feat(aiplatform): update the api

#### aiplatform:v1

The following keys were deleted:
- schemas.GoogleCloudAiplatformV1GenerationConfig.properties.tokenResolution.type (Total Keys: 1)

The following keys were added:
- resources.projects.resources.locations.resources.reasoningEngines.methods.streamQuery (Total Keys: 12)
- schemas.GoogleCloudAiplatformV1GenerationConfig.properties.mediaResolution.type (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1ModelContainerSpec.properties.livenessProbe.$ref (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1Probe.properties.grpc.$ref (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1Probe.properties.httpGet.$ref (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1Probe.properties.tcpSocket.$ref (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1ProbeGrpcAction (Total Keys: 5)
- schemas.GoogleCloudAiplatformV1ProbeHttpGetAction (Total Keys: 9)
- schemas.GoogleCloudAiplatformV1ProbeHttpHeader (Total Keys: 4)
- schemas.GoogleCloudAiplatformV1ProbeTcpSocketAction (Total Keys: 5)
- schemas.GoogleCloudAiplatformV1StreamQueryReasoningEngineRequest (Total Keys: 5)

The following keys were changed:
- endpoints (Total Keys: 1)

#### aiplatform:v1beta1

The following keys were deleted:
- schemas.GoogleCloudAiplatformV1beta1GenerationConfig.properties.tokenResolution.type (Total Keys: 1)

The following keys were added:
- resources.projects.resources.locations.resources.featureGroups.methods.getIamPolicy (Total Keys: 14)
- resources.projects.resources.locations.resources.featureGroups.methods.setIamPolicy (Total Keys: 12)
- resources.projects.resources.locations.resources.featureGroups.methods.testIamPermissions (Total Keys: 14)
- schemas.GoogleCloudAiplatformV1beta1AuthConfigApiKeyConfig.properties.apiKeyString.type (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1GenerationConfig.properties.mediaResolution.type (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1ModelContainerSpec.properties.livenessProbe.$ref (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1Probe.properties.grpc.$ref (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1Probe.properties.httpGet.$ref (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1Probe.properties.tcpSocket.$ref (Total Keys: 1)
- schemas.GoogleCloudAiplatformV1beta1ProbeGrpcAction (Total Keys: 5)
- schemas.GoogleCloudAiplatformV1beta1ProbeHttpGetAction (Total Keys: 9)
- schemas.GoogleCloudAiplatformV1beta1ProbeHttpHeader (Total Keys: 4)
- schemas.GoogleCloudAiplatformV1beta1ProbeTcpSocketAction (Total Keys: 5)

The following keys were changed:
- endpoints (Total Keys: 1)

docs/dyn/aiplatform_v1.datasets.html

@@ -130,7 +130,7 @@ <h3>Method Details</h3>
   &quot;metadataArtifact&quot;: &quot;A String&quot;, # Output only. The resource name of the Artifact that was created in MetadataStore when creating the Dataset. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
   &quot;metadataSchemaUri&quot;: &quot;A String&quot;, # Required. Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/.
   &quot;modelReference&quot;: &quot;A String&quot;, # Optional. Reference to the public base model last used by the dataset. Only set for prompt datasets.
-  &quot;name&quot;: &quot;A String&quot;, # Output only. Identifier. The resource name of the Dataset.
+  &quot;name&quot;: &quot;A String&quot;, # Output only. Identifier. The resource name of the Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`
   &quot;satisfiesPzi&quot;: True or False, # Output only. Reserved for future use.
   &quot;satisfiesPzs&quot;: True or False, # Output only. Reserved for future use.
   &quot;savedQueries&quot;: [ # All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec.
@@ -246,7 +246,7 @@ <h3>Method Details</h3>
   &quot;metadataArtifact&quot;: &quot;A String&quot;, # Output only. The resource name of the Artifact that was created in MetadataStore when creating the Dataset. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
   &quot;metadataSchemaUri&quot;: &quot;A String&quot;, # Required. Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/.
   &quot;modelReference&quot;: &quot;A String&quot;, # Optional. Reference to the public base model last used by the dataset. Only set for prompt datasets.
-  &quot;name&quot;: &quot;A String&quot;, # Output only. Identifier. The resource name of the Dataset.
+  &quot;name&quot;: &quot;A String&quot;, # Output only. Identifier. The resource name of the Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`
   &quot;satisfiesPzi&quot;: True or False, # Output only. Reserved for future use.
   &quot;satisfiesPzs&quot;: True or False, # Output only. Reserved for future use.
   &quot;savedQueries&quot;: [ # All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec.
@@ -304,7 +304,7 @@ <h3>Method Details</h3>
       &quot;metadataArtifact&quot;: &quot;A String&quot;, # Output only. The resource name of the Artifact that was created in MetadataStore when creating the Dataset. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
       &quot;metadataSchemaUri&quot;: &quot;A String&quot;, # Required. Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/.
       &quot;modelReference&quot;: &quot;A String&quot;, # Optional. Reference to the public base model last used by the dataset. Only set for prompt datasets.
-      &quot;name&quot;: &quot;A String&quot;, # Output only. Identifier. The resource name of the Dataset.
+      &quot;name&quot;: &quot;A String&quot;, # Output only. Identifier. The resource name of the Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`
       &quot;satisfiesPzi&quot;: True or False, # Output only. Reserved for future use.
       &quot;satisfiesPzs&quot;: True or False, # Output only. Reserved for future use.
       &quot;savedQueries&quot;: [ # All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec.
@@ -347,7 +347,7 @@ <h3>Method Details</h3>
   <pre>Updates a Dataset.
 
 Args:
-  name: string, Output only. Identifier. The resource name of the Dataset. (required)
+  name: string, Output only. Identifier. The resource name of the Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}` (required)
   body: object, The request body.
     The object takes the form of:
 
@@ -367,7 +367,7 @@ <h3>Method Details</h3>
   &quot;metadataArtifact&quot;: &quot;A String&quot;, # Output only. The resource name of the Artifact that was created in MetadataStore when creating the Dataset. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
   &quot;metadataSchemaUri&quot;: &quot;A String&quot;, # Required. Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/.
   &quot;modelReference&quot;: &quot;A String&quot;, # Optional. Reference to the public base model last used by the dataset. Only set for prompt datasets.
-  &quot;name&quot;: &quot;A String&quot;, # Output only. Identifier. The resource name of the Dataset.
+  &quot;name&quot;: &quot;A String&quot;, # Output only. Identifier. The resource name of the Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`
   &quot;satisfiesPzi&quot;: True or False, # Output only. Reserved for future use.
   &quot;satisfiesPzs&quot;: True or False, # Output only. Reserved for future use.
   &quot;savedQueries&quot;: [ # All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec.
@@ -412,7 +412,7 @@ <h3>Method Details</h3>
   &quot;metadataArtifact&quot;: &quot;A String&quot;, # Output only. The resource name of the Artifact that was created in MetadataStore when creating the Dataset. The Artifact resource name pattern is `projects/{project}/locations/{location}/metadataStores/{metadata_store}/artifacts/{artifact}`.
   &quot;metadataSchemaUri&quot;: &quot;A String&quot;, # Required. Points to a YAML file stored on Google Cloud Storage describing additional information about the Dataset. The schema is defined as an OpenAPI 3.0.2 Schema Object. The schema files that can be used here are found in gs://google-cloud-aiplatform/schema/dataset/metadata/.
   &quot;modelReference&quot;: &quot;A String&quot;, # Optional. Reference to the public base model last used by the dataset. Only set for prompt datasets.
-  &quot;name&quot;: &quot;A String&quot;, # Output only. Identifier. The resource name of the Dataset.
+  &quot;name&quot;: &quot;A String&quot;, # Output only. Identifier. The resource name of the Dataset. Format: `projects/{project}/locations/{location}/datasets/{dataset}`
   &quot;satisfiesPzi&quot;: True or False, # Output only. Reserved for future use.
   &quot;satisfiesPzs&quot;: True or False, # Output only. Reserved for future use.
   &quot;savedQueries&quot;: [ # All SavedQueries belong to the Dataset will be returned in List/Get Dataset response. The annotation_specs field will not be populated except for UI cases which will only use annotation_spec_count. In CreateDataset request, a SavedQuery is created together if this field is set, up to one SavedQuery can be set in CreateDatasetRequest. The SavedQuery should not contain any AnnotationSpec.

docs/dyn/aiplatform_v1.endpoints.html

@@ -218,6 +218,7 @@ <h3>Method Details</h3>
     &quot;frequencyPenalty&quot;: 3.14, # Optional. Frequency penalties.
     &quot;logprobs&quot;: 42, # Optional. Logit probabilities.
     &quot;maxOutputTokens&quot;: 42, # Optional. The maximum number of output tokens to generate per message.
+    &quot;mediaResolution&quot;: &quot;A String&quot;, # Optional. If specified, the media resolution specified will be used.
     &quot;presencePenalty&quot;: 3.14, # Optional. Positive penalties.
     &quot;responseLogprobs&quot;: True or False, # Optional. If true, export the logprobs results in response.
     &quot;responseMimeType&quot;: &quot;A String&quot;, # Optional. Output response mimetype of the generated candidate text. Supported mimetype: - `text/plain`: (default) Text output. - `application/json`: JSON response in the candidates. The model needs to be prompted to output the appropriate response type, otherwise the behavior is undefined. This is a preview feature.
@@ -278,7 +279,6 @@ <h3>Method Details</h3>
       &quot;A String&quot;,
     ],
     &quot;temperature&quot;: 3.14, # Optional. Controls the randomness of predictions.
-    &quot;tokenResolution&quot;: &quot;A String&quot;, # Optional. If specified, the token resolution specified will be used.
     &quot;topK&quot;: 3.14, # Optional. If specified, top-k sampling will be used.
     &quot;topP&quot;: 3.14, # Optional. If specified, nucleus sampling will be used.
   },
@@ -497,6 +497,7 @@ <h3>Method Details</h3>
     &quot;frequencyPenalty&quot;: 3.14, # Optional. Frequency penalties.
     &quot;logprobs&quot;: 42, # Optional. Logit probabilities.
     &quot;maxOutputTokens&quot;: 42, # Optional. The maximum number of output tokens to generate per message.
+    &quot;mediaResolution&quot;: &quot;A String&quot;, # Optional. If specified, the media resolution specified will be used.
     &quot;presencePenalty&quot;: 3.14, # Optional. Positive penalties.
     &quot;responseLogprobs&quot;: True or False, # Optional. If true, export the logprobs results in response.
     &quot;responseMimeType&quot;: &quot;A String&quot;, # Optional. Output response mimetype of the generated candidate text. Supported mimetype: - `text/plain`: (default) Text output. - `application/json`: JSON response in the candidates. The model needs to be prompted to output the appropriate response type, otherwise the behavior is undefined. This is a preview feature.
@@ -557,7 +558,6 @@ <h3>Method Details</h3>
       &quot;A String&quot;,
     ],
     &quot;temperature&quot;: 3.14, # Optional. Controls the randomness of predictions.
-    &quot;tokenResolution&quot;: &quot;A String&quot;, # Optional. If specified, the token resolution specified will be used.
     &quot;topK&quot;: 3.14, # Optional. If specified, top-k sampling will be used.
     &quot;topP&quot;: 3.14, # Optional. If specified, nucleus sampling will be used.
   },
@@ -936,6 +936,7 @@ <h3>Method Details</h3>
     &quot;frequencyPenalty&quot;: 3.14, # Optional. Frequency penalties.
     &quot;logprobs&quot;: 42, # Optional. Logit probabilities.
     &quot;maxOutputTokens&quot;: 42, # Optional. The maximum number of output tokens to generate per message.
+    &quot;mediaResolution&quot;: &quot;A String&quot;, # Optional. If specified, the media resolution specified will be used.
     &quot;presencePenalty&quot;: 3.14, # Optional. Positive penalties.
     &quot;responseLogprobs&quot;: True or False, # Optional. If true, export the logprobs results in response.
     &quot;responseMimeType&quot;: &quot;A String&quot;, # Optional. Output response mimetype of the generated candidate text. Supported mimetype: - `text/plain`: (default) Text output. - `application/json`: JSON response in the candidates. The model needs to be prompted to output the appropriate response type, otherwise the behavior is undefined. This is a preview feature.
@@ -996,7 +997,6 @@ <h3>Method Details</h3>
       &quot;A String&quot;,
     ],
     &quot;temperature&quot;: 3.14, # Optional. Controls the randomness of predictions.
-    &quot;tokenResolution&quot;: &quot;A String&quot;, # Optional. If specified, the token resolution specified will be used.
     &quot;topK&quot;: 3.14, # Optional. If specified, top-k sampling will be used.
     &quot;topP&quot;: 3.14, # Optional. If specified, nucleus sampling will be used.
   },