Gemini-2.5-Pro 开发者指南：5种优化 API 接入的关键方法

from google import genai

# 初始化客户端
client = genai.Client(api_key="YOUR_API_KEY")

# 发送请求
response = client.models.generate_content(
    model="gemini-2.5-pro",
    contents="你是谁",
)

# 输出结果
print(response.text)

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

const ai = new GoogleGenAI({ apiKey: "YOUR_API_KEY" });

async function analyzeImage() {
  const model = ai.models.getGenerativeModel({ model: "gemini-2.5-pro" });
  
  // 图片需转为base64
  const fileData = await readFileAsBase64("image.jpg");
  
  const result = await model.generateContent({
    contents: [
      {
        role: "user",
        parts: [
          { text: "这张图片里有什么内容?" },
          { inlineData: { data: fileData, mimeType: "image/jpeg" } },
        ],
      },
    ],
  });
  
  console.log(result.response.text());
}

analyzeImage();

package main

import (
    "context"
    "encoding/json"
    "fmt"
    "log"

    "google.golang.org/genai"
)

func main() {
    ctx := context.Background()
    client, err := genai.NewClient(ctx, &genai.ClientConfig{
        APIKey:  "YOUR_API_KEY",
        Backend: genai.BackendGeminiAPI,
    })
    if err != nil {
        log.Fatal(err)
    }

    // 定义JSON输出格式
    schema := map[string]interface{}{
        "type": "object",
        "properties": map[string]interface{}{
            "name": map[string]interface{}{"type": "string"},
            "age": map[string]interface{}{"type": "integer"},
            "skills": map[string]interface{}{
                "type": "array",
                "items": map[string]interface{}{"type": "string"},
            },
        },
    }

    // 设置响应格式
    outputStructure := &genai.GenerationConfig{
        ResponseSchema:  schema,
        ResponseMimeType: "application/json",
    }

    // 发送请求
    result, err := client.Models.GenerateContent(
        ctx,
        "gemini-2.5-pro",
        genai.Text("创建一个虚拟人物的详细信息"),
        outputStructure,
    )
    if err != nil {
        log.Fatal(err)
    }

    fmt.Println(result.Text())
}

curl -X POST "https://generativelanguage.googleapis.com/v1beta/models/gemini-2.5-pro:generateContent?key=YOUR_API_KEY" \
  -H "Content-Type: application/json" \
  -d '{
    "contents": [
      {
        "parts": [
          {
            "text": "解决以下问题并展示思考过程：商店以40元卖商品，利润率25%，成本是多少？"
          }
        ]
      }
    ],
    "generation_config": {
      "temperature": 0.1,
      "show_thinking": true
    }
  }'

import requests
import json

# API配置
api_key = "YOUR_API_KEY"
api_url = "https://api.allmhub.com/v1/chat/completions"

headers = {
    "Content-Type": "application/json",
    "Authorization": f"Bearer {api_key}"
}

data = {
    "model": "gemini-2.5-pro",
    "messages": [
        {"role": "system", "content": "你是一个AI助手。"},
        {"role": "user", "content": "你是谁"}
    ],
    "temperature": 0.7
}

response = requests.post(api_url, headers=headers, data=json.dumps(data))
result = response.json()

print(result["choices"][0]["message"]["content"])

curl https://api.allmhub.com/v1/chat/completions \
  -H "Content-Type: application/json" \
  -H "Authorization: Bearer $API_KEY" \
  -d '{
    "model": "gemini-2.5-pro",
    "stream": false,
    "messages": [
      {"role": "system", "content": "你是一个专业的AI助手。"},
      {"role": "user", "content": "你是谁"} 
    ]
  }'