三星电子在全球范围内部署 ChatGPT Enterprise 与 Codex

import os
import requests
from typing import Dict, Any, Optional

class EnterpriseAIGateway:
    def __init__(self, api_key: str, base_url: str = "https://api.n1n.ai/v1"):
        self.api_key = api_key
        self.base_url = base_url
        self.headers = {
            "Authorization": f"Bearer {self.api_key}",
            "Content-Type": "application/json"
        }

    def generate_completion(
        self,
        prompt: str,
        primary_model: str = "gpt-4o",
        fallback_model: str = "claude-3-5-sonnet"
    ) -> Optional[Dict[str, Any]]:
        """
        向主模型发送请求。如果遇到限流或服务器错误，网关会自动将请求路由至备用模型。
        """
        payload = {
            "messages": [{"role": "user", "content": prompt}],
            "temperature": 0.2,
            "max_tokens": 1024
        }

        # 尝试调用主模型
        payload["model"] = primary_model
        try:
            print(f"[网关] 正在尝试主模型: {primary_model}")
            response = requests.post(
                f"{self.base_url}/chat/completions",
                json=payload,
                headers=self.headers,
                timeout=30
            )
            if response.status_code == 200:
                return response.json()
            else:
                print(f"[警告] 主模型请求失败，状态码: {response.status_code}。正在切换至备用模型...")
        except Exception as e:
            print(f"[错误] 无法连接到主模型: {str(e)}")

        # 尝试调用备用模型
        payload["model"] = fallback_model
        try:
            print(f"[网关] 正在尝试备用模型: {fallback_model}")
            response = requests.post(
                f"{self.base_url}/chat/completions",
                json=payload,
                headers=self.headers,
                timeout=30
            )
            if response.status_code == 200:
                return response.json()
            else:
                print(f"[错误] 备用模型同样请求失败，状态码: {response.status_code}。")
                return None
        except Exception as e:
            print(f"[严重错误] 备用模型路由异常: {str(e)}")
            return None

# 使用示例：
# 在 n1n.ai 注册并获取 API Key 后，配置到环境变量中
GATEWAY_API_KEY = os.getenv("N1N_API_KEY", "your_n1n_api_key_here")
gateway = EnterpriseAIGateway(api_key=GATEWAY_API_KEY)

# 测试代码生成任务
coding_prompt = "使用 Python 编写一个高效的函数，计算两个字符串的最长公共子序列。"
result = gateway.generate_completion(
    prompt=coding_prompt,
    primary_model="gpt-4o",
    fallback_model="claude-3-5-sonnet"
)

if result:
    print("请求成功！")
    print(result["choices"][0]["message"]["content"])
else:
    print("所有模型请求均失败，请检查网络或 API 配置。")