182 lines
6.0 KiB
Python
182 lines
6.0 KiB
Python
"""
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AI对话日志记录模块
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用于记录大模型对话的输入和输出信息，方便排查问题
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"""
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import os
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import json
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import time
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from datetime import datetime
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from pathlib import Path
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from typing import Dict, Optional, Any
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from threading import Lock
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class AILogger:
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"""AI对话日志记录器"""
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def __init__(self, log_dir: Optional[str] = None):
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"""
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初始化日志记录器
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Args:
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log_dir: 日志文件保存目录，默认为项目根目录下的 logs/ai_conversations 目录
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"""
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if log_dir is None:
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# 默认日志目录：项目根目录下的 logs/ai_conversations
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project_root = Path(__file__).parent.parent
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log_dir = project_root / "logs" / "ai_conversations"
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self.log_dir = Path(log_dir)
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self.log_dir.mkdir(parents=True, exist_ok=True)
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# 线程锁，确保日志写入的线程安全
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self._lock = Lock()
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# 是否启用日志记录（可通过环境变量控制）
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self.enabled = os.getenv('AI_LOG_ENABLED', 'true').lower() == 'true'
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print(f"[AI日志] 日志记录器初始化完成，日志目录: {self.log_dir}")
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print(f"[AI日志] 日志记录状态: {'启用' if self.enabled else '禁用'}")
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def log_conversation(
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self,
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prompt: str,
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api_request: Dict[str, Any],
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api_response: Optional[Dict[str, Any]] = None,
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extracted_data: Optional[Dict[str, Any]] = None,
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error: Optional[str] = None,
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session_id: Optional[str] = None
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) -> str:
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"""
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记录一次完整的AI对话
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Args:
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prompt: 输入提示词
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api_request: API请求参数
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api_response: API响应内容（完整响应）
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extracted_data: 提取后的结构化数据
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error: 错误信息（如果有）
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session_id: 会话ID（可选，用于关联多次对话）
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Returns:
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日志文件路径
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"""
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if not self.enabled:
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return ""
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try:
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with self._lock:
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# 生成时间戳和会话ID
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timestamp = datetime.now().strftime("%Y%m%d_%H%M%S_%f")[:-3] # 精确到毫秒
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if session_id is None:
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session_id = f"session_{int(time.time() * 1000)}"
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# 创建日志记录
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log_entry = {
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"timestamp": datetime.now().isoformat(),
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"session_id": session_id,
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"prompt": prompt,
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"api_request": {
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"endpoint": api_request.get("endpoint", "unknown"),
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"model": api_request.get("model", "unknown"),
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"messages": api_request.get("messages", []),
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"temperature": api_request.get("temperature"),
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"max_tokens": api_request.get("max_tokens"),
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"enable_thinking": api_request.get("enable_thinking", False),
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},
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"api_response": api_response,
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"extracted_data": extracted_data,
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"error": error,
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"success": error is None
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}
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# 保存到文件（按日期组织）
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date_str = datetime.now().strftime("%Y%m%d")
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log_file = self.log_dir / f"conversation_{date_str}_{timestamp}.json"
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with open(log_file, 'w', encoding='utf-8') as f:
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json.dump(log_entry, f, ensure_ascii=False, indent=2)
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print(f"[AI日志] 对话日志已保存: {log_file.name}")
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return str(log_file)
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except Exception as e:
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print(f"[AI日志] 保存日志失败: {e}")
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return ""
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def log_request_only(
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self,
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prompt: str,
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api_request: Dict[str, Any],
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session_id: Optional[str] = None
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) -> str:
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"""
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仅记录请求信息（在发送请求前调用）
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Args:
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prompt: 输入提示词
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api_request: API请求参数
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session_id: 会话ID
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Returns:
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日志文件路径
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"""
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return self.log_conversation(
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prompt=prompt,
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api_request=api_request,
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session_id=session_id
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)
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def get_recent_logs(self, limit: int = 10) -> list:
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"""
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获取最近的日志文件列表
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Args:
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limit: 返回的日志文件数量
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Returns:
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日志文件路径列表（按时间倒序）
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"""
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try:
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log_files = sorted(
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self.log_dir.glob("conversation_*.json"),
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key=lambda x: x.stat().st_mtime,
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reverse=True
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)
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return [str(f) for f in log_files[:limit]]
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except Exception as e:
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print(f"[AI日志] 获取日志列表失败: {e}")
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return []
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def read_log(self, log_file: str) -> Optional[Dict]:
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"""
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读取指定的日志文件
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Args:
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log_file: 日志文件路径
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Returns:
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日志内容字典，如果读取失败返回None
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"""
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try:
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log_path = Path(log_file)
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if not log_path.is_absolute():
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log_path = self.log_dir / log_file
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with open(log_path, 'r', encoding='utf-8') as f:
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return json.load(f)
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except Exception as e:
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print(f"[AI日志] 读取日志文件失败: {e}")
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return None
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# 全局日志记录器实例
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_ai_logger: Optional[AILogger] = None
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def get_ai_logger() -> AILogger:
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"""获取全局AI日志记录器实例"""
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global _ai_logger
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if _ai_logger is None:
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_ai_logger = AILogger()
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return _ai_logger
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