] model=gpt-4.1-nano, attempt=1/3 failed: Connection error. [LLM ERROR] retrying...

2026年01月10日 14:45 processing

错误信息

[LLM ERROR] model=gpt-4.1-nano, attempt=1/3 failed: Connection error. [LLM ERROR] retrying after 2 seconds ... [LLM ERROR] model=gpt-4.1-nano, attempt=2/3 failed: Connection error. [LLM ERROR] retrying after 4 seconds ... [LLM ERROR] model=gpt-4.1-nano, attempt=3/3 failed: Connection error. [LLM ERROR] All retries failed. Returning fallback text. [LLM ERROR] model=gpt-4o-mini, attempt=1/3 failed: Connection error. [LLM ERROR] retrying after 2 seconds ... [LLM ERROR] model=gpt-4o-mini, attempt=2/3 failed: Connection error. [LLM ERROR] retrying after 4 seconds ... [LLM ERROR] model=gpt-4o-mini, attempt=3/3 failed: Connection error. [LLM ERROR] All retries failed. Returning fallback text. [LLM ERROR] model=gpt-4o-mini, attempt=1/3 failed: Connection error. [LLM ERROR] retrying after 2 seconds ... [LLM ERROR] model=gpt-4o-mini, attempt=2/3 failed: Connection error. [LLM ERROR] retrying after 4 seconds ... [INFO] Finished streaming 10 episodes to mas_ta/workspace/data/eval_sets/mmlu_sameq_20260110_130029/eval_A1T0_stronger_10.jsonl

AI 解决方案

错误分析：连接错误导致模型调用失败

1. 错误翻译

原文：Connection error
译文：连接错误

2. 原因分析

根本原因：网络连接异常导致无法访问AI模型服务

具体分析：

系统尝试调用多个AI模型（gpt-4.1-nano和gpt-4o-mini）

每个模型都进行了3次重试，均因连接错误失败

使用了指数退避策略（2秒、4秒延迟）

最终所有重试都失败，只能返回备用文本

3. 解决方案

立即修复方案：

import requests
import time

def check_connection():
    """检查网络连接状态"""
    try:
        # 测试基本网络连接
        response = requests.get('https://api.openai.com/v1/models', timeout=5)
        return response.status_code == 200
    except:
        return False

def call_llm_with_retry(model_name, prompt, max_retries=5, initial_delay=2):
    """增强的重试机制"""
    delay = initial_delay
    
    for attempt in range(max_retries):
        # 重试前检查网络连接
        if not check_connection():
            print(f"⚠️ 网络连接异常，等待 {delay} 秒后重试...")
            time.sleep(delay)
            delay *= 2  # 指数退避
            continue
            
        try:
            # 这里是调用API的代码
            # result = call_api(model_name, prompt)
            return "API调用成功"
        except ConnectionError as e:
            print(f" 连接错误 (尝试 {attempt+1}/{max_retries}): {e}")
            time.sleep(delay)
            delay *= 2
        except Exception as e:
            print(f"❌ 其他错误: {e}")
            break
    
    return "备用回复内容"

备用方案：

# 添加本地缓存或备用模型
import pickle
import hashlib

class LLMClient:
    def __init__(self):
        self.cache = {}
        self.fallback_models = ['gpt-4o-mini', 'gpt-4.1-nano']
    
    def get_response(self, prompt, model_index=0):
        # 生成缓存键
        cache_key = hashlib.md5(prompt.encode()).hexdigest()
        
        # 检查缓存
        if cache_key in self.cache:
            return self.cache[cache_key]
        
        # 尝试主模型
        for model in self.fallback_models:
            try:
                response = self._call_model(model, prompt)
                self.cache[cache_key] = response
                return response
            except ConnectionError:
                print(f"⚠️ {model} 连接失败，尝试下一个模型")
                continue
        
        # 所有模型都失败，返回备用响应
        return self._generate_fallback_response(prompt)

4. ️ 预防措施

最佳实践建议：

️ 实现网络健康检查机制

- 在调用API前检查网络连接状态
- 使用多端点测试（如同时测试api.openai.com和status.openai.com）
- 设置连接超时时间，避免长时间等待

建立多层故障转移策略

   主模型 → 备用模型1 → 备用模型2 → 本地缓存 → 预设回复