better：让表情包和文字统一发送

src/chat/focus_chat/expressors/default_expressor.py

@@ -1,6 +1,5 @@
-import time
 import traceback
-from typing import List, Optional, Dict, Any
+from typing import List, Optional, Dict, Any, Tuple
 from src.chat.message_receive.message import MessageRecv, MessageThinking, MessageSending
 from src.chat.message_receive.message import Seg  # Local import needed after move
 from src.chat.message_receive.message import UserInfo
@@ -18,6 +17,7 @@ from src.chat.utils.info_catcher import info_catcher_manager
 from src.manager.mood_manager import mood_manager
 from src.chat.heart_flow.utils_chat import get_chat_type_and_target_info
 from src.chat.message_receive.chat_stream import ChatStream
+from src.chat.focus_chat.hfc_utils import parse_thinking_id_to_timestamp
 
 logger = get_logger("expressor")
 
@@ -41,7 +41,7 @@ class DefaultExpressor:
     async def initialize(self):
         self.is_group_chat, self.chat_target_info = await get_chat_type_and_target_info(self.chat_id)
 
-    async def _create_thinking_message(self, anchor_message: Optional[MessageRecv]) -> Optional[str]:
+    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。")
@@ -49,6 +49,7 @@ class DefaultExpressor:
 
         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,
             user_nickname=global_config.BOT_NICKNAME,
@@ -58,9 +59,6 @@ class DefaultExpressor:
         # logger.debug(f"创建思考消息chat：{chat}")
         # logger.debug(f"创建思考消息bot_user_info：{bot_user_info}")
         # logger.debug(f"创建思考消息messageinfo：{messageinfo}")
-
-        thinking_time_point = round(time.time(), 2)
-        thinking_id = "mt" + str(thinking_time_point)
         thinking_message = MessageThinking(
             message_id=thinking_id,
             chat_stream=chat,
@@ -69,9 +67,8 @@ class DefaultExpressor:
             thinking_start_time=thinking_time_point,
         )
         logger.debug(f"创建思考消息thinking_message：{thinking_message}")
-        # Access MessageManager directly (using heart_fc_sender)
+
         await self.heart_fc_sender.register_thinking(thinking_message)
-        return thinking_id
 
     async def deal_reply(
         self,
@@ -79,11 +76,10 @@ class DefaultExpressor:
         action_data: Dict[str, Any],
         reasoning: str,
         anchor_message: MessageRecv,
+        thinking_id: str,
     ) -> tuple[bool, Optional[List[str]]]:
         # 创建思考消息
-        thinking_id = await self._create_thinking_message(anchor_message)
+        await self._create_thinking_message(anchor_message, thinking_id)
-        if not thinking_id:
-            raise Exception("无法创建思考消息")
 
         reply = None  # 初始化 reply，防止未定义
         try:
@@ -102,8 +98,14 @@ class DefaultExpressor:
                         action_data=action_data,
                     )
 
+                with Timer("选择表情", cycle_timers):
+                    emoji_keyword = action_data.get("emojis", [])
+                    emoji_base64 = await self._choose_emoji(emoji_keyword)
+                    if emoji_base64:
+                        reply.append(("emoji", emoji_base64))
+
                 if reply:
-                    with Timer("发送文本消息", cycle_timers):
+                    with Timer("发送消息", cycle_timers):
                         await self._send_response_messages(
                             anchor_message=anchor_message,
                             thinking_id=thinking_id,
@@ -113,12 +115,6 @@ class DefaultExpressor:
                 else:
                     logger.warning(f"{self.log_prefix} 文本回复生成失败")
 
-            # 处理表情部分
-            emoji_keyword = action_data.get("emojis", [])
-            if emoji_keyword:
-                await self._handle_emoji(anchor_message, [], emoji_keyword)
-                has_sent_something = True
-
             if not has_sent_something:
                 logger.warning(f"{self.log_prefix} 回复动作未包含任何有效内容")
 
@@ -195,40 +191,46 @@ class DefaultExpressor:
                     logger.info(f"想要表达：{in_mind_reply}")
                     logger.info(f"理由：{reason}")
                     logger.info(f"生成回复: {content}\n")
+
                 info_catcher.catch_after_llm_generated(
                     prompt=prompt, response=content, reasoning_content=reasoning_content, model_name=model_name
                 )
 
             except Exception as llm_e:
                 # 精简报错信息
-                logger.error(f"{self.log_prefix}[Replier-{thinking_id}] LLM 生成失败: {llm_e}")
+                logger.error(f"{self.log_prefix}LLM 生成失败: {llm_e}")
                 return None  # LLM 调用失败则无法生成回复
 
-            # 5. 处理 LLM 响应
-            if not content:
-                logger.warning(f"{self.log_prefix}[Replier-{thinking_id}] LLM 生成了空内容。")
-                return None
-
             processed_response = process_llm_response(content)
 
+            # 5. 处理 LLM 响应
+            if not content:
+                logger.warning(f"{self.log_prefix}LLM 生成了空内容。")
+                return None
             if not processed_response:
-                logger.warning(f"{self.log_prefix}[Replier-{thinking_id}] 处理后的回复为空。")
+                logger.warning(f"{self.log_prefix}处理后的回复为空。")
                 return None
 
-            return processed_response
+            reply_set = []
+            for str in processed_response:
+                reply_seg = ("text", str)
+                reply_set.append(reply_seg)
+
+            return reply_set
 
         except Exception as e:
-            logger.error(f"{self.log_prefix}[Replier-{thinking_id}] 回复生成意外失败: {e}")
+            logger.error(f"{self.log_prefix}回复生成意外失败: {e}")
             traceback.print_exc()
             return None
 
         # --- 发送器 (Sender) --- #
 
     async def _send_response_messages(
-        self, anchor_message: Optional[MessageRecv], response_set: List[str], thinking_id: str
+        self, anchor_message: Optional[MessageRecv], response_set: List[Tuple[str, str]], thinking_id: 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_id
         if chat is None:
             logger.error(f"{self.log_prefix} 无法发送回复，chat_stream 为空。")
             return None
@@ -236,98 +238,104 @@ class DefaultExpressor:
             logger.error(f"{self.log_prefix} 无法发送回复，anchor_message 为空。")
             return None
 
-        chat_id = self.chat_id
         stream_name = 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
         thinking_start_time = await self.heart_fc_sender.get_thinking_start_time(chat_id, thinking_id)
 
         if thinking_start_time is None:
-            logger.warning(f"[{stream_name}] {thinking_id} 思考过程未找到或已结束，无法发送回复。")
+            logger.error(f"[{stream_name}]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
-        bot_user_info = UserInfo(
-            user_id=global_config.BOT_QQ,
-            user_nickname=global_config.BOT_NICKNAME,
-            platform=chat.platform,
-        )
 
         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]
+
             part_message_id = f"{thinking_id}_{i}"
-            message_segment = Seg(type="text", data=msg_text)
+            message_segment = Seg(type=type, data=data)
-            bot_message = MessageSending(
+
-                message_id=part_message_id,  # 使用片段的唯一ID
+            if type == "emoji":
-                chat_stream=chat,
+                is_emoji = True
-                bot_user_info=bot_user_info,
+            else:
-                sender_info=anchor_message.message_info.user_info,
+                is_emoji = False
+            reply_to = not mark_head
+
+            bot_message = self._build_single_sending_message(
+                anchor_message=anchor_message,
+                message_id=part_message_id,
                 message_segment=message_segment,
-                reply=anchor_message,  # 回复原始锚点
+                reply_to=reply_to,
-                is_head=not mark_head,
+                is_emoji=is_emoji,
-                is_emoji=False,
+                thinking_id=thinking_id,
-                thinking_start_time=thinking_start_time,  # 传递原始思考开始时间
             )
+
             try:
                 if not mark_head:
                     mark_head = True
                     first_bot_msg = bot_message  # 保存第一个成功发送的消息对象
-                    await self.heart_fc_sender.type_and_send_message(bot_message, typing=False)
+                    typing = False
                 else:
-                    await self.heart_fc_sender.type_and_send_message(bot_message, typing=True)
+                    typing = True
+
+                await self.heart_fc_sender.send_message(bot_message, has_thinking=True, typing=typing)
 
                 reply_message_ids.append(part_message_id)  # 记录我们生成的ID
 
             except Exception as e:
-                logger.error(
+                logger.error(f"{self.log_prefix}发送回复片段 {i} ({part_message_id}) 时失败: {e}")
-                    f"{self.log_prefix}[Sender-{thinking_id}] 发送回复片段 {i} ({part_message_id}) 时失败: {e}"
-                )
                 # 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}[Sender-{thinking_id}] 完成思考状态 {thinking_id} 时出错: {e}")
+            logger.error(f"{self.log_prefix}完成思考状态 {thinking_id} 时出错: {e}")
 
         return first_bot_msg  # 返回第一个成功发送的消息对象
 
-    async def _handle_emoji(self, anchor_message: Optional[MessageRecv], response_set: List[str], send_emoji: str = ""):
+    async def _choose_emoji(self, send_emoji: str):
-        """处理表情包 (尝试锚定到 anchor_message)，使用 HeartFCSender"""
+        """
-        if not anchor_message or not anchor_message.chat_stream:
+        选择表情，根据send_emoji文本选择表情，返回表情base64
-            logger.error(f"{self.log_prefix} 无法处理表情包，缺少有效的锚点消息或聊天流。")
+        """
-            return
-
-        chat = anchor_message.chat_stream
-
         emoji_raw = await emoji_manager.get_emoji_for_text(send_emoji)
-
         if emoji_raw:
-            emoji_path, description = emoji_raw
+            emoji_path, _description = emoji_raw
+            emoji_base64 = image_path_to_base64(emoji_path)
+        return emoji_base64
 
-            emoji_cq = image_path_to_base64(emoji_path)
+    async def _build_single_sending_message(
-            thinking_time_point = round(time.time(), 2)  # 用于唯一ID
+        self,
-            message_segment = Seg(type="emoji", data=emoji_cq)
+        anchor_message: MessageRecv,
+        message_id: str,
+        message_segment: Seg,
+        reply_to: bool,
+        is_emoji: bool,
+        thinking_id: str,
+    ) -> MessageSending:
+        """构建单个发送消息"""
+
+        thinking_start_time = await self.heart_fc_sender.get_thinking_start_time(self.chat_id, thinking_id)
         bot_user_info = UserInfo(
             user_id=global_config.BOT_QQ,
             user_nickname=global_config.BOT_NICKNAME,
-                platform=anchor_message.message_info.platform,
+            platform=self.chat_stream.platform,
         )
+
         bot_message = MessageSending(
-                message_id="me" + str(thinking_time_point),  # 表情消息的唯一ID
+            message_id=message_id,  # 使用片段的唯一ID
-                chat_stream=chat,
+            chat_stream=self.chat_stream,
             bot_user_info=bot_user_info,
             sender_info=anchor_message.message_info.user_info,
             message_segment=message_segment,
             reply=anchor_message,  # 回复原始锚点
-                is_head=False,  # 表情通常不是头部消息
+            is_head=reply_to,
-                is_emoji=True,
+            is_emoji=is_emoji,
-                # 不需要 thinking_start_time
+            thinking_start_time=thinking_start_time,  # 传递原始思考开始时间
         )
 
-            try:
+        return bot_message
-                await self.heart_fc_sender.send_and_store(bot_message)
-            except Exception as e:
-                logger.error(f"{self.log_prefix} 发送表情包 {bot_message.message_info.message_id} 时失败: {e}")

src/chat/focus_chat/expressors/exprssion_learner.py

@@ -58,9 +58,9 @@ def init_prompt() -> None:
 {chat_str}
 
 请从上面这段群聊中概括除了人名为"麦麦"之外的人的语法和句法特点，只考虑纯文字，不要考虑表情包和图片
-不要总结【图片】，【动画表情】，[图片]，[动画表情]，不总结 表情符号
+不要总结【图片】，【动画表情】，[图片]，[动画表情]，不总结 表情符号 at @ 回复 和[回复]
 不要涉及具体的人名，只考虑语法和句法特点,
-语法和句法特点要包括，句子长短（具体字数），如何分局，有何种语病，如何拆分句子。
+语法和句法特点要包括，句子长短（具体字数），有何种语病，如何拆分句子。
 总结成如下格式的规律，总结的内容要简洁，不浮夸：
 当"xxx"时，可以"xxx"
 

src/chat/focus_chat/heartFC_chat.py

@@ -30,7 +30,7 @@ from src.chat.heart_flow.observation.hfcloop_observation import HFCloopObservati
 from src.chat.heart_flow.observation.working_observation import WorkingObservation
 from src.chat.focus_chat.info_processors.tool_processor import ToolProcessor
 from src.chat.focus_chat.expressors.default_expressor import DefaultExpressor
-from src.chat.focus_chat.hfc_utils import _create_empty_anchor_message
+from src.chat.focus_chat.hfc_utils import create_empty_anchor_message, parse_thinking_id_to_timestamp
 from src.chat.focus_chat.memory_activator import MemoryActivator
 
 install(extra_lines=3)
@@ -203,9 +203,9 @@ class HeartFChatting:
         self._cycle_counter = 0
         self._cycle_history: Deque[CycleDetail] = deque(maxlen=10)  # 保留最近10个循环的信息
         self._current_cycle: Optional[CycleDetail] = None
-        self._lian_xu_bu_hui_fu_ci_shu: int = 0  # <--- 新增：连续不回复计数器
+        self.total_no_reply_count: int = 0  # <--- 新增：连续不回复计数器
         self._shutting_down: bool = False  # <--- 新增：关闭标志位
-        self._lian_xu_deng_dai_shi_jian: float = 0.0  # <--- 新增：累计等待时间
+        self.total_waiting_time: float = 0.0  # <--- 新增：累计等待时间
 
     async def _initialize(self) -> bool:
         """
@@ -325,11 +325,12 @@ class HeartFChatting:
                         await asyncio.sleep(0.1)  # 短暂等待避免空转
                         continue
 
-                    # 记录规划开始时间点
+                    # thinking_id 是思考过程的ID，用于标记每一轮思考
-                    planner_start_db_time = time.time()
+                    thinking_id = "tid" + str(round(time.time(), 2))
 
                     # 主循环：思考->决策->执行
-                    action_taken, thinking_id = await self._think_plan_execute_loop(cycle_timers, planner_start_db_time)
+
+                    action_taken = await self._think_plan_execute_loop(cycle_timers, thinking_id)
 
                     # 更新循环信息
                     self._current_cycle.set_thinking_id(thinking_id)
@@ -391,9 +392,8 @@ class HeartFChatting:
             if acquired and self._processing_lock.locked():
                 self._processing_lock.release()
 
-    async def _think_plan_execute_loop(self, cycle_timers: dict, planner_start_db_time: float) -> tuple[bool, str]:
+    async def _think_plan_execute_loop(self, cycle_timers: dict, thinking_id: str) -> tuple[bool, str]:
         try:
-            await asyncio.sleep(1)
             with Timer("观察", cycle_timers):
                 await self.observations[0].observe()
                 await self.memory_observation.observe()
@@ -515,7 +515,7 @@ class HeartFChatting:
 
             self.hfcloop_observation.add_loop_info(self._current_cycle)
 
-            return await self._handle_action(action, reasoning, action_data, cycle_timers, planner_start_db_time)
+            return await self._handle_action(action, reasoning, action_data, cycle_timers, thinking_id)
 
         except Exception as e:
             logger.error(f"{self.log_prefix} 并行+串行处理失败: {e}")
@@ -523,7 +523,12 @@ class HeartFChatting:
             return False, ""
 
     async def _handle_action(
-        self, action: str, reasoning: str, action_data: dict, cycle_timers: dict, planner_start_db_time: float
+        self,
+        action: str,
+        reasoning: str,
+        action_data: dict,
+        cycle_timers: dict,
+        thinking_id: str,
     ) -> tuple[bool, str]:
         """
         处理规划动作
@@ -550,17 +555,17 @@ class HeartFChatting:
 
         try:
             if action == "reply":
-                return await handler(reasoning, action_data, cycle_timers)
+                return await handler(reasoning, action_data, cycle_timers, thinking_id)
             else:  # no_reply
-                return await handler(reasoning, planner_start_db_time, cycle_timers), ""
+                return await handler(reasoning, cycle_timers, thinking_id)
         except Exception as e:
             logger.error(f"{self.log_prefix} 处理{action}时出错: {e}")
             # 出错时也重置计数器
-            self._lian_xu_bu_hui_fu_ci_shu = 0
+            self.total_no_reply_count = 0
-            self._lian_xu_deng_dai_shi_jian = 0.0
+            self.total_waiting_time = 0.0
             return False, ""
 
-    async def _handle_no_reply(self, reasoning: str, planner_start_db_time: float, cycle_timers: dict) -> bool:
+    async def _handle_no_reply(self, reasoning: str, cycle_timers: dict, thinking_id: str) -> bool:
         """
         处理不回复的情况
 
@@ -584,53 +589,50 @@ class HeartFChatting:
         try:
             with Timer("等待新消息", cycle_timers):
                 # 等待新消息、超时或关闭信号，并获取结果
-                await self._wait_for_new_message(observation, planner_start_db_time, self.log_prefix)
+                await self._wait_for_new_message(observation, thinking_id, self.log_prefix)
             # 从计时器获取实际等待时间
             current_waiting = cycle_timers.get("等待新消息", 0.0)
 
             if not self._shutting_down:
-                self._lian_xu_bu_hui_fu_ci_shu += 1
+                self.total_no_reply_count += 1
-                self._lian_xu_deng_dai_shi_jian += current_waiting  # 累加等待时间
+                self.total_waiting_time += current_waiting  # 累加等待时间
                 logger.debug(
-                    f"{self.log_prefix} 连续不回复计数增加: {self._lian_xu_bu_hui_fu_ci_shu}/{CONSECUTIVE_NO_REPLY_THRESHOLD}, "
+                    f"{self.log_prefix} 连续不回复计数增加: {self.total_no_reply_count}/{CONSECUTIVE_NO_REPLY_THRESHOLD}, "
-                    f"本次等待: {current_waiting:.2f}秒, 累计等待: {self._lian_xu_deng_dai_shi_jian:.2f}秒"
+                    f"本次等待: {current_waiting:.2f}秒, 累计等待: {self.total_waiting_time:.2f}秒"
                 )
 
                 # 检查是否同时达到次数和时间阈值
                 time_threshold = 0.66 * WAITING_TIME_THRESHOLD * CONSECUTIVE_NO_REPLY_THRESHOLD
                 if (
-                    self._lian_xu_bu_hui_fu_ci_shu >= CONSECUTIVE_NO_REPLY_THRESHOLD
+                    self.total_no_reply_count >= CONSECUTIVE_NO_REPLY_THRESHOLD
-                    and self._lian_xu_deng_dai_shi_jian >= time_threshold
+                    and self.total_waiting_time >= time_threshold
                 ):
                     logger.info(
-                        f"{self.log_prefix} 连续不回复达到阈值 ({self._lian_xu_bu_hui_fu_ci_shu}次) "
+                        f"{self.log_prefix} 连续不回复达到阈值 ({self.total_no_reply_count}次) "
-                        f"且累计等待时间达到 {self._lian_xu_deng_dai_shi_jian:.2f}秒 (阈值 {time_threshold}秒)，"
+                        f"且累计等待时间达到 {self.total_waiting_time:.2f}秒 (阈值 {time_threshold}秒)，"
                         f"调用回调请求状态转换"
                     )
                     # 调用回调。注意：这里不重置计数器和时间，依赖回调函数成功改变状态来隐式重置上下文。
                     await self.on_consecutive_no_reply_callback()
-                elif self._lian_xu_bu_hui_fu_ci_shu >= CONSECUTIVE_NO_REPLY_THRESHOLD:
+                elif self.total_no_reply_count >= CONSECUTIVE_NO_REPLY_THRESHOLD:
                     # 仅次数达到阈值，但时间未达到
                     logger.debug(
-                        f"{self.log_prefix} 连续不回复次数达到阈值 ({self._lian_xu_bu_hui_fu_ci_shu}次) "
+                        f"{self.log_prefix} 连续不回复次数达到阈值 ({self.total_no_reply_count}次) "
-                        f"但累计等待时间 {self._lian_xu_deng_dai_shi_jian:.2f}秒 未达到时间阈值 ({time_threshold}秒)，暂不调用回调"
+                        f"但累计等待时间 {self.total_waiting_time:.2f}秒 未达到时间阈值 ({time_threshold}秒)，暂不调用回调"
                     )
                 # else: 次数和时间都未达到阈值，不做处理
 
-            return True
+            return True, thinking_id
 
         except asyncio.CancelledError:
-            # 如果在等待过程中任务被取消（可能是因为 shutdown）
             logger.info(f"{self.log_prefix} 处理 'no_reply' 时等待被中断 (CancelledError)")
-            # 让异常向上传播，由 _hfc_loop 的异常处理逻辑接管
             raise
         except Exception as e:  # 捕获调用管理器或其他地方可能发生的错误
             logger.error(f"{self.log_prefix} 处理 'no_reply' 时发生错误: {e}")
             logger.error(traceback.format_exc())
-            # 发生意外错误时，可以选择是否重置计数器，这里选择不重置
+            return False, thinking_id
-            return False  # 表示动作未成功
 
-    async def _wait_for_new_message(self, observation, planner_start_db_time: float, log_prefix: str) -> bool:
+    async def _wait_for_new_message(self, observation: ChattingObservation, thinking_id: str, log_prefix: str) -> bool:
         """
         等待新消息 或 检测到关闭信号
 
@@ -650,8 +652,10 @@ class HeartFChatting:
                 return False  # 表示因为关闭而退出
             # -----------------------------------
 
+            thinking_id_timestamp = parse_thinking_id_to_timestamp(thinking_id)
+
             # 检查新消息
-            if await observation.has_new_messages_since(planner_start_db_time):
+            if await observation.has_new_messages_since(thinking_id_timestamp):
                 logger.info(f"{log_prefix} 检测到新消息")
                 return True
 
@@ -925,38 +929,42 @@ class HeartFChatting:
             "llm_error": llm_error,  # 返回错误状态
         }
 
-    async def _handle_reply(self, reasoning: str, reply_data: dict, cycle_timers: dict) -> tuple[bool, str]:
+    async def _handle_reply(
+        self, reasoning: str, reply_data: dict, cycle_timers: dict, thinking_id: str
+    ) -> tuple[bool, str]:
         """
         处理统一的回复动作 - 可包含文本和表情，顺序任意
 
         reply_data格式:
         {
-            "text": ["你好啊", "今天天气真不错"],  # 文本内容列表（可选）
+            "text": "你好啊"  # 文本内容列表（可选）
-            "emojis": ["微笑", "阳光"]  # 表情关键词列表（可选）
+            "target": "锚定消息",  # 锚定消息的文本内容
+            "emojis": "微笑"  # 表情关键词列表（可选）
         }
         """
         # 重置连续不回复计数器
-        self._lian_xu_bu_hui_fu_ci_shu = 0
+        self.total_no_reply_count = 0
-        self._lian_xu_deng_dai_shi_jian = 0.0
+        self.total_waiting_time = 0.0
 
-        # 获取锚定消息
+        # 从聊天观察获取锚定消息
         observations: ChattingObservation = self.observations[0]
         anchor_message = observations.serch_message_by_text(reply_data["target"])
 
         # 如果没有找到锚点消息，创建一个占位符
         if not anchor_message:
             logger.info(f"{self.log_prefix} 未找到锚点消息，创建占位符")
-            anchor_message = await _create_empty_anchor_message(
+            anchor_message = await create_empty_anchor_message(
                 self.chat_stream.platform, self.chat_stream.group_info, self.chat_stream
             )
-            if not anchor_message:
-                logger.error(f"{self.log_prefix} 创建占位符失败，无法继续处理回复")
-                return False, ""
         else:
             anchor_message.update_chat_stream(self.chat_stream)
 
         success, reply_set = await self.expressor.deal_reply(
-            cycle_timers=cycle_timers, action_data=reply_data, anchor_message=anchor_message, reasoning=reasoning
+            cycle_timers=cycle_timers,
+            action_data=reply_data,
+            anchor_message=anchor_message,
+            reasoning=reasoning,
+            thinking_id=thinking_id,
         )
 
         reply_text = ""

src/chat/focus_chat/heartFC_sender.py

@@ -7,6 +7,7 @@ from src.chat.utils.utils import truncate_message
 from src.common.logger_manager import get_logger
 from src.chat.utils.utils import calculate_typing_time
 from rich.traceback import install
+import traceback
 
 install(extra_lines=3)
 
@@ -16,17 +17,16 @@ logger = get_logger("sender")
 
 async def send_message(message: MessageSending) -> None:
     """合并后的消息发送函数，包含WS发送和日志记录"""
-    message_preview = truncate_message(message.processed_plain_text)
+    message_preview = truncate_message(message.processed_plain_text, max_length=40)
 
     try:
         # 直接调用API发送消息
         await global_api.send_message(message)
-        logger.success(f"发送消息   '{message_preview}'   成功")
+        logger.success(f"已将消息  '{message_preview}'  发往平台'{message.message_info.platform}'")
 
     except Exception as e:
-        logger.error(f"发送消息   '{message_preview}'   失败: {str(e)}")
+        logger.error(f"发送消息   '{message_preview}'   发往平台'{message.message_info.platform}' 失败: {str(e)}")
-        if not message.message_info.platform:
+        traceback.print_exc()
-            raise ValueError(f"未找到平台：{message.message_info.platform} 的url配置，请检查配置文件") from e
         raise e  # 重新抛出其他异常
 
 
@@ -66,21 +66,24 @@ class HeartFCSender:
                     del self.thinking_messages[chat_id]
                     logger.debug(f"[{chat_id}] Removed empty thinking message container.")
 
-    def is_thinking(self, chat_id: str, message_id: str) -> bool:
-        """检查指定的消息 ID 是否当前正处于思考状态。"""
-        return chat_id in self.thinking_messages and message_id in self.thinking_messages[chat_id]
-
     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 type_and_send_message(self, message: MessageSending, typing=False):
+    async def send_message(self, message: MessageSending, has_thinking=False, typing=False):
         """
-        立即处理、发送并存储单个 MessageSending 消息。
+        处理、发送并存储一条消息。
-        调用此方法前，应先调用 register_thinking 注册对应的思考消息。
+
-        此方法执行后会调用 complete_thinking 清理思考状态。
+        参数：
+            message: MessageSending 对象，待发送的消息。
+            has_thinking: 是否管理思考状态，表情包无思考状态（如需调用 register_thinking/complete_thinking）。
+            typing: 是否模拟打字等待（根据 has_thinking 控制等待时长）。
+
+        用法：
+            - has_thinking=True 时，自动处理思考消息的时间和清理。
+            - typing=True 时，发送前会有打字等待。
         """
         if not message.chat_stream:
             logger.error("消息缺少 chat_stream，无法发送")
@@ -93,6 +96,7 @@ class HeartFCSender:
         message_id = message.message_info.message_id
 
         try:
+            if has_thinking:
                 _ = message.update_thinking_time()
 
                 # --- 条件应用 set_reply 逻辑 ---
@@ -102,18 +106,19 @@ class HeartFCSender:
                     and message.reply.processed_plain_text != "[System Trigger Context]"
                 ):
                     logger.debug(f"[{chat_id}] 应用 set_reply 逻辑: {message.processed_plain_text[:20]}...")
-                message.set_reply(message.reply)
-            # --- 结束条件 set_reply ---
 
             await message.process()
 
             if typing:
+                if has_thinking:
                     typing_time = calculate_typing_time(
                         input_string=message.processed_plain_text,
                         thinking_start_time=message.thinking_start_time,
                         is_emoji=message.is_emoji,
                     )
                     await asyncio.sleep(typing_time)
+                else:
+                    await asyncio.sleep(0.5)
 
             await send_message(message)
             await self.storage.store_message(message, message.chat_stream)
@@ -123,30 +128,3 @@ class HeartFCSender:
             raise e
         finally:
             await self.complete_thinking(chat_id, message_id)
-
-    async def send_and_store(self, message: MessageSending):
-        """处理、发送并存储单个消息，不涉及思考状态管理。"""
-        if not message.chat_stream:
-            logger.error(f"[{message.message_info.platform or 'UnknownPlatform'}] 消息缺少 chat_stream，无法发送")
-            return
-        if not message.message_info or not message.message_info.message_id:
-            logger.error(
-                f"[{message.chat_stream.stream_id if message.chat_stream else 'UnknownStream'}] 消息缺少 message_info 或 message_id，无法发送"
-            )
-            return
-
-        chat_id = message.chat_stream.stream_id
-        message_id = message.message_info.message_id  # 获取消息ID用于日志
-
-        try:
-            await message.process()
-
-            await asyncio.sleep(0.5)
-
-            await send_message(message)  # 使用现有的发送方法
-            await self.storage.store_message(message, message.chat_stream)  # 使用现有的存储方法
-
-        except Exception as e:
-            logger.error(f"[{chat_id}] 处理或存储消息 {message_id} 时出错: {e}")
-            # 重新抛出异常，让调用者知道失败了
-            raise e

src/chat/focus_chat/heartflow_processor.py

@@ -9,7 +9,8 @@ from maim_message import Seg
 from src.chat.heart_flow.heartflow import heartflow
 from src.common.logger_manager import get_logger
 from ..message_receive.chat_stream import chat_manager
-from ..message_receive.message_buffer import message_buffer
+
+# from ..message_receive.message_buffer import message_buffer
 from ..utils.timer_calculator import Timer
 from src.chat.person_info.relationship_manager import relationship_manager
 from typing import Optional, Tuple, Dict, Any
@@ -169,7 +170,7 @@ class HeartFCProcessor:
             messageinfo = message.message_info
 
             # 2. 消息缓冲与流程序化
-            await message_buffer.start_caching_messages(message)
+            # await message_buffer.start_caching_messages(message)
 
             chat = await chat_manager.get_or_create_stream(
                 platform=messageinfo.platform,
@@ -188,16 +189,16 @@ class HeartFCProcessor:
                 return
 
             # 4. 缓冲检查
-            buffer_result = await message_buffer.query_buffer_result(message)
+            # buffer_result = await message_buffer.query_buffer_result(message)
-            if not buffer_result:
+            # if not buffer_result:
-                msg_type = _get_message_type(message)
+            #     msg_type = _get_message_type(message)
-                type_messages = {
+            #     type_messages = {
-                    "text": f"触发缓冲，消息：{message.processed_plain_text}",
+            #         "text": f"触发缓冲，消息：{message.processed_plain_text}",
-                    "image": "触发缓冲，表情包/图片等待中",
+            #         "image": "触发缓冲，表情包/图片等待中",
-                    "seglist": "触发缓冲，消息列表等待中",
+            #         "seglist": "触发缓冲，消息列表等待中",
-                }
+            #     }
-                logger.debug(type_messages.get(msg_type, "触发未知类型缓冲"))
+            #     logger.debug(type_messages.get(msg_type, "触发未知类型缓冲"))
-                return
+            #     return
 
             # 5. 消息存储
             await self.storage.store_message(message, chat)
@@ -210,7 +211,7 @@ class HeartFCProcessor:
 
             # 7. 日志记录
             mes_name = chat.group_info.group_name if chat.group_info else "私聊"
-            current_time = time.strftime("%H点%M分%S秒", time.localtime(message.message_info.time))
+            current_time = time.strftime("%H:%M:%S", time.localtime(message.message_info.time))
             logger.info(
                 f"[{current_time}][{mes_name}]"
                 f"{userinfo.user_nickname}:"

src/chat/focus_chat/heartflow_prompt_builder.py

@@ -32,11 +32,11 @@ def init_prompt():
 以上是聊天内容，你需要了解聊天记录中的内容
 
 {chat_target}
-你的名字是{bot_name}，{prompt_personality}，在这聊天中，"{target_message}"引起了你的注意，你想表达：{in_mind_reply},原因是：{reason}。你现在要思考怎么回复
+你的名字是{bot_name}，{prompt_personality}，在这聊天中，"{target_message}"引起了你的注意，对这句话，你想表达：{in_mind_reply},原因是：{reason}。你现在要思考怎么回复
 你需要使用合适的语法和句法，参考聊天内容，组织一条日常且口语化的回复。
 请你根据情景使用以下句法：
 {grammar_habbits}
-回复尽量简短一些。可以参考贴吧，知乎和微博的回复风格，你可以完全重组回复，保留最基本的表达含义就好，但注意回复要简短。
+回复尽量简短一些。可以参考贴吧，知乎和微博的回复风格，你可以完全重组回复，保留最基本的表达含义就好，但注意回复要简短，但重组后保持语意通顺。
 回复不要浮夸，不要用夸张修辞，平淡一些。不要输出多余内容(包括前后缀，冒号和引号，括号，表情包，at或 @等 )，只输出一条回复就好。
 现在，你说：
 """,

src/chat/focus_chat/hfc_utils.py

@@ -1,5 +1,4 @@
 import time
-import traceback
 from typing import Optional
 from src.chat.message_receive.message import MessageRecv, BaseMessageInfo
 from src.chat.message_receive.chat_stream import ChatStream
@@ -10,7 +9,7 @@ import json
 logger = get_logger(__name__)
 
 
-async def _create_empty_anchor_message(
+async def create_empty_anchor_message(
     platform: str, group_info: dict, chat_stream: ChatStream
 ) -> Optional[MessageRecv]:
     """
@@ -18,7 +17,6 @@ async def _create_empty_anchor_message(
     如果重构失败或观察为空，则创建一个占位符。
     """
 
-    try:
     placeholder_id = f"mid_pf_{int(time.time() * 1000)}"
     placeholder_user = UserInfo(user_id="system_trigger", user_nickname="System Trigger", platform=platform)
     placeholder_msg_info = BaseMessageInfo(
@@ -36,13 +34,19 @@ async def _create_empty_anchor_message(
     }
     anchor_message = MessageRecv(placeholder_msg_dict)
     anchor_message.update_chat_stream(chat_stream)
-        logger.debug(f"创建占位符锚点消息: ID={anchor_message.message_info.message_id}")
+
     return anchor_message
 
-    except Exception as e:
+
-        logger.error(f"Error getting/creating anchor message: {e}")
+def parse_thinking_id_to_timestamp(thinking_id: str) -> float:
-        logger.error(traceback.format_exc())
+    """
-        return None
+    将形如 'tid<timestamp>' 的 thinking_id 解析回 float 时间戳
+    例如: 'tid1718251234.56' -> 1718251234.56
+    """
+    if not thinking_id.startswith("tid"):
+        raise ValueError("thinking_id 格式不正确")
+    ts_str = thinking_id[3:]
+    return float(ts_str)
 
 
 def get_keywords_from_json(json_str: str) -> list[str]:

src/chat/person_info/relationship_manager.py

@@ -94,13 +94,23 @@ class RelationshipManager:
             return False
 
     @staticmethod
-    async def first_knowing_some_one(platform, user_id, user_nickname, user_cardname, user_avatar):
+    async def first_knowing_some_one(
+        platform: str, user_id: str, user_nickname: str, user_cardname: str, user_avatar: str
+    ):
         """判断是否认识某人"""
         person_id = person_info_manager.get_person_id(platform, user_id)
-        await person_info_manager.update_one_field(person_id, "nickname", user_nickname)
+        data = {
-        # await person_info_manager.update_one_field(person_id, "user_cardname", user_cardname)
+            "platform": platform,
-        # await person_info_manager.update_one_field(person_id, "user_avatar", user_avatar)
+            "user_id": user_id,
-        await person_info_manager.qv_person_name(person_id, user_nickname, user_cardname, user_avatar)
+            "nickname": user_nickname,
+            "konw_time": int(time.time()),
+        }
+        await person_info_manager.update_one_field(
+            person_id=person_id, field_name="nickname", value=user_nickname, data=data
+        )
+        await person_info_manager.qv_person_name(
+            person_id=person_id, user_nickname=user_nickname, user_cardname=user_cardname, user_avatar=user_avatar
+        )
 
     async def calculate_update_relationship_value(self, user_info: UserInfo, platform: str, label: str, stance: str):
         """计算并变更关系值

src/config/config.py

@@ -622,12 +622,6 @@ class BotConfig:
             # config.ban_user_id = set(groups_config.get("ban_user_id", []))
             config.ban_user_id = set(str(user) for user in groups_config.get("ban_user_id", []))
 
-        def platforms(parent: dict):
-            platforms_config = parent["platforms"]
-            if platforms_config and isinstance(platforms_config, dict):
-                for k in platforms_config.keys():
-                    config.api_urls[k] = platforms_config[k]
-
         def experimental(parent: dict):
             experimental_config = parent["experimental"]
             config.enable_friend_chat = experimental_config.get("enable_friend_chat", config.enable_friend_chat)
@@ -662,7 +656,6 @@ class BotConfig:
             "remote": {"func": remote, "support": ">=0.0.10", "necessary": False},
             "keywords_reaction": {"func": keywords_reaction, "support": ">=0.0.2", "necessary": False},
             "chinese_typo": {"func": chinese_typo, "support": ">=0.0.3", "necessary": False},
-            "platforms": {"func": platforms, "support": ">=1.0.0"},
             "response_splitter": {"func": response_splitter, "support": ">=0.0.11", "necessary": False},
             "experimental": {"func": experimental, "support": ">=0.0.11", "necessary": False},
             "chat": {"func": chat, "support": ">=1.6.0", "necessary": False},

template/bot_config_template.toml

@@ -59,7 +59,7 @@ gender = "男" # 性别
 appearance = "用几句话描述外貌特征" # 外貌特征 该选项还在调试中，暂时未生效
 
 [platforms] # 必填项目，填写每个平台适配器提供的链接
-nonebot-qq="http://127.0.0.1:18002/api/message"
+qq="http://127.0.0.1:18002/api/message"
 
 [chat] #麦麦的聊天通用设置
 allow_focus_mode = false # 是否允许专注聊天状态