feat：PFC重构，模块化拆分

src/plugins/PFC/action_planner.py

@@ -1,27 +1,25 @@
 import datetime
-import asyncio
-from typing import List, Optional, Dict, Any, Tuple, Literal, Set
-from enum import Enum
+from typing import List, Dict, Tuple
 from src.common.logger import get_module_logger
-from ..chat.chat_stream import ChatStream
-from ..message.message_base import UserInfo, Seg
-from ..chat.message import Message
+from ..message.message_base import UserInfo
 from ..models.utils_model import LLM_request
 from ..config.config import global_config
-from src.plugins.chat.message import MessageSending
-from ..message.api import global_api
-from ..storage.storage import MessageStorage
 from .chat_observer import ChatObserver
-from .reply_checker import ReplyChecker
 from .pfc_utils import get_items_from_json
 from src.individuality.individuality import Individuality
-from .chat_states import NotificationHandler, Notification, NotificationType
-import time
-from dataclasses import dataclass, field
-from .pfc import DecisionInfo, DecisionInfoType
+from .observation_info import ObservationInfo
+from .conversation import ConversationInfo
 
 logger = get_module_logger("action_planner")
 
+class ActionPlannerInfo:
+    def __init__(self):
+        self.done_action = []
+        self.goal_list = []
+        self.knowledge_list = []
+        self.memory_list = []
+
+
 class ActionPlanner:
     """行动规划器"""
     
@@ -38,73 +36,60 @@ class ActionPlanner:
         
     async def plan(
         self, 
-        goal: str, 
-        method: str, 
-        reasoning: str,
-        action_history: List[Dict[str, str]] = None,
-        decision_info: DecisionInfoType = None  # Use DecisionInfoType here
+        observation_info: ObservationInfo,
+        conversation_info: ConversationInfo
     ) -> Tuple[str, str]:
         """规划下一步行动
         
         Args:
-            goal: 对话目标
-            method: 实现方法
-            reasoning: 目标原因
-            action_history: 行动历史记录
-            decision_info: 决策信息
+            observation_info: 决策信息
+            conversation_info: 对话信息
             
         Returns:
             Tuple[str, str]: (行动类型, 行动原因)
         """
         # 构建提示词
-        logger.debug(f"开始规划行动：当前目标: {goal}")
+        logger.debug(f"开始规划行动：当前目标: {conversation_info.goal_list}")
         
-        # 获取最近20条消息
-        messages = self.chat_observer.get_message_history(limit=20)
+        #构建对话目标
+        if conversation_info.goal_list:
+            goal, reasoning = conversation_info.goal_list[-1]
+        else:
+            goal = "目前没有明确对话目标"
+            reasoning = "目前没有明确对话目标，最好思考一个对话目标"
+            
+            
+        # 获取聊天历史记录
+        chat_history_list = observation_info.chat_history
         chat_history_text = ""
-        for msg in messages:
-            time_str = datetime.datetime.fromtimestamp(msg["time"]).strftime("%H:%M:%S")
-            user_info = UserInfo.from_dict(msg.get("user_info", {}))
-            sender = user_info.user_nickname or f"用户{user_info.user_id}"
-            if sender == self.name:
-                sender = "你说"
-            chat_history_text += f"{time_str},{sender}:{msg.get('processed_plain_text', '')}\n"
+        for msg in chat_history_list:
+            chat_history_text += f"{msg}\n"
+        
+        if observation_info.new_messages_count > 0:
+            new_messages_list = observation_info.unprocessed_messages
+            
+            chat_history_text += f"有{observation_info.new_messages_count}条新消息：\n"
+            for msg in new_messages_list:
+                chat_history_text += f"{msg}\n"
+            
+            observation_info.clear_unprocessed_messages()
+                
             
         personality_text = f"你的名字是{self.name}，{self.personality_info}"
         
         # 构建action历史文本
-        action_history_text = ""
-        if action_history and action_history[-1]['action'] == "direct_reply":
-            action_history_text = "你刚刚发言回复了对方"
+        action_history_list = conversation_info.action_history
+        action_history_text = "你之前做的事情是："
+        for action in action_history_list:
+            action_history_text += f"{action}\n"
             
-        # 构建决策信息文本
-        decision_info_text = ""
-        if decision_info:
-            decision_info_text = "当前对话状态：\n"
-            if decision_info.is_cold_chat:
-                decision_info_text += f"对话处于冷场状态，已持续{int(decision_info.cold_chat_duration)}秒\n"
-            
-            if decision_info.new_messages_count > 0:
-                decision_info_text += f"有{decision_info.new_messages_count}条新消息未处理\n"
-                
-            user_response_time = decision_info.get_user_response_time()
-            if user_response_time:
-                decision_info_text += f"距离用户上次发言已过去{int(user_response_time)}秒\n"
-                
-            bot_response_time = decision_info.get_bot_response_time()
-            if bot_response_time:
-                decision_info_text += f"距离你上次发言已过去{int(bot_response_time)}秒\n"
-                
-            if decision_info.active_users:
-                decision_info_text += f"当前活跃用户数: {len(decision_info.active_users)}\n"
+
 
         prompt = f"""{personality_text}。现在你在参与一场QQ聊天，请分析以下内容，根据信息决定下一步行动：
 
 当前对话目标：{goal}
-实现该对话目标的方式：{method}
 产生该对话目标的原因：{reasoning}
 
-{decision_info_text}
 {action_history_text}
 
 最近的对话记录：
@@ -117,7 +102,6 @@ wait: 当你做出了发言,对方尚未回复时等待对方的回复
 listening: 倾听对方发言，当你认为对方发言尚未结束时采用
 direct_reply: 不符合上述情况，回复对方，注意不要过多或者重复发言
 rethink_goal: 重新思考对话目标，当发现对话目标不合适时选择，会重新思考对话目标
-judge_conversation: 判断对话是否结束，当发现对话目标已经达到或者希望停止对话时选择，会判断对话是否结束
 
 请以JSON格式输出，包含以下字段：
 1. action: 行动类型，注意你之前的行为
@@ -134,7 +118,7 @@ judge_conversation: 判断对话是否结束，当发现对话目标已经达到
             success, result = get_items_from_json(
                 content,
                 "action", "reason",
-                default_values={"action": "direct_reply", "reason": "默认原因"}
+                default_values={"action": "direct_reply", "reason": "没有明确原因"}
             )
             
             if not success:
@@ -144,7 +128,7 @@ judge_conversation: 判断对话是否结束，当发现对话目标已经达到
             reason = result["reason"]
             
             # 验证action类型
-            if action not in ["direct_reply", "fetch_knowledge", "wait", "listening", "rethink_goal", "judge_conversation"]:
+            if action not in ["direct_reply", "fetch_knowledge", "wait", "listening", "rethink_goal"]:
                 logger.warning(f"未知的行动类型: {action}，默认使用listening")
                 action = "listening"