大改，未验证

src/agent_assistant.py

@@ -12,6 +12,7 @@ from datetime import datetime
 from src.config.unified_config import get_config
 from src.agent.llm_client import LLMManager
 from src.web.service_manager import service_manager
+from src.agent.react_agent import ReactAgent
 
 logger = logging.getLogger(__name__)
 
@@ -25,7 +26,10 @@ class TSPAgentAssistant:
         self.is_agent_mode = True
         self.execution_history = []
 
-        # 工具注册表
+        # ReAct Agent（核心）
+        self.react_agent = ReactAgent()
+
+        # 工具注册表（保留兼容旧 API）
         self.tools = {}
         self.tool_performance = {}
 
@@ -194,13 +198,15 @@ class TSPAgentAssistant:
     def get_agent_status(self) -> Dict[str, Any]:
         """获取Agent状态"""
         try:
+            react_status = self.react_agent.get_status()
             return {
                 "success": True,
                 "is_active": self.is_agent_mode,
                 "ai_monitoring_active": self.ai_monitoring_active,
-                "total_tools": len(self.tools),
-                "total_executions": len(self.execution_history),
-                "tools": self.get_available_tools(),
+                "total_tools": react_status["tool_count"],
+                "available_tools": react_status["available_tools"],
+                "total_executions": len(self.execution_history) + react_status["history_count"],
+                "react_agent": react_status,
                 "performance": self.get_tool_performance_report()
             }
         except Exception as e:
@@ -321,29 +327,23 @@ class TSPAgentAssistant:
     async def process_message_agent(self, message: str, user_id: str = "admin", 
                                   work_order_id: Optional[int] = None, 
                                   enable_proactive: bool = True) -> Dict[str, Any]:
-        """处理消息 (实战化)"""
+        """处理消息 - 使用 ReAct Agent"""
         try:
             logger.info(f"Agent收到消息: {message}")
-            
-            # 1. 识别意图和推荐工具
-            prompt = f"用户消息: {message}\n请分析用户意图，并从工具列表中选择最合适的工具。工具列表: {json.dumps(self.get_available_tools())}\n请直接返回你的分析和建议响应。"
-            
-            response_text = await self.llm_manager.generate(prompt)
-            
-            # 2. 模拟动作生成
-            actions = []
-            if "工单" in message or "查询" in message:
-                actions.append({"type": "tool_call", "tool": "search_work_order", "status": "suggested"})
-            
-            return {
-                "success": True,
-                "response": response_text,
-                "actions": actions,
-                "user_id": user_id,
-                "work_order_id": work_order_id,
-                "status": "completed",
-                "timestamp": datetime.now().isoformat()
-            }
+            result = await self.react_agent.chat(
+                message=message,
+                user_id=user_id,
+            )
+            result["user_id"] = user_id
+            result["work_order_id"] = work_order_id
+            result["status"] = "completed" if result.get("success") else "error"
+            result["timestamp"] = datetime.now().isoformat()
+            # 兼容旧字段
+            result["actions"] = [
+                {"type": "tool_call", "tool": tc["tool"], "status": "executed"}
+                for tc in result.get("tool_calls", [])
+            ]
+            return result
         except Exception as e:
             logger.error(f"处理消息失败: {e}")
             return {"error": str(e)}