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chore: regenerate aiplatform client (googleapis#29851)
Generated in GitHub action: https://togithub.com/googleapis/googleapis/google-api-java-client-services/actions/workflows/codegen.yaml
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‎clients/google-api-services-aiplatform/v1/2.0.0/README.md‎

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@@ -22,7 +22,7 @@ Add the following lines to your `pom.xml` file:
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<dependency>
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<groupId>com.google.apis</groupId>
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<artifactId>google-api-services-aiplatform</artifactId>
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<version>v1-rev20251003-2.0.0</version>
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<version>v1-rev20251010-2.0.0</version>
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</dependency>
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</dependencies>
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</project>
@@ -35,7 +35,7 @@ repositories {
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mavenCentral()
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}
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dependencies {
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implementation 'com.google.apis:google-api-services-aiplatform:v1-rev20251003-2.0.0'
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implementation 'com.google.apis:google-api-services-aiplatform:v1-rev20251010-2.0.0'
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}
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```
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‎clients/google-api-services-aiplatform/v1/2.0.0/com/google/api/services/aiplatform/v1/Aiplatform.java‎

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@@ -80894,6 +80894,146 @@ public CountTokens set(String parameterName, Object value) {
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return (CountTokens) super.set(parameterName, value);
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}
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}
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/**
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* Embed content with multimodal inputs.
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*
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* Create a request for the method "models.embedContent".
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*
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* This request holds the parameters needed by the aiplatform server. After setting any optional
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* parameters, call the {@link EmbedContent#execute()} method to invoke the remote operation.
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*
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* @param model Required. The name of the publisher model requested to serve the prediction. Format:
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* `projects/{project}/locations/{location}/publishers/models`
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* @param content the {@link com.google.api.services.aiplatform.v1.model.GoogleCloudAiplatformV1EmbedContentRequest}
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* @return the request
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*/
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public EmbedContent embedContent(java.lang.String model, com.google.api.services.aiplatform.v1.model.GoogleCloudAiplatformV1EmbedContentRequest content) throws java.io.IOException {
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EmbedContent result = new EmbedContent(model, content);
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initialize(result);
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return result;
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}
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public class EmbedContent extends AiplatformRequest<com.google.api.services.aiplatform.v1.model.GoogleCloudAiplatformV1EmbedContentResponse> {
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private static final String REST_PATH = "v1/{+model}:embedContent";
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private final java.util.regex.Pattern MODEL_PATTERN =
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java.util.regex.Pattern.compile("^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$");
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/**
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* Embed content with multimodal inputs.
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*
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* Create a request for the method "models.embedContent".
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*
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* This request holds the parameters needed by the the aiplatform server. After setting any
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* optional parameters, call the {@link EmbedContent#execute()} method to invoke the remote
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* operation. <p> {@link
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* EmbedContent#initialize(com.google.api.client.googleapis.services.AbstractGoogleClientRequest)}
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* must be called to initialize this instance immediately after invoking the constructor. </p>
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*
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* @param model Required. The name of the publisher model requested to serve the prediction. Format:
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* `projects/{project}/locations/{location}/publishers/models`
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* @param content the {@link com.google.api.services.aiplatform.v1.model.GoogleCloudAiplatformV1EmbedContentRequest}
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* @since 1.13
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*/
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protected EmbedContent(java.lang.String model, com.google.api.services.aiplatform.v1.model.GoogleCloudAiplatformV1EmbedContentRequest content) {
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super(Aiplatform.this, "POST", REST_PATH, content, com.google.api.services.aiplatform.v1.model.GoogleCloudAiplatformV1EmbedContentResponse.class);
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this.model = com.google.api.client.util.Preconditions.checkNotNull(model, "Required parameter model must be specified.");
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if (!getSuppressPatternChecks()) {
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com.google.api.client.util.Preconditions.checkArgument(MODEL_PATTERN.matcher(model).matches(),
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"Parameter model must conform to the pattern " +
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"^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$");
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}
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}
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@Override
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public EmbedContent set$Xgafv(java.lang.String $Xgafv) {
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return (EmbedContent) super.set$Xgafv($Xgafv);
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}
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@Override
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public EmbedContent setAccessToken(java.lang.String accessToken) {
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return (EmbedContent) super.setAccessToken(accessToken);
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}
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@Override
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public EmbedContent setAlt(java.lang.String alt) {
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return (EmbedContent) super.setAlt(alt);
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}
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@Override
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public EmbedContent setCallback(java.lang.String callback) {
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return (EmbedContent) super.setCallback(callback);
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}
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@Override
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public EmbedContent setFields(java.lang.String fields) {
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return (EmbedContent) super.setFields(fields);
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}
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@Override
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public EmbedContent setKey(java.lang.String key) {
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return (EmbedContent) super.setKey(key);
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}
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@Override
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public EmbedContent setOauthToken(java.lang.String oauthToken) {
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return (EmbedContent) super.setOauthToken(oauthToken);
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}
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@Override
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public EmbedContent setPrettyPrint(java.lang.Boolean prettyPrint) {
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return (EmbedContent) super.setPrettyPrint(prettyPrint);
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}
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@Override
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public EmbedContent setQuotaUser(java.lang.String quotaUser) {
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return (EmbedContent) super.setQuotaUser(quotaUser);
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}
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@Override
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public EmbedContent setUploadType(java.lang.String uploadType) {
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return (EmbedContent) super.setUploadType(uploadType);
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}
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@Override
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public EmbedContent setUploadProtocol(java.lang.String uploadProtocol) {
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return (EmbedContent) super.setUploadProtocol(uploadProtocol);
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}
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/**
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* Required. The name of the publisher model requested to serve the prediction. Format:
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* `projects/{project}/locations/{location}/publishers/models`
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*/
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@com.google.api.client.util.Key
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private java.lang.String model;
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/** Required. The name of the publisher model requested to serve the prediction. Format:
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`projects/{project}/locations/{location}/publishers/models`
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*/
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public java.lang.String getModel() {
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return model;
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}
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/**
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* Required. The name of the publisher model requested to serve the prediction. Format:
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* `projects/{project}/locations/{location}/publishers/models`
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*/
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public EmbedContent setModel(java.lang.String model) {
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if (!getSuppressPatternChecks()) {
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com.google.api.client.util.Preconditions.checkArgument(MODEL_PATTERN.matcher(model).matches(),
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"Parameter model must conform to the pattern " +
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"^projects/[^/]+/locations/[^/]+/publishers/[^/]+/models/[^/]+$");
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}
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this.model = model;
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return this;
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}
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@Override
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public EmbedContent set(String parameterName, Object value) {
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return (EmbedContent) super.set(parameterName, value);
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}
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}
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/**
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* Fetch an asynchronous online prediction operation.
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*

‎clients/google-api-services-aiplatform/v1/2.0.0/com/google/api/services/aiplatform/v1/model/GoogleCloudAiplatformV1EmbedContentRequest.java‎

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/*
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* Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except
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* in compliance with the License. You may obtain a copy of the License at
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*
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* http://www.apache.org/licenses/LICENSE-2.0
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*
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* Unless required by applicable law or agreed to in writing, software distributed under the License
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* is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express
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* or implied. See the License for the specific language governing permissions and limitations under
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* the License.
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*/
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/*
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* This code was generated by https://github.com/googleapis/google-api-java-client-services/
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* Modify at your own risk.
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*/
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package com.google.api.services.aiplatform.v1.model;
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/**
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* Request message for PredictionService.EmbedContent.
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*
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* <p> This is the Java data model class that specifies how to parse/serialize into the JSON that is
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* transmitted over HTTP when working with the Vertex AI API. For a detailed explanation see:
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* <a href="https://developers.google.com/api-client-library/java/google-http-java-client/json">https://developers.google.com/api-client-library/java/google-http-java-client/json</a>
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* </p>
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*
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* @author Google, Inc.
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*/
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@SuppressWarnings("javadoc")
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public final class GoogleCloudAiplatformV1EmbedContentRequest extends com.google.api.client.json.GenericJson {
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/**
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* Optional. Whether to silently truncate the input content if it's longer than the maximum
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* sequence length.
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* The value may be {@code null}.
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*/
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@com.google.api.client.util.Key
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private java.lang.Boolean autoTruncate;
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/**
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* Required. Input content to be embedded. Required.
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* The value may be {@code null}.
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*/
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@com.google.api.client.util.Key
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private GoogleCloudAiplatformV1Content content;
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/**
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* Optional. Optional reduced dimension for the output embedding. If set, excessive values in the
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* output embedding are truncated from the end.
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* The value may be {@code null}.
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*/
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@com.google.api.client.util.Key
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private java.lang.Integer outputDimensionality;
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/**
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* Optional. The task type of the embedding.
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* The value may be {@code null}.
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*/
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@com.google.api.client.util.Key
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private java.lang.String taskType;
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/**
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* Optional. An optional title for the text.
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* The value may be {@code null}.
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*/
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@com.google.api.client.util.Key
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private java.lang.String title;
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/**
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* Optional. Whether to silently truncate the input content if it's longer than the maximum
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* sequence length.
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* @return value or {@code null} for none
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*/
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public java.lang.Boolean getAutoTruncate() {
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return autoTruncate;
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}
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/**
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* Optional. Whether to silently truncate the input content if it's longer than the maximum
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* sequence length.
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* @param autoTruncate autoTruncate or {@code null} for none
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*/
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public GoogleCloudAiplatformV1EmbedContentRequest setAutoTruncate(java.lang.Boolean autoTruncate) {
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this.autoTruncate = autoTruncate;
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return this;
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}
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/**
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* Required. Input content to be embedded. Required.
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* @return value or {@code null} for none
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*/
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public GoogleCloudAiplatformV1Content getContent() {
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return content;
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}
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/**
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* Required. Input content to be embedded. Required.
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* @param content content or {@code null} for none
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*/
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public GoogleCloudAiplatformV1EmbedContentRequest setContent(GoogleCloudAiplatformV1Content content) {
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this.content = content;
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return this;
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}
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/**
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* Optional. Optional reduced dimension for the output embedding. If set, excessive values in the
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* output embedding are truncated from the end.
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* @return value or {@code null} for none
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*/
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public java.lang.Integer getOutputDimensionality() {
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return outputDimensionality;
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}
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/**
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* Optional. Optional reduced dimension for the output embedding. If set, excessive values in the
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* output embedding are truncated from the end.
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* @param outputDimensionality outputDimensionality or {@code null} for none
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*/
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public GoogleCloudAiplatformV1EmbedContentRequest setOutputDimensionality(java.lang.Integer outputDimensionality) {
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this.outputDimensionality = outputDimensionality;
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return this;
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}
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/**
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* Optional. The task type of the embedding.
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* @return value or {@code null} for none
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*/
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public java.lang.String getTaskType() {
129+
return taskType;
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}
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/**
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* Optional. The task type of the embedding.
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* @param taskType taskType or {@code null} for none
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*/
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public GoogleCloudAiplatformV1EmbedContentRequest setTaskType(java.lang.String taskType) {
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this.taskType = taskType;
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return this;
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}
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/**
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* Optional. An optional title for the text.
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* @return value or {@code null} for none
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*/
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public java.lang.String getTitle() {
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return title;
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}
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/**
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* Optional. An optional title for the text.
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* @param title title or {@code null} for none
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*/
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public GoogleCloudAiplatformV1EmbedContentRequest setTitle(java.lang.String title) {
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this.title = title;
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return this;
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}
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@Override
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public GoogleCloudAiplatformV1EmbedContentRequest set(String fieldName, Object value) {
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return (GoogleCloudAiplatformV1EmbedContentRequest) super.set(fieldName, value);
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}
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@Override
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public GoogleCloudAiplatformV1EmbedContentRequest clone() {
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return (GoogleCloudAiplatformV1EmbedContentRequest) super.clone();
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}
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}

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