常见错误解决方案

import logging
import json
from datetime import datetime
from openai import OpenAI, APIError, RateLimitError, AuthenticationError

# 配置日志
logging.basicConfig(
    level=logging.INFO,
    format='%(asctime)s - %(levelname)s - %(message)s',
    handlers=[
        logging.FileHandler('api_errors.log'),
        logging.StreamHandler()
    ]
)

class APIErrorHandler:
    def __init__(self, client):
        self.client = client
        self.error_stats = {
            'auth_errors': 0,
            'rate_limits': 0,
            'timeouts': 0,
            'server_errors': 0,
            'other_errors': 0
        }
    
    def handle_error(self, error, context=None):
        """统一的错误处理"""
        error_info = {
            'timestamp': datetime.now().isoformat(),
            'error_type': type(error).__name__,
            'error_message': str(error),
            'context': context
        }
        
        if isinstance(error, AuthenticationError):
            self.error_stats['auth_errors'] += 1
            logging.error(f"认证错误: {error}")
            return {
                'retry': False,
                'message': '请检查API密钥配置',
                'action': 'CHECK_API_KEY'
            }
        
        elif isinstance(error, RateLimitError):
            self.error_stats['rate_limits'] += 1
            retry_after = error.response.headers.get('Retry-After', 60)
            logging.warning(f"速率限制: 等待{retry_after}秒")
            return {
                'retry': True,
                'wait_time': int(retry_after),
                'message': f'速率限制，{retry_after}秒后重试',
                'action': 'WAIT_AND_RETRY'
            }
        
        elif isinstance(error, APIError):
            if error.status_code >= 500:
                self.error_stats['server_errors'] += 1
                logging.error(f"服务器错误: {error}")
                return {
                    'retry': True,
                    'wait_time': 5,
                    'message': '服务器错误，稍后重试',
                    'action': 'RETRY_WITH_BACKOFF'
                }
            else:
                self.error_stats['other_errors'] += 1
                logging.error(f"API错误: {error}")
                return {
                    'retry': False,
                    'message': f'请求错误: {error}',
                    'action': 'CHECK_REQUEST'
                }
        
        else:
            self.error_stats['other_errors'] += 1
            logging.error(f"未知错误: {error}")
            return {
                'retry': False,
                'message': f'未知错误: {error}',
                'action': 'CONTACT_SUPPORT'
            }
    
    def get_statistics(self):
        """获取错误统计"""
        return self.error_stats
    
    def safe_call(self, func, *args, **kwargs):
        """安全执行API调用"""
        max_retries = kwargs.pop('max_retries', 3)
        retry_count = 0
        
        while retry_count < max_retries:
            try:
                result = func(*args, **kwargs)
                logging.info(f"API调用成功")
                return result
            
            except Exception as e:
                retry_count += 1
                error_response = self.handle_error(e, {
                    'function': func.__name__,
                    'retry_count': retry_count,
                    'args': str(args)[:100]
                })
                
                if not error_response['retry'] or retry_count >= max_retries:
                    raise
                
                wait_time = error_response.get('wait_time', 2 ** retry_count)
                logging.info(f"等待{wait_time}秒后重试...")
                time.sleep(wait_time)
        
        raise Exception(f"达到最大重试次数: {max_retries}")

# 使用示例
client = OpenAI(api_key="YOUR_API_KEY")
error_handler = APIErrorHandler(client)

try:
    response = error_handler.safe_call(
        client.chat.completions.create,
        model="gpt-3.5-turbo",
        messages=[{"role": "user", "content": "Hello"}],
        max_retries=5
    )
    print(response)
except Exception as e:
    print(f"最终失败: {e}")
    print(f"错误统计: {error_handler.get_statistics()}")