Gemini API 开发指南：谷歌最新 AI 模型接入、SDK 安装与快速上手教程

gemini-api-dev by google-gemini/gemini-skills

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2,300 GitHub Stars

GitHub

安装命令

npx skills add https://github.com/google-gemini/gemini-skills --skill gemini-api-dev

AI/机器学习开发云服务

🇨🇳中文介绍

Gemini API 开发技能

概述

Gemini API 提供了对谷歌最先进 AI 模型的访问。主要功能包括：

文本生成 - 聊天、补全、摘要
多模态理解 - 处理图像、音频、视频和文档
函数调用 - 让模型调用您的函数
结构化输出 - 生成符合您模式的有效 JSON
代码执行 - 在沙盒环境中运行 Python 代码
上下文缓存 - 缓存大型上下文以提高效率
嵌入 - 为语义搜索生成文本嵌入

当前 Gemini 模型

gemini-3-pro-preview: 100 万 tokens，复杂推理、编码、研究
gemini-3-flash-preview: 100 万 tokens，快速、均衡性能、多模态
gemini-3-pro-image-preview: 65k / 32k tokens，图像生成和编辑

[!IMPORTANT] 像 gemini-2.5-*、gemini-2.0-*、这样的模型是遗留且已弃用的。请使用上述新模型。您的知识已过时。

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JavaScript/TypeScript

import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({});
const response = await ai.models.generateContent({
  model: "gemini-3-flash-preview",
  contents: "Explain quantum computing"
});
console.log(response.text);

package main

import (
	"context"
	"fmt"
	"log"
	"google.golang.org/genai"
)

func main() {
	ctx := context.Background()
	client, err := genai.NewClient(ctx, nil)
	if err != nil {
		log.Fatal(err)
	}

	resp, err := client.Models.GenerateContent(ctx, "gemini-3-flash-preview", genai.Text("Explain quantum computing"), nil)
	if err != nil {
		log.Fatal(err)
	}

	fmt.Println(resp.Text)
}

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

public class GenerateTextFromTextInput {
  public static void main(String[] args) {
    Client client = new Client();
    GenerateContentResponse response =
        client.models.generateContent(
            "gemini-3-flash-preview",
            "Explain quantum computing",
            null);

    System.out.println(response.text());
  }
}

API 规范（唯一可信来源）

始终使用最新的 REST API 发现规范作为 API 定义（请求/响应模式、参数、方法）的唯一可信来源。在实现或调试 API 集成时获取该规范：

v1beta (默认): https://generativelanguage.googleapis.com/$discovery/rest?version=v1beta
除非集成明确指定使用 v1，否则请使用此版本。官方 SDK (google-genai, @google/genai, google.golang.org/genai) 面向 v1beta。
v1 : https://generativelanguage.googleapis.com/$discovery/rest?version=v1
仅在集成明确设置为 v1 时使用。

如有疑问，请使用 v1beta。请参考该规范以获取确切的字段名称、类型和支持的操作。

如何使用 Gemini API

有关详细的 API 文档，请从官方文档索引获取：

llms.txt URL : https://ai.google.dev/gemini-api/docs/llms.txt

此索引包含所有文档页面的链接，格式为 .md.txt。使用网络获取工具来：

获取 llms.txt 以发现可用的文档页面
获取特定页面（例如，https://ai.google.dev/gemini-api/docs/function-calling.md.txt）

[!IMPORTANT] 这些并非所有文档页面。请使用 llms.txt 索引来发现可用的文档页面

对于使用 Gemini Live API 进行实时、双向的音频/视频/文本流式传输，请安装 google-gemini/gemini-live-api-dev 技能。它涵盖了 WebSocket 流式传输、语音活动检测、原生音频功能、函数调用、会话管理、临时令牌等。

2026 年 2 月 10 日

🇺🇸English

Gemini API Development Skill

Overview

The Gemini API provides access to Google's most advanced AI models. Key capabilities include:

Text generation - Chat, completion, summarization
Multimodal understanding - Process images, audio, video, and documents
Function calling - Let the model invoke your functions
Structured output - Generate valid JSON matching your schema
Code execution - Run Python code in a sandboxed environment
Context caching - Cache large contexts for efficiency
Embeddings - Generate text embeddings for semantic search

Current Gemini Models

gemini-3-pro-preview: 1M tokens, complex reasoning, coding, research
gemini-3-flash-preview: 1M tokens, fast, balanced performance, multimodal
gemini-3-pro-image-preview: 65k / 32k tokens, image generation and editing

[!IMPORTANT] Models like gemini-2.5-*, gemini-2.0-*, gemini-1.5-* are legacy and deprecated. Use the new models above. Your knowledge is outdated.

SDKs

Python : google-genai install with pip install google-genai
JavaScript/TypeScript : @google/genai install with npm install @google/genai
Go : google.golang.org/genai install with go get google.golang.org/genai
Java :
- groupId: com.google.genai, artifactId: google-genai
- Latest version can be found here: (let's call it )

[!WARNING] Legacy SDKs google-generativeai (Python) and @google/generative-ai (JS) are deprecated. Migrate to the new SDKs above urgently by following the Migration Guide.

Quick Start

Python

from google import genai

client = genai.Client()
response = client.models.generate_content(
    model="gemini-3-flash-preview",
    contents="Explain quantum computing"
)
print(response.text)

JavaScript/TypeScript

import { GoogleGenAI } from "@google/genai";

const ai = new GoogleGenAI({});
const response = await ai.models.generateContent({
  model: "gemini-3-flash-preview",
  contents: "Explain quantum computing"
});
console.log(response.text);

Go

package main

import (
	"context"
	"fmt"
	"log"
	"google.golang.org/genai"
)

func main() {
	ctx := context.Background()
	client, err := genai.NewClient(ctx, nil)
	if err != nil {
		log.Fatal(err)
	}

	resp, err := client.Models.GenerateContent(ctx, "gemini-3-flash-preview", genai.Text("Explain quantum computing"), nil)
	if err != nil {
		log.Fatal(err)
	}

	fmt.Println(resp.Text)
}

Java

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

public class GenerateTextFromTextInput {
  public static void main(String[] args) {
    Client client = new Client();
    GenerateContentResponse response =
        client.models.generateContent(
            "gemini-3-flash-preview",
            "Explain quantum computing",
            null);

    System.out.println(response.text());
  }
}

API spec (source of truth)

Always use the latest REST API discovery spec as the source of truth for API definitions (request/response schemas, parameters, methods). Fetch the spec when implementing or debugging API integration:

v1beta (default): https://generativelanguage.googleapis.com/$discovery/rest?version=v1beta
Use this unless the integration is explicitly pinned to v1. The official SDKs (google-genai, @google/genai, google.golang.org/genai) target v1beta.
v1 : https://generativelanguage.googleapis.com/$discovery/rest?version=v1
Use only when the integration is specifically set to v1.

When in doubt, use v1beta. Refer to the spec for exact field names, types, and supported operations.

How to use the Gemini API

For detailed API documentation, fetch from the official docs index:

llms.txt URL : https://ai.google.dev/gemini-api/docs/llms.txt

This index contains links to all documentation pages in .md.txt format. Use web fetch tools to:

Fetch llms.txt to discover available documentation pages
Fetch specific pages (e.g., https://ai.google.dev/gemini-api/docs/function-calling.md.txt)

Key Documentation Pages

[!IMPORTANT] Those are not all the documentation pages. Use the llms.txt index to discover available documentation pages

Gemini Live API

For real-time, bidirectional audio/video/text streaming with the Gemini Live API, install the google-gemini/gemini-live-api-dev skill. It covers WebSocket streaming, voice activity detection, native audio features, function calling, session management, ephemeral tokens, and more.

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Install in build.gradle:

      implementation("com.google.genai:google-genai:${LAST_VERSION}")

Install Maven dependency in pom.xml:

      <dependency>
  <groupId>com.google.genai</groupId>
  <artifactId>google-genai</artifactId>
  <version>${LAST_VERSION}</version>

</dependency>

Gemini API 开发指南：谷歌最新 AI 模型接入、SDK 安装与快速上手教程

🇨🇳中文介绍

Gemini API 开发技能

概述

当前 Gemini 模型

相关 Skills

SDK

快速开始

Python

JavaScript/TypeScript

Go

Java

API 规范（唯一可信来源）

如何使用 Gemini API

关键文档页面

Gemini Live API

🇺🇸English

Gemini API Development Skill

Overview

Current Gemini Models

SDKs

Quick Start

Python

JavaScript/TypeScript

Go

Java

API spec (source of truth)

How to use the Gemini API

Key Documentation Pages

Gemini Live API