Package com.google.cloud.aiplatform.v1

Class PredictionServiceClient

java.lang.Object
com.google.cloud.aiplatform.v1.PredictionServiceClient
All Implemented Interfaces:
BackgroundResource, AutoCloseable
@Generated("by gapic-generator-java") public class PredictionServiceClient extends Object implements BackgroundResource
Service Description: A service for online predictions and explanations.

This class provides the ability to make remote calls to the backing service through method calls that map to API methods. Sample code to get started: 


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   EndpointName endpoint =
       EndpointName.ofProjectLocationEndpointName("[PROJECT]", "[LOCATION]", "[ENDPOINT]");
   List<Value> instances = new ArrayList<>();
   Value parameters = Value.newBuilder().setBoolValue(true).build();
   PredictResponse response = predictionServiceClient.predict(endpoint, instances, parameters);
 }

Note: close() needs to be called on the PredictionServiceClient object to clean up resources such as threads. In the example above, try-with-resources is used, which automatically calls close().

Methods
Method Description Method Variants

Predict

Perform an online prediction.

Request object method variants only take one parameter, a request object, which must be constructed before the call.

  • predict(PredictRequest request)

"Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method.

  • predict(EndpointName endpoint, List<Value> instances, Value parameters)

  • predict(String endpoint, List<Value> instances, Value parameters)

Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.

  • predictCallable()

RawPredict

Perform an online prediction with an arbitrary HTTP payload.

The response includes the following HTTP headers:

  • `X-Vertex-AI-Endpoint-Id`: ID of the [Endpoint][google.cloud.aiplatform.v1.Endpoint] that served this prediction.
  • `X-Vertex-AI-Deployed-Model-Id`: ID of the Endpoint's [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] that served this prediction.

Request object method variants only take one parameter, a request object, which must be constructed before the call.

  • rawPredict(RawPredictRequest request)

"Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method.

  • rawPredict(EndpointName endpoint, HttpBody httpBody)

  • rawPredict(String endpoint, HttpBody httpBody)

Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.

  • rawPredictCallable()

StreamRawPredict

Perform a streaming online prediction with an arbitrary HTTP payload.

Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.

  • streamRawPredictCallable()

DirectPredict

Perform an unary online prediction request to a gRPC model server for Vertex first-party products and frameworks.

Request object method variants only take one parameter, a request object, which must be constructed before the call.

  • directPredict(DirectPredictRequest request)

Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.

  • directPredictCallable()

DirectRawPredict

Perform an unary online prediction request to a gRPC model server for custom containers.

Request object method variants only take one parameter, a request object, which must be constructed before the call.

  • directRawPredict(DirectRawPredictRequest request)

Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.

  • directRawPredictCallable()

StreamDirectPredict

Perform a streaming online prediction request to a gRPC model server for Vertex first-party products and frameworks.

Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.

  • streamDirectPredictCallable()

StreamDirectRawPredict

Perform a streaming online prediction request to a gRPC model server for custom containers.

Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.

  • streamDirectRawPredictCallable()

StreamingPredict

Perform a streaming online prediction request for Vertex first-party products and frameworks.

Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.

  • streamingPredictCallable()

ServerStreamingPredict

Perform a server-side streaming online prediction request for Vertex LLM streaming.

Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.

  • serverStreamingPredictCallable()

StreamingRawPredict

Perform a streaming online prediction request through gRPC.

Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.

  • streamingRawPredictCallable()

Explain

Perform an online explanation.

If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is specified, the corresponding DeployModel must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is not specified, all DeployedModels must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated.

Request object method variants only take one parameter, a request object, which must be constructed before the call.

  • explain(ExplainRequest request)

"Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method.

  • explain(EndpointName endpoint, List<Value> instances, Value parameters, String deployedModelId)

  • explain(String endpoint, List<Value> instances, Value parameters, String deployedModelId)

Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.

  • explainCallable()

GenerateContent

Generate content with multimodal inputs.

Request object method variants only take one parameter, a request object, which must be constructed before the call.

  • generateContent(GenerateContentRequest request)

"Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method.

  • generateContent(String model, List<Content> contents)

Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.

  • generateContentCallable()

StreamGenerateContent

Generate content with multimodal inputs with streaming support.

Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.

  • streamGenerateContentCallable()

EmbedContent

Embed content with multimodal inputs.

Request object method variants only take one parameter, a request object, which must be constructed before the call.

  • embedContent(EmbedContentRequest request)

"Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method.

  • embedContent(EndpointName model, Content content)

  • embedContent(String model, Content content)

Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.

  • embedContentCallable()

ListLocations

Lists information about the supported locations for this service.

Request object method variants only take one parameter, a request object, which must be constructed before the call.

  • listLocations(ListLocationsRequest request)

Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.

  • listLocationsPagedCallable()

  • listLocationsCallable()

GetLocation

Gets information about a location.

Request object method variants only take one parameter, a request object, which must be constructed before the call.

  • getLocation(GetLocationRequest request)

Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.

  • getLocationCallable()

SetIamPolicy

Sets the access control policy on the specified resource. Replacesany existing policy.

Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED`errors.

Request object method variants only take one parameter, a request object, which must be constructed before the call.

  • setIamPolicy(SetIamPolicyRequest request)

Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.

  • setIamPolicyCallable()

GetIamPolicy

Gets the access control policy for a resource. Returns an empty policyif the resource exists and does not have a policy set.

Request object method variants only take one parameter, a request object, which must be constructed before the call.

  • getIamPolicy(GetIamPolicyRequest request)

Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.

  • getIamPolicyCallable()

TestIamPermissions

Returns permissions that a caller has on the specified resource. If theresource does not exist, this will return an empty set ofpermissions, not a `NOT_FOUND` error.

Note: This operation is designed to be used for buildingpermission-aware UIs and command-line tools, not for authorizationchecking. This operation may "fail open" without warning.

Request object method variants only take one parameter, a request object, which must be constructed before the call.

  • testIamPermissions(TestIamPermissionsRequest request)

Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.

  • testIamPermissionsCallable()

See the individual methods for example code.

Many parameters require resource names to be formatted in a particular way. To assist with these names, this class includes a format method for each type of name, and additionally a parse method to extract the individual identifiers contained within names that are returned.

This class can be customized by passing in a custom instance of PredictionServiceSettings to create(). For example:

To customize credentials: 


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 PredictionServiceSettings predictionServiceSettings =
     PredictionServiceSettings.newBuilder()
         .setCredentialsProvider(FixedCredentialsProvider.create(myCredentials))
         .build();
 PredictionServiceClient predictionServiceClient =
     PredictionServiceClient.create(predictionServiceSettings);

To customize the endpoint: 


 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 PredictionServiceSettings predictionServiceSettings =
     PredictionServiceSettings.newBuilder().setEndpoint(myEndpoint).build();
 PredictionServiceClient predictionServiceClient =
     PredictionServiceClient.create(predictionServiceSettings);

Please refer to the GitHub repository's samples for more quickstart code snippets.

  • Constructor Details

    • PredictionServiceClient

      protected PredictionServiceClient(PredictionServiceSettings settings) throws IOException
      Constructs an instance of PredictionServiceClient, using the given settings. This is protected so that it is easy to make a subclass, but otherwise, the static factory methods should be preferred.
      Throws:
      IOException

    • PredictionServiceClient

      protected PredictionServiceClient(PredictionServiceStub stub)

  • Method Details

    • create

      public static final PredictionServiceClient create() throws IOException
      Constructs an instance of PredictionServiceClient with default settings.
      Throws:
      IOException

    • create

      public static final PredictionServiceClient create(PredictionServiceSettings settings) throws IOException
      Constructs an instance of PredictionServiceClient, using the given settings. The channels are created based on the settings passed in, or defaults for any settings that are not set.
      Throws:
      IOException

    • create

      public static final PredictionServiceClient create(PredictionServiceStub stub)
      Constructs an instance of PredictionServiceClient, using the given stub for making calls. This is for advanced usage - prefer using create(PredictionServiceSettings).

    • getSettings

      public final PredictionServiceSettings getSettings()

    • getStub

      public PredictionServiceStub getStub()

    • predict

      public final PredictResponse predict(EndpointName endpoint, List<com.google.protobuf.Value> instances, com.google.protobuf.Value parameters)
      Perform an online prediction.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   EndpointName endpoint =
       EndpointName.ofProjectLocationEndpointName("[PROJECT]", "[LOCATION]", "[ENDPOINT]");
   List<Value> instances = new ArrayList<>();
   Value parameters = Value.newBuilder().setBoolValue(true).build();
   PredictResponse response = predictionServiceClient.predict(endpoint, instances, parameters);
 }
      Parameters:
      endpoint - Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
      instances - Required. The instances that are the input to the prediction call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the prediction call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].
      parameters - The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' [Model's ][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] [parameters_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri].
      Throws:
      ApiException - if the remote call fails

    • predict

      public final PredictResponse predict(String endpoint, List<com.google.protobuf.Value> instances, com.google.protobuf.Value parameters)
      Perform an online prediction.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   String endpoint =
       EndpointName.ofProjectLocationEndpointName("[PROJECT]", "[LOCATION]", "[ENDPOINT]")
           .toString();
   List<Value> instances = new ArrayList<>();
   Value parameters = Value.newBuilder().setBoolValue(true).build();
   PredictResponse response = predictionServiceClient.predict(endpoint, instances, parameters);
 }
      Parameters:
      endpoint - Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
      instances - Required. The instances that are the input to the prediction call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the prediction call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].
      parameters - The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' [Model's ][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] [parameters_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri].
      Throws:
      ApiException - if the remote call fails

    • predict

      public final PredictResponse predict(PredictRequest request)
      Perform an online prediction.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   PredictRequest request =
       PredictRequest.newBuilder()
           .setEndpoint(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .addAllInstances(new ArrayList<Value>())
           .setParameters(Value.newBuilder().setBoolValue(true).build())
           .putAllLabels(new HashMap<String, String>())
           .build();
   PredictResponse response = predictionServiceClient.predict(request);
 }
      Parameters:
      request - The request object containing all of the parameters for the API call.
      Throws:
      ApiException - if the remote call fails

    • predictCallable

      public final UnaryCallable<PredictRequest,PredictResponse> predictCallable()
      Perform an online prediction.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   PredictRequest request =
       PredictRequest.newBuilder()
           .setEndpoint(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .addAllInstances(new ArrayList<Value>())
           .setParameters(Value.newBuilder().setBoolValue(true).build())
           .putAllLabels(new HashMap<String, String>())
           .build();
   ApiFuture<PredictResponse> future =
       predictionServiceClient.predictCallable().futureCall(request);
   // Do something.
   PredictResponse response = future.get();
 }

    • rawPredict

      public final HttpBody rawPredict(EndpointName endpoint, HttpBody httpBody)
      Perform an online prediction with an arbitrary HTTP payload.

      The response includes the following HTTP headers:

      • `X-Vertex-AI-Endpoint-Id`: ID of the [Endpoint][google.cloud.aiplatform.v1.Endpoint] that served this prediction.
      • `X-Vertex-AI-Deployed-Model-Id`: ID of the Endpoint's [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] that served this prediction.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   EndpointName endpoint =
       EndpointName.ofProjectLocationEndpointName("[PROJECT]", "[LOCATION]", "[ENDPOINT]");
   HttpBody httpBody = HttpBody.newBuilder().build();
   HttpBody response = predictionServiceClient.rawPredict(endpoint, httpBody);
 }
      Parameters:
      endpoint - Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
      httpBody - The prediction input. Supports HTTP headers and arbitrary data payload.

      A [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] may have an upper limit on the number of instances it supports per request. When this limit it is exceeded for an AutoML model, the [RawPredict][google.cloud.aiplatform.v1.PredictionService.RawPredict] method returns an error. When this limit is exceeded for a custom-trained model, the behavior varies depending on the model.

      You can specify the schema for each instance in the [predict_schemata.instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri] field when you create a [Model][google.cloud.aiplatform.v1.Model]. This schema applies when you deploy the `Model` as a `DeployedModel` to an [Endpoint][google.cloud.aiplatform.v1.Endpoint] and use the `RawPredict` method.

      Throws:
      ApiException - if the remote call fails

    • rawPredict

      public final HttpBody rawPredict(String endpoint, HttpBody httpBody)
      Perform an online prediction with an arbitrary HTTP payload.

      The response includes the following HTTP headers:

      • `X-Vertex-AI-Endpoint-Id`: ID of the [Endpoint][google.cloud.aiplatform.v1.Endpoint] that served this prediction.
      • `X-Vertex-AI-Deployed-Model-Id`: ID of the Endpoint's [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] that served this prediction.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   String endpoint =
       EndpointName.ofProjectLocationEndpointName("[PROJECT]", "[LOCATION]", "[ENDPOINT]")
           .toString();
   HttpBody httpBody = HttpBody.newBuilder().build();
   HttpBody response = predictionServiceClient.rawPredict(endpoint, httpBody);
 }
      Parameters:
      endpoint - Required. The name of the Endpoint requested to serve the prediction. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
      httpBody - The prediction input. Supports HTTP headers and arbitrary data payload.

      A [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] may have an upper limit on the number of instances it supports per request. When this limit it is exceeded for an AutoML model, the [RawPredict][google.cloud.aiplatform.v1.PredictionService.RawPredict] method returns an error. When this limit is exceeded for a custom-trained model, the behavior varies depending on the model.

      You can specify the schema for each instance in the [predict_schemata.instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri] field when you create a [Model][google.cloud.aiplatform.v1.Model]. This schema applies when you deploy the `Model` as a `DeployedModel` to an [Endpoint][google.cloud.aiplatform.v1.Endpoint] and use the `RawPredict` method.

      Throws:
      ApiException - if the remote call fails

    • rawPredict

      public final HttpBody rawPredict(RawPredictRequest request)
      Perform an online prediction with an arbitrary HTTP payload.

      The response includes the following HTTP headers:

      • `X-Vertex-AI-Endpoint-Id`: ID of the [Endpoint][google.cloud.aiplatform.v1.Endpoint] that served this prediction.
      • `X-Vertex-AI-Deployed-Model-Id`: ID of the Endpoint's [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] that served this prediction.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   RawPredictRequest request =
       RawPredictRequest.newBuilder()
           .setEndpoint(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .setHttpBody(HttpBody.newBuilder().build())
           .build();
   HttpBody response = predictionServiceClient.rawPredict(request);
 }
      Parameters:
      request - The request object containing all of the parameters for the API call.
      Throws:
      ApiException - if the remote call fails

    • rawPredictCallable

      public final UnaryCallable<RawPredictRequest,HttpBody> rawPredictCallable()
      Perform an online prediction with an arbitrary HTTP payload.

      The response includes the following HTTP headers:

      • `X-Vertex-AI-Endpoint-Id`: ID of the [Endpoint][google.cloud.aiplatform.v1.Endpoint] that served this prediction.
      • `X-Vertex-AI-Deployed-Model-Id`: ID of the Endpoint's [DeployedModel][google.cloud.aiplatform.v1.DeployedModel] that served this prediction.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   RawPredictRequest request =
       RawPredictRequest.newBuilder()
           .setEndpoint(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .setHttpBody(HttpBody.newBuilder().build())
           .build();
   ApiFuture<HttpBody> future = predictionServiceClient.rawPredictCallable().futureCall(request);
   // Do something.
   HttpBody response = future.get();
 }

    • streamRawPredictCallable

      public final ServerStreamingCallable<StreamRawPredictRequest,HttpBody> streamRawPredictCallable()
      Perform a streaming online prediction with an arbitrary HTTP payload.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   StreamRawPredictRequest request =
       StreamRawPredictRequest.newBuilder()
           .setEndpoint(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .setHttpBody(HttpBody.newBuilder().build())
           .build();
   ServerStream<HttpBody> stream =
       predictionServiceClient.streamRawPredictCallable().call(request);
   for (HttpBody response : stream) {
     // Do something when a response is received.
   }
 }

    • directPredict

      public final DirectPredictResponse directPredict(DirectPredictRequest request)
      Perform an unary online prediction request to a gRPC model server for Vertex first-party products and frameworks.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   DirectPredictRequest request =
       DirectPredictRequest.newBuilder()
           .setEndpoint(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .addAllInputs(new ArrayList<Tensor>())
           .setParameters(Tensor.newBuilder().build())
           .build();
   DirectPredictResponse response = predictionServiceClient.directPredict(request);
 }
      Parameters:
      request - The request object containing all of the parameters for the API call.
      Throws:
      ApiException - if the remote call fails

    • directPredictCallable

      public final UnaryCallable<DirectPredictRequest,DirectPredictResponse> directPredictCallable()
      Perform an unary online prediction request to a gRPC model server for Vertex first-party products and frameworks.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   DirectPredictRequest request =
       DirectPredictRequest.newBuilder()
           .setEndpoint(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .addAllInputs(new ArrayList<Tensor>())
           .setParameters(Tensor.newBuilder().build())
           .build();
   ApiFuture<DirectPredictResponse> future =
       predictionServiceClient.directPredictCallable().futureCall(request);
   // Do something.
   DirectPredictResponse response = future.get();
 }

    • directRawPredict

      public final DirectRawPredictResponse directRawPredict(DirectRawPredictRequest request)
      Perform an unary online prediction request to a gRPC model server for custom containers.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   DirectRawPredictRequest request =
       DirectRawPredictRequest.newBuilder()
           .setEndpoint(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .setMethodName("methodName-723163380")
           .setInput(ByteString.EMPTY)
           .build();
   DirectRawPredictResponse response = predictionServiceClient.directRawPredict(request);
 }
      Parameters:
      request - The request object containing all of the parameters for the API call.
      Throws:
      ApiException - if the remote call fails

    • directRawPredictCallable

      public final UnaryCallable<DirectRawPredictRequest,DirectRawPredictResponse> directRawPredictCallable()
      Perform an unary online prediction request to a gRPC model server for custom containers.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   DirectRawPredictRequest request =
       DirectRawPredictRequest.newBuilder()
           .setEndpoint(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .setMethodName("methodName-723163380")
           .setInput(ByteString.EMPTY)
           .build();
   ApiFuture<DirectRawPredictResponse> future =
       predictionServiceClient.directRawPredictCallable().futureCall(request);
   // Do something.
   DirectRawPredictResponse response = future.get();
 }

    • streamDirectPredictCallable

      public final BidiStreamingCallable<StreamDirectPredictRequest,StreamDirectPredictResponse> streamDirectPredictCallable()
      Perform a streaming online prediction request to a gRPC model server for Vertex first-party products and frameworks.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   BidiStream<StreamDirectPredictRequest, StreamDirectPredictResponse> bidiStream =
       predictionServiceClient.streamDirectPredictCallable().call();
   StreamDirectPredictRequest request =
       StreamDirectPredictRequest.newBuilder()
           .setEndpoint(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .addAllInputs(new ArrayList<Tensor>())
           .setParameters(Tensor.newBuilder().build())
           .build();
   bidiStream.send(request);
   for (StreamDirectPredictResponse response : bidiStream) {
     // Do something when a response is received.
   }
 }

    • streamDirectRawPredictCallable

      public final BidiStreamingCallable<StreamDirectRawPredictRequest,StreamDirectRawPredictResponse> streamDirectRawPredictCallable()
      Perform a streaming online prediction request to a gRPC model server for custom containers.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   BidiStream<StreamDirectRawPredictRequest, StreamDirectRawPredictResponse> bidiStream =
       predictionServiceClient.streamDirectRawPredictCallable().call();
   StreamDirectRawPredictRequest request =
       StreamDirectRawPredictRequest.newBuilder()
           .setEndpoint(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .setMethodName("methodName-723163380")
           .setInput(ByteString.EMPTY)
           .build();
   bidiStream.send(request);
   for (StreamDirectRawPredictResponse response : bidiStream) {
     // Do something when a response is received.
   }
 }

    • streamingPredictCallable

      public final BidiStreamingCallable<StreamingPredictRequest,StreamingPredictResponse> streamingPredictCallable()
      Perform a streaming online prediction request for Vertex first-party products and frameworks.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   BidiStream<StreamingPredictRequest, StreamingPredictResponse> bidiStream =
       predictionServiceClient.streamingPredictCallable().call();
   StreamingPredictRequest request =
       StreamingPredictRequest.newBuilder()
           .setEndpoint(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .addAllInputs(new ArrayList<Tensor>())
           .setParameters(Tensor.newBuilder().build())
           .build();
   bidiStream.send(request);
   for (StreamingPredictResponse response : bidiStream) {
     // Do something when a response is received.
   }
 }

    • serverStreamingPredictCallable

      public final ServerStreamingCallable<StreamingPredictRequest,StreamingPredictResponse> serverStreamingPredictCallable()
      Perform a server-side streaming online prediction request for Vertex LLM streaming.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   StreamingPredictRequest request =
       StreamingPredictRequest.newBuilder()
           .setEndpoint(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .addAllInputs(new ArrayList<Tensor>())
           .setParameters(Tensor.newBuilder().build())
           .build();
   ServerStream<StreamingPredictResponse> stream =
       predictionServiceClient.serverStreamingPredictCallable().call(request);
   for (StreamingPredictResponse response : stream) {
     // Do something when a response is received.
   }
 }

    • streamingRawPredictCallable

      public final BidiStreamingCallable<StreamingRawPredictRequest,StreamingRawPredictResponse> streamingRawPredictCallable()
      Perform a streaming online prediction request through gRPC.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   BidiStream<StreamingRawPredictRequest, StreamingRawPredictResponse> bidiStream =
       predictionServiceClient.streamingRawPredictCallable().call();
   StreamingRawPredictRequest request =
       StreamingRawPredictRequest.newBuilder()
           .setEndpoint(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .setMethodName("methodName-723163380")
           .setInput(ByteString.EMPTY)
           .build();
   bidiStream.send(request);
   for (StreamingRawPredictResponse response : bidiStream) {
     // Do something when a response is received.
   }
 }

    • explain

      public final ExplainResponse explain(EndpointName endpoint, List<com.google.protobuf.Value> instances, com.google.protobuf.Value parameters, String deployedModelId)
      Perform an online explanation.

      If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is specified, the corresponding DeployModel must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is not specified, all DeployedModels must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   EndpointName endpoint =
       EndpointName.ofProjectLocationEndpointName("[PROJECT]", "[LOCATION]", "[ENDPOINT]");
   List<Value> instances = new ArrayList<>();
   Value parameters = Value.newBuilder().setBoolValue(true).build();
   String deployedModelId = "deployedModelId-1817547906";
   ExplainResponse response =
       predictionServiceClient.explain(endpoint, instances, parameters, deployedModelId);
 }
      Parameters:
      endpoint - Required. The name of the Endpoint requested to serve the explanation. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
      instances - Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].
      parameters - The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' [Model's ][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] [parameters_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri].
      deployedModelId - If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding [Endpoint.traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split].
      Throws:
      ApiException - if the remote call fails

    • explain

      public final ExplainResponse explain(String endpoint, List<com.google.protobuf.Value> instances, com.google.protobuf.Value parameters, String deployedModelId)
      Perform an online explanation.

      If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is specified, the corresponding DeployModel must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is not specified, all DeployedModels must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   String endpoint =
       EndpointName.ofProjectLocationEndpointName("[PROJECT]", "[LOCATION]", "[ENDPOINT]")
           .toString();
   List<Value> instances = new ArrayList<>();
   Value parameters = Value.newBuilder().setBoolValue(true).build();
   String deployedModelId = "deployedModelId-1817547906";
   ExplainResponse response =
       predictionServiceClient.explain(endpoint, instances, parameters, deployedModelId);
 }
      Parameters:
      endpoint - Required. The name of the Endpoint requested to serve the explanation. Format: `projects/{project}/locations/{location}/endpoints/{endpoint}`
      instances - Required. The instances that are the input to the explanation call. A DeployedModel may have an upper limit on the number of instances it supports per request, and when it is exceeded the explanation call errors in case of AutoML Models, or, in case of customer created Models, the behaviour is as documented by that Model. The schema of any single instance may be specified via Endpoint's DeployedModels' [Model's][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] [instance_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.instance_schema_uri].
      parameters - The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' [Model's ][google.cloud.aiplatform.v1.DeployedModel.model] [PredictSchemata's][google.cloud.aiplatform.v1.Model.predict_schemata] [parameters_schema_uri][google.cloud.aiplatform.v1.PredictSchemata.parameters_schema_uri].
      deployedModelId - If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding [Endpoint.traffic_split][google.cloud.aiplatform.v1.Endpoint.traffic_split].
      Throws:
      ApiException - if the remote call fails

    • explain

      public final ExplainResponse explain(ExplainRequest request)
      Perform an online explanation.

      If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is specified, the corresponding DeployModel must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is not specified, all DeployedModels must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   ExplainRequest request =
       ExplainRequest.newBuilder()
           .setEndpoint(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .addAllInstances(new ArrayList<Value>())
           .setParameters(Value.newBuilder().setBoolValue(true).build())
           .setExplanationSpecOverride(ExplanationSpecOverride.newBuilder().build())
           .setDeployedModelId("deployedModelId-1817547906")
           .build();
   ExplainResponse response = predictionServiceClient.explain(request);
 }
      Parameters:
      request - The request object containing all of the parameters for the API call.
      Throws:
      ApiException - if the remote call fails

    • explainCallable

      public final UnaryCallable<ExplainRequest,ExplainResponse> explainCallable()
      Perform an online explanation.

      If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is specified, the corresponding DeployModel must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated. If [deployed_model_id][google.cloud.aiplatform.v1.ExplainRequest.deployed_model_id] is not specified, all DeployedModels must have [explanation_spec][google.cloud.aiplatform.v1.DeployedModel.explanation_spec] populated.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   ExplainRequest request =
       ExplainRequest.newBuilder()
           .setEndpoint(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .addAllInstances(new ArrayList<Value>())
           .setParameters(Value.newBuilder().setBoolValue(true).build())
           .setExplanationSpecOverride(ExplanationSpecOverride.newBuilder().build())
           .setDeployedModelId("deployedModelId-1817547906")
           .build();
   ApiFuture<ExplainResponse> future =
       predictionServiceClient.explainCallable().futureCall(request);
   // Do something.
   ExplainResponse response = future.get();
 }

    • generateContent

      public final GenerateContentResponse generateContent(String model, List<Content> contents)
      Generate content with multimodal inputs.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   String model = "model104069929";
   List<Content> contents = new ArrayList<>();
   GenerateContentResponse response = predictionServiceClient.generateContent(model, contents);
 }
      Parameters:
      model - Required. The fully qualified name of the publisher model or tuned model endpoint to use.

      Publisher model format: `projects/{project}/locations/{location}/publishers/*/models/*`

      Tuned model endpoint format: `projects/{project}/locations/{location}/endpoints/{endpoint}`

      contents - Required. The content of the current conversation with the model.

      For single-turn queries, this is a single instance. For multi-turn queries, this is a repeated field that contains conversation history + latest request.

      Throws:
      ApiException - if the remote call fails

    • generateContent

      public final GenerateContentResponse generateContent(GenerateContentRequest request)
      Generate content with multimodal inputs.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   GenerateContentRequest request =
       GenerateContentRequest.newBuilder()
           .setModel("model104069929")
           .addAllContents(new ArrayList<Content>())
           .setSystemInstruction(Content.newBuilder().build())
           .setCachedContent(
               CachedContentName.of("[PROJECT]", "[LOCATION]", "[CACHED_CONTENT]").toString())
           .addAllTools(new ArrayList<Tool>())
           .setToolConfig(ToolConfig.newBuilder().build())
           .putAllLabels(new HashMap<String, String>())
           .addAllSafetySettings(new ArrayList<SafetySetting>())
           .setModelArmorConfig(ModelArmorConfig.newBuilder().build())
           .setGenerationConfig(GenerationConfig.newBuilder().build())
           .build();
   GenerateContentResponse response = predictionServiceClient.generateContent(request);
 }
      Parameters:
      request - The request object containing all of the parameters for the API call.
      Throws:
      ApiException - if the remote call fails

    • generateContentCallable

      public final UnaryCallable<GenerateContentRequest,GenerateContentResponse> generateContentCallable()
      Generate content with multimodal inputs.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   GenerateContentRequest request =
       GenerateContentRequest.newBuilder()
           .setModel("model104069929")
           .addAllContents(new ArrayList<Content>())
           .setSystemInstruction(Content.newBuilder().build())
           .setCachedContent(
               CachedContentName.of("[PROJECT]", "[LOCATION]", "[CACHED_CONTENT]").toString())
           .addAllTools(new ArrayList<Tool>())
           .setToolConfig(ToolConfig.newBuilder().build())
           .putAllLabels(new HashMap<String, String>())
           .addAllSafetySettings(new ArrayList<SafetySetting>())
           .setModelArmorConfig(ModelArmorConfig.newBuilder().build())
           .setGenerationConfig(GenerationConfig.newBuilder().build())
           .build();
   ApiFuture<GenerateContentResponse> future =
       predictionServiceClient.generateContentCallable().futureCall(request);
   // Do something.
   GenerateContentResponse response = future.get();
 }

    • streamGenerateContentCallable

      public final ServerStreamingCallable<GenerateContentRequest,GenerateContentResponse> streamGenerateContentCallable()
      Generate content with multimodal inputs with streaming support.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   GenerateContentRequest request =
       GenerateContentRequest.newBuilder()
           .setModel("model104069929")
           .addAllContents(new ArrayList<Content>())
           .setSystemInstruction(Content.newBuilder().build())
           .setCachedContent(
               CachedContentName.of("[PROJECT]", "[LOCATION]", "[CACHED_CONTENT]").toString())
           .addAllTools(new ArrayList<Tool>())
           .setToolConfig(ToolConfig.newBuilder().build())
           .putAllLabels(new HashMap<String, String>())
           .addAllSafetySettings(new ArrayList<SafetySetting>())
           .setModelArmorConfig(ModelArmorConfig.newBuilder().build())
           .setGenerationConfig(GenerationConfig.newBuilder().build())
           .build();
   ServerStream<GenerateContentResponse> stream =
       predictionServiceClient.streamGenerateContentCallable().call(request);
   for (GenerateContentResponse response : stream) {
     // Do something when a response is received.
   }
 }

    • embedContent

      public final EmbedContentResponse embedContent(EndpointName model, Content content)
      Embed content with multimodal inputs.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   EndpointName model =
       EndpointName.ofProjectLocationPublisherModelName(
           "[PROJECT]", "[LOCATION]", "[PUBLISHER]", "[MODEL]");
   Content content = Content.newBuilder().build();
   EmbedContentResponse response = predictionServiceClient.embedContent(model, content);
 }
      Parameters:
      model - Required. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*`
      content - Required. Input content to be embedded.
      Throws:
      ApiException - if the remote call fails

    • embedContent

      public final EmbedContentResponse embedContent(String model, Content content)
      Embed content with multimodal inputs.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   String model =
       EndpointName.ofProjectLocationEndpointName("[PROJECT]", "[LOCATION]", "[ENDPOINT]")
           .toString();
   Content content = Content.newBuilder().build();
   EmbedContentResponse response = predictionServiceClient.embedContent(model, content);
 }
      Parameters:
      model - Required. The name of the publisher model requested to serve the prediction. Format: `projects/{project}/locations/{location}/publishers/*/models/*`
      content - Required. Input content to be embedded.
      Throws:
      ApiException - if the remote call fails

    • embedContent

      public final EmbedContentResponse embedContent(EmbedContentRequest request)
      Embed content with multimodal inputs.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   EmbedContentRequest request =
       EmbedContentRequest.newBuilder()
           .setModel(
               EndpointName.ofProjectLocationPublisherModelName(
                       "[PROJECT]", "[LOCATION]", "[PUBLISHER]", "[MODEL]")
                   .toString())
           .setContent(Content.newBuilder().build())
           .setTitle("title110371416")
           .setOutputDimensionality(-495931909)
           .setAutoTruncate(true)
           .setEmbedContentConfig(EmbedContentRequest.EmbedContentConfig.newBuilder().build())
           .build();
   EmbedContentResponse response = predictionServiceClient.embedContent(request);
 }
      Parameters:
      request - The request object containing all of the parameters for the API call.
      Throws:
      ApiException - if the remote call fails

    • embedContentCallable

      public final UnaryCallable<EmbedContentRequest,EmbedContentResponse> embedContentCallable()
      Embed content with multimodal inputs.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   EmbedContentRequest request =
       EmbedContentRequest.newBuilder()
           .setModel(
               EndpointName.ofProjectLocationPublisherModelName(
                       "[PROJECT]", "[LOCATION]", "[PUBLISHER]", "[MODEL]")
                   .toString())
           .setContent(Content.newBuilder().build())
           .setTitle("title110371416")
           .setOutputDimensionality(-495931909)
           .setAutoTruncate(true)
           .setEmbedContentConfig(EmbedContentRequest.EmbedContentConfig.newBuilder().build())
           .build();
   ApiFuture<EmbedContentResponse> future =
       predictionServiceClient.embedContentCallable().futureCall(request);
   // Do something.
   EmbedContentResponse response = future.get();
 }

    • listLocations

      public final PredictionServiceClient.ListLocationsPagedResponse listLocations(ListLocationsRequest request)
      Lists information about the supported locations for this service.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   ListLocationsRequest request =
       ListLocationsRequest.newBuilder()
           .setName("name3373707")
           .setFilter("filter-1274492040")
           .setPageSize(883849137)
           .setPageToken("pageToken873572522")
           .build();
   for (Location element : predictionServiceClient.listLocations(request).iterateAll()) {
     // doThingsWith(element);
   }
 }
      Parameters:
      request - The request object containing all of the parameters for the API call.
      Throws:
      ApiException - if the remote call fails

    • listLocationsPagedCallable

      public final UnaryCallable<ListLocationsRequest,PredictionServiceClient.ListLocationsPagedResponse> listLocationsPagedCallable()
      Lists information about the supported locations for this service.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   ListLocationsRequest request =
       ListLocationsRequest.newBuilder()
           .setName("name3373707")
           .setFilter("filter-1274492040")
           .setPageSize(883849137)
           .setPageToken("pageToken873572522")
           .build();
   ApiFuture<Location> future =
       predictionServiceClient.listLocationsPagedCallable().futureCall(request);
   // Do something.
   for (Location element : future.get().iterateAll()) {
     // doThingsWith(element);
   }
 }

    • listLocationsCallable

      public final UnaryCallable<ListLocationsRequest,ListLocationsResponse> listLocationsCallable()
      Lists information about the supported locations for this service.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   ListLocationsRequest request =
       ListLocationsRequest.newBuilder()
           .setName("name3373707")
           .setFilter("filter-1274492040")
           .setPageSize(883849137)
           .setPageToken("pageToken873572522")
           .build();
   while (true) {
     ListLocationsResponse response =
         predictionServiceClient.listLocationsCallable().call(request);
     for (Location element : response.getLocationsList()) {
       // doThingsWith(element);
     }
     String nextPageToken = response.getNextPageToken();
     if (!Strings.isNullOrEmpty(nextPageToken)) {
       request = request.toBuilder().setPageToken(nextPageToken).build();
     } else {
       break;
     }
   }
 }

    • getLocation

      public final Location getLocation(GetLocationRequest request)
      Gets information about a location.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   GetLocationRequest request = GetLocationRequest.newBuilder().setName("name3373707").build();
   Location response = predictionServiceClient.getLocation(request);
 }
      Parameters:
      request - The request object containing all of the parameters for the API call.
      Throws:
      ApiException - if the remote call fails

    • getLocationCallable

      public final UnaryCallable<GetLocationRequest,Location> getLocationCallable()
      Gets information about a location.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   GetLocationRequest request = GetLocationRequest.newBuilder().setName("name3373707").build();
   ApiFuture<Location> future =
       predictionServiceClient.getLocationCallable().futureCall(request);
   // Do something.
   Location response = future.get();
 }

    • setIamPolicy

      public final Policy setIamPolicy(SetIamPolicyRequest request)
      Sets the access control policy on the specified resource. Replacesany existing policy.

      Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED`errors.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   SetIamPolicyRequest request =
       SetIamPolicyRequest.newBuilder()
           .setResource(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .setPolicy(Policy.newBuilder().build())
           .setUpdateMask(FieldMask.newBuilder().build())
           .build();
   Policy response = predictionServiceClient.setIamPolicy(request);
 }
      Parameters:
      request - The request object containing all of the parameters for the API call.
      Throws:
      ApiException - if the remote call fails

    • setIamPolicyCallable

      public final UnaryCallable<SetIamPolicyRequest,Policy> setIamPolicyCallable()
      Sets the access control policy on the specified resource. Replacesany existing policy.

      Can return `NOT_FOUND`, `INVALID_ARGUMENT`, and `PERMISSION_DENIED`errors.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   SetIamPolicyRequest request =
       SetIamPolicyRequest.newBuilder()
           .setResource(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .setPolicy(Policy.newBuilder().build())
           .setUpdateMask(FieldMask.newBuilder().build())
           .build();
   ApiFuture<Policy> future = predictionServiceClient.setIamPolicyCallable().futureCall(request);
   // Do something.
   Policy response = future.get();
 }

    • getIamPolicy

      public final Policy getIamPolicy(GetIamPolicyRequest request)
      Gets the access control policy for a resource. Returns an empty policyif the resource exists and does not have a policy set.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   GetIamPolicyRequest request =
       GetIamPolicyRequest.newBuilder()
           .setResource(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .setOptions(GetPolicyOptions.newBuilder().build())
           .build();
   Policy response = predictionServiceClient.getIamPolicy(request);
 }
      Parameters:
      request - The request object containing all of the parameters for the API call.
      Throws:
      ApiException - if the remote call fails

    • getIamPolicyCallable

      public final UnaryCallable<GetIamPolicyRequest,Policy> getIamPolicyCallable()
      Gets the access control policy for a resource. Returns an empty policyif the resource exists and does not have a policy set.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   GetIamPolicyRequest request =
       GetIamPolicyRequest.newBuilder()
           .setResource(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .setOptions(GetPolicyOptions.newBuilder().build())
           .build();
   ApiFuture<Policy> future = predictionServiceClient.getIamPolicyCallable().futureCall(request);
   // Do something.
   Policy response = future.get();
 }

    • testIamPermissions

      public final TestIamPermissionsResponse testIamPermissions(TestIamPermissionsRequest request)
      Returns permissions that a caller has on the specified resource. If theresource does not exist, this will return an empty set ofpermissions, not a `NOT_FOUND` error.

      Note: This operation is designed to be used for buildingpermission-aware UIs and command-line tools, not for authorizationchecking. This operation may "fail open" without warning.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   TestIamPermissionsRequest request =
       TestIamPermissionsRequest.newBuilder()
           .setResource(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .addAllPermissions(new ArrayList<String>())
           .build();
   TestIamPermissionsResponse response = predictionServiceClient.testIamPermissions(request);
 }
      Parameters:
      request - The request object containing all of the parameters for the API call.
      Throws:
      ApiException - if the remote call fails

    • testIamPermissionsCallable

      public final UnaryCallable<TestIamPermissionsRequest,TestIamPermissionsResponse> testIamPermissionsCallable()
      Returns permissions that a caller has on the specified resource. If theresource does not exist, this will return an empty set ofpermissions, not a `NOT_FOUND` error.

      Note: This operation is designed to be used for buildingpermission-aware UIs and command-line tools, not for authorizationchecking. This operation may "fail open" without warning.

      Sample code: 

      
 // This snippet has been automatically generated and should be regarded as a code template only.
 // It will require modifications to work:
 // - It may require correct/in-range values for request initialization.
 // - It may require specifying regional endpoints when creating the service client as shown in
 // https://cloud.google.com/java/docs/setup#configure_endpoints_for_the_client_library
 try (PredictionServiceClient predictionServiceClient = PredictionServiceClient.create()) {
   TestIamPermissionsRequest request =
       TestIamPermissionsRequest.newBuilder()
           .setResource(
               EndpointName.ofProjectLocationEndpointName(
                       "[PROJECT]", "[LOCATION]", "[ENDPOINT]")
                   .toString())
           .addAllPermissions(new ArrayList<String>())
           .build();
   ApiFuture<TestIamPermissionsResponse> future =
       predictionServiceClient.testIamPermissionsCallable().futureCall(request);
   // Do something.
   TestIamPermissionsResponse response = future.get();
 }

    • close

      public final void close()
      Specified by:
      close in interface AutoCloseable

    • shutdown

      public void shutdown()
      Specified by:
      shutdown in interface BackgroundResource

    • isShutdown

      public boolean isShutdown()
      Specified by:
      isShutdown in interface BackgroundResource

    • isTerminated

      public boolean isTerminated()
      Specified by:
      isTerminated in interface BackgroundResource

    • shutdownNow

      public void shutdownNow()
      Specified by:
      shutdownNow in interface BackgroundResource

    • awaitTermination

      public boolean awaitTermination(long duration, TimeUnit unit) throws InterruptedException
      Specified by:
      awaitTermination in interface BackgroundResource
      Throws:
      InterruptedException