Merge pull request #3130 from MicrosoftDocs/repo_sync_working_branch

Confirm merge from repo_sync_working_branch to main to sync with https://github.com/MicrosoftDocs/azure-ai-docs (branch main)

Author: Taojunshen

articles/ai-services/anomaly-detector/includes/quickstarts/anomaly-detector-client-library-java-multivariate.md

@@ -241,7 +241,7 @@ UUID resultId = UUID.fromString(substring[substring.length - 1]);
 DetectionResult detectionResult;
 while (true) {
     detectionResult = anomalyDetectorClient.getDetectionResult(resultId);
-    DetectionStatus detectionStatus = detectionResult.getSummary().getStatus();;
+    DetectionStatus detectionStatus = detectionResult.getSummary().getStatus();
     if (detectionStatus == DetectionStatus.READY || detectionStatus == DetectionStatus.FAILED) {
         break;
     }

articles/ai-services/document-intelligence/how-to-guides/includes/v4-0/java-sdk.md

@@ -177,7 +177,7 @@ String documentUrl = "https://raw.githubusercontent.com/Azure-Samples/cognitive-
 String modelId = "prebuilt-read";
 
 SyncPoller < OperationResult, AnalyzeResult > analyzeLayoutResultPoller =
-  client.beginAnalyzeDocument(modelId, invoiceUrl);;
+  client.beginAnalyzeDocument(modelId, invoiceUrl);
 
 AnalyzeResult analyzeLayoutResult = analyzeLayoutResultPoller.getFinalResult().getAnalyzeResult();
 
@@ -338,7 +338,7 @@ String modelId = "prebuilt-document";
 SyncPoller < OperationResult, AnalyzeResult > analyzeDocumentPoller =
   client.beginAnalyzeDocument(modelId, generalDocumentUrl);
 
-AnalyzeResult analyzeResult = analyzeDocumentPoller.getFinalResult().getAnalyzeResult();;
+AnalyzeResult analyzeResult = analyzeDocumentPoller.getFinalResult().getAnalyzeResult();
 
 // pages
 analyzeResult.getPages().forEach(documentPage -> {

articles/ai-services/openai/includes/java.md

@@ -103,8 +103,8 @@ dependencies {
     public class GetCompletionsSample {
     
         public static void main(String[] args) {
-            String azureOpenaiKey = System.getenv("AZURE_OPENAI_API_KEY");;
-            String endpoint = System.getenv("AZURE_OPENAI_ENDPOINT");;
+            String azureOpenaiKey = System.getenv("AZURE_OPENAI_API_KEY");
+            String endpoint = System.getenv("AZURE_OPENAI_ENDPOINT");
             String deploymentOrModelId = "gpt-35-turbo-instruct";
     
             OpenAIClient client = new OpenAIClientBuilder()

articles/ai-services/openai/monitor-openai-reference.md

@@ -19,7 +19,7 @@ See [Monitor Azure OpenAI](./how-to/monitor-openai.md) for details on the data y
 
 ### Supported metrics for Microsoft.CognitiveServices/accounts
 
-Here are the most important metrics we think you should monitor for Azure OpenAI. Later in this article is a longer list of all available Azure AI services metrics which contains more details on metrics in this shorter list.
+Here are the most important metrics we think you should monitor for Azure OpenAI. Later in this article is a longer list of all available Azure AI services metrics which contains more details on metrics in this shorter list. _Please see below list for most up to date information. We're working on refreshing the tables in the following sections._
 
 - Azure OpenAI Requests
 - Active Tokens
@@ -42,9 +42,9 @@ You can also monitor Content Safety metrics that are used by other Azure AI serv
 - Safety System Event
 - Total Volume Sent for Safety Check 
 
-
 > [!NOTE]
 > The **Provisioned-managed Utilization** metric is now deprecated and is no longer recommended. This metric has been replaced by the **Provisioned-managed Utilization V2** metric.
+> Tokens per Second, Time to Response, Time Between Tokens are currently not available for pay-as-you-go (Standard) deployments. 
 
 Cognitive Services metrics have the category **Cognitive Services - HTTP Requests** in the following table. These metrics are legacy metrics that are common to all Azure AI Services resources. Microsoft no longer recommends that you use these metrics with Azure OpenAI.
 

articles/ai-services/speech-service/includes/language-support/viseme.md

@@ -109,8 +109,7 @@ ms.author: Zoubaolian
 | vi-VN           | Vietnamese (Vietnam) |Viseme ID|
 | zh-CN           | Chinese (Mandarin, Simplified)  |Viseme ID <br> Blend shapes|
 | zh-HK           | Chinese (Cantonese, Traditional)|Viseme ID|
-| zh-TW           | Chinese (Taiwanese Mandarin, Traditional)|Viseme ID|
-
+| zh-HK           | Chinese (Taiwanese Mandarin, Traditional)|Viseme ID (except `zh-TW-HsiaoYuNeural`)|
 
 
 

articles/machine-learning/v1/how-to-deploy-pipelines.md

@@ -177,7 +177,7 @@ Gson gson = new Gson();
 
 HttpRequest tokenAuthenticationRequest = tokenAuthenticationRequest(tenantId, clientId, clientSecret, resourceManagerUrl);
 Optional<String> authBody = getRequestBody(client, tokenAuthenticationRequest);
-Optional<String> authKey = authBody.flatMap(body -> Optional.of(gson.fromJson(body, AuthenticationBody.class).access_token);;
+Optional<String> authKey = authBody.flatMap(body -> Optional.of(gson.fromJson(body, AuthenticationBody.class).access_token));
 Optional<HttpRequest> scoringRequest = authKey.flatMap(key -> Optional.of(scoringRequest(key, scoringUri, dataToBeScored)));
 Optional<String> scoringResult = scoringRequest.flatMap(req -> getRequestBody(client, req));
 // ... etc (`scoringResult.orElse()`) ...