com.google.cloud.recommendationengine.v1beta1.PredictionServiceClient Maven / Gradle / Ivy
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/*
* Copyright 2024 Google LLC
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* https://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package com.google.cloud.recommendationengine.v1beta1;
import com.google.api.core.ApiFuture;
import com.google.api.core.ApiFutures;
import com.google.api.core.BetaApi;
import com.google.api.gax.core.BackgroundResource;
import com.google.api.gax.paging.AbstractFixedSizeCollection;
import com.google.api.gax.paging.AbstractPage;
import com.google.api.gax.paging.AbstractPagedListResponse;
import com.google.api.gax.rpc.PageContext;
import com.google.api.gax.rpc.UnaryCallable;
import com.google.cloud.recommendationengine.v1beta1.stub.PredictionServiceStub;
import com.google.cloud.recommendationengine.v1beta1.stub.PredictionServiceStubSettings;
import com.google.common.util.concurrent.MoreExecutors;
import com.google.protobuf.Value;
import java.io.IOException;
import java.util.List;
import java.util.Map;
import java.util.concurrent.TimeUnit;
import javax.annotation.Generated;
// AUTO-GENERATED DOCUMENTATION AND CLASS.
/**
* Service Description: Service for making recommendation prediction.
*
* 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:
*
*
{@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()) {
* PlacementName name =
* PlacementName.of("[PROJECT]", "[LOCATION]", "[CATALOG]", "[EVENT_STORE]", "[PLACEMENT]");
* UserEvent userEvent = UserEvent.newBuilder().build();
* for (Map.Entry element :
* predictionServiceClient.predict(name, userEvent).iterateAll()) {
* // doThingsWith(element);
* }
* }
* }
*
* 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
Makes a recommendation prediction. If using API Key based authentication, the API Key must be registered using the [PredictionApiKeyRegistry][google.cloud.recommendationengine.v1beta1.PredictionApiKeyRegistry] service. [Learn more](/recommendations-ai/docs/setting-up#register-key).
* 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(PlacementName name, UserEvent userEvent)
*
predict(String name, UserEvent userEvent)
*
* Callable method variants take no parameters and return an immutable API callable object, which can be used to initiate calls to the service.
*
* predictPagedCallable()
*
predictCallable()
*
*
*
*
*
* 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:
*
*
{@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
* PredictionServiceSettings predictionServiceSettings =
* PredictionServiceSettings.newBuilder()
* .setCredentialsProvider(FixedCredentialsProvider.create(myCredentials))
* .build();
* PredictionServiceClient predictionServiceClient =
* PredictionServiceClient.create(predictionServiceSettings);
* }
*
* To customize the endpoint:
*
*
{@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
* PredictionServiceSettings predictionServiceSettings =
* PredictionServiceSettings.newBuilder().setEndpoint(myEndpoint).build();
* PredictionServiceClient predictionServiceClient =
* PredictionServiceClient.create(predictionServiceSettings);
* }
*
* To use REST (HTTP1.1/JSON) transport (instead of gRPC) for sending and receiving requests over
* the wire:
*
*
{@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
* PredictionServiceSettings predictionServiceSettings =
* PredictionServiceSettings.newHttpJsonBuilder().build();
* PredictionServiceClient predictionServiceClient =
* PredictionServiceClient.create(predictionServiceSettings);
* }
*
* Please refer to the GitHub repository's samples for more quickstart code snippets.
*/
@BetaApi
@Generated("by gapic-generator-java")
public class PredictionServiceClient implements BackgroundResource {
private final PredictionServiceSettings settings;
private final PredictionServiceStub stub;
/** Constructs an instance of PredictionServiceClient with default settings. */
public static final PredictionServiceClient create() throws IOException {
return create(PredictionServiceSettings.newBuilder().build());
}
/**
* 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.
*/
public static final PredictionServiceClient create(PredictionServiceSettings settings)
throws IOException {
return new PredictionServiceClient(settings);
}
/**
* Constructs an instance of PredictionServiceClient, using the given stub for making calls. This
* is for advanced usage - prefer using create(PredictionServiceSettings).
*/
public static final PredictionServiceClient create(PredictionServiceStub stub) {
return new PredictionServiceClient(stub);
}
/**
* 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.
*/
protected PredictionServiceClient(PredictionServiceSettings settings) throws IOException {
this.settings = settings;
this.stub = ((PredictionServiceStubSettings) settings.getStubSettings()).createStub();
}
protected PredictionServiceClient(PredictionServiceStub stub) {
this.settings = null;
this.stub = stub;
}
public final PredictionServiceSettings getSettings() {
return settings;
}
public PredictionServiceStub getStub() {
return stub;
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Makes a recommendation prediction. If using API Key based authentication, the API Key must be
* registered using the
* [PredictionApiKeyRegistry][google.cloud.recommendationengine.v1beta1.PredictionApiKeyRegistry]
* service. [Learn more](/recommendations-ai/docs/setting-up#register-key).
*
*
Sample code:
*
*
{@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()) {
* PlacementName name =
* PlacementName.of("[PROJECT]", "[LOCATION]", "[CATALOG]", "[EVENT_STORE]", "[PLACEMENT]");
* UserEvent userEvent = UserEvent.newBuilder().build();
* for (Map.Entry element :
* predictionServiceClient.predict(name, userEvent).iterateAll()) {
* // doThingsWith(element);
* }
* }
* }
*
* @param name Required. Full resource name of the format:
* `{name=projects/*/locations/global/catalogs/default_catalog/eventStores/default_event_store/placements/*}`
* The id of the recommendation engine placement. This id is used to identify the set of
* models that will be used to make the prediction.
* We currently support three placements with the following IDs by default:
*
* - `shopping_cart`: Predicts items frequently bought together with one or more catalog
* items in the same shopping session. Commonly displayed after `add-to-cart` events, on
* product detail pages, or on the shopping cart page.
*
*
* - `home_page`: Predicts the next product that a user will most likely engage with or
* purchase based on the shopping or viewing history of the specified `userId` or
* `visitorId`. For example - Recommendations for you.
*
*
* - `product_detail`: Predicts the next product that a user will most likely engage with
* or purchase. The prediction is based on the shopping or viewing history of the
* specified `userId` or `visitorId` and its relevance to a specified `CatalogItem`.
* Typically used on product detail pages. For example - More items like this.
*
*
* - `recently_viewed_default`: Returns up to 75 items recently viewed by the specified
* `userId` or `visitorId`, most recent ones first. Returns nothing if neither of them
* has viewed any items yet. For example - Recently viewed.
*
* The full list of available placements can be seen at
* https://console.cloud.google.com/recommendation/datafeeds/default_catalog/dashboard
* @param userEvent Required. Context about the user, what they are looking at and what action
* they took to trigger the predict request. Note that this user event detail won't be
* ingested to userEvent logs. Thus, a separate userEvent write request is required for event
* logging.
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final PredictPagedResponse predict(PlacementName name, UserEvent userEvent) {
PredictRequest request =
PredictRequest.newBuilder()
.setName(name == null ? null : name.toString())
.setUserEvent(userEvent)
.build();
return predict(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Makes a recommendation prediction. If using API Key based authentication, the API Key must be
* registered using the
* [PredictionApiKeyRegistry][google.cloud.recommendationengine.v1beta1.PredictionApiKeyRegistry]
* service. [Learn more](/recommendations-ai/docs/setting-up#register-key).
*
*
Sample code:
*
*
{@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 name =
* PlacementName.of("[PROJECT]", "[LOCATION]", "[CATALOG]", "[EVENT_STORE]", "[PLACEMENT]")
* .toString();
* UserEvent userEvent = UserEvent.newBuilder().build();
* for (Map.Entry element :
* predictionServiceClient.predict(name, userEvent).iterateAll()) {
* // doThingsWith(element);
* }
* }
* }
*
* @param name Required. Full resource name of the format:
* `{name=projects/*/locations/global/catalogs/default_catalog/eventStores/default_event_store/placements/*}`
* The id of the recommendation engine placement. This id is used to identify the set of
* models that will be used to make the prediction.
* We currently support three placements with the following IDs by default:
*
* - `shopping_cart`: Predicts items frequently bought together with one or more catalog
* items in the same shopping session. Commonly displayed after `add-to-cart` events, on
* product detail pages, or on the shopping cart page.
*
*
* - `home_page`: Predicts the next product that a user will most likely engage with or
* purchase based on the shopping or viewing history of the specified `userId` or
* `visitorId`. For example - Recommendations for you.
*
*
* - `product_detail`: Predicts the next product that a user will most likely engage with
* or purchase. The prediction is based on the shopping or viewing history of the
* specified `userId` or `visitorId` and its relevance to a specified `CatalogItem`.
* Typically used on product detail pages. For example - More items like this.
*
*
* - `recently_viewed_default`: Returns up to 75 items recently viewed by the specified
* `userId` or `visitorId`, most recent ones first. Returns nothing if neither of them
* has viewed any items yet. For example - Recently viewed.
*
* The full list of available placements can be seen at
* https://console.cloud.google.com/recommendation/datafeeds/default_catalog/dashboard
* @param userEvent Required. Context about the user, what they are looking at and what action
* they took to trigger the predict request. Note that this user event detail won't be
* ingested to userEvent logs. Thus, a separate userEvent write request is required for event
* logging.
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final PredictPagedResponse predict(String name, UserEvent userEvent) {
PredictRequest request =
PredictRequest.newBuilder().setName(name).setUserEvent(userEvent).build();
return predict(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Makes a recommendation prediction. If using API Key based authentication, the API Key must be
* registered using the
* [PredictionApiKeyRegistry][google.cloud.recommendationengine.v1beta1.PredictionApiKeyRegistry]
* service. [Learn more](/recommendations-ai/docs/setting-up#register-key).
*
*
Sample code:
*
*
{@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()
* .setName(
* PlacementName.of(
* "[PROJECT]", "[LOCATION]", "[CATALOG]", "[EVENT_STORE]", "[PLACEMENT]")
* .toString())
* .setUserEvent(UserEvent.newBuilder().build())
* .setPageSize(883849137)
* .setPageToken("pageToken873572522")
* .setFilter("filter-1274492040")
* .setDryRun(true)
* .putAllParams(new HashMap())
* .putAllLabels(new HashMap())
* .build();
* for (Map.Entry element :
* predictionServiceClient.predict(request).iterateAll()) {
* // doThingsWith(element);
* }
* }
* }
*
* @param request The request object containing all of the parameters for the API call.
* @throws com.google.api.gax.rpc.ApiException if the remote call fails
*/
public final PredictPagedResponse predict(PredictRequest request) {
return predictPagedCallable().call(request);
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Makes a recommendation prediction. If using API Key based authentication, the API Key must be
* registered using the
* [PredictionApiKeyRegistry][google.cloud.recommendationengine.v1beta1.PredictionApiKeyRegistry]
* service. [Learn more](/recommendations-ai/docs/setting-up#register-key).
*
* Sample code:
*
*
{@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()
* .setName(
* PlacementName.of(
* "[PROJECT]", "[LOCATION]", "[CATALOG]", "[EVENT_STORE]", "[PLACEMENT]")
* .toString())
* .setUserEvent(UserEvent.newBuilder().build())
* .setPageSize(883849137)
* .setPageToken("pageToken873572522")
* .setFilter("filter-1274492040")
* .setDryRun(true)
* .putAllParams(new HashMap())
* .putAllLabels(new HashMap())
* .build();
* ApiFuture> future =
* predictionServiceClient.predictPagedCallable().futureCall(request);
* // Do something.
* for (Map.Entry element : future.get().iterateAll()) {
* // doThingsWith(element);
* }
* }
* }
*/
public final UnaryCallable predictPagedCallable() {
return stub.predictPagedCallable();
}
// AUTO-GENERATED DOCUMENTATION AND METHOD.
/**
* Makes a recommendation prediction. If using API Key based authentication, the API Key must be
* registered using the
* [PredictionApiKeyRegistry][google.cloud.recommendationengine.v1beta1.PredictionApiKeyRegistry]
* service. [Learn more](/recommendations-ai/docs/setting-up#register-key).
*
* Sample code:
*
*
{@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()
* .setName(
* PlacementName.of(
* "[PROJECT]", "[LOCATION]", "[CATALOG]", "[EVENT_STORE]", "[PLACEMENT]")
* .toString())
* .setUserEvent(UserEvent.newBuilder().build())
* .setPageSize(883849137)
* .setPageToken("pageToken873572522")
* .setFilter("filter-1274492040")
* .setDryRun(true)
* .putAllParams(new HashMap())
* .putAllLabels(new HashMap())
* .build();
* while (true) {
* PredictResponse response = predictionServiceClient.predictCallable().call(request);
* for (Map.Entry element : response.getMetadataList()) {
* // doThingsWith(element);
* }
* String nextPageToken = response.getNextPageToken();
* if (!Strings.isNullOrEmpty(nextPageToken)) {
* request = request.toBuilder().setPageToken(nextPageToken).build();
* } else {
* break;
* }
* }
* }
* }
*/
public final UnaryCallable predictCallable() {
return stub.predictCallable();
}
@Override
public final void close() {
stub.close();
}
@Override
public void shutdown() {
stub.shutdown();
}
@Override
public boolean isShutdown() {
return stub.isShutdown();
}
@Override
public boolean isTerminated() {
return stub.isTerminated();
}
@Override
public void shutdownNow() {
stub.shutdownNow();
}
@Override
public boolean awaitTermination(long duration, TimeUnit unit) throws InterruptedException {
return stub.awaitTermination(duration, unit);
}
public static class PredictPagedResponse
extends AbstractPagedListResponse<
PredictRequest,
PredictResponse,
Map.Entry,
PredictPage,
PredictFixedSizeCollection> {
public static ApiFuture createAsync(
PageContext> context,
ApiFuture futureResponse) {
ApiFuture futurePage =
PredictPage.createEmptyPage().createPageAsync(context, futureResponse);
return ApiFutures.transform(
futurePage, input -> new PredictPagedResponse(input), MoreExecutors.directExecutor());
}
private PredictPagedResponse(PredictPage page) {
super(page, PredictFixedSizeCollection.createEmptyCollection());
}
}
public static class PredictPage
extends AbstractPage, PredictPage> {
private PredictPage(
PageContext> context,
PredictResponse response) {
super(context, response);
}
private static PredictPage createEmptyPage() {
return new PredictPage(null, null);
}
@Override
protected PredictPage createPage(
PageContext> context,
PredictResponse response) {
return new PredictPage(context, response);
}
@Override
public ApiFuture createPageAsync(
PageContext> context,
ApiFuture futureResponse) {
return super.createPageAsync(context, futureResponse);
}
}
public static class PredictFixedSizeCollection
extends AbstractFixedSizeCollection<
PredictRequest,
PredictResponse,
Map.Entry,
PredictPage,
PredictFixedSizeCollection> {
private PredictFixedSizeCollection(List pages, int collectionSize) {
super(pages, collectionSize);
}
private static PredictFixedSizeCollection createEmptyCollection() {
return new PredictFixedSizeCollection(null, 0);
}
@Override
protected PredictFixedSizeCollection createCollection(
List pages, int collectionSize) {
return new PredictFixedSizeCollection(pages, collectionSize);
}
}
}