feat：尝试建立hfc逻辑

src/chat/heart_flow/heartFC_chat.py

@@ -1,231 +1,377 @@
-from rich.traceback import install
-from typing import Optional, List, TYPE_CHECKING
+from typing import TYPE_CHECKING, Any, Dict, List, Optional, Tuple
 
 import asyncio
+import random
 import time
 import traceback
-import random
 
-from src.common.logger import get_logger
-from src.common.utils.utils_config import ExpressionConfigUtils, ChatConfigUtils
-from src.config.config import global_config
-from src.config.file_watcher import FileChange
-from src.chat.message_receive.chat_manager import chat_manager
+from rich.traceback import install
+
 from src.bw_learner.expression_learner import ExpressionLearner
 from src.bw_learner.jargon_miner import JargonMiner
+from src.chat.event_helpers import build_event_message
+from src.chat.logger.plan_reply_logger import PlanReplyLogger
+from src.chat.message_receive.chat_manager import BotChatSession
+from src.chat.message_receive.chat_manager import chat_manager as _chat_manager
+from src.chat.planner_actions.action_manager import ActionManager
+from src.chat.planner_actions.action_modifier import ActionModifier
+from src.chat.planner_actions.planner import ActionPlanner
+from src.chat.utils.prompt_builder import global_prompt_manager
+from src.chat.utils.timer_calculator import Timer
+from src.chat.utils.utils import record_replyer_action_temp
+from src.common.data_models.info_data_model import ActionPlannerInfo
+from src.common.data_models.message_component_data_model import MessageSequence, TextComponent
+from src.common.logger import get_logger
+from src.common.utils.utils_config import ChatConfigUtils, ExpressionConfigUtils
+from src.config.config import global_config
+from src.config.file_watcher import FileChange
+from src.core.event_bus import event_bus
+from src.core.types import ActionInfo, EventType
+from src.person_info.person_info import Person
+from src.services import (
+    database_service as database_api,
+    generator_service as generator_api,
+    message_service as message_api,
+    send_service as send_api,
+)
+from src.services.message_service import build_readable_messages_with_id, get_messages_before_time_in_chat
 
 from .heartFC_utils import CycleDetail
 
 if TYPE_CHECKING:
     from src.chat.message_receive.message import SessionMessage
 
+
 install(extra_lines=5)
 
 logger = get_logger("heartFC_chat")
 
 
 class HeartFChatting:
-    """
-    管理一个连续的Focus Chat聊天会话
-    用于在特定的聊天会话里面生成回复
-    """
+    """管理一个持续运行的 Focus Chat 会话。"""
 
     def __init__(self, session_id: str):
-        """
-        初始化 HeartFChatting 实例
-
-        Args:
-            session_id: 聊天会话ID
-        """
-        # 基础属性
         self.session_id = session_id
-        session_name = chat_manager.get_session_name(session_id) or session_id
+        self.chat_stream: BotChatSession = _chat_manager.get_session_by_session_id(self.session_id)  # type: ignore[assignment]
+        if not self.chat_stream:
+            raise ValueError(f"无法找到聊天会话 {self.session_id}")
+
+        session_name = _chat_manager.get_session_name(session_id) or session_id
         self.log_prefix = f"[{session_name}]"
         self.session_name = session_name
 
-        # 系统运行状态
+        self.action_manager = ActionManager()
+        self.action_planner = ActionPlanner(chat_id=self.session_id, action_manager=self.action_manager)
+        self.action_modifier = ActionModifier(action_manager=self.action_manager, chat_id=self.session_id)
+
         self._running: bool = False
         self._loop_task: Optional[asyncio.Task] = None
-        self._cycle_counter: int = 0
-        self._hfc_lock: asyncio.Lock = asyncio.Lock()  # 用于保护 _hfc_func 的并发访问
-        # 聊天频率相关
-        self._consecutive_no_reply_count = 0  # 跟踪连续 no_reply 次数，用于动态调整阈值
-        self._talk_frequency_adjust: float = 1.0  # 发言频率修正值，默认为1.0，可以根据需要调整
-
-        # HFC内消息缓存
-        self.message_cache: List[SessionMessage] = []
-
-        # Asyncio Event 用于控制循环的开始和结束
         self._cycle_event = asyncio.Event()
+        self._hfc_lock = asyncio.Lock()
+
+        self._cycle_counter = 0
+        self._current_cycle_detail: Optional[CycleDetail] = None
+        self.history_loop: List[CycleDetail] = []
+
+        self.last_read_time = time.time() - 2
+        self.last_active_time = time.time()
+        self._talk_frequency_adjust = 1.0
+        self._consecutive_no_reply_count = 0
+
+        self.message_cache: List["SessionMessage"] = []
+
+        self._min_messages_for_extraction = 30
+        self._min_extraction_interval = 60
+        self._last_extraction_time = 0.0
 
-        # 表达方式相关内容
-        self._min_messages_for_extraction = 30  # 最少提取消息数
-        self._min_extraction_interval = 60  # 最小提取时间间隔，单位为秒
-        self._last_extraction_time: float = 0.0  # 上次提取的时间戳
         expr_use, jargon_learn, expr_learn = ExpressionConfigUtils.get_expression_config_for_chat(session_id)
-        self._enable_expression_use = expr_use  # 允许使用表达方式，但不一定启用学习
-        self._enable_expression_learning = expr_learn  # 允许学习表达方式
-        self._enable_jargon_learning = jargon_learn  # 允许学习黑话
-        # 表达学习器
-        self._expression_learner: ExpressionLearner = ExpressionLearner(session_id)
-        # 黑话挖掘器
-        self._jargon_miner: JargonMiner = JargonMiner(session_id, session_name=session_name)
-
-        # TODO: ChatSummarizer 聊天总结器重构
-
-    # ====== 公开方法 ======
+        self._enable_expression_use = expr_use
+        self._enable_expression_learning = expr_learn
+        self._enable_jargon_learning = jargon_learn
+        self._expression_learner = ExpressionLearner(session_id)
+        self._jargon_miner = JargonMiner(session_id, session_name=session_name)
 
     async def start(self):
-        """启动 HeartFChatting 的主循环"""
-        # 先检查是否已经启动运行
         if self._running:
-            logger.debug(f"{self.log_prefix} 已经在运行中，无需重复启动")
+            logger.debug(f"{self.log_prefix} HeartFChatting 已在运行中")
             return
 
         try:
             self._running = True
-            self._cycle_event.clear()  # 确保事件初始状态为未设置
-
+            self._cycle_event.clear()
             self._loop_task = asyncio.create_task(self.main_loop())
             self._loop_task.add_done_callback(self._handle_loop_completion)
-
             logger.info(f"{self.log_prefix} HeartFChatting 启动完成")
-        except Exception as e:
-            logger.error(f"{self.log_prefix} 启动 HeartFChatting 失败: {e}", exc_info=True)
-            self._running = False  # 确保状态正确
-            self._cycle_event.set()  # 确保事件被设置，避免死锁
-            self._loop_task = None  # 确保任务引用被清理
+        except Exception as exc:
+            logger.error(f"{self.log_prefix} HeartFChatting 启动失败: {exc}", exc_info=True)
+            self._running = False
+            self._cycle_event.set()
+            self._loop_task = None
             raise
 
     async def stop(self):
-        """停止 HeartFChatting 的主循环"""
         if not self._running:
-            logger.debug(f"{self.log_prefix} HeartFChatting 已经停止，无需重复停止")
+            logger.debug(f"{self.log_prefix} HeartFChatting 已停止")
             return
 
         self._running = False
-        self._cycle_event.set()  # 触发事件，通知循环结束
+        self._cycle_event.set()
 
         if self._loop_task:
-            self._loop_task.cancel()  # 取消主循环任务
+            self._loop_task.cancel()
             try:
-                await self._loop_task  # 等待任务完成
+                await self._loop_task
             except asyncio.CancelledError:
-                logger.info(f"{self.log_prefix} HeartFChatting 主循环已成功取消")
-            except Exception as e:
-                logger.error(f"{self.log_prefix} 停止 HeartFChatting 时发生错误: {e}", exc_info=True)
+                logger.info(f"{self.log_prefix} HeartFChatting 主循环已取消")
+            except Exception as exc:
+                logger.error(f"{self.log_prefix} 停止 HeartFChatting 时发生错误: {exc}", exc_info=True)
             finally:
-                self._loop_task = None  # 确保任务引用被清理
+                self._loop_task = None
 
         logger.info(f"{self.log_prefix} HeartFChatting 已停止")
 
     def adjust_talk_frequency(self, new_value: float):
-        """调整发言频率的调整值
-
-        Args:
-            new_value: 新的修正值，必须为非负数。值越大，修正发言频率越高；值越小，修正发言频率越低。
-        """
         self._talk_frequency_adjust = max(0.0, new_value)
 
     async def register_message(self, message: "SessionMessage"):
-        """注册一条消息到 HeartFChatting 的缓存中，并检测其是否产生提及，决定是否唤醒聊天
-
-        Args:
-            message: 待注册的消息对象
-        """
         self.message_cache.append(message)
-        # 先检查at必回复
+
         if global_config.chat.inevitable_at_reply and message.is_at:
-            async with self._hfc_lock:  # 确保与主循环逻辑的互斥访问
-                await self._judge_and_response(message)
-            return  # 直接返回，避免同一条消息被主循环再次处理
-        # 再检查提及必回复
+            self.last_read_time = time.time()
+            async with self._hfc_lock:
+                await self._judge_and_response(mentioned_message=message, recent_messages_list=[message])
+            return
+
         if global_config.chat.mentioned_bot_reply and message.is_mentioned:
-            # 直接获取锁，确保一定一定触发回复逻辑，不受当前是否正在执行主循环的影响
-            async with self._hfc_lock:  # 确保与主循环逻辑的互斥访问
-                await self._judge_and_response(message)
+            self.last_read_time = time.time()
+            async with self._hfc_lock:
+                await self._judge_and_response(mentioned_message=message, recent_messages_list=[message])
             return
 
     async def main_loop(self):
         try:
             while self._running and not self._cycle_event.is_set():
                 if not self._hfc_lock.locked():
-                    async with self._hfc_lock:  # 确保主循环逻辑的互斥访问
+                    async with self._hfc_lock:
                         await self._hfc_func()
-                await asyncio.sleep(5)
+                await asyncio.sleep(0.1)
         except asyncio.CancelledError:
-            logger.info(f"{self.log_prefix} HeartFChatting: 主循环被取消，正在关闭")
-        except Exception as e:
-            logger.error(f"{self.log_prefix} 麦麦聊天意外错误: {e}，将于3s后尝试重新启动")
-            await self.stop()  # 确保状态正确
+            logger.info(f"{self.log_prefix} HeartFChatting: 主循环被取消")
+        except Exception as exc:
+            logger.error(f"{self.log_prefix} HeartFChatting: 主循环异常: {exc}", exc_info=True)
+            await self.stop()
             await asyncio.sleep(3)
-            await self.start()  # 尝试重新启动
+            await self.start()
 
     async def _config_callback(self, file_change: Optional[FileChange] = None):
-        """配置文件变更回调函数"""
-        # TODO: 根据配置文件变动重新计算相关参数：
-        """
-        需要计算的参数：
-        self._enable_expression_use = expr_use # 允许使用表达方式，但不一定启用学习
-        self._enable_expression_learning = expr_learn # 允许学习表达方式
-        self._enable_jargon_learning = jargon_learn # 允许学习黑话
-        """
+        del file_change
+        expr_use, jargon_learn, expr_learn = ExpressionConfigUtils.get_expression_config_for_chat(self.session_id)
+        self._enable_expression_use = expr_use
+        self._enable_expression_learning = expr_learn
+        self._enable_jargon_learning = jargon_learn
 
-    # ====== 心流聊天核心逻辑 ======
-    async def _hfc_func(self, mentioned_message: Optional["SessionMessage"] = None):
-        """心流聊天的主循环逻辑"""
-        if self._consecutive_no_reply_count >= 5:
-            threshold = 2
-        elif self._consecutive_no_reply_count >= 3:
-            threshold = 2 if random.random() < 0.5 else 1
-        else:
-            threshold = 1
+    async def _hfc_func(self):
+        recent_messages_list = message_api.get_messages_by_time_in_chat(
+            chat_id=self.session_id,
+            start_time=self.last_read_time,
+            end_time=time.time(),
+            limit=20,
+            limit_mode="latest",
+            filter_mai=True,
+            filter_command=False,
+            filter_intercept_message_level=1,
+        )
 
-        if len(self.message_cache) < threshold:
+        if len(recent_messages_list) < 1:
             await asyncio.sleep(0.2)
             return True
 
-        talk_value_threshold = (
-            random.random() * ChatConfigUtils.get_talk_value(self.session_id) * self._talk_frequency_adjust
-        )
-        if mentioned_message and global_config.chat.mentioned_bot_reply:
-            await self._judge_and_response(mentioned_message)
-        elif random.random() < talk_value_threshold:
-            await self._judge_and_response()
+        self.last_read_time = time.time()
+
+        mentioned_message: Optional["SessionMessage"] = None
+        for message in recent_messages_list:
+            if global_config.chat.inevitable_at_reply and message.is_at:
+                mentioned_message = message
+            elif global_config.chat.mentioned_bot_reply and message.is_mentioned:
+                mentioned_message = message
+
+        talk_value = ChatConfigUtils.get_talk_value(self.session_id) * self._talk_frequency_adjust
+        if mentioned_message:
+            await self._judge_and_response(mentioned_message=mentioned_message, recent_messages_list=recent_messages_list)
+        elif random.random() < talk_value:
+            await self._judge_and_response(recent_messages_list=recent_messages_list)
         return True
 
-    async def _judge_and_response(self, mentioned_message: Optional["SessionMessage"] = None):
-        """判定和生成回复"""
-        asyncio.create_task(self._trigger_expression_learning(self.message_cache))
-        # TODO: 完成反思器之后的逻辑
-        start_time = time.time()
-        current_cycle_detail = self._start_cycle()
+    async def _judge_and_response(
+        self,
+        mentioned_message: Optional["SessionMessage"] = None,
+        recent_messages_list: Optional[List["SessionMessage"]] = None,
+    ):
+        recent_messages = list(recent_messages_list or self.message_cache[-20:])
+        if recent_messages:
+            asyncio.create_task(self._trigger_expression_learning(recent_messages))
+
+        cycle_timers, thinking_id = self._start_cycle()
         logger.info(f"{self.log_prefix} 开始第{self._cycle_counter}次思考")
 
-        # TODO: 动作检查逻辑
-        # TODO: Planner逻辑
-        # TODO: 动作执行逻辑
+        try:
+            async with global_prompt_manager.async_message_scope(self._get_template_name()):
+                available_actions: Dict[str, ActionInfo] = {}
+                try:
+                    await self.action_modifier.modify_actions()
+                    available_actions = self.action_manager.get_using_actions()
+                except Exception as exc:
+                    logger.error(f"{self.log_prefix} 动作修改失败: {exc}", exc_info=True)
 
-        cycle_detail = self._end_cycle(current_cycle_detail)
-        if wait_time := global_config.chat.planner_smooth - (time.time() - start_time) > 0:
-            await asyncio.sleep(wait_time)
-        else:
-            await asyncio.sleep(0.1)  # 最小等待时间，避免过快循环
-        return True
+                is_group_chat, chat_target_info, _ = self.action_planner.get_necessary_info()
+                message_list_before_now = get_messages_before_time_in_chat(
+                    chat_id=self.session_id,
+                    timestamp=time.time(),
+                    limit=int(global_config.chat.max_context_size * 0.6),
+                    filter_intercept_message_level=1,
+                )
+                chat_content_block, message_id_list = build_readable_messages_with_id(
+                    messages=message_list_before_now,
+                    timestamp_mode="normal_no_YMD",
+                    read_mark=self.action_planner.last_obs_time_mark,
+                    truncate=True,
+                    show_actions=True,
+                )
+
+                prompt, filtered_actions = await self._build_planner_prompt_with_event(
+                    available_actions=available_actions,
+                    is_group_chat=is_group_chat,
+                    chat_target_info=chat_target_info,
+                    chat_content_block=chat_content_block,
+                    message_id_list=message_id_list,
+                )
+                if prompt is None:
+                    return False
+
+                with Timer("规划器", cycle_timers):
+                    reasoning, action_to_use_info, llm_raw_output, llm_reasoning, llm_duration_ms = (
+                        await self.action_planner._execute_main_planner(
+                            prompt=prompt,
+                            message_id_list=message_id_list,
+                            filtered_actions=filtered_actions,
+                            available_actions=available_actions,
+                            loop_start_time=self.last_read_time,
+                        )
+                    )
+
+                action_to_use_info = self._ensure_force_reply_action(
+                    actions=action_to_use_info,
+                    force_reply_message=mentioned_message,
+                    available_actions=available_actions,
+                )
+                self.action_planner.add_plan_log(reasoning, action_to_use_info)
+                self.action_planner.last_obs_time_mark = time.time()
+                self._log_plan(
+                    prompt=prompt,
+                    reasoning=reasoning,
+                    llm_raw_output=llm_raw_output,
+                    llm_reasoning=llm_reasoning,
+                    llm_duration_ms=llm_duration_ms,
+                    actions=action_to_use_info,
+                )
+
+                logger.info(
+                    f"{self.log_prefix} 决定执行{len(action_to_use_info)}个动作: {' '.join([a.action_type for a in action_to_use_info])}"
+                )
+
+                action_tasks = [
+                    asyncio.create_task(
+                        self._execute_action(
+                            action,
+                            action_to_use_info,
+                            thinking_id,
+                            available_actions,
+                            cycle_timers,
+                        )
+                    )
+                    for action in action_to_use_info
+                ]
+                results = await asyncio.gather(*action_tasks, return_exceptions=True)
+
+                reply_loop_info = None
+                reply_text_from_reply = ""
+                action_success = False
+                action_reply_text = ""
+                execute_result_str = ""
+
+                for result in results:
+                    if isinstance(result, BaseException):
+                        logger.error(f"{self.log_prefix} 动作执行异常: {result}", exc_info=True)
+                        continue
+
+                    execute_result_str += f"{result['action_type']} 执行结果:{result['result']}\n"
+                    if result["action_type"] == "reply":
+                        if result["success"]:
+                            reply_loop_info = result["loop_info"]
+                            reply_text_from_reply = result["result"]
+                        else:
+                            logger.warning(f"{self.log_prefix} reply 动作执行失败")
+                    else:
+                        action_success = result["success"]
+                        action_reply_text = result["result"]
+
+                self.action_planner.add_plan_excute_log(result=execute_result_str)
+
+                if reply_loop_info:
+                    loop_info = reply_loop_info
+                    loop_info["loop_action_info"].update(
+                        {
+                            "action_taken": action_success,
+                            "taken_time": time.time(),
+                        }
+                    )
+                else:
+                    loop_info = {
+                        "loop_plan_info": {
+                            "action_result": action_to_use_info,
+                        },
+                        "loop_action_info": {
+                            "action_taken": action_success,
+                            "reply_text": action_reply_text,
+                            "taken_time": time.time(),
+                        },
+                    }
+                    reply_text_from_reply = action_reply_text
+
+                current_cycle_detail = self._end_cycle(self._current_cycle_detail, loop_info)
+                logger.debug(f"{self.log_prefix} 本轮最终输出: {reply_text_from_reply}")
+                return current_cycle_detail is not None
+        except Exception as exc:
+            logger.error(f"{self.log_prefix} 判定与回复流程失败: {exc}", exc_info=True)
+            if self._current_cycle_detail:
+                self._end_cycle(
+                    self._current_cycle_detail,
+                    {
+                        "loop_plan_info": {"action_result": []},
+                        "loop_action_info": {
+                            "action_taken": False,
+                            "reply_text": "",
+                            "taken_time": time.time(),
+                            "error": str(exc),
+                        },
+                    },
+                )
+            return False
 
     def _handle_loop_completion(self, task: asyncio.Task):
-        """当 _hfc_func 任务完成时执行的回调。"""
         try:
             if exception := task.exception():
-                logger.error(f"{self.log_prefix} HeartFChatting: 脱离了聊天(异常): {exception}")
-                logger.error(traceback.format_exc())  # Log full traceback for exceptions
+                logger.error(f"{self.log_prefix} HeartFChatting: 主循环异常退出: {exception}")
+                logger.error(traceback.format_exc())
             else:
-                logger.info(f"{self.log_prefix} HeartFChatting: 脱离了聊天 (外部停止)")
+                logger.info(f"{self.log_prefix} HeartFChatting: 主循环已退出")
         except asyncio.CancelledError:
-            logger.info(f"{self.log_prefix} HeartFChatting: 结束了聊天")
+            logger.info(f"{self.log_prefix} HeartFChatting: 聊天已结束")
 
-    # ====== 学习器触发逻辑 ======
     async def _trigger_expression_learning(self, messages: List["SessionMessage"]):
+        if not messages:
+            return
+
         self._expression_learner.add_messages(messages)
         if time.time() - self._last_extraction_time < self._min_extraction_interval:
             return
@@ -233,12 +379,14 @@ class HeartFChatting:
             return
         if not self._enable_expression_learning:
             return
+
         extraction_end_time = time.time()
         logger.info(
             f"聊天流 {self.session_name} 提取到 {len(messages)} 条消息，"
             f"时间窗口: {self._last_extraction_time:.2f} - {extraction_end_time:.2f}"
         )
         self._last_extraction_time = extraction_end_time
+
         try:
             jargon_miner = self._jargon_miner if self._enable_jargon_learning else None
             learnt_style = await self._expression_learner.learn(jargon_miner)
@@ -246,43 +394,398 @@ class HeartFChatting:
                 logger.info(f"{self.log_prefix} 表达学习完成")
             else:
                 logger.debug(f"{self.log_prefix} 表达学习未获得有效结果")
-        except Exception as e:
-            logger.error(f"{self.log_prefix} 表达学习失败: {e}", exc_info=True)
+        except Exception as exc:
+            logger.error(f"{self.log_prefix} 表达学习失败: {exc}", exc_info=True)
 
-    # ====== 记录循环执行信息相关逻辑 ======
-    def _start_cycle(self) -> CycleDetail:
+    def _start_cycle(self) -> Tuple[Dict[str, float], str]:
         self._cycle_counter += 1
-        current_cycle_detail = CycleDetail(cycle_id=self._cycle_counter)
-        current_cycle_detail.thinking_id = f"tid{str(round(time.time(), 2))}"
-        return current_cycle_detail
+        self._current_cycle_detail = CycleDetail(cycle_id=self._cycle_counter)
+        self._current_cycle_detail.thinking_id = f"tid{str(round(time.time(), 2))}"
+        return self._current_cycle_detail.time_records, self._current_cycle_detail.thinking_id
 
-    def _end_cycle(self, cycle_detail: CycleDetail, only_long_execution: bool = True):
+    def _end_cycle(self, cycle_detail: Optional[CycleDetail], loop_info: Optional[Dict[str, Any]] = None):
+        if cycle_detail is None:
+            return None
+
+        cycle_detail.loop_plan_info = (loop_info or {}).get("loop_plan_info")
+        cycle_detail.loop_action_info = (loop_info or {}).get("loop_action_info")
         cycle_detail.end_time = time.time()
-        timer_strings: List[str] = [
+        self.history_loop.append(cycle_detail)
+
+        timer_strings = [
             f"{name}: {duration:.2f}s"
             for name, duration in cycle_detail.time_records.items()
-            if not only_long_execution or duration >= 0.1
+            if duration >= 0.1
         ]
         logger.info(
-            f"{self.log_prefix} 第 {cycle_detail.cycle_id} 个心流循环完成"
-            f"耗时: {cycle_detail.end_time - cycle_detail.start_time:.2f}秒\n"
+            f"{self.log_prefix} 第{cycle_detail.cycle_id} 个心流循环完成，"
+            f"耗时: {cycle_detail.end_time - cycle_detail.start_time:.2f}s；"
             f"详细计时: {', '.join(timer_strings) if timer_strings else '无'}"
         )
-
         return cycle_detail
 
-    # ====== Action相关逻辑 ======
-    async def _execute_action(self, *args, **kwargs):
-        """原ExecuteAction"""
-        raise NotImplementedError("执行动作的逻辑尚未实现")  # TODO: 实现动作执行的逻辑，替换掉*args, **kwargs*占位符
+    async def _execute_action(
+        self,
+        action_planner_info: ActionPlannerInfo,
+        chosen_action_plan_infos: List[ActionPlannerInfo],
+        thinking_id: str,
+        available_actions: Dict[str, ActionInfo],
+        cycle_timers: Dict[str, float],
+    ):
+        try:
+            with Timer(f"动作{action_planner_info.action_type}", cycle_timers):
+                if action_planner_info.action_type == "no_reply":
+                    reason = action_planner_info.reasoning or "选择不回复"
+                    self._consecutive_no_reply_count += 1
+                    await database_api.store_action_info(
+                        chat_stream=self.chat_stream,
+                        display_prompt=reason,
+                        thinking_id=thinking_id,
+                        action_data={},
+                        action_name="no_reply",
+                        action_reasoning=reason,
+                    )
+                    return {
+                        "action_type": "no_reply",
+                        "success": True,
+                        "result": "选择不回复",
+                        "loop_info": None,
+                    }
 
-    async def _execute_other_actions(self, *args, **kwargs):
-        """原HandleAction"""
-        raise NotImplementedError(
-            "执行其他动作的逻辑尚未实现"
-        )  # TODO: 实现其他动作执行的逻辑, 替换掉*args, **kwargs*占位符
+                if action_planner_info.action_type == "reply":
+                    self._consecutive_no_reply_count = 0
+                    reason = action_planner_info.reasoning or ""
+                    think_level = self._get_think_level(action_planner_info)
+                    planner_reasoning = action_planner_info.action_reasoning or reason
 
-    # ====== 响应发送相关方法 ======
-    async def _send_response(self, *args, **kwargs):
-        raise NotImplementedError("发送回复的逻辑尚未实现")  # TODO: 实现发送回复的逻辑，替换掉*args, **kwargs*占位符
-        # 传入的消息至少应该是个MessageSequence实例，最好是SessionMessage实例，随后可直接转化为MessageSending实例
+                    record_replyer_action_temp(
+                        chat_id=self.session_id,
+                        reason=reason,
+                        think_level=think_level,
+                    )
+                    await database_api.store_action_info(
+                        chat_stream=self.chat_stream,
+                        display_prompt=reason,
+                        thinking_id=thinking_id,
+                        action_data={},
+                        action_name="reply",
+                        action_reasoning=reason,
+                    )
+
+                    unknown_words, quote_message = self._extract_reply_metadata(action_planner_info)
+                    success, llm_response = await generator_api.generate_reply(
+                        chat_stream=self.chat_stream,
+                        reply_message=action_planner_info.action_message,
+                        available_actions=available_actions,
+                        chosen_actions=chosen_action_plan_infos,
+                        reply_reason=planner_reasoning,
+                        unknown_words=unknown_words,
+                        enable_tool=global_config.tool.enable_tool,
+                        request_type="replyer",
+                        from_plugin=False,
+                        reply_time_point=action_planner_info.action_data.get("loop_start_time", time.time())
+                        if action_planner_info.action_data
+                        else time.time(),
+                        think_level=think_level,
+                    )
+                    if not success or not llm_response or not llm_response.reply_set:
+                        if action_planner_info.action_message:
+                            logger.info(
+                                f"对 {action_planner_info.action_message.processed_plain_text} 的回复生成失败"
+                            )
+                        else:
+                            logger.info(f"{self.log_prefix} 回复生成失败")
+                        return {
+                            "action_type": "reply",
+                            "success": False,
+                            "result": "回复生成失败",
+                            "loop_info": None,
+                        }
+
+                    loop_info, reply_text, _ = await self._send_and_store_reply(
+                        response_set=llm_response.reply_set,
+                        action_message=action_planner_info.action_message,  # type: ignore[arg-type]
+                        cycle_timers=cycle_timers,
+                        thinking_id=thinking_id,
+                        actions=chosen_action_plan_infos,
+                        selected_expressions=llm_response.selected_expressions,
+                        quote_message=quote_message,
+                    )
+                    self.last_active_time = time.time()
+                    return {
+                        "action_type": "reply",
+                        "success": True,
+                        "result": reply_text,
+                        "loop_info": loop_info,
+                    }
+
+                with Timer("动作执行", cycle_timers):
+                    success, result = await self._handle_action(
+                        action=action_planner_info.action_type,
+                        action_reasoning=action_planner_info.action_reasoning or "",
+                        action_data=action_planner_info.action_data or {},
+                        cycle_timers=cycle_timers,
+                        thinking_id=thinking_id,
+                        action_message=action_planner_info.action_message,
+                    )
+                if success:
+                    self.last_active_time = time.time()
+                return {
+                    "action_type": action_planner_info.action_type,
+                    "success": success,
+                    "result": result,
+                    "loop_info": None,
+                }
+        except Exception as exc:
+            logger.error(f"{self.log_prefix} 执行动作时出错: {exc}", exc_info=True)
+            return {
+                "action_type": action_planner_info.action_type,
+                "success": False,
+                "result": "",
+                "loop_info": None,
+                "error": str(exc),
+            }
+
+    async def _handle_action(
+        self,
+        action: str,
+        action_reasoning: str,
+        action_data: dict,
+        cycle_timers: Dict[str, float],
+        thinking_id: str,
+        action_message: Optional["SessionMessage"] = None,
+    ) -> Tuple[bool, str]:
+        try:
+            action_handler = self.action_manager.create_action(
+                action_name=action,
+                action_data=action_data,
+                action_reasoning=action_reasoning,
+                cycle_timers=cycle_timers,
+                thinking_id=thinking_id,
+                chat_stream=self.chat_stream,
+                log_prefix=self.log_prefix,
+                action_message=action_message,
+            )
+            if not action_handler:
+                logger.warning(f"{self.log_prefix} 未能创建动作处理器: {action}")
+                return False, ""
+
+            success, action_text = await action_handler.execute()
+            return success, action_text
+        except Exception as exc:
+            logger.error(f"{self.log_prefix} 处理动作 {action} 时出错: {exc}", exc_info=True)
+            return False, ""
+
+    async def _send_and_store_reply(
+        self,
+        response_set: MessageSequence,
+        action_message: "SessionMessage",
+        cycle_timers: Dict[str, float],
+        thinking_id: str,
+        actions: List[ActionPlannerInfo],
+        selected_expressions: Optional[List[int]] = None,
+        quote_message: Optional[bool] = None,
+    ) -> Tuple[Dict[str, Any], str, Dict[str, float]]:
+        with Timer("回复发送", cycle_timers):
+            reply_text = await self._send_response(
+                reply_set=response_set,
+                message_data=action_message,
+                selected_expressions=selected_expressions,
+                quote_message=quote_message,
+            )
+
+        platform = action_message.platform or getattr(self.chat_stream, "platform", "unknown")
+        person = Person(platform=platform, user_id=action_message.message_info.user_info.user_id)
+        action_prompt_display = f"你对{person.person_name}进行了回复：{reply_text}"
+        await database_api.store_action_info(
+            chat_stream=self.chat_stream,
+            display_prompt=action_prompt_display,
+            thinking_id=thinking_id,
+            action_data={"reply_text": reply_text},
+            action_name="reply",
+        )
+
+        loop_info: Dict[str, Any] = {
+            "loop_plan_info": {
+                "action_result": actions,
+            },
+            "loop_action_info": {
+                "action_taken": True,
+                "reply_text": reply_text,
+                "command": "",
+                "taken_time": time.time(),
+            },
+        }
+        return loop_info, reply_text, cycle_timers
+
+    async def _send_response(
+        self,
+        reply_set: MessageSequence,
+        message_data: "SessionMessage",
+        selected_expressions: Optional[List[int]] = None,
+        quote_message: Optional[bool] = None,
+    ) -> str:
+        if global_config.chat.llm_quote:
+            need_reply = bool(quote_message)
+        else:
+            new_message_count = message_api.count_new_messages(
+                chat_id=self.session_id,
+                start_time=self.last_read_time,
+                end_time=time.time(),
+            )
+            need_reply = new_message_count >= random.randint(2, 3) or time.time() - self.last_read_time > 90
+
+        reply_text = ""
+        first_replied = False
+        for component in reply_set.components:
+            if not isinstance(component, TextComponent):
+                continue
+            data = component.text
+            if not first_replied:
+                await send_api.text_to_stream(
+                    text=data,
+                    stream_id=self.session_id,
+                    reply_message=message_data,
+                    set_reply=need_reply,
+                    typing=False,
+                    selected_expressions=selected_expressions,
+                )
+                first_replied = True
+            else:
+                await send_api.text_to_stream(
+                    text=data,
+                    stream_id=self.session_id,
+                    reply_message=message_data,
+                    set_reply=False,
+                    typing=True,
+                    selected_expressions=selected_expressions,
+                )
+            reply_text += data
+        return reply_text
+
+    async def _build_planner_prompt_with_event(
+        self,
+        available_actions: Dict[str, ActionInfo],
+        is_group_chat: bool,
+        chat_target_info: Any,
+        chat_content_block: str,
+        message_id_list: List[Tuple[str, "SessionMessage"]],
+    ) -> Tuple[Optional[str], Dict[str, ActionInfo]]:
+        filtered_actions = self.action_planner._filter_actions_by_activation_type(available_actions, chat_content_block)
+        prompt, _ = await self.action_planner.build_planner_prompt(
+            is_group_chat=is_group_chat,
+            chat_target_info=chat_target_info,
+            current_available_actions=filtered_actions,
+            chat_content_block=chat_content_block,
+            message_id_list=message_id_list,
+        )
+        event_message = build_event_message(EventType.ON_PLAN, llm_prompt=prompt, stream_id=self.session_id)
+        continue_flag, modified_message = await event_bus.emit(EventType.ON_PLAN, event_message)
+        if not continue_flag:
+            logger.info(f"{self.log_prefix} ON_PLAN 事件中止了本轮 HFC")
+            return None, filtered_actions
+        if modified_message and modified_message._modify_flags.modify_llm_prompt and modified_message.llm_prompt:
+            prompt = modified_message.llm_prompt
+        return prompt, filtered_actions
+
+    def _ensure_force_reply_action(
+        self,
+        actions: List[ActionPlannerInfo],
+        force_reply_message: Optional["SessionMessage"],
+        available_actions: Dict[str, ActionInfo],
+    ) -> List[ActionPlannerInfo]:
+        if not force_reply_message:
+            return actions
+
+        has_reply_to_force_message = any(
+            action.action_type == "reply"
+            and action.action_message
+            and action.action_message.message_id == force_reply_message.message_id
+            for action in actions
+        )
+        if has_reply_to_force_message:
+            return actions
+
+        actions = [action for action in actions if action.action_type != "no_reply"]
+        actions.insert(
+            0,
+            ActionPlannerInfo(
+                action_type="reply",
+                reasoning="用户提及了我，必须回复该消息",
+                action_data={"loop_start_time": self.last_read_time},
+                action_message=force_reply_message,
+                available_actions=available_actions,
+                action_reasoning=None,
+            ),
+        )
+        logger.info(f"{self.log_prefix} 检测到强制回复消息，已补充 reply 动作")
+        return actions
+
+    def _log_plan(
+        self,
+        prompt: str,
+        reasoning: str,
+        llm_raw_output: Optional[str],
+        llm_reasoning: Optional[str],
+        llm_duration_ms: Optional[float],
+        actions: List[ActionPlannerInfo],
+    ) -> None:
+        try:
+            PlanReplyLogger.log_plan(
+                chat_id=self.session_id,
+                prompt=prompt,
+                reasoning=reasoning,
+                raw_output=llm_raw_output,
+                raw_reasoning=llm_reasoning,
+                actions=actions,
+                timing={
+                    "llm_duration_ms": round(llm_duration_ms, 2) if llm_duration_ms is not None else None,
+                    "loop_start_time": self.last_read_time,
+                },
+                extra=None,
+            )
+        except Exception:
+            logger.exception(f"{self.log_prefix} 记录 plan 日志失败")
+
+    def _extract_reply_metadata(
+        self,
+        action_planner_info: ActionPlannerInfo,
+    ) -> Tuple[Optional[List[str]], Optional[bool]]:
+        unknown_words: Optional[List[str]] = None
+        quote_message: Optional[bool] = None
+        action_data = action_planner_info.action_data or {}
+
+        raw_unknown_words = action_data.get("unknown_words")
+        if isinstance(raw_unknown_words, list):
+            cleaned_unknown_words = []
+            for item in raw_unknown_words:
+                if isinstance(item, str) and (cleaned_item := item.strip()):
+                    cleaned_unknown_words.append(cleaned_item)
+            if cleaned_unknown_words:
+                unknown_words = cleaned_unknown_words
+
+        raw_quote = action_data.get("quote")
+        if isinstance(raw_quote, bool):
+            quote_message = raw_quote
+        elif isinstance(raw_quote, str):
+            quote_message = raw_quote.lower() in {"true", "1", "yes"}
+        elif isinstance(raw_quote, (int, float)):
+            quote_message = bool(raw_quote)
+
+        return unknown_words, quote_message
+
+    def _get_think_level(self, action_planner_info: ActionPlannerInfo) -> int:
+        think_mode = global_config.chat.think_mode
+        if think_mode == "default":
+            return 0
+        if think_mode == "deep":
+            return 1
+        if think_mode == "dynamic":
+            action_data = action_planner_info.action_data or {}
+            return int(action_data.get("think_level", 1))
+        return 0
+
+    def _get_template_name(self) -> Optional[str]:
+        if self.chat_stream.context:
+            return self.chat_stream.context.template_name
+        return None