Update AutoRest C# version to 3.0.0-beta.20230518.1 (Azure#36373)

* Update Generator Version 3.0.0-beta.20230518.1

* Update SDK codes

* Update SDK codes

* update AnomalyDetector samples

* update api of healthinsights

---------

Co-authored-by: FAREAST\chunyu <chunyu@microsoft.com>

Author: azure-sdk

eng/Packages.Data.props

@@ -167,7 +167,7 @@
     All should have PrivateAssets="All" set so they don't become package dependencies
   -->
   <ItemGroup>
-    <PackageReference Update="Microsoft.Azure.AutoRest.CSharp" Version="3.0.0-beta.20230517.2" PrivateAssets="All" />
+    <PackageReference Update="Microsoft.Azure.AutoRest.CSharp" Version="3.0.0-beta.20230518.1" PrivateAssets="All" />
     <PackageReference Update="Azure.ClientSdk.Analyzers" Version="0.1.1-dev.20230131.1" PrivateAssets="All" />
     <PackageReference Update="coverlet.collector" Version="1.3.0" PrivateAssets="All" />
     <PackageReference Update="Microsoft.CodeAnalysis.NetAnalyzers" Version="7.0.1" PrivateAssets="All" />

eng/emitter-package.json

@@ -1,6 +1,6 @@
 {
     "main": "dist/src/index.js",
     "dependencies": {
-      "@azure-tools/typespec-csharp": "0.2.0-beta.20230517.2"
+      "@azure-tools/typespec-csharp": "0.2.0-beta.20230518.1"
     }
 }

sdk/anomalydetector/Azure.AI.AnomalyDetector/api/Azure.AI.AnomalyDetector.netstandard2.0.cs

@@ -30,7 +30,7 @@ public partial class AnomalyDetectionModel
         internal AnomalyDetectionModel() { }
         public System.DateTimeOffset CreatedTime { get { throw null; } }
         public System.DateTimeOffset LastUpdatedTime { get { throw null; } }
-        public string ModelId { get { throw null; } }
+        public System.Guid ModelId { get { throw null; } }
         public Azure.AI.AnomalyDetector.ModelInfo ModelInfo { get { throw null; } }
     }
     public partial class AnomalyDetectorClient
@@ -59,10 +59,10 @@ public AnomalyDetectorClient(System.Uri endpoint, Azure.AzureKeyCredential crede
         public virtual Azure.Response DetectUnivariateLastPoint(Azure.Core.RequestContent content, Azure.RequestContext context = null) { throw null; }
         public virtual System.Threading.Tasks.Task<Azure.Response<Azure.AI.AnomalyDetector.UnivariateLastDetectionResult>> DetectUnivariateLastPointAsync(Azure.AI.AnomalyDetector.UnivariateDetectionOptions options, System.Threading.CancellationToken cancellationToken = default(System.Threading.CancellationToken)) { throw null; }
         public virtual System.Threading.Tasks.Task<Azure.Response> DetectUnivariateLastPointAsync(Azure.Core.RequestContent content, Azure.RequestContext context = null) { throw null; }
-        public virtual Azure.Response GetMultivariateBatchDetectionResult(string resultId, Azure.RequestContext context) { throw null; }
-        public virtual Azure.Response<Azure.AI.AnomalyDetector.MultivariateDetectionResult> GetMultivariateBatchDetectionResult(string resultId, System.Threading.CancellationToken cancellationToken = default(System.Threading.CancellationToken)) { throw null; }
-        public virtual System.Threading.Tasks.Task<Azure.Response> GetMultivariateBatchDetectionResultAsync(string resultId, Azure.RequestContext context) { throw null; }
-        public virtual System.Threading.Tasks.Task<Azure.Response<Azure.AI.AnomalyDetector.MultivariateDetectionResult>> GetMultivariateBatchDetectionResultAsync(string resultId, System.Threading.CancellationToken cancellationToken = default(System.Threading.CancellationToken)) { throw null; }
+        public virtual Azure.Response GetMultivariateBatchDetectionResult(System.Guid resultId, Azure.RequestContext context) { throw null; }
+        public virtual Azure.Response<Azure.AI.AnomalyDetector.MultivariateDetectionResult> GetMultivariateBatchDetectionResult(System.Guid resultId, System.Threading.CancellationToken cancellationToken = default(System.Threading.CancellationToken)) { throw null; }
+        public virtual System.Threading.Tasks.Task<Azure.Response> GetMultivariateBatchDetectionResultAsync(System.Guid resultId, Azure.RequestContext context) { throw null; }
+        public virtual System.Threading.Tasks.Task<Azure.Response<Azure.AI.AnomalyDetector.MultivariateDetectionResult>> GetMultivariateBatchDetectionResultAsync(System.Guid resultId, System.Threading.CancellationToken cancellationToken = default(System.Threading.CancellationToken)) { throw null; }
         public virtual Azure.Response GetMultivariateModel(string modelId, Azure.RequestContext context) { throw null; }
         public virtual Azure.Response<Azure.AI.AnomalyDetector.AnomalyDetectionModel> GetMultivariateModel(string modelId, System.Threading.CancellationToken cancellationToken = default(System.Threading.CancellationToken)) { throw null; }
         public virtual System.Threading.Tasks.Task<Azure.Response> GetMultivariateModelAsync(string modelId, Azure.RequestContext context) { throw null; }
@@ -186,10 +186,10 @@ public ErrorResponse(string code, string message) { }
     }
     public partial class ModelInfo
     {
-        public ModelInfo(string dataSource, System.DateTimeOffset startTime, System.DateTimeOffset endTime) { }
+        public ModelInfo(System.Uri dataSource, System.DateTimeOffset startTime, System.DateTimeOffset endTime) { }
         public Azure.AI.AnomalyDetector.AlignPolicy AlignPolicy { get { throw null; } set { } }
         public Azure.AI.AnomalyDetector.DataSchema? DataSchema { get { throw null; } set { } }
-        public string DataSource { get { throw null; } set { } }
+        public System.Uri DataSource { get { throw null; } set { } }
         public Azure.AI.AnomalyDetector.DiagnosticsInfo DiagnosticsInfo { get { throw null; } }
         public string DisplayName { get { throw null; } set { } }
         public System.DateTimeOffset EndTime { get { throw null; } set { } }
@@ -228,8 +228,8 @@ public ModelState() { }
     }
     public partial class MultivariateBatchDetectionOptions
     {
-        public MultivariateBatchDetectionOptions(string dataSource, System.DateTimeOffset startTime, System.DateTimeOffset endTime) { }
-        public string DataSource { get { throw null; } set { } }
+        public MultivariateBatchDetectionOptions(System.Uri dataSource, System.DateTimeOffset startTime, System.DateTimeOffset endTime) { }
+        public System.Uri DataSource { get { throw null; } set { } }
         public System.DateTimeOffset EndTime { get { throw null; } set { } }
         public System.DateTimeOffset StartTime { get { throw null; } set { } }
         public int? TopContributorCount { get { throw null; } set { } }
@@ -265,7 +265,7 @@ internal MultivariateBatchDetectionResultSummary() { }
     public partial class MultivariateDetectionResult
     {
         internal MultivariateDetectionResult() { }
-        public string ResultId { get { throw null; } }
+        public System.Guid ResultId { get { throw null; } }
         public System.Collections.Generic.IReadOnlyList<Azure.AI.AnomalyDetector.AnomalyState> Results { get { throw null; } }
         public Azure.AI.AnomalyDetector.MultivariateBatchDetectionResultSummary Summary { get { throw null; } }
     }

sdk/anomalydetector/Azure.AI.AnomalyDetector/samples/Sample2_DetectLastPointAnomaly.md

@@ -13,7 +13,7 @@ You can set `endpoint` and `apiKey` based on an environment variable, a configur
 //read endpoint and apiKey
 string endpoint = TestEnvironment.Endpoint;
 string apiKey = TestEnvironment.ApiKey;
-string dataSource = TestEnvironment.DataSource;
+Uri dataSource = new Uri(TestEnvironment.DataSource);
 
 Uri endpointUri = new Uri(endpoint);
 AzureKeyCredential credential = new AzureKeyCredential(apiKey);

sdk/anomalydetector/Azure.AI.AnomalyDetector/samples/Sample3_DetectChangePoint.md

@@ -13,7 +13,7 @@ You can set `endpoint` and `apiKey` based on an environment variable, a configur
 //read endpoint and apiKey
 string endpoint = TestEnvironment.Endpoint;
 string apiKey = TestEnvironment.ApiKey;
-string dataSource = TestEnvironment.DataSource;
+Uri dataSource = new Uri(TestEnvironment.DataSource);
 
 Uri endpointUri = new Uri(endpoint);
 AzureKeyCredential credential = new AzureKeyCredential(apiKey);

sdk/anomalydetector/Azure.AI.AnomalyDetector/samples/Sample4_MultivariateDetect.md

@@ -13,7 +13,7 @@ You can set `endpoint` and `apiKey` based on an environment variable, a configur
 //read endpoint and apiKey
 string endpoint = TestEnvironment.Endpoint;
 string apiKey = TestEnvironment.ApiKey;
-string dataSource = TestEnvironment.DataSource;
+Uri dataSource = new Uri(TestEnvironment.DataSource);
 
 Uri endpointUri = new Uri(endpoint);
 AzureKeyCredential credential = new AzureKeyCredential(apiKey);
@@ -31,7 +31,7 @@ You could add the data source, along with start time and end time to a `ModelInf
 Call `CreateAndTrainMultivariateModel` with the created data feed and extract the model ID from the response. Afterwards, you can get the model info, including the model status, by calling `GetMultivariateModelValue` with the model ID. Wait until the model status is ready.
 
 ```C# Snippet:TrainMultivariateModel
-private string TrainModel(AnomalyDetectorClient client, string dataSource, DateTimeOffset startTime, DateTimeOffset endTime, int maxTryout = 500)
+private string TrainModel(AnomalyDetectorClient client, Uri dataSource, DateTimeOffset startTime, DateTimeOffset endTime, int maxTryout = 500)
 {
     try
     {
@@ -46,7 +46,7 @@ private string TrainModel(AnomalyDetectorClient client, string dataSource, DateT
 
         Console.WriteLine("Training new model...(it may take a few minutes)");
         AnomalyDetectionModel response = client.TrainMultivariateModel(modelInfo);
-        string trainedModelId = response.ModelId;
+        string trainedModelId = response.ModelId.ToString();
         Console.WriteLine($"Training model id is {trainedModelId}");
 
         // Wait until the model is ready. It usually takes several minutes
@@ -98,7 +98,7 @@ private string TrainModel(AnomalyDetectorClient client, string dataSource, DateT
 To detect anomalies using your newly trained model, create a private async Task named `BatchDetect`. You will create a new `DetectionRequest`, pass that as a parameter to `DetectMultivariateBatchAnomaly` and get a `DetectionResult` and extract result ID from it. With the result ID, you could get the detection content and detection status by `GetMultivariateBatchDetectionResultValue`. Return the detection content when the detection status is ready.
 
 ```C# Snippet:DetectMultivariateAnomaly
-private MultivariateDetectionResult BatchDetect(AnomalyDetectorClient client, string datasource, string modelId, DateTimeOffset startTime, DateTimeOffset endTime, int maxTryout = 500)
+private MultivariateDetectionResult BatchDetect(AnomalyDetectorClient client, Uri datasource, string modelId, DateTimeOffset startTime, DateTimeOffset endTime, int maxTryout = 500)
 {
     try
     {
@@ -107,8 +107,8 @@ private MultivariateDetectionResult BatchDetect(AnomalyDetectorClient client, st
 
         Console.WriteLine("Start batch detection, this might take a few minutes...");
         MultivariateDetectionResult response = client.DetectMultivariateBatchAnomaly(modelId, request);
-        string resultId = response.ResultId;
-        Console.WriteLine($"result id is: {resultId}");
+        Guid resultId = response.ResultId;
+        Console.WriteLine($"result id is: {resultId.ToString()}");
 
         // get detection result
         MultivariateDetectionResult resultResponse = client.GetMultivariateBatchDetectionResult(resultId);