SDK de IA generativa do Google

O SDK de IA generativa do Google oferece uma interface unificada para os modelos do Gemini pela API Gemini Developer e pela API Gemini na Gemini Enterprise Agent Platform. Com algumas exceções, o código executado em uma plataforma será executado nas duas. Isso significa que você pode criar um protótipo de aplicativo usando a API Gemini Developer e migrar o aplicativo para a Gemini Enterprise Agent Platform sem reescrever o código.

Para saber mais sobre as diferenças entre a API Gemini Developer e o Gemini na Gemini Enterprise Agent Platform, consulte Migrar da API Gemini Developer para a API Gemini na Gemini Enterprise Agent Platform.

Python

O SDK de IA generativa do Google para Python está disponível no PyPI e no GitHub:

Para saber mais, consulte a referência do SDK para Python.

Instalar

pip install --upgrade google-genai

Defina variáveis de ambiente para usar o SDK de IA generativa com a Vertex AI: 

# Replace the `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION` values
# with appropriate values for your project.
export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT
export GOOGLE_CLOUD_LOCATION=global
export GOOGLE_GENAI_USE_ENTERPRISE=True

Guia de início rápido

Escolha uma das seguintes opções, dependendo se você está usando a Agent Platform no modo expresso ou não.

  • Usar a Agent Platform (com todos os Google Cloud recursos e serviços)
from google import genai
from google.genai.types import HttpOptions

client = genai.Client(http_options=HttpOptions(api_version="v1"))
response = client.models.generate_content(
    model="gemini-2.5-flash",
    contents="How does AI work?",
)
print(response.text)
# Example response:
# Okay, let's break down how AI works. It's a broad field, so I'll focus on the ...
#
# Here's a simplified overview:
# ...
  • Usar a Agent Platform no modo expresso
from google import genai

# TODO(developer): Update below line
API_KEY = "YOUR_API_KEY"

client = genai.Client(vertexai=True, api_key=API_KEY)

response = client.models.generate_content(
    model="gemini-2.5-flash",
    contents="Explain bubble sort to me.",
)

print(response.text)
# Example response:
# Bubble Sort is a simple sorting algorithm that repeatedly steps through the list

Go

O SDK de IA generativa do Google para Go está disponível no go.dev e no GitHub:

Instalar

go get google.golang.org/genai

Defina variáveis de ambiente para usar o SDK de IA generativa com a Vertex AI: 

# Replace the `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION` values
# with appropriate values for your project.
export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT
export GOOGLE_CLOUD_LOCATION=global
export GOOGLE_GENAI_USE_ENTERPRISE=True

Guia de início rápido

import (
	"context"
	"fmt"
	"io"

	"google.golang.org/genai"
)

// generateWithText shows how to generate text using a text prompt.
func generateWithText(w io.Writer) error {
	ctx := context.Background()

	client, err := genai.NewClient(ctx, &genai.ClientConfig{
		HTTPOptions: genai.HTTPOptions{APIVersion: "v1"},
	})
	if err != nil {
		return fmt.Errorf("failed to create genai client: %w", err)
	}

	resp, err := client.Models.GenerateContent(ctx,
		"gemini-2.5-flash",
		genai.Text("How does AI work?"),
		nil,
	)
	if err != nil {
		return fmt.Errorf("failed to generate content: %w", err)
	}

	respText := resp.Text()

	fmt.Fprintln(w, respText)
	// Example response:
	// That's a great question! Understanding how AI works can feel like ...
	// ...
	// **1. The Foundation: Data and Algorithms**
	// ...

	return nil
}

Node.js

O SDK de IA generativa do Google para TypeScript e JavaScript está disponível no npm e no GitHub:

Instalar

npm install @google/genai

Defina variáveis de ambiente para usar o SDK de IA generativa com a Vertex AI: 

# Replace the `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION` values
# with appropriate values for your project.
export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT
export GOOGLE_CLOUD_LOCATION=global
export GOOGLE_GENAI_USE_ENTERPRISE=True

Guia de início rápido

/**
 * @license
 * Copyright 2025 Google LLC
 * SPDX-License-Identifier: Apache-2.0
 */
import {GoogleGenAI} from '@google/genai';

const GEMINI_API_KEY = process.env.GEMINI_API_KEY;
const GOOGLE_CLOUD_PROJECT = process.env.GOOGLE_CLOUD_PROJECT;
const GOOGLE_CLOUD_LOCATION = process.env.GOOGLE_CLOUD_LOCATION;
const GOOGLE_GENAI_USE_VERTEXAI = process.env.GOOGLE_GENAI_USE_VERTEXAI;

async function generateContentFromMLDev() {
  const ai = new GoogleGenAI({vertexai: false, apiKey: GEMINI_API_KEY});
  const response = await ai.models.generateContent({
    model: 'gemini-2.0-flash',
    contents: 'why is the sky blue?',
  });
  console.debug(response.text);
}

async function generateContentFromVertexAI() {
  const ai = new GoogleGenAI({
    vertexai: true,
    project: GOOGLE_CLOUD_PROJECT,
    location: GOOGLE_CLOUD_LOCATION,
  });
  const response = await ai.models.generateContent({
    model: 'gemini-2.0-flash',
    contents: 'why is the sky blue?',
  });
  console.debug(response.text);
}

async function main() {
  if (GOOGLE_GENAI_USE_VERTEXAI) {
    await generateContentFromVertexAI().catch((e) =>
      console.error('got error', e),
    );
  } else {
    await generateContentFromMLDev().catch((e) =>
      console.error('got error', e),
    );
  }
}

main();

Java

O SDK de IA generativa do Google para Java está disponível no Maven Central e no GitHub:

Instalação do Maven

<dependencies>
  <dependency>
    <groupId>com.google.genai</groupId>
    <artifactId>google-genai</artifactId>
    <version>1.4.1</version>
  </dependency>
</dependencies>

Defina variáveis de ambiente para usar o SDK de IA generativa com a Vertex AI: 

# Replace the `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION` values
# with appropriate values for your project.
export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT
export GOOGLE_CLOUD_LOCATION=global
export GOOGLE_GENAI_USE_ENTERPRISE=True

Guia de início rápido

/*
 * Copyright 2025 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.
 */

/**
 * Usage:
 *
 * <p>1a. If you are using Vertex AI, setup ADC to get credentials:
 * https://cloud.google.com/docs/authentication/provide-credentials-adc#google-idp
 *
 * <p>Then set Project, Location, and USE_VERTEXAI flag as environment variables:
 *
 * <p>export GOOGLE_CLOUD_PROJECT=YOUR_PROJECT
 *
 * <p>export GOOGLE_CLOUD_LOCATION=YOUR_LOCATION
 *
 * <p>export GOOGLE_GENAI_USE_VERTEXAI=true
 *
 * <p>1b. If you are using Gemini Developer API, set an API key environment variable. You can find a
 * list of available API keys here: https://aistudio.google.com/app/apikey
 *
 * <p>export GOOGLE_API_KEY=YOUR_API_KEY
 *
 * <p>2. Compile the java package and run the sample code.
 *
 * <p>mvn clean compile exec:java -Dexec.mainClass="com.google.genai.examples.GenerateContent"
 * -Dexec.args="YOUR_MODEL_ID"
 */
package com.google.genai.examples;

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

/** An example of using the Unified Gen AI Java SDK to generate content. */
public final class GenerateContent {
  public static void main(String[] args) {
    final String modelId;
    if (args.length != 0) {
      modelId = args[0];
    } else {
      modelId = Constants.GEMINI_MODEL_NAME;
    }

    // Instantiate the client. The client by default uses the Gemini Developer API. It gets the API
    // key from the environment variable `GOOGLE_API_KEY`. Vertex AI API can be used by setting the
    // environment variables `GOOGLE_CLOUD_LOCATION` and `GOOGLE_CLOUD_PROJECT`, as well as setting
    // `GOOGLE_GENAI_USE_VERTEXAI` to "true".
    //
    // Note: Some services are only available in a specific API backend (Gemini or Vertex), you will
    // get a `UnsupportedOperationException` if you try to use a service that is not available in
    // the backend you are using.
    Client client = new Client();

    if (client.vertexAI()) {
      System.out.println("Using Vertex AI");
    } else {
      System.out.println("Using Gemini Developer API");
    }

    GenerateContentResponse response =
        client.models.generateContent(modelId, "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());

    // Gets the http headers from the response.
    response
        .sdkHttpResponse()
        .ifPresent(
            httpResponse ->
                System.out.println("Response headers: " + httpResponse.headers().orElse(null)));
  }

  private GenerateContent() {}
}

C#

O SDK de IA generativa do Google para .NET está disponível no NuGet e no GitHub:

Instalar

dotnet add package Google.GenAI

Defina variáveis de ambiente para usar o SDK de IA generativa com a Vertex AI: 

# Replace the `GOOGLE_CLOUD_PROJECT` and `GOOGLE_CLOUD_LOCATION` values
# with appropriate values for your project.
export GOOGLE_CLOUD_PROJECT=GOOGLE_CLOUD_PROJECT
export GOOGLE_CLOUD_LOCATION=global
export GOOGLE_GENAI_USE_ENTERPRISE=True

Guia de início rápido

/*
 * Copyright 2025 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.
 */

using Google.GenAI;
using Google.GenAI.Types;

public class GenerateContentSimpleText {
  public static async Task SendRequestAsync() {
    string apiKey = System.Environment.GetEnvironmentVariable("GOOGLE_API_KEY");
    var geminiClient = new Client(apiKey: apiKey);
    try {
      var geminiResponse = await geminiClient.Models.GenerateContentAsync(
          model: "gemini-2.0-flash", contents: "What is the capital of France?");
      Console.WriteLine("Gemini API Response:");
      Console.WriteLine(geminiResponse.Text);
    } catch (HttpRequestException ex) {
      Console.WriteLine($"An error occurred with Gemini API: {ex.ToString()}");
    }

    string project = System.Environment.GetEnvironmentVariable("GOOGLE_CLOUD_PROJECT");
    string location = System.Environment.GetEnvironmentVariable("GOOGLE_CLOUD_LOCATION") ?? "us-central1";
    Content contents = new Content {
      Role = "user", Parts = new List<Part> { new Part { Text = "What is the capital of France?" } }
    };

    var vertexClient = new Client(project: project, location: location, vertexAI: true);
    try {
      var vertexResponse = await vertexClient.Models.GenerateContentAsync(model: "gemini-2.0-flash",
                                                                          contents: contents);
      Console.WriteLine("Vertex AI API Response:");
      Console.WriteLine(vertexResponse.Text);
    } catch (Exception ex) {
      Console.WriteLine($"An error occurred with Vertex AI API: {ex.Message}");
    }
  }
}