c3560b43fd
- Added documentation for audit tracking (IP address, invocation method). - Updated database model descriptions for enhanced WorkOrder and Conversation fields. - Documented the new UnifiedConfig system. - Reflected enhanced logging transparency for knowledge base parsing. Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>
359 lines
14 KiB
Python
359 lines
14 KiB
Python
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# -*- coding: utf-8 -*-
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"""
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自动监控服务
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实现Agent的主动调用功能
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"""
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import asyncio跳过系统检查，直接启动服务...
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import logging
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import threading
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import time
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from datetime import datetime, timedelta
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from typing import Dict, Any, List, Optional
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import json
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logger = logging.getLogger(__name__)
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class AutoMonitorService:
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"""自动监控服务"""
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def __init__(self, agent_assistant):
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self.agent_assistant = agent_assistant
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self.is_running = False
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self.monitor_thread = None
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self.check_interval = 300 # 5分钟检查一次
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self.last_check_time = None
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self.monitoring_stats = {
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"total_checks": 0,
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"proactive_actions": 0,
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"last_action_time": None,
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"error_count": 0
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}
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def start_auto_monitoring(self) -> bool:
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"""启动自动监控"""
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try:
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if self.is_running:
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logger.warning("自动监控已在运行中")
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return True
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self.is_running = True
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self.monitor_thread = threading.Thread(target=self._monitoring_loop, daemon=True)
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self.monitor_thread.start()
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logger.info("自动监控服务已启动")
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return True
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except Exception as e:
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logger.error(f"启动自动监控失败: {e}")
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return False
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def stop_auto_monitoring(self) -> bool:
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"""停止自动监控"""
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try:
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self.is_running = False
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if self.monitor_thread and self.monitor_thread.is_alive():
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self.monitor_thread.join(timeout=5)
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logger.info("自动监控服务已停止")
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return True
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except Exception as e:
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logger.error(f"停止自动监控失败: {e}")
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return False
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def _monitoring_loop(self):
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"""监控循环"""
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logger.info("自动监控循环已启动")
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while self.is_running:
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try:
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# 执行监控检查
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self._perform_monitoring_check()
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# 等待下次检查
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time.sleep(self.check_interval)
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except Exception as e:
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logger.error(f"监控循环错误: {e}")
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self.monitoring_stats["error_count"] += 1
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time.sleep(60) # 出错后等待1分钟
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def _perform_monitoring_check(self):
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"""执行监控检查"""
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try:
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self.monitoring_stats["total_checks"] += 1
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self.last_check_time = datetime.now()
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logger.info(f"执行第 {self.monitoring_stats['total_checks']} 次自动监控检查")
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# 1. 检查系统健康状态
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self._check_system_health()
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# 2. 检查预警状态
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self._check_alert_status()
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# 3. 检查工单积压
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self._check_workorder_backlog()
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# 4. 检查知识库质量
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self._check_knowledge_quality()
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# 5. 检查用户满意度
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self._check_user_satisfaction()
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# 6. 检查系统性能
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self._check_system_performance()
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except Exception as e:
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logger.error(f"执行监控检查失败: {e}")
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self.monitoring_stats["error_count"] += 1
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def _check_system_health(self):
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"""检查系统健康状态"""
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try:
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health = self.agent_assistant.get_system_health()
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health_score = health.get("health_score", 1.0)
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if health_score < 0.7:
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self._trigger_proactive_action({
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"type": "system_health_warning",
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"priority": "high",
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"description": f"系统健康分数较低: {health_score:.2f}",
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"action": "建议立即检查系统状态",
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"data": health
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})
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except Exception as e:
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logger.error(f"检查系统健康状态失败: {e}")
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def _check_alert_status(self):
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"""检查预警状态"""
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try:
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alerts = self.agent_assistant.get_active_alerts()
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alert_count = len(alerts) if isinstance(alerts, list) else 0
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if alert_count > 5:
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self._trigger_proactive_action({
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"type": "alert_overflow",
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"priority": "high",
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"description": f"活跃预警数量过多: {alert_count}",
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"action": "建议立即处理预警",
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"data": {"alert_count": alert_count}
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})
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except Exception as e:
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logger.error(f"检查预警状态失败: {e}")
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def _check_workorder_backlog(self):
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"""检查工单积压"""
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try:
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# 获取工单统计
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workorders = self.agent_assistant.get_workorders()
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if isinstance(workorders, list):
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open_count = len([w for w in workorders if w.get("status") == "open"])
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in_progress_count = len([w for w in workorders if w.get("status") == "in_progress"])
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total_pending = open_count + in_progress_count
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if total_pending > 10:
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self._trigger_proactive_action({
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"type": "workorder_backlog",
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"priority": "medium",
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"description": f"待处理工单过多: {total_pending}",
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"action": "建议增加处理人员或优化流程",
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"data": {
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"open_count": open_count,
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"in_progress_count": in_progress_count,
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"total_pending": total_pending
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}
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})
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except Exception as e:
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logger.error(f"检查工单积压失败: {e}")
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def _check_knowledge_quality(self):
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"""检查知识库质量"""
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try:
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stats = self.agent_assistant.knowledge_manager.get_knowledge_stats()
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avg_confidence = stats.get("average_confidence", 0.8)
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total_entries = stats.get("total_entries", 0)
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if avg_confidence < 0.6:
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self._trigger_proactive_action({
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"type": "knowledge_quality_low",
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"priority": "medium",
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"description": f"知识库平均置信度较低: {avg_confidence:.2f}",
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"action": "建议更新和优化知识库内容",
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"data": {"avg_confidence": avg_confidence, "total_entries": total_entries}
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})
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except Exception as e:
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logger.error(f"检查知识库质量失败: {e}")
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def _check_user_satisfaction(self):
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"""检查用户满意度"""
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try:
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# 模拟检查用户满意度
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# 这里可以从数据库或API获取真实的满意度数据
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satisfaction_score = 0.75 # 模拟数据
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if satisfaction_score < 0.7:
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self._trigger_proactive_action({
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"type": "low_satisfaction",
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"priority": "high",
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"description": f"用户满意度较低: {satisfaction_score:.2f}",
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"action": "建议分析低满意度原因并改进服务",
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"data": {"satisfaction_score": satisfaction_score}
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})
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except Exception as e:
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logger.error(f"检查用户满意度失败: {e}")
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def _check_system_performance(self):
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"""检查系统性能"""
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try:
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# 模拟检查系统性能指标
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response_time = 1.2 # 模拟响应时间（秒）
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error_rate = 0.02 # 模拟错误率
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if response_time > 2.0:
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self._trigger_proactive_action({
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"type": "slow_response",
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"priority": "medium",
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"description": f"系统响应时间过慢: {response_time:.2f}秒",
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"action": "建议优化系统性能",
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"data": {"response_time": response_time}
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})
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if error_rate > 0.05:
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self._trigger_proactive_action({
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"type": "high_error_rate",
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"priority": "high",
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"description": f"系统错误率过高: {error_rate:.2%}",
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"action": "建议立即检查系统错误",
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"data": {"error_rate": error_rate}
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})
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except Exception as e:
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logger.error(f"检查系统性能失败: {e}")
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def _trigger_proactive_action(self, action_data: Dict[str, Any]):
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"""触发主动行动"""
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try:
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self.monitoring_stats["proactive_actions"] += 1
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self.monitoring_stats["last_action_time"] = datetime.now()
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logger.info(f"触发主动行动: {action_data['type']} - {action_data['description']}")
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# 记录主动行动
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self._log_proactive_action(action_data)
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# 根据行动类型执行相应操作
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self._execute_proactive_action(action_data)
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except Exception as e:
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logger.error(f"触发主动行动失败: {e}")
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def _log_proactive_action(self, action_data: Dict[str, Any]):
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"""记录主动行动"""
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try:
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log_entry = {
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"timestamp": datetime.now().isoformat(),
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"action_type": action_data["type"],
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"priority": action_data["priority"],
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"description": action_data["description"],
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"action": action_data["action"],
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"data": action_data.get("data", {})
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}
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# 这里可以将日志保存到数据库或文件
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logger.info(f"主动行动记录: {json.dumps(log_entry, ensure_ascii=False)}")
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except Exception as e:
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logger.error(f"记录主动行动失败: {e}")
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def _execute_proactive_action(self, action_data: Dict[str, Any]):
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"""执行主动行动"""
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try:
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action_type = action_data["type"]
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if action_type == "system_health_warning":
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self._handle_system_health_warning(action_data)
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elif action_type == "alert_overflow":
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self._handle_alert_overflow(action_data)
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elif action_type == "workorder_backlog":
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self._handle_workorder_backlog(action_data)
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elif action_type == "knowledge_quality_low":
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self._handle_knowledge_quality_low(action_data)
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elif action_type == "low_satisfaction":
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self._handle_low_satisfaction(action_data)
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elif action_type == "slow_response":
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self._handle_slow_response(action_data)
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elif action_type == "high_error_rate":
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self._handle_high_error_rate(action_data)
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else:
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logger.warning(f"未知的主动行动类型: {action_type}")
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except Exception as e:
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logger.error(f"执行主动行动失败: {e}")
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def _handle_system_health_warning(self, action_data: Dict[str, Any]):
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"""处理系统健康警告"""
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logger.info("处理系统健康警告")
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# 这里可以实现具体的处理逻辑，如发送通知、重启服务等
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def _handle_alert_overflow(self, action_data: Dict[str, Any]):
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"""处理预警溢出"""
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logger.info("处理预警溢出")
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# 这里可以实现具体的处理逻辑，如自动处理预警、发送通知等
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def _handle_workorder_backlog(self, action_data: Dict[str, Any]):
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"""处理工单积压"""
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logger.info("处理工单积压")
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# 这里可以实现具体的处理逻辑，如自动分配工单、发送提醒等
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def _handle_knowledge_quality_low(self, action_data: Dict[str, Any]):
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"""处理知识库质量低"""
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logger.info("处理知识库质量低")
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# 这里可以实现具体的处理逻辑，如自动更新知识库、发送提醒等
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def _handle_low_satisfaction(self, action_data: Dict[str, Any]):
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"""处理低满意度"""
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logger.info("处理低满意度")
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# 这里可以实现具体的处理逻辑，如分析原因、发送通知等
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def _handle_slow_response(self, action_data: Dict[str, Any]):
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"""处理响应慢"""
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logger.info("处理响应慢")
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# 这里可以实现具体的处理逻辑，如优化配置、发送通知等
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def _handle_high_error_rate(self, action_data: Dict[str, Any]):
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"""处理高错误率"""
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logger.info("处理高错误率")
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# 这里可以实现具体的处理逻辑，如检查日志、发送通知等
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def get_monitoring_status(self) -> Dict[str, Any]:
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"""获取监控状态"""
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return {
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"is_running": self.is_running,
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"check_interval": self.check_interval,
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"last_check_time": self.last_check_time.isoformat() if self.last_check_time else None,
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"stats": self.monitoring_stats
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}
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def update_check_interval(self, interval: int) -> bool:
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"""更新检查间隔"""
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try:
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if interval < 60: # 最少1分钟
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logger.warning("检查间隔不能少于60秒")
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return False
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self.check_interval = interval
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logger.info(f"检查间隔已更新为 {interval} 秒")
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return True
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except Exception as e:
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logger.error(f"更新检查间隔失败: {e}")
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return False
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