Add examples for google-ai-gemini module

google-ai-gemini-examples/pom.xml

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+<?xml version="1.0" encoding="UTF-8"?>
+<project xmlns="http://maven.apache.org/POM/4.0.0"
+         xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance"
+         xsi:schemaLocation="http://maven.apache.org/POM/4.0.0 http://maven.apache.org/xsd/maven-4.0.0.xsd">
+    <modelVersion>4.0.0</modelVersion>
+
+    <groupId>dev.langchain4j</groupId>
+    <artifactId>google-ai-gemini-examples</artifactId>
+    <version>1.9.1</version>
+
+    <properties>
+        <maven.compiler.source>17</maven.compiler.source>
+        <maven.compiler.target>17</maven.compiler.target>
+        <project.build.sourceEncoding>UTF-8</project.build.sourceEncoding>
+    </properties>
+
+    <dependencyManagement>
+        <dependencies>
+            <dependency>
+                <groupId>dev.langchain4j</groupId>
+                <artifactId>langchain4j-bom</artifactId>
+                <version>1.9.1</version>
+                <type>pom</type>
+                <scope>import</scope>
+            </dependency>
+        </dependencies>
+    </dependencyManagement>
+
+    <dependencies>
+
+        <dependency>
+            <groupId>dev.langchain4j</groupId>
+            <artifactId>langchain4j-google-ai-gemini</artifactId>
+        </dependency>
+
+        <dependency>
+            <groupId>dev.langchain4j</groupId>
+            <artifactId>langchain4j</artifactId>
+        </dependency>
+
+        <dependency>
+            <groupId>dev.langchain4j</groupId>
+            <artifactId>langchain4j-embeddings-all-minilm-l6-v2</artifactId>
+        </dependency>
+
+        <dependency>
+            <groupId>org.tinylog</groupId>
+            <artifactId>tinylog-impl</artifactId>
+            <version>2.6.2</version>
+        </dependency>
+        <dependency>
+            <groupId>org.tinylog</groupId>
+            <artifactId>slf4j-tinylog</artifactId>
+            <version>2.6.2</version>
+        </dependency>
+
+    </dependencies>
+
+</project>

google-ai-gemini-examples/src/main/java/dev/langchain4j/example/gemini/Example01_SimpleChat.java

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+package dev.langchain4j.example.gemini;
+
+import dev.langchain4j.model.chat.ChatModel;
+import dev.langchain4j.model.googleai.GoogleAiGeminiChatModel;
+
+/**
+ * A simple example demonstrating basic chat functionality with Google AI Gemini.
+ *
+ * <p>This example shows how to:
+ * <ul>
+ *   <li>Create a {@link GoogleAiGeminiChatModel} using the builder pattern</li>
+ *   <li>Send a simple text message and receive a response</li>
+ * </ul>
+ *
+ * <p>Requires the {@code GOOGLE_AI_GEMINI_API_KEY} environment variable to be set or by other means to get the API key.
+ */
+public class Example01_SimpleChat {
+    public static void main(String[] args) {
+        String apiKey = System.getenv("GOOGLE_AI_GEMINI_API_KEY");
+        ChatModel model = GoogleAiGeminiChatModel.builder()
+                .apiKey(apiKey)
+                .modelName("gemini-2.5-flash-lite")
+                .build();
+
+        String response = model.chat("What is the capital of France?");
+
+        System.out.println(response);
+    }
+}

google-ai-gemini-examples/src/main/java/dev/langchain4j/example/gemini/Example02_StreamingChat.java

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+package dev.langchain4j.example.gemini;
+
+import dev.langchain4j.model.chat.response.ChatResponse;
+import dev.langchain4j.model.chat.response.StreamingChatResponseHandler;
+import dev.langchain4j.model.googleai.GoogleAiGeminiStreamingChatModel;
+
+import java.util.concurrent.CompletableFuture;
+import java.util.concurrent.ExecutionException;
+import java.util.concurrent.TimeoutException;
+
+import static java.util.concurrent.TimeUnit.SECONDS;
+
+/**
+ * Demonstrates streaming chat responses with Google AI Gemini.
+ *
+ * <p>This example shows how to:
+ * <ul>
+ *   <li>Create a {@link GoogleAiGeminiStreamingChatModel}</li>
+ *   <li>Receive tokens as they are generated in real-time</li>
+ *   <li>Handle completion and error callbacks</li>
+ * </ul>
+ *
+ * <p>Requires the {@code GOOGLE_AI_GEMINI_API_KEY} environment variable to be set.
+ */
+public class Example02_StreamingChat {
+     static class WaitingChatResponseHandler implements StreamingChatResponseHandler {
+        // Future used to wait for a response
+        private final CompletableFuture<ChatResponse> futureResponse = new CompletableFuture<>();
+
+        @Override
+        public void onPartialResponse(String partialResponse) {
+            System.out.print(partialResponse);
+        }
+
+        @Override
+        public void onCompleteResponse(ChatResponse completeResponse) {
+            System.out.println("\n\n--- Complete ---");
+            System.out.println("Finish reason: " + completeResponse.finishReason());
+            System.out.println("Tokens used: " + completeResponse.tokenUsage().totalTokenCount());
+            System.out.println("Completed message text: " + completeResponse.aiMessage().text());
+            futureResponse.complete(completeResponse);
+        }
+
+        @Override
+        public void onError(Throwable error) {
+            System.err.println("Error: " + error.getMessage());
+        }
+    };
+
+    public static void main(String[] args) throws InterruptedException, ExecutionException, TimeoutException {
+        var model = GoogleAiGeminiStreamingChatModel.builder()
+                .apiKey(System.getenv("GOOGLE_AI_GEMINI_API_KEY"))
+                .modelName("gemini-2.5-flash-lite")
+                .build();
+
+        // Set up the handler - what to do when messages are received.
+        var handler = new WaitingChatResponseHandler();
+
+        // Send the chat request. This will start calling onPartialResponse as tokens are returned from Gemini. And
+        // later calls onCompleteResponse - with the entire message - once Gemini is finished.
+        model.chat("Explain quantum computing in simple terms", handler);
+
+        // Wait for the future to complete or 60 seconds, whatever comes first.
+        handler.futureResponse.get(60, SECONDS);
+    }
+}

google-ai-gemini-examples/src/main/java/dev/langchain4j/example/gemini/Example03_SimpleEmbedding.java

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+package dev.langchain4j.example.gemini;
+
+import dev.langchain4j.data.embedding.Embedding;
+import dev.langchain4j.model.googleai.GoogleAiEmbeddingModel;
+import dev.langchain4j.model.output.Response;
+
+/**
+ * Demonstrates generating embeddings with Google AI Gemini.
+ *
+ * <p>This example shows how to:
+ * <ul>
+ *   <li>Create a {@link GoogleAiEmbeddingModel}</li>
+ *   <li>Generate an embedding vector from text</li>
+ *   <li>Access embedding dimensions and values</li>
+ * </ul>
+ *
+ * <p>Requires the {@code GOOGLE_AI_GEMINI_API_KEY} environment variable to be set.
+ *
+ * <p>Learn <a href="https://ai.google.dev/gemini-api/docs/embeddings>more</a></p>
+ */
+public class Example03_SimpleEmbedding {
+
+    public static void main(String[] args) {
+        GoogleAiEmbeddingModel model = GoogleAiEmbeddingModel.builder()
+                .apiKey(System.getenv("GOOGLE_AI_GEMINI_API_KEY"))
+                .modelName("gemini-embedding-001")
+                .outputDimensionality(1536)
+                .build();
+
+        Response<Embedding> response = model.embed("The quick brown fox jumps over the lazy dog.");
+
+        Embedding embedding = response.content();
+
+        System.out.println("Embedding dimension: " + embedding.dimension());
+        System.out.println("First 10 values: ");
+        for (int i = 0; i < 10; i++) {
+            System.out.printf("  [%d]: %.6f%n", i, embedding.vector()[i]);
+        }
+    }
+}

google-ai-gemini-examples/src/main/java/dev/langchain4j/example/gemini/Example04_TokenCounting.java

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+package dev.langchain4j.example.gemini;
+
+import dev.langchain4j.data.message.SystemMessage;
+import dev.langchain4j.data.message.UserMessage;
+import dev.langchain4j.model.googleai.GoogleAiGeminiTokenCountEstimator;
+
+import java.util.List;
+
+/**
+ * Demonstrates token counting with Google AI Gemini.
+ *
+ * <p>This example shows how to:
+ * <ul>
+ *   <li>Create a {@link GoogleAiGeminiTokenCountEstimator}</li>
+ *   <li>Estimate tokens in plain text</li>
+ *   <li>Estimate tokens in single and multiple messages</li>
+ * </ul>
+ *
+ * <p>Requires the {@code GOOGLE_AI_GEMINI_API_KEY} environment variable to be set.
+ *
+ * <p>Learn <a href="https://ai.google.dev/gemini-api/docs/tokens">more</a></p>
+ */
+public class Example04_TokenCounting {
+
+    public static void main(String[] args) {
+        GoogleAiGeminiTokenCountEstimator tokenEstimator = GoogleAiGeminiTokenCountEstimator.builder()
+                .apiKey(System.getenv("GOOGLE_AI_GEMINI_API_KEY"))
+                .modelName("gemini-2.5-flash-lite")
+                .build();
+
+        // Count tokens in plain text
+        String text = "The quick brown fox jumps over the lazy dog.";
+        int textTokens = tokenEstimator.estimateTokenCountInText(text);
+        System.out.println("Plain Text token count: " + textTokens);
+
+        // Count tokens in a single message
+        UserMessage userMessage = UserMessage.from("What is the capital of France?");
+        int messageTokens = tokenEstimator.estimateTokenCountInMessage(userMessage);
+        System.out.println("\nSingle message token count: " + messageTokens);
+
+        // Count tokens in multiple messages
+        SystemMessage systemMessage = SystemMessage.from("You are a helpful assistant.");
+        UserMessage question = UserMessage.from("Explain quantum computing in simple terms.");
+        int conversationTokens = tokenEstimator.estimateTokenCountInMessages(List.of(systemMessage, question));
+        System.out.println("\nConversation token count: " + conversationTokens);
+    }
+}

google-ai-gemini-examples/src/main/java/dev/langchain4j/example/gemini/Example05_ChatWithJsonResponse.java

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+package dev.langchain4j.example.gemini;
+
+import dev.langchain4j.model.chat.ChatModel;
+import dev.langchain4j.model.chat.request.ChatRequest;
+import dev.langchain4j.model.chat.request.ResponseFormat;
+import dev.langchain4j.model.chat.request.json.JsonObjectSchema;
+import dev.langchain4j.model.chat.request.json.JsonSchema;
+import dev.langchain4j.model.chat.request.json.JsonStringSchema;
+import dev.langchain4j.model.chat.request.json.JsonIntegerSchema;
+import dev.langchain4j.model.chat.request.json.JsonArraySchema;
+import dev.langchain4j.model.chat.response.ChatResponse;
+import dev.langchain4j.model.googleai.GoogleAiGeminiChatModel;
+import dev.langchain4j.data.message.UserMessage;
+
+import java.util.List;
+
+/**
+ * Demonstrates structured JSON responses with Google AI Gemini.
+ *
+ * <p>This example shows how to:
+ * <ul>
+ *   <li>Define a JSON schema for the expected response structure</li>
+ *   <li>Configure the model to return responses matching the schema</li>
+ *   <li>Parse structured data from model responses</li>
+ * </ul>
+ *
+ * <p>Requires the {@code GOOGLE_AI_GEMINI_API_KEY} environment variable to be set.
+ *
+ * <p>Learn <a href="https://docs.langchain4j.dev/tutorials/structured-outputs">more</a></p>
+ */
+public class Example05_ChatWithJsonResponse {
+
+    public static void main(String[] args) {
+        ChatModel model = GoogleAiGeminiChatModel.builder()
+                .apiKey(System.getenv("GOOGLE_AI_GEMINI_API_KEY"))
+                .modelName("gemini-2.5-flash-lite")
+                .build();
+
+        JsonObjectSchema personSchema = JsonObjectSchema.builder()
+                .addStringProperty("name")
+                .addIntegerProperty("age")
+                .addStringProperty("occupation")
+                .addProperty("hobbies", JsonArraySchema.builder()
+                        .items(new JsonStringSchema())
+                        .build())
+                .required("name", "age", "occupation", "hobbies")
+                .build();
+
+        ResponseFormat responseFormat = ResponseFormat.builder()
+                .type(ResponseFormat.JSON.type())
+                .jsonSchema(JsonSchema.builder().name("person").rootElement(personSchema).build())
+                .build();
+
+        ChatRequest request = ChatRequest.builder()
+                .messages(List.of(UserMessage.from(
+                        "Generate a fictional person with a name, age, occupation, and 3 hobbies.")))
+                .responseFormat(responseFormat)
+                .build();
+
+        ChatResponse response = model.chat(request);
+
+        System.out.println("Structured JSON response:");
+        System.out.println(response.aiMessage().text());
+    }
+}