2025年GPT-4o生图API完全指南：接口调用、优化技巧与实战案例

# Python示例代码
import openai

# 设置API密钥
openai.api_key = "sk-xxx" # 替换为您的API密钥

# 调用GPT-4o生图API
response = openai.Image.create(
    model="gpt-4o", # 注意这里使用gpt-4o而非dall-e-3
    prompt="一只戴着太阳镜的猫咪，在海滩上冲浪，逼真风格，4K高清",
    n=1,
    size="1024x1024",
    quality="standard",
    style="vivid" # 可选natural或vivid
)

# 获取生成的图像URL
image_url = response['data'][0]['url']
print(image_url)

# Python示例代码
import requests
import json

# API配置
api_key = "lz_xxx" # 替换为您的laozhang.ai API密钥
api_url = "https://api.laozhang.ai/v1/images/generations"

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

# 请求数据
data = {
    "model": "gpt-4o",
    "prompt": "一只戴着太阳镜的猫咪，在海滩上冲浪，逼真风格，4K高清",
    "n": 1,
    "size": "1024x1024",
    "quality": "standard",
    "style": "vivid"
}

# 发送请求
response = requests.post(api_url, headers=headers, json=data)
result = response.json()

# 获取生成的图像URL
if "data" in result and len(result["data"]) > 0:
    image_url = result["data"][0]["url"]
    print(f"生成的图像URL: {image_url}")
else:
    print(f"生成失败: {result}")

// Node.js示例代码
const { OpenAI } = require('openai');

// 初始化OpenAI客户端
const openai = new OpenAI({
  apiKey: 'lz_xxx', // 替换为您的API密钥
  baseURL: 'https://api.laozhang.ai/v1' // 使用laozhang.ai中转API
});

async function generateImage() {
  try {
    const response = await openai.images.generate({
      model: "gpt-4o",
      prompt: "一只戴着太阳镜的猫咪，在海滩上冲浪，逼真风格，4K高清",
      n: 1,
      size: "1024x1024",
      quality: "standard",
      style: "vivid"
    });
    
    console.log(response.data[0].url);
  } catch (error) {
    console.error('生成图像失败:', error);
  }
}

generateImage();

# 电商产品图生成示例
import requests
import json

api_key = "lz_xxx" # 替换为您的API密钥
api_url = "https://api.laozhang.ai/v1/images/generations"

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

# 产品展示提示词
product_prompt = """
高品质皮革笔记本，深棕色，放置在原木办公桌上，旁边有一支钢笔和一杯咖啡，
自然光从左侧照射，营造温暖氛围，产品细节清晰可见，
专业产品摄影风格，锐利对焦，柔和背景虚化，4K超高清
"""

data = {
    "model": "gpt-4o",
    "prompt": product_prompt,
    "n": 1,
    "size": "1024x1024",
    "quality": "hd",
    "style": "natural"  # 使用natural获得更真实的产品图
}

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

# 多轮编辑示例
import requests
import json

api_key = "lz_xxx" # 替换为您的API密钥
api_url = "https://api.laozhang.ai/v1/chat/completions"

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

# 初始对话
messages = [
    {"role": "system", "content": "你是一个专业的图像生成助手。"},
    {"role": "user", "content": "生成一个现代简约风格的客厅设计"}
]

# 第一轮生成
data = {
    "model": "gpt-4o",
    "messages": messages,
    "max_tokens": 1000
}

response = requests.post(api_url, headers=headers, json=data)
result = response.json()
assistant_response = result["choices"][0]["message"]["content"]
messages.append({"role": "assistant", "content": assistant_response})

# 第二轮修改
messages.append({"role": "user", "content": "将配色方案改为灰色和浅蓝色，添加更多自然光"})
data = {
    "model": "gpt-4o",
    "messages": messages,
    "max_tokens": 1000
}

response = requests.post(api_url, headers=headers, json=data)
result = response.json()
print(result["choices"][0]["message"]["content"])

# 图像优化示例 (需使用聊天补全API)
import requests
import json
import base64

api_key = "lz_xxx" # 替换为您的API密钥
api_url = "https://api.laozhang.ai/v1/chat/completions"

# 读取并编码图像
def encode_image(image_path):
    with open(image_path, "rb") as image_file:
        return base64.b64encode(image_file.read()).decode('utf-8')

# 获取base64编码的图像
base64_image = encode_image("your_image.jpg")

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

# 构建包含图像的消息
messages = [
    {
        "role": "user",
        "content": [
            {"type": "text", "text": "分析这张产品图并生成一个更专业的版本，改进光线和构图"},
            {"type": "image_url", "image_url": {"url": f"data:image/jpeg;base64,{base64_image}"}}
        ]
    }
]

data = {
    "model": "gpt-4o",
    "messages": messages,
    "max_tokens": 1000
}

response = requests.post(api_url, headers=headers, json=data)
result = response.json()
print(result["choices"][0]["message"]["content"])