Google Gen AI SDK

Google Gen AI SDK 透過 Vertex AI 的 Gemini Developer API 和 Gemini API，為 Gemini 2.5 Pro 和 Gemini 2.0 模型提供統一的介面。除了少數例外情況，在一個平台上執行的程式碼都能在兩個平台上執行。也就是說，您可以使用 Gemini Developer API 製作應用程式原型，然後將應用程式遷移至 Vertex AI，無須重寫程式碼。

如要進一步瞭解 Gemini 開發人員 API 與 Vertex AI 中的 Gemini 之間的差異，請參閱「從 Gemini 開發人員 API 遷移至 Vertex AI 中的 Gemini API」。

Gen AI SDK for Python

Google Gen AI SDK for Python 可在 PyPI 和 GitHub 上取得：

詳情請參閱 Python SDK 參考資料。

安裝

pip install --upgrade google-genai

設定環境變數，以便在 Vertex AI 中使用 Gen AI SDK：

# 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_VERTEXAI=True

快速入門導覽課程

請根據您是否使用 Express 模式，選擇下列其中一個選項。

  • 使用 Vertex AI (含所有 Google Cloud 功能和服務)
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:
# ...
  • 在快速模式下使用 Vertex AI
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

Gen AI SDK for Go

您可以在 go.dev 和 GitHub 取得 Google Gen AI SDK for Go：

安裝

go get google.golang.org/genai

設定環境變數，以便在 Vertex AI 中使用 Gen AI SDK：

# 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_VERTEXAI=True

快速入門導覽課程

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

適用於 TypeScript 和 JavaScript 的 Google Gen AI SDK 可在 npm 和 GitHub 上取得：

安裝

npm install @google/genai

設定環境變數，以便在 Vertex AI 中使用 Gen AI SDK：

# 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_VERTEXAI=True

快速入門導覽課程

/**
 * @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

Java 適用的 Google Gen AI SDK 可在 Maven Central 和 GitHub 取得：

Maven 安裝

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

設定環境變數，以便在 Vertex AI 中使用 Gen AI SDK：

# 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_VERTEXAI=True

快速入門導覽課程

/*
 * 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) {
    String modelId = "gemini-2.0-flash-001";
    if (args.length != 0) {
      modelId = args[0];
    }

    // 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());
  }

  private GenerateContent() {}
}