
读完本文,你将能够从任何编程语言中释放“AI的力量”。我们正生活在这样一个时代
Gemini API(谷歌生成式AI API)支持多种编程语言的调用。本文将介绍主流编程语言的使用方法及示例代码,详细讲解API的配置与调用流程,帮助你快速上手。
1. 什么是Gemini API?
Gemini API是谷歌推出的多模态生成式AI接口,支持文本生成、图像生成、代码生成等功能,是OpenAI的ChatGPT的竞争对手。该API托管于Google Cloud,通过获取API密钥即可从多种编程语言中调用。
2. Gemini API准备工作:获取API密钥与环境配置
登录Google Cloud控制台,创建项目并启用Gemini API,获取API密钥。你可以通过环境变量配置或直接在程序中指定API密钥使用。
Gemini API(Googleの生成AI API)は、多様なプログラミング言語での活用が可能です。本記事では、代表的な言語での使い方とサンプルコードを紹介し、APIの導入から実行までの流れをわかりやすく解説します。
3. Python示例
import google.generativeai as genai
genai.configure(api_key="YOUR_API_KEY")
model = genai.GenerativeModel("gemini-pro")
response = model.generate_content("Hello, please introduce yourself.")
print(response.text)
4. Java示例
Java使用HTTP客户端发送API请求。示例代码如下:
HttpClient client = HttpClient.newHttpClient();
HttpRequest request = HttpRequest.newBuilder()
.uri(URI.create("https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=YOUR_API_KEY"))
.header("Content-Type", "application/json")
.POST(HttpRequest.BodyPublishers.ofString("{\"contents\": [{\"parts\": [{\"text\": \"Hello, please introduce yourself.\"}]}]}"))
.build();
HttpResponse<String> response = client.send(request, HttpResponse.BodyHandlers.ofString());
System.out.println(response.body());
5. C#示例
var client = new HttpClient();
var request = new HttpRequestMessage
{
Method = HttpMethod.Post,
RequestUri = new Uri("https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=YOUR_API_KEY"),
Content = new StringContent("{\"contents\": [{\"parts\": [{\"text\": \"Hello, please introduce yourself.\"}]}]}", Encoding.UTF8, "application/json")
};
var response = await client.SendAsync(request);
var responseBody = await response.Content.ReadAsStringAsync();
Console.WriteLine(responseBody);
6. Google Apps Script(GAS)示例
function callGemini() {
var apiKey = "YOUR_API_KEY";
var url = "https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=" + apiKey;
var payload = {
"contents": [
{
"parts": [
{"text": "Hello, please introduce yourself."}
]
}
]
};
var options = {
"method" : "post",
"contentType": "application/json",
"payload" : JSON.stringify(payload)
};
var response = UrlFetchApp.fetch(url, options);
Logger.log(response.getContentText());
}
7. JavaScript示例(Node.js)
const fetch = require("node-fetch");
const url = "https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=YOUR_API_KEY";
const body = {
contents: [
{
parts: [{ text: "Hello, please introduce yourself." }]
}
]
};
fetch(url, {
method: "POST",
headers: { "Content-Type": "application/json" },
body: JSON.stringify(body)
})
.then(res => res.json())
.then(data => console.log(data))
.catch(err => console.error(err));
8. Shell脚本示例(cURL)
curl -X POST \
-H "Content-Type: application/json" \
-d '{
"contents": [
{
"parts": [
{"text": "Hello, please introduce yourself."}
]
}
]
}' \
"https://generativelanguage.googleapis.com/v1beta/models/gemini-pro:generateContent?key=YOUR_API_KEY"
9. 参考链接
10. 总结
Gemini API支持多种语言调用,简化了生成式AI的应用部署。尤其Python和JavaScript官方库完善,非常适合初学者和开发者快速入门。请根据本文示例代码,将Gemini API集成到你的项目中,开启AI能力的新篇章。