import com.google.genai.Client;

// The simplest way for instantiation. The client gets the API key from the
// environment variable `GOOGLE_API_KEY` and use Gemini API when the environment
// variable `GOOGLE_GENAI_USE_VERTEXAI` is not set or set to `false`.
Client client = new Client();

// Use Builder class for instantiation. Explicitly set the API key to use Gemini
// Developer backend.
Client client = Client.builder().apiKey("your-api-key").build();

import com.google.genai.Client;

// The client gets the project and location from the environment variable
// `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION`. It uses Vertex AI APIs
// when the environment variable `GOOGLE_GENAI_USE_VERTEXAI` is set to `true`.
Client client = new Client();

// Use Builder class for instantiation. Explicitly set the project and location,
// and set `vertexAI(true)` to use Vertex AI backend.
Client client = Client.builder()
  .project("your-project")
  .location("your-location")
  .vertexAI(true)
  .build();

package <your package name>;

import com.google.genai.Client;
import com.google.genai.types.GenerateContentResponse;

public class GenerateContentWithTextInput {
  public static void main(String[] args) {
    // Instantiate the client. The client by default uses the Gemini API. It
    //  gets the API key from the environment variable `GOOGLE_API_KEY`.
    Client client = new Client();

    GenerateContentResponse response =
        client.models.generateContent("gemini-2.0-flash-001", "What is your name?", null);

    // Gets the text string from the response by the quick accessor method `text()`.
    System.out.println("Unary response: " + response.text());
  }
}

package <your package name>;

import com.google.common.collect.ImmutableList;
import com.google.genai.Client;
import com.google.genai.types.Content;
import com.google.genai.types.GenerateContentResponse;
import com.google.genai.types.Part;

public class GenerateContentWithImageInput {
  public static void main(String[] args) {
    // Instantiate the client using Vertex API. The client gets the project and
    // location from the environment variables `GOOGLE_CLOUD_PROJECT` and
    // `GOOGLE_CLOUD_LOCATION`.
    Client client = Client.builder().vertexAI(true).build();

    // Construct a multimodal content with quick constructors
    Content content =
        Content.fromParts(
            Part.fromText("describe the image"),
            Part.fromUri("gs://path/to/image.jpg", "image/jpeg"));

    GenerateContentResponse response =
        client.models.generateContent("gemini-2.0-flash-001", content, null);

    System.out.println("Response: " + response.text());
  }
}

import com.google.common.collect.ImmutableList;
import com.google.genai.Client;
import com.google.genai.types.GenerateContentConfig;
import com.google.genai.types.GenerateContentResponse;
import com.google.genai.types.Tool;
import java.lang.reflect.Method;

public class GenerateContentWithFunctionCall {
  public static String getCurrentWeather(String location, String unit) {
    return "The weather in " + location + " is " + "very nice.";
  }

  public static void main(String[] args) throws NoSuchMethodException {
    Client client = new Client();

    Method method =
        GenerateContentWithFunctionCall.class.getMethod(
            "getCurrentWeather", String.class, String.class);

    GenerateContentConfig config =
        GenerateContentConfig.builder()
            .tools(
                ImmutableList.of(
                    Tool.builder().functions(ImmutableList.of(method)).build()))
            .build();

    GenerateContentResponse response =
        client.models.generateContent(
            "gemini-2.0-flash-001",
            "What is the weather in Vancouver?",
            config);

    System.out.println("The response is: " + response.text());
    System.out.println(
        "The automatic function calling history is: "
            + response.automaticFunctionCallingHistory().get());
  }
}

package <your package name>;

import com.google.genai.Client;
import com.google.genai.ResponseStream;
import com.google.genai.types.GenerateContentResponse;

public class StreamGeneration {
  public static void main(String[] args) {
    // Instantiate the client using Vertex API. The client gets the project and location from the
    // environment variables `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION`.
    Client client = Client.builder().vertexAI(true).build();

    ResponseStream<GenerateContentResponse> responseStream =
        client.models.generateContentStream(
            "gemini-2.0-flash-001", "Tell me a story in 300 words.", null);

    System.out.println("Streaming response: ");
    for (GenerateContentResponse res : responseStream) {
      System.out.print(res.text());
    }

    // To save resources and avoid connection leaks, it is recommended to close the response
    // stream after consumption (or using try block to get the response stream).
    responseStream.close();
  }
}

package <your package name>;

import com.google.genai.Client;
import com.google.genai.types.GenerateContentResponse;
import java.util.concurrent.CompletableFuture;

public class GenerateContentAsync {
  public static void main(String[] args) {
    // Instantiates the client using Gemini API, and sets the API key in the builder.
    Client client = Client.builder().apiKey("your-api-key").build();

    CompletableFuture<GenerateContentResponse> responseFuture =
        client.async.models.generateContent(
            "gemini-2.0-flash-001", "Introduce Google AI Studio.", null);

    responseFuture
        .thenAccept(
            response -> {
              System.out.println("Async response: " + response.text());
            })
        .join();
  }
}

package <your package name>;

import com.google.common.collect.ImmutableList;
import com.google.genai.Client;
import com.google.genai.types.Content;
import com.google.genai.types.GenerateContentConfig;
import com.google.genai.types.GenerateContentResponse;
import com.google.genai.types.GoogleSearch;
import com.google.genai.types.HarmBlockThreshold;
import com.google.genai.types.HarmCategory;
import com.google.genai.types.Part;
import com.google.genai.types.SafetySetting;
import com.google.genai.types.Tool;

public class GenerateContentWithConfigs {
  public static void main(String[] args) {
    Client client = new Client();

    // Sets the safety settings in the config.
    ImmutableList<SafetySetting> safetySettings =
        ImmutableList.of(
            SafetySetting.builder()
                .category(HarmCategory.Known.HARM_CATEGORY_HATE_SPEECH)
                .threshold(HarmBlockThreshold.Known.BLOCK_ONLY_HIGH)
                .build(),
            SafetySetting.builder()
                .category(HarmCategory.Known.HARM_CATEGORY_DANGEROUS_CONTENT)
                .threshold(HarmBlockThreshold.Known.BLOCK_LOW_AND_ABOVE)
                .build());

    // Sets the system instruction in the config.
    Content systemInstruction = Content.fromParts(Part.fromText("You are a history teacher."));

    // Sets the Google Search tool in the config.
    Tool googleSearchTool = Tool.builder().googleSearch(GoogleSearch.builder().build()).build();

    GenerateContentConfig config =
        GenerateContentConfig.builder()
            .candidateCount(1)
            .maxOutputTokens(1024)
            .safetySettings(safetySettings)
            .systemInstruction(systemInstruction)
            .tools(ImmutableList.of(googleSearchTool))
            .build();

    GenerateContentResponse response =
        client.models.generateContent("gemini-2.0-flash-001", "Tell me the history of LLM", config);

    System.out.println("Response: " + response.text());
  }
}

package <your package name>;

import com.google.common.collect.ImmutableMap;
import com.google.genai.Client;
import com.google.genai.types.GenerateContentConfig;
import com.google.genai.types.GenerateContentResponse;
import com.google.genai.types.Schema;
import com.google.genai.types.Type;

public class GenerateContentWithSchema {
  public static void main(String[] args) {
    Client client = new Client();

    Schema schema =
        Schema.builder()
            .type("object")
            .properties(
                ImmutableMap.of(
                    "name", Schema.builder().type(Type.Known.STRING).description("Your Name").build()))
            .build();
    GenerateContentConfig config =
        GenerateContentConfig.builder()
            .responseMimeType("application/json")
            .candidateCount(1)
            .responseSchema(schema)
            .build();

    GenerateContentResponse response =
        client.models.generateContent("gemini-2.0-flash-001", "Tell me your name", config);

    System.out.println("Response: " + response.text());
  }
}