diff --git a/src/plugins/PFC/action_planner.py b/src/plugins/PFC/action_planner.py
index d4f13452e..ad69fea1d 100644
--- a/src/plugins/PFC/action_planner.py
+++ b/src/plugins/PFC/action_planner.py
@@ -1,14 +1,12 @@
-import datetime
-from typing import List, Dict, Tuple
+from typing import Tuple
 from src.common.logger import get_module_logger
-from ..message.message_base import UserInfo
 from ..models.utils_model import LLM_request
 from ..config.config import global_config
 from .chat_observer import ChatObserver
 from .pfc_utils import get_items_from_json
 from src.individuality.individuality import Individuality
 from .observation_info import ObservationInfo
-from .conversation import ConversationInfo
+from .conversation_info import ConversationInfo
 
 logger = get_module_logger("action_planner")
 
@@ -78,7 +76,7 @@ class ActionPlanner:
         personality_text = f"你的名字是{self.name}，{self.personality_info}"
         
         # 构建action历史文本
-        action_history_list = conversation_info.action_history
+        action_history_list = conversation_info.done_action
         action_history_text = "你之前做的事情是："
         for action in action_history_list:
             action_history_text += f"{action}\n"
diff --git a/src/plugins/PFC/conversation.py b/src/plugins/PFC/conversation.py
index 0d9457980..fecac1523 100644
--- a/src/plugins/PFC/conversation.py
+++ b/src/plugins/PFC/conversation.py
@@ -3,30 +3,20 @@ import datetime
 from typing import Dict, Any
 from ..chat.message import Message
 from .pfc_types import ConversationState
-from .pfc import ChatObserver, GoalAnalyzer, Waiter, DirectMessageSender, PFCNotificationHandler
+from .pfc import ChatObserver, GoalAnalyzer, Waiter, DirectMessageSender
 from src.common.logger import get_module_logger
 from .action_planner import ActionPlanner
 from .observation_info import ObservationInfo
+from .conversation_info import ConversationInfo
 from .reply_generator import ReplyGenerator
 from ..chat.chat_stream import ChatStream
 from ..message.message_base import UserInfo
-from ..config.config import global_config
 from src.plugins.chat.chat_stream import chat_manager
 from .pfc_KnowledgeFetcher import KnowledgeFetcher
-from .chat_states import NotificationType
-import time
 import traceback
 
 logger = get_module_logger("pfc_conversation")
 
-class ConversationInfo:
-    def __init__(self):
-        self.done_action = []
-        self.goal_list = []
-        self.knowledge_list = []
-        self.memory_list = []
-        
-        
 
 class Conversation:
     """对话类，负责管理单个对话的状态和行为"""
@@ -58,9 +48,6 @@ class Conversation:
             # 获取聊天流信息
             self.chat_stream = chat_manager.get_stream(self.stream_id)
             
-            # 创建通知处理器
-            self.notification_handler = PFCNotificationHandler(self)
-            
             self.stop_action_planner = False
         except Exception as e:
             logger.error(f"初始化对话实例：注册运行组件失败: {e}")
@@ -113,7 +100,7 @@ class Conversation:
             # 执行行动
             await self._handle_action(action, reason, self.observation_info, self.conversation_info)
 
-    async def _check_new_messages_after_planning(self):
+    def _check_new_messages_after_planning(self):
         """检查在规划后是否有新消息"""
         if self.observation_info.new_messages_count > 0:
             logger.info(f"发现{self.observation_info.new_messages_count}条新消息，可能需要重新考虑行动")
@@ -146,33 +133,33 @@ class Conversation:
         logger.info(f"执行行动: {action}, 原因: {reason}")
         
         # 记录action历史，先设置为stop，完成后再设置为done
-        conversation_info.action_history.append({
+        conversation_info.done_action.append({
             "action": action,
             "reason": reason,
-            "status": "stop",
+            "status": "start",
             "time": datetime.datetime.now().strftime("%H:%M:%S")
         })
         
         
         if action == "direct_reply":
             self.state = ConversationState.GENERATING
-            messages = self.chat_observer.get_message_history(limit=30)
             self.generated_reply = await self.reply_generator.generate(
-                self.current_goal,
-                self.current_method,
-                [self._convert_to_message(msg) for msg in messages],
-                self.knowledge_cache
+                observation_info,
+                conversation_info
             )
             
-            # 检查回复是否合适
-            is_suitable, reason, need_replan = await self.reply_generator.check_reply(
-                self.generated_reply,
-                self.current_goal
-            )
+            # # 检查回复是否合适
+            # is_suitable, reason, need_replan = await self.reply_generator.check_reply(
+            #     self.generated_reply,
+            #     self.current_goal
+            # )
+            
+            if self._check_new_messages_after_planning():
+                return None
             
             await self._send_reply()
             
-            conversation_info.action_history.append({
+            conversation_info.done_action.append({
                 "action": action,
                 "reason": reason,
                 "status": "done",
@@ -197,9 +184,8 @@ class Conversation:
         
         elif action == "rethink_goal":
             self.state = ConversationState.RETHINKING
-            goal_list = observation_info.goal_list
-            new_goal_list = await self.goal_analyzer.analyze_goal(goal_list)
-            observation_info.goal_list = new_goal_list
+            await self.goal_analyzer.analyze_goal(conversation_info, observation_info)
+
             
         elif action == "listening":
             self.state = ConversationState.LISTENING
diff --git a/src/plugins/PFC/conversation_info.py b/src/plugins/PFC/conversation_info.py
new file mode 100644
index 000000000..5b8262a16
--- /dev/null
+++ b/src/plugins/PFC/conversation_info.py
@@ -0,0 +1,8 @@
+
+
+class ConversationInfo:
+    def __init__(self):
+        self.done_action = []
+        self.goal_list = []
+        self.knowledge_list = []
+        self.memory_list = []
\ No newline at end of file
diff --git a/src/plugins/PFC/pfc.py b/src/plugins/PFC/pfc.py
index 96c147650..25c4728e0 100644
--- a/src/plugins/PFC/pfc.py
+++ b/src/plugins/PFC/pfc.py
@@ -15,14 +15,12 @@ from ..storage.storage import MessageStorage
 from .chat_observer import ChatObserver
 from .pfc_utils import get_items_from_json
 from src.individuality.individuality import Individuality
-from .chat_states import NotificationHandler, Notification, NotificationType
-from .waiter import Waiter
-from .message_sender import DirectMessageSender
-from .notification_handler import PFCNotificationHandler
+from .conversation_info import ConversationInfo
+from .observation_info import ObservationInfo
 import time
 
 if TYPE_CHECKING:
-    from .conversation import Conversation
+    pass
 
 logger = get_module_logger("pfc")
 
@@ -45,42 +43,55 @@ class GoalAnalyzer:
         self.max_goals = 3  # 同时保持的最大目标数量
         self.current_goal_and_reason = None
 
-    async def analyze_goal(self) -> Tuple[str, str, str]:
+    async def analyze_goal(self, conversation_info: ConversationInfo, observation_info: ObservationInfo):
         """分析对话历史并设定目标
 
         Args:
-            chat_history: 聊天历史记录列表
-
+            conversation_info: 对话信息
+            observation_info: 观察信息
+            
         Returns:
             Tuple[str, str, str]: (目标, 方法, 原因)
         """
-        max_retries = 3
-        for retry in range(max_retries):
-            try:
-                # 构建提示词
-                messages = self.chat_observer.get_message_history(limit=20)
-                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"
-
-                personality_text = f"你的名字是{self.name}，{self.personality_info}"
-
-                # 构建当前已有目标的文本
-                existing_goals_text = ""
-                if self.goals:
-                    existing_goals_text = "当前已有的对话目标:\n"
-                    for i, (goal, _, reason) in enumerate(self.goals):
-                        existing_goals_text += f"{i + 1}. 目标: {goal}, 原因: {reason}\n"
-
-                prompt = f"""{personality_text}。现在你在参与一场QQ聊天，请分析以下聊天记录，并根据你的性格特征确定多个明确的对话目标。
+         #构建对话目标
+        goal_list = conversation_info.goal_list
+        goal_text = ""
+        for goal, reason in goal_list:
+            goal_text += f"目标：{goal};"
+            goal_text += f"原因：{reason}\n"
+            
+            
+        # 获取聊天历史记录
+        chat_history_list = observation_info.chat_history
+        chat_history_text = ""
+        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_list = conversation_info.done_action
+        action_history_text = "你之前做的事情是："
+        for action in action_history_list:
+            action_history_text += f"{action}\n"
+            
+            
+        prompt = f"""{personality_text}。现在你在参与一场QQ聊天，请分析以下聊天记录，并根据你的性格特征确定多个明确的对话目标。
 这些目标应该反映出对话的不同方面和意图。
 
-{existing_goals_text}
+{action_history_text}
+当前对话目标：
+{goal_text}
 
 聊天记录：
 {chat_history_text}
@@ -91,54 +102,37 @@ class GoalAnalyzer:
 3. 添加新目标
 4. 删除不再相关的目标
 
-请以JSON格式输出一个当前最主要的对话目标，包含以下字段：
+请以JSON格式输出当前的所有对话目标，包含以下字段：
 1. goal: 对话目标（简短的一句话）
 2. reasoning: 对话原因，为什么设定这个目标（简要解释）
 
 输出格式示例：
 {{
-    "goal": "回答用户关于Python编程的具体问题",
-    "reasoning": "用户提出了关于Python的技术问题，需要专业且准确的解答"
+"goal": "回答用户关于Python编程的具体问题",
+"reasoning": "用户提出了关于Python的技术问题，需要专业且准确的解答"
+}},
+{{
+"goal": "回答用户关于python安装的具体问题",
+"reasoning": "用户提出了关于Python的技术问题，需要专业且准确的解答"
 }}"""
 
-                logger.debug(f"发送到LLM的提示词: {prompt}")
-                content, _ = await self.llm.generate_response_async(prompt)
-                logger.debug(f"LLM原始返回内容: {content}")
-
-                # 使用简化函数提取JSON内容
-                success, result = get_items_from_json(
-                    content, "goal", "reasoning", required_types={"goal": str, "reasoning": str}
-                )
-
-                if not success:
-                    logger.error(f"无法解析JSON，重试第{retry + 1}次")
-                    continue
-
-                goal = result["goal"]
-                reasoning = result["reasoning"]
-
-                # 使用默认的方法
-                method = "以友好的态度回应"
-
-                # 更新目标列表
-                await self._update_goals(goal, method, reasoning)
-
-                # 返回当前最主要的目标
-                if self.goals:
-                    current_goal, current_method, current_reasoning = self.goals[0]
-                    return current_goal, current_method, current_reasoning
-                else:
-                    return goal, method, reasoning
-
-            except Exception as e:
-                logger.error(f"分析对话目标时出错: {str(e)}，重试第{retry + 1}次")
-                if retry == max_retries - 1:
-                    return "保持友好的对话", "以友好的态度回应", "确保对话顺利进行"
-                continue
-
-        # 所有重试都失败后的默认返回
-        return "保持友好的对话", "以友好的态度回应", "确保对话顺利进行"
+        logger.debug(f"发送到LLM的提示词: {prompt}")
+        content, _ = await self.llm.generate_response_async(prompt)
+        logger.debug(f"LLM原始返回内容: {content}")
+        
+        # 使用简化函数提取JSON内容
+        success, result = get_items_from_json(
+            content,
+            "goal", "reasoning",
+            required_types={"goal": str, "reasoning": str}
+        )
+        #TODO
+        
+        
+        conversation_info.goal_list.append(result)
 
+        
+    
     async def _update_goals(self, new_goal: str, method: str, reasoning: str):
         """更新目标列表
 
diff --git a/src/plugins/PFC/reply_generator.py b/src/plugins/PFC/reply_generator.py
index 6ef5f1e20..beec9dd3e 100644
--- a/src/plugins/PFC/reply_generator.py
+++ b/src/plugins/PFC/reply_generator.py
@@ -1,13 +1,12 @@
-import datetime
-from typing import List, Optional, Dict, Tuple
+from typing import Tuple
 from src.common.logger import get_module_logger
-from ..message.message_base import UserInfo
-from ..chat.message import Message
 from ..models.utils_model import LLM_request
 from ..config.config import global_config
 from .chat_observer import ChatObserver
 from .reply_checker import ReplyChecker
 from src.individuality.individuality import Individuality
+from .observation_info import ObservationInfo
+from .conversation_info import ConversationInfo
 
 logger = get_module_logger("reply_generator")
 
@@ -29,11 +28,8 @@ class ReplyGenerator:
         
     async def generate(
         self,
-        goal: str,
-        chat_history: List[Message],
-        knowledge_cache: Dict[str, str],
-        previous_reply: Optional[str] = None,
-        retry_count: int = 0
+        observation_info: ObservationInfo,
+        conversation_info: ConversationInfo
     ) -> str:
         """生成回复
         
@@ -48,44 +44,33 @@ class ReplyGenerator:
             str: 生成的回复
         """
         # 构建提示词
-        logger.debug(f"开始生成回复：当前目标: {goal}")
-        self.chat_observer.trigger_update()  # 触发立即更新
-        if not await self.chat_observer.wait_for_update():
-            logger.warning("等待消息更新超时")
-                
-        messages = self.chat_observer.get_message_history(limit=20)
+        logger.debug(f"开始生成回复：当前目标: {conversation_info.goal_list}")
+
+        goal_list = conversation_info.goal_list
+        goal_text = ""
+        for goal, reason in goal_list:
+            goal_text += f"目标：{goal};"
+            goal_text += f"原因：{reason}\n"
+        
+        # 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"
+            
         
         # 整理知识缓存
         knowledge_text = ""
-        if knowledge_cache:
-            knowledge_text = "\n相关知识："
-            if isinstance(knowledge_cache, dict):
-                for _source, content in knowledge_cache.items():
-                    knowledge_text += f"\n{content}"
-            elif isinstance(knowledge_cache, list):
-                for item in knowledge_cache:
-                    knowledge_text += f"\n{item}"
+        knowledge_list = conversation_info.knowledge_list
+        for knowledge in knowledge_list:
+            knowledge_text += f"知识：{knowledge}\n"
                 
-        # 添加上一次生成的回复信息
-        previous_reply_text = ""
-        if previous_reply:
-            previous_reply_text = f"\n上一次生成的回复（需要改进）：\n{previous_reply}"
-        
         personality_text = f"你的名字是{self.name}，{self.personality_info}"
         
         prompt = f"""{personality_text}。现在你在参与一场QQ聊天，请根据以下信息生成回复：
 
-当前对话目标：{goal}
+当前对话目标：{goal_text}
 {knowledge_text}
-{previous_reply_text}
 最近的聊天记录：
 {chat_history_text}
 
@@ -94,7 +79,6 @@ class ReplyGenerator:
 2. 体现你的性格特征
 3. 自然流畅，像正常聊天一样，简短
 4. 适当利用相关知识，但不要生硬引用
-{'5. 改进上一次回复中的问题' if previous_reply else ''}
 
 请注意把握聊天内容，不要回复的太有条理，可以有个性。请分清"你"和对方说的话，不要把"你"说的话当做对方说的话，这是你自己说的话。
 请你回复的平淡一些，简短一些，说中文，不要刻意突出自身学科背景，尽量不要说你说过的话