SDK Google Gen AI

L'SDK Google Gen AI fornisce un'interfaccia unificata per Gemini 2.0 e 1.5 tramite sia l'API Gemini Developer sia l'API Gemini su Vertex AI. Con alcune eccezioni, il codice che viene eseguito su una piattaforma verrà eseguito su entrambe. Ciò significa che puoi realizzare il prototipo di un'applicazione utilizzando l'API Developer e poi eseguirne la migrazione a Vertex AI senza riscriverne il codice.

Gen AI SDK for Python

L'SDK Google AI generativa per Python è disponibile su PyPI e GitHub:

Per scoprire di più, consulta la documentazione di riferimento dell'SDK Python.

Installa

pip install --upgrade google-genai

Imposta le variabili di ambiente per utilizzare l'SDK 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

Guida rapida

Scegli una delle seguenti opzioni, a seconda che tu stia utilizzando Vertex AI in modalità Express o meno.

  • Utilizzare Vertex AI (con tutte le funzionalità e i servizi) Google Cloud
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:
# ...
  • Utilizzare Vertex AI in modalità Express
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

Google Gen AI SDK per Go è disponibile su go.dev e GitHub:

Installa

go get google.golang.org/genai

Imposta le variabili di ambiente per utilizzare l'SDK 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

Guida rapida

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 Node.js

L'SDK Google Gen AI per TypeScript e JavaScript è disponibile su npm e GitHub:

Installa

npm install @google/genai

Imposta le variabili di ambiente per utilizzare l'SDK 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

Guida rapida

/**
 * @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();

Gen AI SDK for Java

L'SDK Google AI generativa per Java è disponibile su Maven Central e GitHub:

Installazione Maven

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

Imposta le variabili di ambiente per utilizzare l'SDK 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

Guida rapida

/*
 * 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;

/** An example of using the Unified Gen AI Java SDK to generate content. */
public class GenerateContent {
  public static void main(String[] args) {
    // 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());
  }
}