refactor(LLMAPI): 重构LLM接口以支持新版本OpenAI SDK

- 升级openai依赖至2.x版本并替换旧版SDK调用方式
- 引入OpenAI和AsyncOpenAI客户端实例替代全局配置
- 更新所有聊天完成请求方法以适配新版API格式
- 为异步流式响应处理添加异常捕获和错误提示
- 统一超时时间和最大token数等默认参数设置
- 修复部分变量命名冲突和潜在的空值引用问题
- 添加打印彩色日志的辅助函数避免循环导入问题

backend/AgentCoord/RehearsalEngine_V2/Action/baseAction.py

@@ -80,7 +80,14 @@ class BaseAction():
                 Important_Mark = ""
             action_Record += PROMPT_TEMPLATE_ACTION_RECORD.format(AgentName = actionInfo["AgentName"], Action_Description = actionInfo["AgentName"], Action_Result = actionInfo["Action_Result"], Important_Mark = Important_Mark)
 
-        prompt = PROMPT_TEMPLATE_TAKE_ACTION_BASE.format(agentName = agentName, agentProfile = AgentProfile_Dict[agentName], General_Goal = General_Goal, Current_Task_Description = TaskDescription, Input_Objects = inputObject_Record, History_Action = action_Record, Action_Description = self.info["Description"], Action_Custom_Note = self.Action_Custom_Note)
+        # Handle missing agent profiles gracefully
+        if agentName not in AgentProfile_Dict:
+            print_colored(text=f"Warning: Agent '{agentName}' not found in AgentProfile_Dict. Using default profile.", text_color="yellow")
+            agentProfile = f"AI Agent named {agentName}"
+        else:
+            agentProfile = AgentProfile_Dict[agentName]
+
+        prompt = PROMPT_TEMPLATE_TAKE_ACTION_BASE.format(agentName = agentName, agentProfile = agentProfile, General_Goal = General_Goal, Current_Task_Description = TaskDescription, Input_Objects = inputObject_Record, History_Action = action_Record, Action_Description = self.info["Description"], Action_Custom_Note = self.Action_Custom_Note)
         print_colored(text = prompt, text_color="red")
         messages = [{"role":"system", "content": prompt}]
         ActionResult = LLM_Completion(messages,True,False)