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Google Gen AI SDK

El SDK de Google Gen AI proporciona una interfaz unificada a Gemini 2.0 a través de la API para desarrolladores de Gemini y la API de Gemini en Vertex AI. Con algunas excepciones, el código que se ejecuta en una plataforma se ejecutará en ambas. Esto significa que puedes crear prototipos de una aplicación con la API para desarrolladores y, luego, migrar la aplicación a Vertex AI sin reescribir el código.

El SDK de IA generativa de Google también admite los modelos de Gemini 1.5.

Gen AI SDK for Python

El SDK de Google Gen AI para Python está disponible en PyPI y GitHub:

Para obtener más información, consulta la referencia del SDK de Python.

Instalar

pip install google-genai

Establece variables de entorno para usar el SDK de Gen AI con 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=us-central1
export GOOGLE_GENAI_USE_VERTEXAI=True

Guía de inicio rápido

Elige una de las siguientes opciones, según si usas Vertex AI en el modo exprés o no.

Usa Vertex AI (con todas las Google Cloud funciones y servicios)

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-2.0-flash-001",
    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:
# ...

Cómo usar Vertex AI en modo exprés

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-2.0-flash-001",
    contents="""Explain bubble sort to me.""",
)

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

Gen AI SDK for Go

El SDK de IA generativa de Google para Go está disponible en go.dev y GitHub:

Instalar

go get google.golang.org/genai

Establece variables de entorno para usar el SDK de Gen AI con 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=us-central1
export GOOGLE_GENAI_USE_VERTEXAI=True

Guía de inicio 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-2.0-flash-001",
		genai.Text("How does AI work?"),
		nil,
	)
	if err != nil {
		return fmt.Errorf("failed to generate content: %w", err)
	}

	respText, err := resp.Text()
	if err != nil {
		return fmt.Errorf("failed to convert model response to text: %w", err)
	}
	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
}

Gen AI SDK for Java

El SDK de Google Gen AI para Java está disponible en Maven Central y GitHub:

Instalación de Maven

<dependencies>
  <dependency>
    <groupId>com.google.genai</groupId>
    <artifactId>google-genai</artifactId>
    <version>0.1.0</version>
  </dependency>
</dependencies>

Establece variables de entorno para usar el SDK de Gen AI con 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=us-central1
export GOOGLE_GENAI_USE_VERTEXAI=True

Guía de inicio 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>1b. If you are using Gemini Developer AI, 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"
 */
package com.google.genai.examples;

import com.google.genai.Client;
import com.google.genai.types.GenerateContentResponse;
import java.io.IOException;
import org.apache.http.HttpException;

/** An example of using the Unified Gen AI Java SDK to generate content. */
public class GenerateContent {
  public static void main(String[] args) throws IOException, HttpException {
    // Instantiate the client. The client by default uses the Gemini Developer 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());
  }
}