零成本玩转 Gemini 2.5 Flash Image：Nano Banana 免费 API 完整指南

# 安装依赖：pip install google-generativeai pillow
from google import genai
from PIL import Image

# 使用你的 API 密钥初始化客户端
genai.configure(api_key="YOUR_API_KEY")

# 准备输入图片（可选）
input_image = Image.open("input.jpg")

# 构建请求
prompt = "将这张照片转换为加州海岸线的日落场景，并保持人物外观不变"
model = genai.GenerativeModel('gemini-2.5-flash-image-preview')

response = model.generate_content([prompt, input_image])

# 处理响应
generated_image_data = response.candidates[0].content.parts[0].blob.data
# 你可以将 'generated_image_data' (bytes) 保存为图片文件

print("图片生成成功！")

// 安装：npm install @fal-ai/client
import { fal } from "@fal-ai/client";

// 设置 API 密钥
process.env.FAL_KEY = "YOUR_FAL_API_KEY";

async function editImageWithNanoBanana() {
  const result = await fal.run("fal-ai/nano-banana/edit", {
    input: {
      prompt: "让照片里的人穿上西装，场景变为现代办公室",
      image_urls: ["
      seed: 42, // 固定种子以获得一致结果
      guidance_scale: 7.5 // 控制生成强度
    }
  });

  console.log(`生成完成，图片 URL: ${result.image.url}`);
  console.log(`处理时间: ${result.timings.inference} 秒`);
  return result;
}

# 调用 Google AI Studio API
curl -X POST " \
 -H "Content-Type: application/json" \
 -H "x-goog-api-key: YOUR_API_KEY" \
 -d '{
   "contents": [{
     "parts": [
       {"text": "创建一张具有影棚灯光效果的专业头像照"},
       {"inline_data": {
         "mime_type": "image/jpeg",
         "data": "BASE64_ENCODED_IMAGE"
       }}
     ]
   }],
   "generationConfig": {
     "temperature": 0.4,
     "topK": 32,
     "topP": 1,
     "maxOutputTokens": 1290
   }
 }'

# 中转服务器端代码示例 (Flask)
from flask import Flask, request, jsonify
import requests

app = Flask(__name__)
GOOGLE_API_KEY = "YOUR_API_KEY"

@app.route('/nano-banana/generate', methods=['POST'])
def proxy_generate():
    # 接收国内请求
    data = request.json
    # 转发到 Google API
    response = requests.post(
        "
        headers={"x-goog-api-key": GOOGLE_API_KEY},
        json=data,
        timeout=30
    )
    return jsonify(response.json())

if __name__ == '__main__':
    app.run(host='0.0.0.0', port=8080)

// OpenRouter 调用示例
const response = await fetch(" {
  method: "POST",
  headers: {
    "Authorization": `Bearer ${OPENROUTER_API_KEY}`,
  },
  body: JSON.stringify({
    "model": "google/gemini-2.5-flash-image-preview",
    "messages": [
      { "role": "user", "content": [
        { "type": "text", "text": "编辑这张图片" },
        { "type": "image_url", "image_url": { "url": "data:image/jpeg;base64,..." }}
      ]}
    ]
  })
});

import time
import logging

def generate_with_retry(model, content, max_retries=3):
    """带指数退避重试机制的 API 调用函数"""
    for attempt in range(max_retries):
        try:
            response = model.generate_content(content)
            return response
        except Exception as e:
            if "429" in str(e): # 速率限制错误
                wait_time = 2 ** attempt
                logging.warning(f"触发速率限制，等待 {wait_time} 秒后重试...")
                time.sleep(wait_time)
            elif "500" in str(e) or "503" in str(e): # 服务端错误
                logging.warning("服务端错误，1秒后重试...")
                time.sleep(1)
            else:
                raise e # 其他错误直接抛出
    raise Exception(f"API 调用在 {max_retries} 次重试后仍然失败")