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Remove preview package and add function calling example (GoogleCloudPlatform#9241)
* Use gemini-pro instead of gemini-pro-vision in chat * Update chat test case to use gemini-pro * Remove the preview package Add a function calling example * Missing license header * chore(Checkstyle tweak) * Add missing region tag Fix typo in project ID string * Use the latest libraries-bom that references the 0.4.0 version of the google-cloud-vertexai SDK Use the same example for the token count as in Python and Golang
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‎vertexai/snippets/pom.xml‎

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<groupId>com.google.cloud</groupId>
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<scope>import</scope>
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<type>pom</type>
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<version>26.29.0</version>
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<version>26.32.0</version>
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</dependency>
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</dependencies>
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</dependencyManagement>

‎vertexai/snippets/src/main/java/vertexai/gemini/ChatDiscussion.java‎

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// [START aiplatform_gemini_multiturn_chat]
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import com.google.cloud.vertexai.VertexAI;
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import com.google.cloud.vertexai.api.GenerateContentResponse;
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import com.google.cloud.vertexai.generativeai.preview.ChatSession;
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import com.google.cloud.vertexai.generativeai.preview.GenerativeModel;
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import com.google.cloud.vertexai.generativeai.preview.ResponseHandler;
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import com.google.cloud.vertexai.generativeai.ChatSession;
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import com.google.cloud.vertexai.generativeai.GenerativeModel;
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import com.google.cloud.vertexai.generativeai.ResponseHandler;
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import java.io.IOException;
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public class ChatDiscussion {

‎vertexai/snippets/src/main/java/vertexai/gemini/FunctionCalling.java‎

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/*
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* Copyright 2024 Google LLC
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*
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* Licensed under the Apache License, Version 2.0 (the "License");
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* you may not use this file except in compliance with the License.
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* 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
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* distributed under the License is distributed on an "AS IS" BASIS,
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* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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* See the License for the specific language governing permissions and
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* limitations under the License.
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*/
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package vertexai.gemini;
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// [START aiplatform_gemini_function_calling]
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import com.google.cloud.vertexai.VertexAI;
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import com.google.cloud.vertexai.api.Content;
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import com.google.cloud.vertexai.api.FunctionDeclaration;
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import com.google.cloud.vertexai.api.GenerateContentResponse;
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import com.google.cloud.vertexai.api.Schema;
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import com.google.cloud.vertexai.api.Tool;
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import com.google.cloud.vertexai.api.Type;
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import com.google.cloud.vertexai.generativeai.ChatSession;
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import com.google.cloud.vertexai.generativeai.ContentMaker;
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import com.google.cloud.vertexai.generativeai.GenerativeModel;
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import com.google.cloud.vertexai.generativeai.PartMaker;
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import com.google.cloud.vertexai.generativeai.ResponseHandler;
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import java.io.IOException;
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import java.util.Arrays;
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import java.util.Collections;
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public class FunctionCalling {
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public static void main(String[] args) throws IOException {
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// TODO(developer): Replace these variables before running the sample.
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String projectId = "your-google-cloud-project-id";
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String location = "us-central1";
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String modelName = "gemini-pro";
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String promptText = "What's the weather like in Paris?";
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whatsTheWeatherLike(projectId, location, modelName, promptText);
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}
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public static String whatsTheWeatherLike(String projectId, String location,
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String modelName, String promptText)
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throws IOException {
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try (VertexAI vertexAI = new VertexAI(projectId, location)) {
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FunctionDeclaration functionDeclaration = FunctionDeclaration.newBuilder()
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.setName("getCurrentWeather")
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.setDescription("Get the current weather in a given location")
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.setParameters(
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Schema.newBuilder()
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.setType(Type.OBJECT)
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.putProperties("location", Schema.newBuilder()
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.setType(Type.STRING)
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.setDescription("location")
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.build()
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)
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.addRequired("location")
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.build()
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)
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.build();
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System.out.println("Function declaration:");
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System.out.println(functionDeclaration);
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// Add the function to a "tool"
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Tool tool = Tool.newBuilder()
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.addFunctionDeclarations(functionDeclaration)
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.build();
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// Start a chat session from a model, with the use of the declared function.
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GenerativeModel model =
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GenerativeModel.newBuilder()
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.setModelName(modelName)
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.setVertexAi(vertexAI)
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.setTools(Arrays.asList(tool))
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.build();
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ChatSession chat = model.startChat();
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System.out.println(String.format("Ask the question: %s", promptText));
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GenerateContentResponse response = chat.sendMessage(promptText);
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// The model will most likely return a function call to the declared
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// function `getCurrentWeather` with "Paris" as the value for the
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// argument `location`.
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System.out.println("\nPrint response: ");
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System.out.println(ResponseHandler.getContent(response));
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// Provide an answer to the model so that it knows what the result
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// of a "function call" is.
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Content content =
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ContentMaker.fromMultiModalData(
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PartMaker.fromFunctionResponse(
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"getCurrentWeather",
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Collections.singletonMap("currentWeather", "sunny")));
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System.out.println("Provide the function response: ");
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System.out.println(content);
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response = chat.sendMessage(content);
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// See what the model replies now
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System.out.println("Print response: ");
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String finalAnswer = ResponseHandler.getText(response);
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System.out.println(finalAnswer);
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return finalAnswer;
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}
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}
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}
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// [END aiplatform_gemini_function_calling]

‎vertexai/snippets/src/main/java/vertexai/gemini/GetTokenCount.java‎

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// [START aiplatform_gemini_token_count]
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import com.google.cloud.vertexai.VertexAI;
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import com.google.cloud.vertexai.api.CountTokensResponse;
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import com.google.cloud.vertexai.generativeai.preview.GenerativeModel;
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import com.google.cloud.vertexai.generativeai.GenerativeModel;
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import java.io.IOException;
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// [END aiplatform_gemini_token_count]
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String location = "us-central1";
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String modelName = "gemini-pro-vision";
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String textPrompt = "How many tokens are there in this prompt?";
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String textPrompt = "Why is the sky blue?";
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getTokenCount(projectId, location, modelName, textPrompt);
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}
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‎vertexai/snippets/src/main/java/vertexai/gemini/MultiTurnMultimodal.java‎

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import com.google.cloud.vertexai.VertexAI;
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import com.google.cloud.vertexai.api.GenerateContentResponse;
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import com.google.cloud.vertexai.api.GenerationConfig;
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import com.google.cloud.vertexai.generativeai.preview.ChatSession;
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import com.google.cloud.vertexai.generativeai.preview.ContentMaker;
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import com.google.cloud.vertexai.generativeai.preview.GenerativeModel;
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import com.google.cloud.vertexai.generativeai.preview.PartMaker;
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import com.google.cloud.vertexai.generativeai.preview.ResponseHandler;
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import com.google.cloud.vertexai.generativeai.ChatSession;
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import com.google.cloud.vertexai.generativeai.ContentMaker;
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import com.google.cloud.vertexai.generativeai.GenerativeModel;
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import com.google.cloud.vertexai.generativeai.PartMaker;
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import com.google.cloud.vertexai.generativeai.ResponseHandler;
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import java.io.IOException;
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public class MultiTurnMultimodal {

‎vertexai/snippets/src/main/java/vertexai/gemini/MultimodalMultiImage.java‎

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import com.google.cloud.vertexai.VertexAI;
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import com.google.cloud.vertexai.api.Content;
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import com.google.cloud.vertexai.api.GenerateContentResponse;
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import com.google.cloud.vertexai.generativeai.preview.ContentMaker;
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import com.google.cloud.vertexai.generativeai.preview.GenerativeModel;
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import com.google.cloud.vertexai.generativeai.preview.PartMaker;
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import com.google.cloud.vertexai.generativeai.preview.ResponseHandler;
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import com.google.cloud.vertexai.generativeai.ContentMaker;
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import com.google.cloud.vertexai.generativeai.GenerativeModel;
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import com.google.cloud.vertexai.generativeai.PartMaker;
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import com.google.cloud.vertexai.generativeai.ResponseHandler;
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import java.io.ByteArrayOutputStream;
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import java.io.IOException;
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import java.io.InputStream;

‎vertexai/snippets/src/main/java/vertexai/gemini/MultimodalQuery.java‎

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// [START aiplatform_gemini_pro_example]
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import com.google.cloud.vertexai.VertexAI;
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import com.google.cloud.vertexai.api.GenerateContentResponse;
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import com.google.cloud.vertexai.generativeai.preview.ContentMaker;
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import com.google.cloud.vertexai.generativeai.preview.GenerativeModel;
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import com.google.cloud.vertexai.generativeai.preview.PartMaker;
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import com.google.cloud.vertexai.generativeai.preview.ResponseHandler;
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import com.google.cloud.vertexai.generativeai.ContentMaker;
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import com.google.cloud.vertexai.generativeai.GenerativeModel;
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import com.google.cloud.vertexai.generativeai.PartMaker;
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import com.google.cloud.vertexai.generativeai.ResponseHandler;
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import java.util.Base64;
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public class MultimodalQuery {

‎vertexai/snippets/src/main/java/vertexai/gemini/MultimodalVideoInput.java‎

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// [START aiplatform_gemini_single_turn_video]
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import com.google.cloud.vertexai.VertexAI;
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import com.google.cloud.vertexai.api.GenerateContentResponse;
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import com.google.cloud.vertexai.generativeai.preview.ContentMaker;
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import com.google.cloud.vertexai.generativeai.preview.GenerativeModel;
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import com.google.cloud.vertexai.generativeai.preview.PartMaker;
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import com.google.cloud.vertexai.generativeai.preview.ResponseHandler;
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import com.google.cloud.vertexai.generativeai.ContentMaker;
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import com.google.cloud.vertexai.generativeai.GenerativeModel;
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import com.google.cloud.vertexai.generativeai.PartMaker;
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import com.google.cloud.vertexai.generativeai.ResponseHandler;
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import java.io.IOException;
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public class MultimodalVideoInput {

‎vertexai/snippets/src/main/java/vertexai/gemini/QuestionAnswer.java‎

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import com.google.cloud.vertexai.VertexAI;
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import com.google.cloud.vertexai.api.GenerateContentResponse;
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import com.google.cloud.vertexai.generativeai.preview.GenerativeModel;
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import com.google.cloud.vertexai.generativeai.preview.ResponseHandler;
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import com.google.cloud.vertexai.generativeai.GenerativeModel;
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import com.google.cloud.vertexai.generativeai.ResponseHandler;
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public class QuestionAnswer {
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‎vertexai/snippets/src/main/java/vertexai/gemini/Quickstart.java‎

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// [START aiplatform_gemini_get_started]
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import com.google.cloud.vertexai.VertexAI;
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import com.google.cloud.vertexai.api.GenerateContentResponse;
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import com.google.cloud.vertexai.generativeai.preview.ContentMaker;
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import com.google.cloud.vertexai.generativeai.preview.GenerativeModel;
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import com.google.cloud.vertexai.generativeai.preview.PartMaker;
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import com.google.cloud.vertexai.generativeai.ContentMaker;
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import com.google.cloud.vertexai.generativeai.GenerativeModel;
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import com.google.cloud.vertexai.generativeai.PartMaker;
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import java.io.IOException;
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public class Quickstart {

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