- 3.49.0 (latest)
- 3.48.0
- 3.47.0
- 3.46.0
- 3.45.0
- 3.44.0
- 3.43.0
- 3.42.0
- 3.41.0
- 3.40.0
- 3.38.0
- 3.37.0
- 3.36.0
- 3.35.0
- 3.34.0
- 3.33.0
- 3.32.0
- 3.31.0
- 3.30.0
- 3.29.0
- 3.28.0
- 3.25.0
- 3.24.0
- 3.23.0
- 3.22.0
- 3.21.0
- 3.20.0
- 3.19.0
- 3.18.0
- 3.17.0
- 3.16.0
- 3.15.0
- 3.14.0
- 3.13.0
- 3.12.0
- 3.11.0
- 3.10.0
- 3.9.0
- 3.8.0
- 3.7.0
- 3.6.0
- 3.5.0
- 3.4.2
- 3.3.0
- 3.2.0
- 3.0.0
- 2.9.8
- 2.8.9
- 2.7.4
- 2.5.3
- 2.4.0
GitHub Repository | Product Reference | REST Documentation | RPC Documentation |
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().
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.
"Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method.
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
RawPredict | Perform an online prediction with an arbitrary HTTP payload. The response includes the following HTTP headers:
|
Request object method variants only take one parameter, a request object, which must be constructed before the call.
"Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method.
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
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.
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
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.
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
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.
|
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.
|
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.
|
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.
|
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.
|
Explain | Perform an online explanation. If deployed_model_id is specified, the corresponding DeployModel must have explanation_spec populated. If deployed_model_id is not specified, all DeployedModels must have explanation_spec populated. |
Request object method variants only take one parameter, a request object, which must be constructed before the call.
"Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method.
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
CountTokens | Perform a token counting. |
Request object method variants only take one parameter, a request object, which must be constructed before the call.
"Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method.
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
GenerateContent | Generate content with multimodal inputs. |
Request object method variants only take one parameter, a request object, which must be constructed before the call.
"Flattened" method variants have converted the fields of the request object into function parameters to enable multiple ways to call the same method.
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
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.
|
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.
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
GetLocation | Gets information about a location. |
Request object method variants only take one parameter, a request object, which must be constructed before the call.
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
SetIamPolicy | Sets the access control policy on the specified resource. Replacesany existing policy. Can return |
Request object method variants only take one parameter, a request object, which must be constructed before the call.
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
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.
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
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 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.
Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
|
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.
Static Methods
create()
public static final PredictionServiceClient create()
Constructs an instance of PredictionServiceClient with default settings.
Returns | |
---|---|
Type | Description |
PredictionServiceClient |
Exceptions | |
---|---|
Type | Description |
IOException |
create(PredictionServiceSettings settings)
public static final PredictionServiceClient create(PredictionServiceSettings settings)
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.
Parameter | |
---|---|
Name | Description |
settings | PredictionServiceSettings |
Returns | |
---|---|
Type | Description |
PredictionServiceClient |
Exceptions | |
---|---|
Type | Description |
IOException |
create(PredictionServiceStub stub)
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).
Parameter | |
---|---|
Name | Description |
stub | PredictionServiceStub |
Returns | |
---|---|
Type | Description |
PredictionServiceClient |
Constructors
PredictionServiceClient(PredictionServiceSettings settings)
protected PredictionServiceClient(PredictionServiceSettings settings)
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.
Parameter | |
---|---|
Name | Description |
settings | PredictionServiceSettings |
PredictionServiceClient(PredictionServiceStub stub)
protected PredictionServiceClient(PredictionServiceStub stub)
Parameter | |
---|---|
Name | Description |
stub | PredictionServiceStub |
Methods
awaitTermination(long duration, TimeUnit unit)
public boolean awaitTermination(long duration, TimeUnit unit)
Parameters | |
---|---|
Name | Description |
duration | long |
unit | TimeUnit |
Returns | |
---|---|
Type | Description |
boolean |
Exceptions | |
---|---|
Type | Description |
InterruptedException |
close()
public final void close()
countTokens(CountTokensRequest request)
public final CountTokensResponse countTokens(CountTokensRequest request)
Perform a token counting.
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()) {
CountTokensRequest request =
CountTokensRequest.newBuilder()
.setEndpoint(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]", "[LOCATION]", "[ENDPOINT]")
.toString())
.setModel("model104069929")
.addAllInstances(new ArrayList<Value>())
.addAllContents(new ArrayList<Content>())
.build();
CountTokensResponse response = predictionServiceClient.countTokens(request);
}
Parameter | |
---|---|
Name | Description |
request | CountTokensRequest The request object containing all of the parameters for the API call. |
Returns | |
---|---|
Type | Description |
CountTokensResponse |
countTokens(EndpointName endpoint, List<Value> instances)
public final CountTokensResponse countTokens(EndpointName endpoint, List<Value> instances)
Perform a token counting.
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<>();
CountTokensResponse response = predictionServiceClient.countTokens(endpoint, instances);
}
Parameters | |
---|---|
Name | Description |
endpoint | EndpointName Required. The name of the Endpoint requested to perform token counting. Format:
|
instances | List<Value> Required. The instances that are the input to token counting call. Schema is identical to the prediction schema of the underlying model. |
Returns | |
---|---|
Type | Description |
CountTokensResponse |
countTokens(String endpoint, List<Value> instances)
public final CountTokensResponse countTokens(String endpoint, List<Value> instances)
Perform a token counting.
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<>();
CountTokensResponse response = predictionServiceClient.countTokens(endpoint, instances);
}
Parameters | |
---|---|
Name | Description |
endpoint | String Required. The name of the Endpoint requested to perform token counting. Format:
|
instances | List<Value> Required. The instances that are the input to token counting call. Schema is identical to the prediction schema of the underlying model. |
Returns | |
---|---|
Type | Description |
CountTokensResponse |
countTokensCallable()
public final UnaryCallable<CountTokensRequest,CountTokensResponse> countTokensCallable()
Perform a token counting.
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()) {
CountTokensRequest request =
CountTokensRequest.newBuilder()
.setEndpoint(
EndpointName.ofProjectLocationEndpointName(
"[PROJECT]", "[LOCATION]", "[ENDPOINT]")
.toString())
.setModel("model104069929")
.addAllInstances(new ArrayList<Value>())
.addAllContents(new ArrayList<Content>())
.build();
ApiFuture<CountTokensResponse> future =
predictionServiceClient.countTokensCallable().futureCall(request);
// Do something.
CountTokensResponse response = future.get();
}
Returns | |
---|---|
Type | Description |
UnaryCallable<CountTokensRequest,CountTokensResponse> |
directPredict(DirectPredictRequest request)
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);
}
Parameter | |
---|---|
Name | Description |
request | DirectPredictRequest The request object containing all of the parameters for the API call. |
Returns | |
---|---|
Type | Description |
DirectPredictResponse |
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();
}
Returns | |
---|---|
Type | Description |
UnaryCallable<DirectPredictRequest,DirectPredictResponse> |
directRawPredict(DirectRawPredictRequest request)
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);
}
Parameter | |
---|---|
Name | Description |
request | DirectRawPredictRequest The request object containing all of the parameters for the API call. |
Returns | |
---|---|
Type | Description |
DirectRawPredictResponse |
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();
}
Returns | |
---|---|
Type | Description |
UnaryCallable<DirectRawPredictRequest,DirectRawPredictResponse> |
explain(EndpointName endpoint, List<Value> instances, Value parameters, String deployedModelId)
public final ExplainResponse explain(EndpointName endpoint, List<Value> instances, Value parameters, String deployedModelId)
Perform an online explanation.
If deployed_model_id is specified, the corresponding DeployModel must have explanation_spec populated. If deployed_model_id is not specified, all DeployedModels must have 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 | |
---|---|
Name | Description |
endpoint | EndpointName Required. The name of the Endpoint requested to serve the explanation. Format:
|
instances | List<Value> 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 PredictSchemata's instance_schema_uri. |
parameters | Value The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri. |
deployedModelId | String If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding Endpoint.traffic_split. |
Returns | |
---|---|
Type | Description |
ExplainResponse |
explain(ExplainRequest request)
public final ExplainResponse explain(ExplainRequest request)
Perform an online explanation.
If deployed_model_id is specified, the corresponding DeployModel must have explanation_spec populated. If deployed_model_id is not specified, all DeployedModels must have 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())
.putAllConcurrentExplanationSpecOverride(
new HashMap<String, ExplanationSpecOverride>())
.setDeployedModelId("deployedModelId-1817547906")
.build();
ExplainResponse response = predictionServiceClient.explain(request);
}
Parameter | |
---|---|
Name | Description |
request | ExplainRequest The request object containing all of the parameters for the API call. |
Returns | |
---|---|
Type | Description |
ExplainResponse |
explain(String endpoint, List<Value> instances, Value parameters, String deployedModelId)
public final ExplainResponse explain(String endpoint, List<Value> instances, Value parameters, String deployedModelId)
Perform an online explanation.
If deployed_model_id is specified, the corresponding DeployModel must have explanation_spec populated. If deployed_model_id is not specified, all DeployedModels must have 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 | |
---|---|
Name | Description |
endpoint | String Required. The name of the Endpoint requested to serve the explanation. Format:
|
instances | List<Value> 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 PredictSchemata's instance_schema_uri. |
parameters | Value The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri. |
deployedModelId | String If specified, this ExplainRequest will be served by the chosen DeployedModel, overriding Endpoint.traffic_split. |
Returns | |
---|---|
Type | Description |
ExplainResponse |
explainCallable()
public final UnaryCallable<ExplainRequest,ExplainResponse> explainCallable()
Perform an online explanation.
If deployed_model_id is specified, the corresponding DeployModel must have explanation_spec populated. If deployed_model_id is not specified, all DeployedModels must have 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())
.putAllConcurrentExplanationSpecOverride(
new HashMap<String, ExplanationSpecOverride>())
.setDeployedModelId("deployedModelId-1817547906")
.build();
ApiFuture<ExplainResponse> future =
predictionServiceClient.explainCallable().futureCall(request);
// Do something.
ExplainResponse response = future.get();
}
Returns | |
---|---|
Type | Description |
UnaryCallable<ExplainRequest,ExplainResponse> |
generateContent(GenerateContentRequest request)
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>())
.addAllTools(new ArrayList<Tool>())
.addAllSafetySettings(new ArrayList<SafetySetting>())
.setGenerationConfig(GenerationConfig.newBuilder().build())
.build();
GenerateContentResponse response = predictionServiceClient.generateContent(request);
}
Parameter | |
---|---|
Name | Description |
request | GenerateContentRequest The request object containing all of the parameters for the API call. |
Returns | |
---|---|
Type | Description |
GenerateContentResponse |
generateContent(String model, List<Content> contents)
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 | |
---|---|
Name | Description |
model | String Required. The name of the publisher model requested to serve the prediction.
Format: |
contents | List<Content> 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. |
Returns | |
---|---|
Type | Description |
GenerateContentResponse |
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>())
.addAllTools(new ArrayList<Tool>())
.addAllSafetySettings(new ArrayList<SafetySetting>())
.setGenerationConfig(GenerationConfig.newBuilder().build())
.build();
ApiFuture<GenerateContentResponse> future =
predictionServiceClient.generateContentCallable().futureCall(request);
// Do something.
GenerateContentResponse response = future.get();
}
Returns | |
---|---|
Type | Description |
UnaryCallable<GenerateContentRequest,GenerateContentResponse> |
getIamPolicy(GetIamPolicyRequest request)
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);
}
Parameter | |
---|---|
Name | Description |
request | com.google.iam.v1.GetIamPolicyRequest The request object containing all of the parameters for the API call. |
Returns | |
---|---|
Type | Description |
com.google.iam.v1.Policy |
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();
}
Returns | |
---|---|
Type | Description |
UnaryCallable<com.google.iam.v1.GetIamPolicyRequest,com.google.iam.v1.Policy> |
getLocation(GetLocationRequest request)
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);
}
Parameter | |
---|---|
Name | Description |
request | com.google.cloud.location.GetLocationRequest The request object containing all of the parameters for the API call. |
Returns | |
---|---|
Type | Description |
com.google.cloud.location.Location |
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();
}
Returns | |
---|---|
Type | Description |
UnaryCallable<com.google.cloud.location.GetLocationRequest,com.google.cloud.location.Location> |
getSettings()
public final PredictionServiceSettings getSettings()
Returns | |
---|---|
Type | Description |
PredictionServiceSettings |
getStub()
public PredictionServiceStub getStub()
Returns | |
---|---|
Type | Description |
PredictionServiceStub |
isShutdown()
public boolean isShutdown()
Returns | |
---|---|
Type | Description |
boolean |
isTerminated()
public boolean isTerminated()
Returns | |
---|---|
Type | Description |
boolean |
listLocations(ListLocationsRequest request)
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);
}
}
Parameter | |
---|---|
Name | Description |
request | com.google.cloud.location.ListLocationsRequest The request object containing all of the parameters for the API call. |
Returns | |
---|---|
Type | Description |
PredictionServiceClient.ListLocationsPagedResponse |
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;
}
}
}
Returns | |
---|---|
Type | Description |
UnaryCallable<com.google.cloud.location.ListLocationsRequest,com.google.cloud.location.ListLocationsResponse> |
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);
}
}
Returns | |
---|---|
Type | Description |
UnaryCallable<com.google.cloud.location.ListLocationsRequest,ListLocationsPagedResponse> |
predict(EndpointName endpoint, List<Value> instances, Value parameters)
public final PredictResponse predict(EndpointName endpoint, List<Value> instances, 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 | |
---|---|
Name | Description |
endpoint | EndpointName Required. The name of the Endpoint requested to serve the prediction. Format:
|
instances | List<Value> 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 PredictSchemata's instance_schema_uri. |
parameters | Value The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri. |
Returns | |
---|---|
Type | Description |
PredictResponse |
predict(PredictRequest request)
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())
.build();
PredictResponse response = predictionServiceClient.predict(request);
}
Parameter | |
---|---|
Name | Description |
request | PredictRequest The request object containing all of the parameters for the API call. |
Returns | |
---|---|
Type | Description |
PredictResponse |
predict(String endpoint, List<Value> instances, Value parameters)
public final PredictResponse predict(String endpoint, List<Value> instances, 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 | |
---|---|
Name | Description |
endpoint | String Required. The name of the Endpoint requested to serve the prediction. Format:
|
instances | List<Value> 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 PredictSchemata's instance_schema_uri. |
parameters | Value The parameters that govern the prediction. The schema of the parameters may be specified via Endpoint's DeployedModels' Model's PredictSchemata's parameters_schema_uri. |
Returns | |
---|---|
Type | Description |
PredictResponse |
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())
.build();
ApiFuture<PredictResponse> future =
predictionServiceClient.predictCallable().futureCall(request);
// Do something.
PredictResponse response = future.get();
}
Returns | |
---|---|
Type | Description |
UnaryCallable<PredictRequest,PredictResponse> |
rawPredict(EndpointName endpoint, HttpBody httpBody)
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 that served this prediction.
X-Vertex-AI-Deployed-Model-Id
: ID of the Endpoint's 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 | |
---|---|
Name | Description |
endpoint | EndpointName Required. The name of the Endpoint requested to serve the prediction. Format:
|
httpBody | com.google.api.HttpBody The prediction input. Supports HTTP headers and arbitrary data payload. A 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 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
field when you create a Model. This schema applies
when you deploy the |
Returns | |
---|---|
Type | Description |
com.google.api.HttpBody |
rawPredict(RawPredictRequest request)
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 that served this prediction.
X-Vertex-AI-Deployed-Model-Id
: ID of the Endpoint's 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);
}
Parameter | |
---|---|
Name | Description |
request | RawPredictRequest The request object containing all of the parameters for the API call. |
Returns | |
---|---|
Type | Description |
com.google.api.HttpBody |
rawPredict(String endpoint, HttpBody httpBody)
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 that served this prediction.
X-Vertex-AI-Deployed-Model-Id
: ID of the Endpoint's 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 | |
---|---|
Name | Description |
endpoint | String Required. The name of the Endpoint requested to serve the prediction. Format:
|
httpBody | com.google.api.HttpBody The prediction input. Supports HTTP headers and arbitrary data payload. A 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 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
field when you create a Model. This schema applies
when you deploy the |
Returns | |
---|---|
Type | Description |
com.google.api.HttpBody |
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 that served this prediction.
X-Vertex-AI-Deployed-Model-Id
: ID of the Endpoint's 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();
}
Returns | |
---|---|
Type | Description |
UnaryCallable<RawPredictRequest,com.google.api.HttpBody> |
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.
}
}
Returns | |
---|---|
Type | Description |
ServerStreamingCallable<StreamingPredictRequest,StreamingPredictResponse> |
setIamPolicy(SetIamPolicyRequest request)
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);
}
Parameter | |
---|---|
Name | Description |
request | com.google.iam.v1.SetIamPolicyRequest The request object containing all of the parameters for the API call. |
Returns | |
---|---|
Type | Description |
com.google.iam.v1.Policy |
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();
}
Returns | |
---|---|
Type | Description |
UnaryCallable<com.google.iam.v1.SetIamPolicyRequest,com.google.iam.v1.Policy> |
shutdown()
public void shutdown()
shutdownNow()
public void shutdownNow()
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.
}
}
Returns | |
---|---|
Type | Description |
BidiStreamingCallable<StreamDirectPredictRequest,StreamDirectPredictResponse> |
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.
}
}
Returns | |
---|---|
Type | Description |
BidiStreamingCallable<StreamDirectRawPredictRequest,StreamDirectRawPredictResponse> |
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>())
.addAllTools(new ArrayList<Tool>())
.addAllSafetySettings(new ArrayList<SafetySetting>())
.setGenerationConfig(GenerationConfig.newBuilder().build())
.build();
ServerStream<GenerateContentResponse> stream =
predictionServiceClient.streamGenerateContentCallable().call(request);
for (GenerateContentResponse response : stream) {
// Do something when a response is received.
}
}
Returns | |
---|---|
Type | Description |
ServerStreamingCallable<GenerateContentRequest,GenerateContentResponse> |
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.
}
}
Returns | |
---|---|
Type | Description |
BidiStreamingCallable<StreamingPredictRequest,StreamingPredictResponse> |
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.
}
}
Returns | |
---|---|
Type | Description |
BidiStreamingCallable<StreamingRawPredictRequest,StreamingRawPredictResponse> |
testIamPermissions(TestIamPermissionsRequest request)
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);
}
Parameter | |
---|---|
Name | Description |
request | com.google.iam.v1.TestIamPermissionsRequest The request object containing all of the parameters for the API call. |
Returns | |
---|---|
Type | Description |
com.google.iam.v1.TestIamPermissionsResponse |
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();
}
Returns | |
---|---|
Type | Description |
UnaryCallable<com.google.iam.v1.TestIamPermissionsRequest,com.google.iam.v1.TestIamPermissionsResponse> |