsoft.com/pricing/details/ai-document-intelligence/).
+> * You can opt in for this paid training service by setting the `maxTrainingHours` to the desired maximum number of hours. API calls with no budget but with the `maxTrainingHours` set as over 10 hours will fail.
+> * As each build takes different amount of time depending on the type and size of the training dataset, billing is calculated for the actual time spent training the neural model, with a minimum of 30 minutes per training job.
+> * This paid billing structure enables you to train larger data sets for longer durations with flexibility in the training hours.
 
 ```bash
 
@@ -304,27 +312,28 @@ GET /documentModels/{myCustomModel}
 }
 ```
 
-This billing structure enables you to train larger data sets for longer durations with flexibility in the training hours.
+> [!NOTE]
+> For Document Intelligence versions `v3.1 (2023-07-31)` and `v3.0 (2022-08-31)`, custom neural model's paid training is not enabled. For the two older versions, you will get a maximum of 30 minutes training duration per model. If you would like to train more than 20 model instances, you can create an [Azure support ticket](service-limits.md#create-and-submit-support-request) to increase in the training limit.
 
 :::moniker-end
 
 :::moniker range="doc-intel-3.1.0"
 
 ## Billing
 
-For Document Intelligence versions `v3.1 (2023-07-31)` and `v3.0 (2022-08-31)`, you will get a maximum of 30 minutes training duration per model, and a maximum of 20 trainings for free per month. If you would like to train more than 20 model instances, you can request for increase in the training limit.
+For Document Intelligence versions `v3.1 (2023-07-31) and v3.0 (2022-08-31)`, you receive a maximum 30 minutes of training duration per model, and a maximum of 20 trainings for free per month. If you would like to train more than 20 model instances, you can create an [Azure support ticket](service-limits.md#create-and-submit-support-request) to increase in the training limit. For the Azure support ticket, enter in the `summary` section a phrase such as `Increase Document Intelligence custom neural training (TPS) limit`. A ticket can only apply at a resource-level, not a subscription level. You can request a training limit increase for a single Document Intelligence resource by specifying your resource ID and region in the support ticket.
 
-If you are interested in training models for longer durations than 30 minutes, we support **paid training** for our newest version, `v4.0 (2024-07-31)`. Using the latest version, you can train your model for a longer duration to process larger documents.
+If you want to train models for longer durations than 30 minutes, we support **paid training** with our newest version, `v4.0 (2024-07-31-preview)`. Using the latest version, you can train your model for a longer duration to process larger documents. For more information about paid training, *see* [Billing v4.0](service-limits.md#billing).
 
 :::moniker-end
 
 :::moniker range="doc-intel-3.0.0"
 
 ## Billing
 
-For Document Intelligence versions `v3.1 (2023-07-31)` and `v3.0 (2022-08-31)`, you will get a maximum of 30 minutes training duration per model, and a maximum of 20 trainings for free per month. If you would like to train more than 20 model instances, you can request for increase in the training limit.
+For Document Intelligence versions `v3.1 (2023-07-31) and v3.0 (2022-08-31)`, you receive a maximum 30 minutes of training duration per model, and a maximum of 20 trainings for free per month. If you would like to train more than 20 model instances, you can create an [Azure support ticket](service-limits.md#create-and-submit-support-request) to increase in the training limit. For the Azure support ticket, enter in the `summary` section a phrase such as `Increase Document Intelligence custom neural training (TPS) limit`. A ticket can only apply at a resource-level, not a subscription level. You can request a training limit increase for a single Document Intelligence resource by specifying your resource ID and region in the support ticket.
 
-If you are interested in training models for longer durations than 30 minutes, we support **paid training** for our newest version, `v4.0 (2024-07-31)`. Using the latest version, you can train your model for a longer duration to process larger documents.
+If you want to train models for longer durations than 30 minutes, we support **paid training** with our newest version, `v4.0 (2024-07-31)`. Using the latest version, you can train your model for a longer duration to process larger documents. For more information about paid training, *see* [Billing v4.0](service-limits.md#billing).
 
 :::moniker-end
 

articles/ai-services/speech-service/batch-transcription-create.md

@@ -108,6 +108,10 @@ You can query the status of your transcriptions with the [Transcriptions_Get](/r
 Call [Transcriptions_Delete](/rest/api/speechtotext/transcriptions/delete)
 regularly from the service, after you retrieve the results. Alternatively, set the `timeToLive` property to ensure the eventual deletion of the results.
 
+> [!TIP]
+> You can also try the Batch Transcription API using Python on [GitHub](https://github.com/Azure-Samples/cognitive-services-speech-sdk/blob/master/samples/batch/python/python-client/main.py).
+
+
 ::: zone-end
 
 ::: zone pivot="speech-cli"
@@ -168,7 +172,7 @@ spx help batch transcription
 
 ::: zone pivot="rest-api"
 
-Here are some property options that you can use to configure a transcription when you call the [Transcriptions_Create](/rest/api/speechtotext/transcriptions/create) operation.
+Here are some property options to configure a transcription when you call the [Transcriptions_Create](/rest/api/speechtotext/transcriptions/create) operation. You can find more examples on the same page, such as [creating a transcription with language identification](/rest/api/speechtotext/transcriptions/create/#create-a-transcription-with-language-identification).
 
 | Property | Description |
 |----------|-------------|