feat：整合normal和focus聊天

src/chat/__init__.py

@@ -5,11 +5,9 @@ MaiBot模块系统
 
 from src.chat.message_receive.chat_stream import get_chat_manager
 from src.chat.emoji_system.emoji_manager import get_emoji_manager
-from src.chat.normal_chat.willing.willing_manager import get_willing_manager
 
 # 导出主要组件供外部使用
 __all__ = [
     "get_chat_manager",
     "get_emoji_manager",
-    "get_willing_manager",
 ]

src/chat/focus_chat/heartFC_chat.py

@@ -1,9 +1,10 @@
 import asyncio
-import contextlib
 import time
 import traceback
 from collections import deque
-from typing import List, Optional, Dict, Any, Deque, Callable, Awaitable
+from typing import Optional, Deque, Callable, Awaitable
+
+from sqlalchemy import False_
 from src.chat.message_receive.chat_stream import get_chat_manager
 from rich.traceback import install
 from src.chat.utils.prompt_builder import global_prompt_manager
@@ -16,6 +17,16 @@ from src.chat.planner_actions.action_manager import ActionManager
 from src.config.config import global_config
 from src.person_info.relationship_builder_manager import relationship_builder_manager
 from src.chat.focus_chat.hfc_utils import CycleDetail
+from random import random
+from src.chat.focus_chat.hfc_utils import create_thinking_message_from_dict, add_messages_to_manager,get_recent_message_stats,cleanup_thinking_message_by_id
+from src.person_info.person_info import get_person_info_manager
+from src.plugin_system.apis import generator_api
+from ..message_receive.message import MessageThinking
+from src.chat.message_receive.normal_message_sender import message_manager
+from src.chat.willing.willing_manager import get_willing_manager
+from .priority_manager import PriorityManager
+from src.chat.utils.chat_message_builder import get_raw_msg_by_timestamp_with_chat_inclusive
+
 
 
 ERROR_LOOP_INFO = {
@@ -34,6 +45,17 @@ ERROR_LOOP_INFO = {
     },
 }
 
+NO_ACTION = {
+    "action_result": {
+        "action_type": "no_action",
+        "action_data": {},
+        "reasoning": "规划器初始化默认",
+        "is_parallel": True,
+    },
+    "chat_context": "",
+    "action_prompt": "",
+}
+
 install(extra_lines=3)
 
 # 注释：原来的动作修改超时常量已移除，因为改为顺序执行
@@ -51,7 +73,6 @@ class HeartFChatting:
     def __init__(
         self,
         chat_id: str,
-        on_stop_focus_chat: Optional[Callable[[], Awaitable[None]]] = None,
     ):
         """
         HeartFChatting 初始化函数
@@ -68,6 +89,10 @@ class HeartFChatting:
 
         self.relationship_builder = relationship_builder_manager.get_or_create_builder(self.stream_id)
 
+        self.loop_mode = "normal"
+        
+        self.recent_replies = []
+        
         # 新增：消息计数器和疲惫阈值
         self._message_count = 0  # 发送的消息计数
         # 基于exit_focus_threshold动态计算疲惫阈值
@@ -90,11 +115,32 @@ class HeartFChatting:
         self._cycle_history: Deque[CycleDetail] = deque(maxlen=10)  # 保留最近10个循环的信息
         self._current_cycle_detail: Optional[CycleDetail] = None
 
-        # 存储回调函数
-        self.on_stop_focus_chat = on_stop_focus_chat
-
         self.reply_timeout_count = 0
         self.plan_timeout_count = 0
+        
+        self.last_read_time = time.time()-1
+        
+        
+        
+        self.willing_amplifier = 1
+
+        self.action_type: Optional[str] = None  # 当前动作类型
+        self.is_parallel_action: bool = False  # 是否是可并行动作
+        
+        self._chat_task: Optional[asyncio.Task] = None
+        self._priority_chat_task: Optional[asyncio.Task] = None # for priority mode consumer
+        
+        self.reply_mode = self.chat_stream.context.get_priority_mode()
+        if self.reply_mode == "priority":
+            self.priority_manager = PriorityManager(
+                normal_queue_max_size=5,
+            )
+        else:
+            self.priority_manager = None
+            
+        self.willing_manager = get_willing_manager()
+        
+        
 
         logger.info(
             f"{self.log_prefix} HeartFChatting 初始化完成，消息疲惫阈值: {self._message_threshold}条（基于exit_focus_threshold={global_config.chat.exit_focus_threshold}计算，仅在auto模式下生效）"
@@ -172,44 +218,169 @@ class HeartFChatting:
         
 
     
-    async def _focus_mode_loopbody(self):
-        logger.info(f"{self.log_prefix} 开始第{self._cycle_counter}次循环")
+    async def _loopbody(self):
+        if self.loop_mode == "focus":
+            logger.info(f"{self.log_prefix} 开始第{self._cycle_counter}次观察")
+            return await self._observe()
+        elif self.loop_mode == "normal":
+            now = time.time()
+            new_messages_data = get_raw_msg_by_timestamp_with_chat_inclusive(
+                chat_id=self.stream_id, timestamp_start=self.last_read_time, timestamp_end=now, limit_mode="earliest"
+            )
+            
+            if new_messages_data:
+                self.last_read_time = now
+            
+                for msg_data in new_messages_data:
+                    try:
+                        self.adjust_reply_frequency()
+                        logger.info(f"{self.log_prefix} 开始第{self._cycle_counter}次循环")
+                        await self.normal_response(msg_data)
+                        # TODO: 这个地方可能导致阻塞，需要优化
+                        return True
+                    except Exception as e:
+                        logger.error(f"[{self.log_prefix}] 处理消息时出错: {e} {traceback.format_exc()}")
+            else:
+                await asyncio.sleep(0.1)
+            
+            return True
+            
 
+
+    async def _observe(self,message_data:dict = None):
         # 创建新的循环信息
         cycle_timers, thinking_id = self.start_cycle()
+        
+        await create_thinking_message_from_dict(message_data,self.chat_stream,thinking_id)
 
-        # 执行规划和处理阶段
-        try:
-            async with global_prompt_manager.async_message_scope(
-                self.chat_stream.context.get_template_name()
-            ):
+        async with global_prompt_manager.async_message_scope(
+            self.chat_stream.context.get_template_name()
+        ):
 
-                loop_start_time = time.time()
-                await self.loop_info.observe()
-                await self.relationship_builder.build_relation()
-
-                # 第一步：动作修改
-                with Timer("动作修改", cycle_timers):
-                    try:
+            loop_start_time = time.time()
+            await self.loop_info.observe()
+            await self.relationship_builder.build_relation()
+            
+            # 第一步：动作修改
+            with Timer("动作修改", cycle_timers):
+                try:
+                    if self.loop_mode == "focus":
                         await self.action_modifier.modify_actions(
                             loop_info=self.loop_info,
                             mode="focus",
                         )
-                    except Exception as e:
-                        logger.error(f"{self.log_prefix} 动作修改失败: {e}")
+                    elif self.loop_mode == "normal":
+                        await self.action_modifier.modify_actions(mode="normal")
+                        available_actions = self.action_manager.get_using_actions_for_mode("normal")
+                except Exception as e:
+                    logger.error(f"{self.log_prefix} 动作修改失败: {e}")
+                    
+            #如果normal，开始一个回复生成进程，先准备好回复（其实是和planer同时进行的）
+            if self.loop_mode == "normal":
+                gen_task = asyncio.create_task(self._generate_normal_response(message_data, available_actions))
+            
 
-                with Timer("规划器", cycle_timers):
-                    plan_result = await self.action_planner.plan()
+            with Timer("规划器", cycle_timers):
+                if self.loop_mode == "focus":
+                    if self.action_modifier.should_skip_planning_for_no_reply():
+                        logger.info(f"[{self.log_prefix}] 没有可用动作，跳过规划")
+                        action_type = "no_reply"
+                    else:
+                        plan_result = await self.action_planner.plan(mode="focus")
+                elif self.loop_mode == "normal":
+                    if self.action_modifier.should_skip_planning_for_no_action():
+                        logger.info(f"[{self.log_prefix}] 没有可用动作，跳过规划")
+                        action_type = "no_action"
+                    else:
+                        plan_result = await self.action_planner.plan(mode="normal")
 
-                action_result = plan_result.get("action_result", {})
-                action_type, action_data, reasoning = (
-                    action_result.get("action_type", "error"),
-                    action_result.get("action_data", {}),
-                    action_result.get("reasoning", "未提供理由"),
+
+
+            action_result = plan_result.get("action_result", {})
+            action_type, action_data, reasoning, is_parallel = (
+                action_result.get("action_type", "error"),
+                action_result.get("action_data", {}),
+                action_result.get("reasoning", "未提供理由"),
+                action_result.get("is_parallel", True),
+            )
+
+            action_data["loop_start_time"] = loop_start_time
+            
+            if self.loop_mode == "normal":
+                if action_type == "no_action":
+                    logger.info(f"[{self.log_prefix}] {global_config.bot.nickname} 决定进行回复")
+                elif is_parallel:
+                    logger.info(
+                        f"[{self.log_prefix}] {global_config.bot.nickname} 决定进行回复, 同时执行{action_type}动作"
+                    )
+                else:
+                    logger.info(f"[{self.log_prefix}] {global_config.bot.nickname} 决定执行{action_type}动作")
+
+            
+            
+            if action_type == "no_action":
+                gather_timeout = global_config.chat.thinking_timeout
+                results = await asyncio.wait_for(
+                    asyncio.gather(gen_task, return_exceptions=True),
+                    timeout=gather_timeout,
                 )
+                response_set = results[0]
+                
+                if response_set:
+                    content = " ".join([item[1] for item in response_set if item[0] == "text"])
 
-                action_data["loop_start_time"] = loop_start_time
+                
+                if not response_set or (
+                    action_type not in ["no_action"] and not is_parallel
+                ):
+                    if not response_set:
+                        logger.warning(f"[{self.log_prefix}] 模型未生成回复内容")
+                    elif action_type not in ["no_action"] and not is_parallel:
+                        logger.info(
+                            f"[{self.log_prefix}] {global_config.bot.nickname} 原本想要回复：{content}，但选择执行{self.action_type}，不发表回复"
+                        )
+                    # 如果模型未生成回复，移除思考消息
+                    await cleanup_thinking_message_by_id(self.chat_stream.stream_id,thinking_id,self.log_prefix)
+                    return False
 
+                logger.info(f"[{self.log_prefix}] {global_config.bot.nickname} 决定的回复内容: {content}")
+
+                # 提取回复文本
+                reply_texts = [item[1] for item in response_set if item[0] == "text"]
+                if not reply_texts:
+                    logger.info(f"[{self.log_prefix}] 回复内容中没有文本，不发送消息")
+                    await cleanup_thinking_message_by_id(self.chat_stream.stream_id,thinking_id,self.log_prefix)
+                    return False
+
+                # 发送回复 (不再需要传入 chat)
+                first_bot_msg = await add_messages_to_manager(message_data, reply_texts, thinking_id,self.chat_stream.stream_id)
+
+                # 检查 first_bot_msg 是否为 None (例如思考消息已被移除的情况)
+                if first_bot_msg:
+                    # 消息段已在接收消息时更新，这里不需要额外处理
+
+                    # 记录回复信息到最近回复列表中
+                    reply_info = {
+                        "time": time.time(),
+                        "user_message": message_data.get("processed_plain_text"),
+                        "user_info": {
+                            "user_id": message_data.get("user_id"),
+                            "user_nickname": message_data.get("user_nickname"),
+                        },
+                        "response": response_set,
+                        "is_reference_reply": message_data.get("reply") is not None,  # 判断是否为引用回复
+                    }
+                    self.recent_replies.append(reply_info)
+                    # 保持最近回复历史在限定数量内
+                    if len(self.recent_replies) > 10:
+                        self.recent_replies = self.recent_replies[-10 :]
+                return response_set if response_set else False
+                
+                
+                
+                
+                
+            else:
                 # 动作执行计时
                 with Timer("动作执行", cycle_timers):
                     success, reply_text, command = await self._handle_action(
@@ -233,55 +404,33 @@ class HeartFChatting:
                     return False
                     #停止该聊天模式的循环
 
-            self.end_cycle(loop_info,cycle_timers)
-            self.print_cycle_info(cycle_timers)
+        self.end_cycle(loop_info,cycle_timers)
+        self.print_cycle_info(cycle_timers)
 
-            await asyncio.sleep(global_config.focus_chat.think_interval)
-            
-            return True
-            
-            
-        except asyncio.CancelledError:
-            logger.info(f"{self.log_prefix} focus循环任务被取消")
-            return False
-        except Exception as e:
-            logger.error(f"{self.log_prefix} 循环处理时出错: {e}")
-            logger.error(traceback.format_exc())
-            
-            # 如果_current_cycle_detail存在但未完成，为其设置错误状态
-            if self._current_cycle_detail and not hasattr(self._current_cycle_detail, "end_time"):
-                error_loop_info = ERROR_LOOP_INFO
-                try:
-                    self._current_cycle_detail.set_loop_info(error_loop_info)
-                    self._current_cycle_detail.complete_cycle()
-                except Exception as inner_e:
-                    logger.error(f"{self.log_prefix} 设置错误状态时出错: {inner_e}")
+        if self.loop_mode == "normal":
+            await self.willing_manager.after_generate_reply_handle(message_data.get("message_id"))
 
-            await asyncio.sleep(1)  # 出错后等待一秒再继续\
-            return False
-        
+        return True
+    
+    
     
     async def _main_chat_loop(self):
         """主循环，持续进行计划并可能回复消息，直到被外部取消。"""
         try:
-            loop_mode = "focus"
-            loop_mode_loopbody = self._focus_mode_loopbody
-            
-            
             while self.running:  # 主循环
-                success = await loop_mode_loopbody()
+                success = await self._loopbody()
                 if not success:
                     break
                 
-            logger.info(f"{self.log_prefix} 麦麦已强制离开 {loop_mode} 聊天模式")
-                
-                
+            logger.info(f"{self.log_prefix} 麦麦已强制离开聊天")
         except asyncio.CancelledError:
             # 设置了关闭标志位后被取消是正常流程
-            logger.info(f"{self.log_prefix} 麦麦已强制离开 {loop_mode} 聊天模式")
-        except Exception as e:
-            logger.error(f"{self.log_prefix} 麦麦 {loop_mode} 聊天模式意外错误: {e}")
+            logger.info(f"{self.log_prefix} 麦麦已关闭聊天")
+        except Exception:
+            logger.error(f"{self.log_prefix} 麦麦聊天意外错误")
             print(traceback.format_exc())
+        # 理论上不能到这里
+        logger.error(f"{self.log_prefix} 麦麦聊天意外错误，结束了聊天循环")
 
     async def _handle_action(
         self,
@@ -376,8 +525,6 @@ class HeartFChatting:
                 return command
         return ""
 
-
-
     def _get_current_fatigue_threshold(self) -> int:
         """动态获取当前的疲惫阈值，基于exit_focus_threshold配置
 
@@ -427,3 +574,226 @@ class HeartFChatting:
 
         logger.info(f"{self.log_prefix} HeartFChatting关闭完成")
 
+
+    def adjust_reply_frequency(self):
+        """
+        根据预设规则动态调整回复意愿（willing_amplifier）。
+        - 评估周期：10分钟
+        - 目标频率：由 global_config.chat.talk_frequency 定义（例如 1条/分钟）
+        - 调整逻辑：
+            - 0条回复 -> 5.0x 意愿
+            - 达到目标回复数 -> 1.0x 意愿（基准）
+            - 达到目标2倍回复数 -> 0.2x 意愿
+            - 中间值线性变化
+        - 增益抑制：如果最近5分钟回复过快，则不增加意愿。
+        """
+        # --- 1. 定义参数 ---
+        evaluation_minutes = 10.0
+        target_replies_per_min = global_config.chat.get_current_talk_frequency(
+            self.stream_id
+        )  # 目标频率：e.g. 1条/分钟
+        target_replies_in_window = target_replies_per_min * evaluation_minutes  # 10分钟内的目标回复数
+
+        if target_replies_in_window <= 0:
+            logger.debug(f"[{self.log_prefix}] 目标回复频率为0或负数，不调整意愿放大器。")
+            return
+
+        # --- 2. 获取近期统计数据 ---
+        stats_10_min = get_recent_message_stats(minutes=evaluation_minutes, chat_id=self.stream_id)
+        bot_reply_count_10_min = stats_10_min["bot_reply_count"]
+
+        # --- 3. 计算新的意愿放大器 (willing_amplifier) ---
+        # 基于回复数在 [0, target*2] 区间内进行分段线性映射
+        if bot_reply_count_10_min <= target_replies_in_window:
+            # 在 [0, 目标数] 区间，意愿从 5.0 线性下降到 1.0
+            new_amplifier = 5.0 + (bot_reply_count_10_min - 0) * (1.0 - 5.0) / (target_replies_in_window - 0)
+        elif bot_reply_count_10_min <= target_replies_in_window * 2:
+            # 在 [目标数, 目标数*2] 区间，意愿从 1.0 线性下降到 0.2
+            over_target_cap = target_replies_in_window * 2
+            new_amplifier = 1.0 + (bot_reply_count_10_min - target_replies_in_window) * (0.2 - 1.0) / (
+                over_target_cap - target_replies_in_window
+            )
+        else:
+            # 超过目标数2倍，直接设为最小值
+            new_amplifier = 0.2
+
+        # --- 4. 检查是否需要抑制增益 ---
+        # "如果邻近5分钟内，回复数量 > 频率/2，就不再进行增益"
+        suppress_gain = False
+        if new_amplifier > self.willing_amplifier:  # 仅在计算结果为增益时检查
+            suppression_minutes = 5.0
+            # 5分钟内目标回复数的一半
+            suppression_threshold = (target_replies_per_min / 2) * suppression_minutes  # e.g., (1/2)*5 = 2.5
+            stats_5_min = get_recent_message_stats(minutes=suppression_minutes, chat_id=self.stream_id)
+            bot_reply_count_5_min = stats_5_min["bot_reply_count"]
+
+            if bot_reply_count_5_min > suppression_threshold:
+                suppress_gain = True
+
+        # --- 5. 更新意愿放大器 ---
+        if suppress_gain:
+            logger.debug(
+                f"[{self.log_prefix}] 回复增益被抑制。最近5分钟内回复数 ({bot_reply_count_5_min}) "
+                f"> 阈值 ({suppression_threshold:.1f})。意愿放大器保持在 {self.willing_amplifier:.2f}"
+            )
+            # 不做任何改动
+        else:
+            # 限制最终值在 [0.2, 5.0] 范围内
+            self.willing_amplifier = max(0.2, min(5.0, new_amplifier))
+            logger.debug(
+                f"[{self.log_prefix}] 调整回复意愿。10分钟内回复: {bot_reply_count_10_min} (目标: {target_replies_in_window:.0f}) -> "
+                f"意愿放大器更新为: {self.willing_amplifier:.2f}"
+            )
+            
+            
+            
+    async def normal_response(self, message_data: dict) -> None:
+        """
+        处理接收到的消息。
+        在"兴趣"模式下，判断是否回复并生成内容。
+        """
+        
+        is_mentioned = message_data.get("is_mentioned", False)
+        interested_rate = message_data.get("interest_rate", 0.0) * self.willing_amplifier
+        
+        reply_probability = (
+            1.0 if is_mentioned and global_config.normal_chat.mentioned_bot_inevitable_reply else 0.0
+        )  # 如果被提及，且开启了提及必回复，则基础概率为1，否则需要意愿判断
+
+        # 意愿管理器：设置当前message信息
+        self.willing_manager.setup(message_data, self.chat_stream)
+
+        # 获取回复概率
+        # 仅在未被提及或基础概率不为1时查询意愿概率
+        if reply_probability < 1:  # 简化逻辑，如果未提及 (reply_probability 为 0)，则获取意愿概率
+            # is_willing = True
+            reply_probability = await self.willing_manager.get_reply_probability(message_data.get("message_id"))
+
+            additional_config = message_data.get("additional_config", {})
+            if additional_config and "maimcore_reply_probability_gain" in additional_config:
+                reply_probability += additional_config["maimcore_reply_probability_gain"]
+                reply_probability = min(max(reply_probability, 0), 1)  # 确保概率在 0-1 之间
+
+        # 处理表情包
+        if message_data.get("is_emoji") or message_data.get("is_picid"):
+            reply_probability = 0
+
+        # 应用疲劳期回复频率调整
+        fatigue_multiplier = self._get_fatigue_reply_multiplier()
+        original_probability = reply_probability
+        reply_probability *= fatigue_multiplier
+
+        # 如果应用了疲劳调整，记录日志
+        if fatigue_multiplier < 1.0:
+            logger.info(
+                f"[{self.log_prefix}] 疲劳期回复频率调整: {original_probability * 100:.1f}% -> {reply_probability * 100:.1f}% (系数: {fatigue_multiplier:.2f})"
+            )
+
+        # 打印消息信息
+        mes_name = self.chat_stream.group_info.group_name if self.chat_stream.group_info else "私聊"
+        if reply_probability > 0.1:
+            logger.info(
+                f"[{mes_name}]"
+                f"{message_data.get('user_nickname')}:"
+                f"{message_data.get('processed_plain_text')}[兴趣:{interested_rate:.2f}][回复概率:{reply_probability * 100:.1f}%]"
+            )
+
+        if random() < reply_probability:
+            await self.willing_manager.before_generate_reply_handle(message_data.get("message_id"))
+            await self._observe(message_data = message_data)
+
+        # 意愿管理器：注销当前message信息 (无论是否回复，只要处理过就删除)
+        self.willing_manager.delete(message_data.get("message_id"))
+        
+        return True
+        
+        
+    async def _generate_normal_response(
+        self, message_data: dict, available_actions: Optional[list]
+    ) -> Optional[list]:
+        """生成普通回复"""
+        try:
+            person_info_manager = get_person_info_manager()
+            person_id = person_info_manager.get_person_id(
+                message_data.get("chat_info_platform"), message_data.get("user_id")
+            )
+            person_name = await person_info_manager.get_value(person_id, "person_name")
+            reply_to_str = f"{person_name}:{message_data.get('processed_plain_text')}"
+
+            success, reply_set = await generator_api.generate_reply(
+                chat_stream=self.chat_stream,
+                reply_to=reply_to_str,
+                available_actions=available_actions,
+                enable_tool=global_config.tool.enable_in_normal_chat,
+                request_type="normal.replyer",
+            )
+
+            if not success or not reply_set:
+                logger.info(f"对 {message_data.get('processed_plain_text')} 的回复生成失败")
+                return None
+
+            return reply_set
+
+        except Exception as e:
+            logger.error(f"[{self.log_prefix}] 回复生成出现错误：{str(e)} {traceback.format_exc()}")
+            return None
+    
+
+    def _get_fatigue_reply_multiplier(self) -> float:
+        """获取疲劳期回复频率调整系数
+
+        Returns:
+            float: 回复频率调整系数，范围0.5-1.0
+        """
+        if not self.get_cooldown_progress_callback:
+            return 1.0  # 没有冷却进度回调，返回正常系数
+
+        try:
+            cooldown_progress = self.get_cooldown_progress_callback()
+
+            if cooldown_progress >= 1.0:
+                return 1.0  # 冷却完成，正常回复频率
+
+            # 疲劳期间：从0.5逐渐恢复到1.0
+            # progress=0时系数为0.5，progress=1时系数为1.0
+            multiplier = 0.2 + (0.8 * cooldown_progress)
+
+            return multiplier
+        except Exception as e:
+            logger.warning(f"[{self.log_prefix}] 获取疲劳调整系数时出错: {e}")
+            return 1.0  # 出错时返回正常系数
+        
+    # async def _check_should_switch_to_focus(self) -> bool:
+    #     """
+    #     检查是否满足切换到focus模式的条件
+
+    #     Returns:
+    #         bool: 是否应该切换到focus模式
+    #     """
+    #     # 检查思考消息堆积情况
+    #     container = await message_manager.get_container(self.stream_id)
+    #     if container:
+    #         thinking_count = sum(1 for msg in container.messages if isinstance(msg, MessageThinking))
+    #         if thinking_count >= 4 * global_config.chat.auto_focus_threshold:  # 如果堆积超过阈值条思考消息
+    #             logger.debug(f"[{self.stream_name}] 检测到思考消息堆积({thinking_count}条)，切换到focus模式")
+    #             return True
+
+    #     if not self.recent_replies:
+    #         return False
+
+    #     current_time = time.time()
+    #     time_threshold = 120 / global_config.chat.auto_focus_threshold
+    #     reply_threshold = 6 * global_config.chat.auto_focus_threshold
+
+    #     one_minute_ago = current_time - time_threshold
+
+    #     # 统计指定时间内的回复数量
+    #     recent_reply_count = sum(1 for reply in self.recent_replies if reply["time"] > one_minute_ago)
+
+    #     should_switch = recent_reply_count > reply_threshold
+    #     if should_switch:
+    #         logger.debug(
+    #             f"[{self.stream_name}] 检测到{time_threshold:.0f}秒内回复数量({recent_reply_count})大于{reply_threshold}，满足切换到focus模式条件"
+    #         )
+
+    #     return should_switch

src/chat/focus_chat/hfc_utils.py

@@ -1,11 +1,19 @@
 import time
 from typing import Optional
-from src.chat.message_receive.message import MessageRecv, BaseMessageInfo
 from src.chat.message_receive.chat_stream import ChatStream
 from src.chat.message_receive.message import UserInfo
 from src.common.logger import get_logger
-import json
 from typing import Dict, Any
+from src.config.config import global_config
+from src.chat.message_receive.message import MessageThinking
+from src.chat.message_receive.normal_message_sender import message_manager
+from typing import List
+from maim_message import Seg
+from src.common.message_repository import count_messages
+from ..message_receive.message import MessageSending, MessageSet, message_from_db_dict
+from src.chat.message_receive.chat_stream import get_chat_manager
+
+
 
 logger = get_logger(__name__)
 
@@ -113,3 +121,129 @@ def parse_thinking_id_to_timestamp(thinking_id: str) -> float:
     ts_str = thinking_id[3:]
     return float(ts_str)
 
+
+async def create_thinking_message_from_dict(message_data: dict, chat_stream: ChatStream, thinking_id: str) -> str:
+    """创建思考消息"""
+    bot_user_info = UserInfo(
+        user_id=global_config.bot.qq_account,
+        user_nickname=global_config.bot.nickname,
+        platform=message_data.get("chat_info_platform"),
+    )
+
+    thinking_message = MessageThinking(
+        message_id=thinking_id,
+        chat_stream=chat_stream,
+        bot_user_info=bot_user_info,
+        reply=None,
+        thinking_start_time=time.time(),
+        timestamp=time.time(),
+    )
+
+    await message_manager.add_message(thinking_message)
+    return thinking_id
+
+async def cleanup_thinking_message_by_id(chat_id: str, thinking_id: str, log_prefix: str):
+    """根据ID清理思考消息"""
+    try:
+        container = await message_manager.get_container(chat_id)
+        if container:
+            for msg in container.messages[:]:
+                if isinstance(msg, MessageThinking) and msg.message_info.message_id == thinking_id:
+                    container.messages.remove(msg)
+                    logger.info(f"{log_prefix}已清理思考消息 {thinking_id}")
+                    break
+    except Exception as e:
+        logger.error(f"{log_prefix} 清理思考消息 {thinking_id} 时出错: {e}")
+
+
+
+async def add_messages_to_manager(
+        message_data: dict, response_set: List[str], thinking_id, chat_id
+    ) -> Optional[MessageSending]:
+        """发送回复消息"""
+        
+        chat_stream = get_chat_manager().get_stream(chat_id)
+        
+        container = await message_manager.get_container(chat_id)  # 使用 self.stream_id
+        thinking_message = None
+
+        for msg in container.messages[:]:
+            # print(msg)
+            if isinstance(msg, MessageThinking) and msg.message_info.message_id == thinking_id:
+                thinking_message = msg
+                container.messages.remove(msg)
+                break
+
+        if not thinking_message:
+            logger.warning(f"[{chat_id}] 未找到对应的思考消息 {thinking_id}，可能已超时被移除")
+            return None
+
+        thinking_start_time = thinking_message.thinking_start_time
+        message_set = MessageSet(chat_stream, thinking_id)  # 使用 self.chat_stream
+
+        sender_info = UserInfo(
+            user_id=message_data.get("user_id"),
+            user_nickname=message_data.get("user_nickname"),
+            platform=message_data.get("chat_info_platform"),
+        )
+        
+        reply = message_from_db_dict(message_data)
+        
+
+        mark_head = False
+        first_bot_msg = None
+        for msg in response_set:
+            if global_config.debug.debug_show_chat_mode:
+                msg += "ⁿ"
+            message_segment = Seg(type="text", data=msg)
+            bot_message = MessageSending(
+                message_id=thinking_id,
+                chat_stream=chat_stream,  # 使用 self.chat_stream
+                bot_user_info=UserInfo(
+                    user_id=global_config.bot.qq_account,
+                    user_nickname=global_config.bot.nickname,
+                    platform=message_data.get("chat_info_platform"),
+                ),
+                sender_info=sender_info,
+                message_segment=message_segment,
+                reply=reply,
+                is_head=not mark_head,
+                is_emoji=False,
+                thinking_start_time=thinking_start_time,
+                apply_set_reply_logic=True,
+            )
+            if not mark_head:
+                mark_head = True
+                first_bot_msg = bot_message
+            message_set.add_message(bot_message)
+
+        await message_manager.add_message(message_set)
+
+        return first_bot_msg
+    
+    
+def get_recent_message_stats(minutes: int = 30, chat_id: str = None) -> dict:
+    """
+    Args:
+        minutes (int): 检索的分钟数，默认30分钟
+        chat_id (str, optional): 指定的chat_id，仅统计该chat下的消息。为None时统计全部。
+    Returns:
+        dict: {"bot_reply_count": int, "total_message_count": int}
+    """
+
+    now = time.time()
+    start_time = now - minutes * 60
+    bot_id = global_config.bot.qq_account
+
+    filter_base = {"time": {"$gte": start_time}}
+    if chat_id is not None:
+        filter_base["chat_id"] = chat_id
+
+    # 总消息数
+    total_message_count = count_messages(filter_base)
+    # bot自身回复数
+    bot_filter = filter_base.copy()
+    bot_filter["user_id"] = bot_id
+    bot_reply_count = count_messages(bot_filter)
+
+    return {"bot_reply_count": bot_reply_count, "total_message_count": total_message_count}

src/chat/focus_chat/priority_manager.py

@@ -2,7 +2,7 @@ import time
 import heapq
 import math
 import json
-from typing import List, Dict, Optional
+from typing import List, Optional
 
 from src.common.logger import get_logger
 

src/chat/heart_flow/chat_state_info.py

@@ -1,13 +0,0 @@
-import enum
-
-
-class ChatState(enum.Enum):
-    ABSENT = "没在看群"
-    NORMAL = "随便水群"
-    FOCUSED = "认真水群"
-
-
-class ChatStateInfo:
-    def __init__(self):
-        self.chat_status: ChatState = ChatState.NORMAL
-        self.current_state_time = 120

src/chat/heart_flow/sub_heartflow.py

@@ -1,13 +1,11 @@
 import asyncio
 import time
-from typing import Optional, List, Dict, Tuple
+from typing import Optional, List, Tuple
 import traceback
 from src.common.logger import get_logger
 from src.chat.message_receive.message import MessageRecv
 from src.chat.message_receive.chat_stream import get_chat_manager
 from src.chat.focus_chat.heartFC_chat import HeartFChatting
-from src.chat.normal_chat.normal_chat import NormalChat
-from src.chat.heart_flow.chat_state_info import ChatState, ChatStateInfo
 from src.chat.utils.utils import get_chat_type_and_target_info
 from src.config.config import global_config
 from rich.traceback import install
@@ -31,11 +29,6 @@ class SubHeartflow:
         self.subheartflow_id = subheartflow_id
         self.chat_id = subheartflow_id
 
-        # 这个聊天流的状态
-        self.chat_state: ChatStateInfo = ChatStateInfo()
-        self.chat_state_changed_time: float = time.time()
-        self.chat_state_last_time: float = 0
-        self.history_chat_state: List[Tuple[ChatState, float]] = []
 
         self.is_group_chat, self.chat_target_info = get_chat_type_and_target_info(self.chat_id)
         self.log_prefix = get_chat_manager().get_stream_name(self.subheartflow_id) or self.subheartflow_id
@@ -47,125 +40,14 @@ class SubHeartflow:
         # CHAT模式激活 随便水群  FOCUS模式激活 认真水群
         self.heart_fc_instance: Optional[HeartFChatting] = HeartFChatting(
                     chat_id=self.subheartflow_id,
-                    on_stop_focus_chat=self._handle_stop_focus_chat_request,
                 )     # 该sub_heartflow的HeartFChatting实例
-        self.normal_chat_instance: Optional[NormalChat] = NormalChat(
-                    chat_stream=get_chat_manager().get_stream(self.chat_id),
-                    on_switch_to_focus_callback=self._handle_switch_to_focus_request,
-                    get_cooldown_progress_callback=self.get_cooldown_progress,
-                )  # 该sub_heartflow的NormalChat实例
 
     async def initialize(self):
         """异步初始化方法，创建兴趣流并确定聊天类型"""
+        await self.heart_fc_instance.start()
 
-        # 根据配置决定初始状态
-        if not self.is_group_chat:
-            logger.debug(f"{self.log_prefix} 检测到是私聊，将直接尝试进入 FOCUSED 状态。")
-            await self.change_chat_state(ChatState.FOCUSED)
-        elif global_config.chat.chat_mode == "focus":
-            logger.debug(f"{self.log_prefix} 配置为 focus 模式，将直接尝试进入 FOCUSED 状态。")
-            await self.change_chat_state(ChatState.FOCUSED)
-        else:  # "auto" 或其他模式保持原有逻辑或默认为 NORMAL
-            logger.debug(f"{self.log_prefix} 配置为 auto 或其他模式，将尝试进入 NORMAL 状态。")
-            await self.change_chat_state(ChatState.NORMAL)
 
-    def update_last_chat_state_time(self):
-        self.chat_state_last_time = time.time() - self.chat_state_changed_time
 
-    async def _stop_normal_chat(self):
-        """
-        停止 NormalChat 实例
-        切出 CHAT 状态时使用
-        """
-        if self.normal_chat_instance:
-            logger.info(f"{self.log_prefix} 离开normal模式")
-            try:
-                logger.debug(f"{self.log_prefix} 开始调用 stop_chat()")
-                # 使用更短的超时时间，强制快速停止
-                await asyncio.wait_for(self.normal_chat_instance.stop_chat(), timeout=3.0)
-                logger.debug(f"{self.log_prefix} stop_chat() 调用完成")
-            except Exception as e:
-                logger.error(f"{self.log_prefix} 停止 NormalChat 监控任务时出错: {e}")
-                # 出错时也要清理实例，避免状态不一致
-                self.normal_chat_instance = None
-            finally:
-                # 确保实例被清理
-                if self.normal_chat_instance:
-                    logger.warning(f"{self.log_prefix} 强制清理 NormalChat 实例")
-                    self.normal_chat_instance = None
-                logger.debug(f"{self.log_prefix} _stop_normal_chat 完成")
-        else:
-            logger.info(f"{self.log_prefix} 没有normal聊天实例，无需停止normal聊天")
-
-    async def _start_normal_chat(self) -> bool:
-        """
-        启动 NormalChat 实例，并进行异步初始化。
-        进入 CHAT 状态时使用。
-        确保 HeartFChatting 已停止。
-        """
-        await self._stop_heart_fc_chat()  # 确保 专注聊天已停止
-
-        try:
-            # 获取聊天流并创建 NormalChat 实例 (同步部分)
-            chat_stream = get_chat_manager().get_stream(self.chat_id)
-            # 在 NormalChat 实例尚未创建时，创建新实例
-            if not self.normal_chat_instance:
-                # 提供回调函数，用于接收需要切换到focus模式的通知
-                self.normal_chat_instance = NormalChat(
-                    chat_stream=chat_stream,
-                    on_switch_to_focus_callback=self._handle_switch_to_focus_request,
-                    get_cooldown_progress_callback=self.get_cooldown_progress,
-                )
-
-            logger.info(f"[{self.log_prefix}] 开始普通聊天")
-            await self.normal_chat_instance.start_chat()  # start_chat now ensures init is called again if needed
-            return True
-        except Exception as e:
-            logger.error(f"[{self.log_prefix}] 启动 NormalChat 或其初始化时出错: {e}")
-            logger.error(traceback.format_exc())
-            self.normal_chat_instance = None  # 启动/初始化失败，清理实例
-            return False
-
-    async def _handle_switch_to_focus_request(self) -> bool:
-        """
-        处理来自NormalChat的切换到focus模式的请求
-
-        Args:
-            stream_id: 请求切换的stream_id
-        Returns:
-            bool: 切换成功返回True，失败返回False
-        """
-        logger.info(f"{self.log_prefix} 收到NormalChat请求切换到focus模式")
-
-        # 检查是否在focus冷却期内
-        if self.is_in_focus_cooldown():
-            logger.info(f"{self.log_prefix} 正在focus冷却期内，忽略切换到focus模式的请求")
-            return False
-
-        # 切换到focus模式
-        current_state = self.chat_state.chat_status
-        if current_state == ChatState.NORMAL:
-            await self.change_chat_state(ChatState.FOCUSED)
-            logger.info(f"{self.log_prefix} 已根据NormalChat请求从NORMAL切换到FOCUSED状态")
-            return True
-        else:
-            logger.warning(f"{self.log_prefix} 当前状态为{current_state.value}，无法切换到FOCUSED状态")
-            return False
-
-    async def _handle_stop_focus_chat_request(self) -> None:
-        """
-        处理来自HeartFChatting的停止focus模式的请求
-        当收到stop_focus_chat命令时被调用
-        """
-        logger.info(f"{self.log_prefix} 收到HeartFChatting请求停止focus模式")
-
-        # 切换到normal模式
-        current_state = self.chat_state.chat_status
-        if current_state == ChatState.FOCUSED:
-            await self.change_chat_state(ChatState.NORMAL)
-            logger.info(f"{self.log_prefix} 已根据HeartFChatting请求从FOCUSED切换到NORMAL状态")
-        else:
-            logger.warning(f"{self.log_prefix} 当前状态为{current_state.value}，无法切换到NORMAL状态")
 
     async def _stop_heart_fc_chat(self):
         """停止并清理 HeartFChatting 实例"""
@@ -204,64 +86,7 @@ class SubHeartflow:
             logger.error(f"{self.log_prefix} _start_heart_fc_chat 执行时出错: {e}")
             logger.error(traceback.format_exc())
             return False
-
-    async def change_chat_state(self, new_state: ChatState) -> None:
-        """
-        改变聊天状态。
-        如果转换到CHAT或FOCUSED状态时超过限制，会保持当前状态。
-        """
-        current_state = self.chat_state.chat_status
-        state_changed = False
-
-
-        if new_state == ChatState.NORMAL:
-            if self.normal_chat_instance.running:
-                logger.info(f"{self.log_prefix} 当前状态已经为normal")
-                return
-            else:
-                if await self._start_normal_chat():
-                    logger.debug(f"{self.log_prefix} 成功进入或保持 NormalChat 状态。")
-                    state_changed = True
-                else:
-                    logger.error(f"{self.log_prefix} 启动 NormalChat 失败，无法进入 CHAT 状态。")
-                    return
-
-        elif new_state == ChatState.FOCUSED:
-            if self.heart_fc_instance.running:
-                logger.info(f"{self.log_prefix} 当前状态已经为focused")
-                return
-            if await self._start_heart_fc_chat():
-                logger.debug(f"{self.log_prefix} 成功进入或保持 HeartFChatting 状态。")
-                state_changed = True
-            else:
-                logger.error(f"{self.log_prefix} 启动 HeartFChatting 失败，无法进入 FOCUSED 状态。")
-                # 启动失败时，保持当前状态
-                return
-
-        # --- 记录focus模式退出时间 ---
-        if state_changed and current_state == ChatState.FOCUSED and new_state != ChatState.FOCUSED:
-            self.last_focus_exit_time = time.time()
-            logger.debug(f"{self.log_prefix} 记录focus模式退出时间: {self.last_focus_exit_time}")
-
-        # --- 更新状态和最后活动时间 ---
-        if state_changed:
-            self.update_last_chat_state_time()
-            self.history_chat_state.append((current_state, self.chat_state_last_time))
-
-            self.chat_state.chat_status = new_state
-            self.chat_state_last_time = 0
-            self.chat_state_changed_time = time.time()
-        else:
-            logger.debug(
-                f"{self.log_prefix} 尝试将状态从 {current_state.value} 变为 {new_state.value}，但未成功或未执行更改。"
-            )
-
-    def add_message_to_normal_chat_cache(self, message: MessageRecv, interest_value: float, is_mentioned: bool):
-        self.interest_dict[message.message_info.message_id] = (message, interest_value, is_mentioned)
-        # 如果字典长度超过10，删除最旧的消息
-        if len(self.interest_dict) > 30:
-            oldest_key = next(iter(self.interest_dict))
-            self.interest_dict.pop(oldest_key)
+        
 
     def is_in_focus_cooldown(self) -> bool:
         """检查是否在focus模式的冷却期内

src/chat/message_receive/normal_message_sender.py

@@ -13,6 +13,7 @@ from ..utils.utils import truncate_message, calculate_typing_time, count_message
 
 from src.common.logger import get_logger
 from rich.traceback import install
+import traceback
 
 install(extra_lines=3)
 
@@ -292,6 +293,7 @@ class MessageManager:
                     await asyncio.gather(*tasks)
                 except Exception as e:
                     logger.error(f"消息处理循环 gather 出错: {e}")
+                    print(traceback.format_exc())
 
             # 等待一小段时间，避免CPU空转
             try:

src/chat/message_receive/uni_message_sender.py

@@ -1,6 +1,6 @@
 import asyncio
-from typing import Dict, Optional  # 重新导入类型
-from src.chat.message_receive.message import MessageSending, MessageThinking
+from typing import Dict  # 重新导入类型
+from src.chat.message_receive.message import MessageSending
 from src.common.message.api import get_global_api
 from src.chat.message_receive.storage import MessageStorage
 from src.chat.utils.utils import truncate_message
@@ -36,42 +36,6 @@ class HeartFCSender:
 
     def __init__(self):
         self.storage = MessageStorage()
-        # 用于存储活跃的思考消息
-        self.thinking_messages: Dict[str, Dict[str, MessageThinking]] = {}
-        self._thinking_lock = asyncio.Lock()  # 保护 thinking_messages 的锁
-
-    async def register_thinking(self, thinking_message: MessageThinking):
-        """注册一个思考中的消息。"""
-        if not thinking_message.chat_stream or not thinking_message.message_info.message_id:
-            logger.error("无法注册缺少 chat_stream 或 message_id 的思考消息")
-            return
-
-        chat_id = thinking_message.chat_stream.stream_id
-        message_id = thinking_message.message_info.message_id
-
-        async with self._thinking_lock:
-            if chat_id not in self.thinking_messages:
-                self.thinking_messages[chat_id] = {}
-            if message_id in self.thinking_messages[chat_id]:
-                logger.warning(f"[{chat_id}] 尝试注册已存在的思考消息 ID: {message_id}")
-            self.thinking_messages[chat_id][message_id] = thinking_message
-            logger.debug(f"[{chat_id}] Registered thinking message: {message_id}")
-
-    async def complete_thinking(self, chat_id: str, message_id: str):
-        """完成并移除一个思考中的消息记录。"""
-        async with self._thinking_lock:
-            if chat_id in self.thinking_messages and message_id in self.thinking_messages[chat_id]:
-                del self.thinking_messages[chat_id][message_id]
-                logger.debug(f"[{chat_id}] Completed thinking message: {message_id}")
-                if not self.thinking_messages[chat_id]:
-                    del self.thinking_messages[chat_id]
-                    logger.debug(f"[{chat_id}] Removed empty thinking message container.")
-
-    async def get_thinking_start_time(self, chat_id: str, message_id: str) -> Optional[float]:
-        """获取已注册思考消息的开始时间。"""
-        async with self._thinking_lock:
-            thinking_message = self.thinking_messages.get(chat_id, {}).get(message_id)
-            return thinking_message.thinking_start_time if thinking_message else None
 
     async def send_message(self, message: MessageSending, typing=False, set_reply=False, storage_message=True):
         """
@@ -121,5 +85,4 @@ class HeartFCSender:
         except Exception as e:
             logger.error(f"[{chat_id}] 处理或存储消息 {message_id} 时出错: {e}")
             raise e
-        finally:
-            await self.complete_thinking(chat_id, message_id)
+

src/chat/planner_actions/action_modifier.py

@@ -526,16 +526,24 @@ class ActionModifier:
 
         return removals
 
-    def get_available_actions_count(self) -> int:
+    def get_available_actions_count(self,mode:str = "focus") -> int:
         """获取当前可用动作数量（排除默认的no_action）"""
-        current_actions = self.action_manager.get_using_actions_for_mode("normal")
+        current_actions = self.action_manager.get_using_actions_for_mode(mode)
         # 排除no_action（如果存在）
         filtered_actions = {k: v for k, v in current_actions.items() if k != "no_action"}
         return len(filtered_actions)
-
-    def should_skip_planning(self) -> bool:
+    
+    def should_skip_planning_for_no_reply(self) -> bool:
         """判断是否应该跳过规划过程"""
-        available_count = self.get_available_actions_count()
+        current_actions = self.action_manager.get_using_actions_for_mode("focus")
+        # 排除no_action（如果存在）
+        if len(current_actions) == 1 and "no_reply" in current_actions:
+            return True
+        return False
+
+    def should_skip_planning_for_no_action(self) -> bool:
+        """判断是否应该跳过规划过程"""
+        available_count = self.action_manager.get_using_actions_for_mode("normal")
         if available_count == 0:
             logger.debug(f"{self.log_prefix} 没有可用动作，跳过规划")
             return True

src/chat/planner_actions/planner.py

@@ -64,20 +64,19 @@ def init_prompt():
 
 
 class ActionPlanner:
-    def __init__(self, chat_id: str, action_manager: ActionManager, mode: str = "focus"):
+    def __init__(self, chat_id: str, action_manager: ActionManager):
         self.chat_id = chat_id
         self.log_prefix = f"[{get_chat_manager().get_stream_name(chat_id) or chat_id}]"
-        self.mode = mode
         self.action_manager = action_manager
         # LLM规划器配置
         self.planner_llm = LLMRequest(
             model=global_config.model.planner,
-            request_type=f"{self.mode}.planner",  # 用于动作规划
+            request_type="planner",  # 用于动作规划
         )
 
         self.last_obs_time_mark = 0.0
 
-    async def plan(self) -> Dict[str, Any]:
+    async def plan(self,mode: str = "focus") -> Dict[str, Any]:
         """
         规划器 (Planner): 使用LLM根据上下文决定做出什么动作。
         """
@@ -92,7 +91,7 @@ class ActionPlanner:
             is_group_chat, chat_target_info = get_chat_type_and_target_info(self.chat_id)
             logger.debug(f"{self.log_prefix}获取到聊天信息 - 群聊: {is_group_chat}, 目标信息: {chat_target_info}")
 
-            current_available_actions_dict = self.action_manager.get_using_actions_for_mode(self.mode)
+            current_available_actions_dict = self.action_manager.get_using_actions_for_mode(mode)
 
             # 获取完整的动作信息
             all_registered_actions = self.action_manager.get_registered_actions()
@@ -122,6 +121,7 @@ class ActionPlanner:
                 is_group_chat=is_group_chat,  # <-- Pass HFC state
                 chat_target_info=chat_target_info,  # <-- 传递获取到的聊天目标信息
                 current_available_actions=current_available_actions,  # <-- Pass determined actions
+                mode=mode,
             )
 
             # --- 调用 LLM (普通文本生成) ---
@@ -215,6 +215,7 @@ class ActionPlanner:
         is_group_chat: bool,  # Now passed as argument
         chat_target_info: Optional[dict],  # Now passed as argument
         current_available_actions,
+        mode: str = "focus",
     ) -> str:
         """构建 Planner LLM 的提示词 (获取模板并填充数据)"""
         try:
@@ -244,7 +245,7 @@ class ActionPlanner:
 
             self.last_obs_time_mark = time.time()
 
-            if self.mode == "focus":
+            if mode == "focus":
                 by_what = "聊天内容"
                 no_action_block = ""
             else:

src/chat/replyer/default_generator.py

@@ -136,33 +136,6 @@ class DefaultReplyer:
         selected_config = random.choices(population=configs, weights=weights, k=1)[0]
         return selected_config
 
-    async def _create_thinking_message(self, anchor_message: Optional[MessageRecv], thinking_id: str):
-        """创建思考消息 (尝试锚定到 anchor_message)"""
-        if not anchor_message or not anchor_message.chat_stream:
-            logger.error(f"{self.log_prefix} 无法创建思考消息，缺少有效的锚点消息或聊天流。")
-            return None
-
-        chat = anchor_message.chat_stream
-        messageinfo = anchor_message.message_info
-        thinking_time_point = parse_thinking_id_to_timestamp(thinking_id)
-        bot_user_info = UserInfo(
-            user_id=global_config.bot.qq_account,
-            user_nickname=global_config.bot.nickname,
-            platform=messageinfo.platform,
-        )
-
-        thinking_message = MessageThinking(
-            message_id=thinking_id,
-            chat_stream=chat,
-            bot_user_info=bot_user_info,
-            reply=anchor_message,  # 回复的是锚点消息
-            thinking_start_time=thinking_time_point,
-        )
-        # logger.debug(f"创建思考消息thinking_message：{thinking_message}")
-
-        await self.heart_fc_sender.register_thinking(thinking_message)
-        return None
-
     async def generate_reply_with_context(
         self,
         reply_data: Dict[str, Any] = None,
@@ -812,108 +785,6 @@ class DefaultReplyer:
 
         return prompt
 
-    async def send_response_messages(
-        self,
-        anchor_message: Optional[MessageRecv],
-        response_set: List[Tuple[str, str]],
-        thinking_id: str = "",
-        display_message: str = "",
-    ) -> Optional[MessageSending]:
-        """发送回复消息 (尝试锚定到 anchor_message)，使用 HeartFCSender"""
-        chat = self.chat_stream
-        chat_id = self.chat_stream.stream_id
-        if chat is None:
-            logger.error(f"{self.log_prefix} 无法发送回复，chat_stream 为空。")
-            return None
-        if not anchor_message:
-            logger.error(f"{self.log_prefix} 无法发送回复，anchor_message 为空。")
-            return None
-
-        stream_name = get_chat_manager().get_stream_name(chat_id) or chat_id  # 获取流名称用于日志
-
-        # 检查思考过程是否仍在进行，并获取开始时间
-        if thinking_id:
-            # print(f"thinking_id: {thinking_id}")
-            thinking_start_time = await self.heart_fc_sender.get_thinking_start_time(chat_id, thinking_id)
-        else:
-            print("thinking_id is None")
-            # thinking_id = "ds" + str(round(time.time(), 2))
-            thinking_start_time = time.time()
-
-        if thinking_start_time is None:
-            logger.error(f"[{stream_name}]replyer思考过程未找到或已结束，无法发送回复。")
-            return None
-
-        mark_head = False
-        # first_bot_msg: Optional[MessageSending] = None
-        reply_message_ids = []  # 记录实际发送的消息ID
-
-        sent_msg_list = []
-
-        for i, msg_text in enumerate(response_set):
-            # 为每个消息片段生成唯一ID
-            type = msg_text[0]
-            data = msg_text[1]
-
-            if global_config.debug.debug_show_chat_mode and type == "text":
-                data += "ᶠ"
-
-            part_message_id = f"{thinking_id}_{i}"
-            message_segment = Seg(type=type, data=data)
-
-            if type == "emoji":
-                is_emoji = True
-            else:
-                is_emoji = False
-            reply_to = not mark_head
-
-            bot_message: MessageSending = await self._build_single_sending_message(
-                anchor_message=anchor_message,
-                message_id=part_message_id,
-                message_segment=message_segment,
-                display_message=display_message,
-                reply_to=reply_to,
-                is_emoji=is_emoji,
-                thinking_id=thinking_id,
-                thinking_start_time=thinking_start_time,
-            )
-
-            try:
-                if (
-                    bot_message.is_private_message()
-                    or bot_message.reply.processed_plain_text != "[System Trigger Context]"
-                    or mark_head
-                ):
-                    set_reply = False
-                else:
-                    set_reply = True
-
-                if not mark_head:
-                    mark_head = True
-                    typing = False
-                else:
-                    typing = True
-
-                sent_msg = await self.heart_fc_sender.send_message(bot_message, typing=typing, set_reply=set_reply)
-
-                reply_message_ids.append(part_message_id)  # 记录我们生成的ID
-
-                sent_msg_list.append((type, sent_msg))
-
-            except Exception as e:
-                logger.error(f"{self.log_prefix}发送回复片段 {i} ({part_message_id}) 时失败: {e}")
-                traceback.print_exc()
-                # 这里可以选择是继续发送下一个片段还是中止
-
-        # 在尝试发送完所有片段后，完成原始的 thinking_id 状态
-        try:
-            await self.heart_fc_sender.complete_thinking(chat_id, thinking_id)
-
-        except Exception as e:
-            logger.error(f"{self.log_prefix}完成思考状态 {thinking_id} 时出错: {e}")
-
-        return sent_msg_list
-
     async def _build_single_sending_message(
         self,
         message_id: str,

src/main.py

@@ -7,7 +7,7 @@ from src.common.remote import TelemetryHeartBeatTask
 from src.manager.async_task_manager import async_task_manager
 from src.chat.utils.statistic import OnlineTimeRecordTask, StatisticOutputTask
 from src.chat.emoji_system.emoji_manager import get_emoji_manager
-from src.chat.normal_chat.willing.willing_manager import get_willing_manager
+from src.chat.willing.willing_manager import get_willing_manager
 from src.chat.message_receive.chat_stream import get_chat_manager
 from src.chat.message_receive.normal_message_sender import message_manager
 from src.chat.message_receive.storage import MessageStorage

src/plugins/built_in/core_actions/no_reply.py

@@ -11,8 +11,6 @@ from src.common.logger import get_logger
 # 导入API模块 - 标准Python包方式
 from src.plugin_system.apis import message_api
 from src.config.config import global_config
-from src.chat.memory_system.Hippocampus import hippocampus_manager
-import math
 
 
 logger = get_logger("core_actions")