feat: 重大功能更新 v1.4.0 - 飞书集成、AI语义相似度、前端优化
主要更新内容: - 🚀 飞书多维表格集成，支持工单数据同步 - 🤖 AI建议与人工描述语义相似度计算 - 🎨 前端UI全面优化，现代化设计 - 📊 智能知识库入库策略（AI准确率<90%使用人工描述） - 🔧 代码重构，模块化架构优化 - 📚 完整文档整合和更新 - 🐛 修复配置导入和数据库字段问题 技术特性: - 使用sentence-transformers进行语义相似度计算 - 快速模式结合TF-IDF和语义方法 - 响应式设计，支持移动端 - 加载状态和动画效果 - 配置化AI准确率阈值
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赵杰 Jie Zhao （雄狮汽车科技）
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src/agent_assistant_new.py
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322
src/agent_assistant_new.py
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# -*- coding: utf-8 -*-
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"""
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增强版TSP助手 - 集成Agent功能
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重构版本：模块化设计，降低代码复杂度
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"""
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import logging
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import asyncio
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from typing import Dict, Any, List, Optional
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from datetime import datetime
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from src.agent.agent_assistant_core import TSPAgentAssistantCore
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from src.agent.agent_message_handler import AgentMessageHandler
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from src.agent.agent_sample_actions import AgentSampleActions
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logger = logging.getLogger(__name__)
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class TSPAgentAssistant(TSPAgentAssistantCore):
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"""TSP Agent助手 - 重构版本"""
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def __init__(self, llm_config=None):
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# 初始化核心功能
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super().__init__(llm_config)
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# 初始化消息处理器
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self.message_handler = AgentMessageHandler(self)
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# 初始化示例动作处理器
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self.sample_actions = AgentSampleActions(self)
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logger.info("TSP Agent助手初始化完成（重构版本）")
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# ==================== 消息处理功能 ====================
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async def process_message_agent(self, message: str, user_id: str = "admin",
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work_order_id: Optional[int] = None,
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enable_proactive: bool = True) -> Dict[str, Any]:
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"""使用Agent处理消息"""
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return await self.message_handler.process_message_agent(
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message, user_id, work_order_id, enable_proactive
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)
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async def process_conversation_agent(self, conversation_data: Dict[str, Any]) -> Dict[str, Any]:
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"""使用Agent处理对话"""
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return await self.message_handler.process_conversation_agent(conversation_data)
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async def process_workorder_agent(self, workorder_data: Dict[str, Any]) -> Dict[str, Any]:
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"""使用Agent处理工单"""
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return await self.message_handler.process_workorder_agent(workorder_data)
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async def process_alert_agent(self, alert_data: Dict[str, Any]) -> Dict[str, Any]:
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"""使用Agent处理预警"""
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return await self.message_handler.process_alert_agent(alert_data)
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# ==================== 建议功能 ====================
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def get_conversation_suggestions(self, context: Dict[str, Any]) -> List[str]:
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"""获取对话建议"""
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return self.message_handler.get_conversation_suggestions(context)
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def get_workorder_suggestions(self, workorder_data: Dict[str, Any]) -> List[str]:
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"""获取工单建议"""
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return self.message_handler.get_workorder_suggestions(workorder_data)
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def get_alert_suggestions(self, alert_data: Dict[str, Any]) -> List[str]:
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"""获取预警建议"""
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return self.message_handler.get_alert_suggestions(alert_data)
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# ==================== 示例动作功能 ====================
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async def trigger_sample_actions(self) -> Dict[str, Any]:
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"""触发示例动作"""
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return await self.sample_actions.trigger_sample_actions()
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async def run_performance_test(self) -> Dict[str, Any]:
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"""运行性能测试"""
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return await self.sample_actions.run_performance_test()
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# ==================== 兼容性方法 ====================
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def get_agent_status(self) -> Dict[str, Any]:
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"""获取Agent状态（兼容性方法）"""
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return super().get_agent_status()
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def toggle_agent_mode(self, enabled: bool) -> bool:
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"""切换Agent模式（兼容性方法）"""
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return super().toggle_agent_mode(enabled)
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def start_proactive_monitoring(self) -> bool:
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"""启动主动监控（兼容性方法）"""
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return super().start_proactive_monitoring()
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def stop_proactive_monitoring(self) -> bool:
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"""停止主动监控（兼容性方法）"""
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return super().stop_proactive_monitoring()
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def run_proactive_monitoring(self) -> Dict[str, Any]:
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"""运行主动监控检查（兼容性方法）"""
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return super().run_proactive_monitoring()
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def run_intelligent_analysis(self) -> Dict[str, Any]:
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"""运行智能分析（兼容性方法）"""
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return super().run_intelligent_analysis()
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def get_action_history(self, limit: int = 50) -> List[Dict[str, Any]]:
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"""获取动作执行历史（兼容性方法）"""
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return super().get_action_history(limit)
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def clear_execution_history(self) -> Dict[str, Any]:
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"""清空执行历史（兼容性方法）"""
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return super().clear_execution_history()
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def get_llm_usage_stats(self) -> Dict[str, Any]:
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"""获取LLM使用统计（兼容性方法）"""
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return super().get_llm_usage_stats()
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# ==================== 高级功能 ====================
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async def comprehensive_analysis(self) -> Dict[str, Any]:
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"""综合分析 - 结合多个模块的分析结果"""
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try:
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# 运行智能分析
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intelligent_analysis = self.run_intelligent_analysis()
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# 运行主动监控
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proactive_monitoring = self.run_proactive_monitoring()
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# 运行性能测试
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performance_test = await self.run_performance_test()
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# 综合结果
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comprehensive_result = {
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"timestamp": self.execution_history[-1]["timestamp"] if self.execution_history else None,
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"intelligent_analysis": intelligent_analysis,
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"proactive_monitoring": proactive_monitoring,
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"performance_test": performance_test,
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"overall_status": self._determine_overall_status(
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intelligent_analysis, proactive_monitoring, performance_test
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)
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}
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# 记录综合分析
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self._record_execution("comprehensive_analysis", comprehensive_result)
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return comprehensive_result
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except Exception as e:
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logger.error(f"综合分析失败: {e}")
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return {"error": str(e)}
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def _determine_overall_status(self, intelligent_analysis: Dict,
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proactive_monitoring: Dict,
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performance_test: Dict) -> str:
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"""确定整体状态"""
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try:
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# 检查各个模块的状态
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statuses = []
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if intelligent_analysis.get("success"):
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statuses.append("intelligent_analysis_ok")
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else:
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statuses.append("intelligent_analysis_error")
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if proactive_monitoring.get("success"):
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statuses.append("proactive_monitoring_ok")
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else:
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statuses.append("proactive_monitoring_error")
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if performance_test.get("success"):
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statuses.append("performance_test_ok")
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else:
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statuses.append("performance_test_error")
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# 根据状态确定整体状态
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if all("ok" in status for status in statuses):
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return "excellent"
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elif any("error" in status for status in statuses):
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return "needs_attention"
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else:
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return "good"
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except Exception:
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return "unknown"
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async def batch_process_requests(self, requests: List[Dict[str, Any]]) -> List[Dict[str, Any]]:
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"""批量处理请求"""
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try:
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results = []
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for request in requests:
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request_type = request.get("type", "message")
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if request_type == "message":
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result = await self.process_message_agent(
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request.get("message", ""),
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request.get("user_id", "admin"),
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request.get("work_order_id"),
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request.get("enable_proactive", True)
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)
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elif request_type == "conversation":
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result = await self.process_conversation_agent(request)
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elif request_type == "workorder":
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result = await self.process_workorder_agent(request)
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elif request_type == "alert":
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result = await self.process_alert_agent(request)
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else:
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result = {"error": f"未知请求类型: {request_type}"}
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results.append(result)
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# 记录批量处理
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self._record_execution("batch_process", {
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"request_count": len(requests),
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"results": results
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})
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return results
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except Exception as e:
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logger.error(f"批量处理请求失败: {e}")
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return [{"error": str(e)} for _ in requests]
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def get_system_summary(self) -> Dict[str, Any]:
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"""获取系统摘要"""
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try:
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# 获取各种状态信息
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agent_status = self.get_agent_status()
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system_health = self.get_system_health()
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workorders_status = self._check_workorders_status()
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# 计算摘要指标
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summary = {
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"timestamp": datetime.now().isoformat(),
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"agent_status": agent_status,
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"system_health": system_health,
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"workorders_status": workorders_status,
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"execution_history_count": len(self.execution_history),
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"llm_usage_stats": self.get_llm_usage_stats(),
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"overall_health_score": system_health.get("health_score", 0)
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}
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return summary
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except Exception as e:
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logger.error(f"获取系统摘要失败: {e}")
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return {"error": str(e)}
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def export_agent_data(self) -> Dict[str, Any]:
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"""导出Agent数据"""
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try:
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export_data = {
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"export_timestamp": datetime.now().isoformat(),
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"agent_status": self.get_agent_status(),
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"execution_history": self.execution_history,
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"llm_usage_stats": self.get_llm_usage_stats(),
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"system_summary": self.get_system_summary()
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}
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return {
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"success": True,
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"data": export_data,
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"message": "Agent数据导出成功"
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}
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except Exception as e:
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logger.error(f"导出Agent数据失败: {e}")
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return {
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"success": False,
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"error": str(e)
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}
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def import_agent_data(self, data: Dict[str, Any]) -> Dict[str, Any]:
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"""导入Agent数据"""
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try:
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# 验证数据格式
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if not isinstance(data, dict):
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raise ValueError("数据格式不正确")
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# 导入执行历史
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if "execution_history" in data:
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self.execution_history = data["execution_history"]
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# 其他数据的导入逻辑...
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return {
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"success": True,
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"message": "Agent数据导入成功"
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}
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except Exception as e:
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logger.error(f"导入Agent数据失败: {e}")
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return {
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"success": False,
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"error": str(e)
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}
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# 测试函数
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async def main():
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"""测试函数"""
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print("🚀 TSP Agent助手测试")
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# 创建Agent助手实例
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agent_assistant = TSPAgentAssistant()
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# 测试基本功能
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status = agent_assistant.get_agent_status()
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print("Agent状态:", status)
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# 测试消息处理
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result = await agent_assistant.process_message_agent("你好，请帮我分析系统状态")
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print("消息处理结果:", result)
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# 测试示例动作
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sample_result = await agent_assistant.trigger_sample_actions()
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print("示例动作结果:", sample_result)
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# 测试综合分析
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analysis_result = await agent_assistant.comprehensive_analysis()
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print("综合分析结果:", analysis_result)
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if __name__ == "__main__":
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asyncio.run(main())
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