feat：改为单planner，并解析多个动作

src/chat/frequency_control/talk_frequency_control.py

@@ -1,6 +1,9 @@
 from typing import Optional
+from datetime import datetime, timedelta
+import statistics
 from src.config.config import global_config
 from src.chat.frequency_control.utils import parse_stream_config_to_chat_id
+from src.common.database.database_model import Messages
 
 
 def get_config_base_talk_frequency(chat_id: Optional[str] = None) -> float:
@@ -124,3 +127,146 @@ def get_global_frequency() -> Optional[float]:
             return get_time_based_frequency(config_item[1:])
 
     return None
+
+
+def get_weekly_hourly_message_stats(chat_id: str):
+    """
+    计算指定聊天最近一周每个小时的消息数量和用户数量
+    
+    Args:
+        chat_id: 聊天ID（对应 Messages 表的 chat_id 字段）
+    
+    Returns:
+        dict: 包含24个小时统计数据，格式为:
+        {
+            "0": {"message_count": [5, 8, 3, 12, 6, 9, 7], "message_std_dev": 2.1},
+            "1": {"message_count": [10, 15, 8, 20, 12, 18, 14], "message_std_dev": 3.2},
+            ...
+        }
+    """
+    # 计算一周前的时间戳
+    one_week_ago = datetime.now() - timedelta(days=7)
+    one_week_ago_timestamp = one_week_ago.timestamp()
+    
+    # 初始化数据结构：按小时存储每天的消息计数
+    hourly_data = {}
+    for hour in range(24):
+        hourly_data[f"hour_{hour}"] = {"daily_counts": []}
+    
+    try:
+        # 查询指定聊天最近一周的消息
+        messages = Messages.select().where(
+            (Messages.time >= one_week_ago_timestamp) &
+            (Messages.chat_id == chat_id)
+        )
+        
+        # 统计每个小时的数据
+        for message in messages:
+            # 将时间戳转换为datetime
+            msg_time = datetime.fromtimestamp(message.time)
+            hour = msg_time.hour
+            
+            # 记录每天的消息计数（按日期分组）
+            day_key = msg_time.strftime("%Y-%m-%d")
+            hour_key = f"{hour}"
+            
+            # 为该小时添加当天的消息计数
+            found = False
+            for day_count in hourly_data[hour_key]["daily_counts"]:
+                if day_count["date"] == day_key:
+                    day_count["count"] += 1
+                    found = True
+                    break
+            
+            if not found:
+                hourly_data[hour_key]["daily_counts"].append({"date": day_key, "count": 1})
+            
+                  
+    except Exception as e:
+        # 如果查询失败，返回空的统计结果
+        print(f"Error getting weekly hourly message stats for chat {chat_id}: {e}")
+        hourly_stats = {}
+        for hour in range(24):
+            hourly_stats[f"hour_{hour}"] = {
+                "message_count": [],
+                "message_std_dev": 0.0
+            }
+        return hourly_stats
+    
+    # 计算每个小时的统计结果
+    hourly_stats = {}
+    for hour in range(24):
+        hour_key = f"hour_{hour}"
+        daily_counts = [day["count"] for day in hourly_data[hour_key]["daily_counts"]]
+        
+        # 计算总消息数
+        total_messages = sum(daily_counts)
+        
+        # 计算标准差
+        message_std_dev = 0.0
+        if len(daily_counts) > 1:
+            message_std_dev = statistics.stdev(daily_counts)
+        elif len(daily_counts) == 1:
+            message_std_dev = 0.0
+        
+        # 按日期排序每日消息计数
+        daily_counts_sorted = sorted(hourly_data[hour_key]["daily_counts"], key=lambda x: x["date"])
+        
+        hourly_stats[hour_key] = {
+            "message_count": [day["count"] for day in daily_counts_sorted],
+            "message_std_dev": message_std_dev
+        }
+    
+    return hourly_stats
+
+def get_recent_15min_stats(chat_id: str):
+    """
+    获取最近15分钟指定聊天的消息数量和发言人数
+    
+    Args:
+        chat_id: 聊天ID（对应 Messages 表的 chat_id 字段）
+    
+    Returns:
+        dict: 包含消息数量和发言人数，格式为:
+        {
+            "message_count": 25,
+            "user_count": 8,
+            "time_range": "2025-01-01 14:30:00 - 2025-01-01 14:45:00"
+        }
+    """
+    # 计算15分钟前的时间戳
+    fifteen_min_ago = datetime.now() - timedelta(minutes=15)
+    fifteen_min_ago_timestamp = fifteen_min_ago.timestamp()
+    current_time = datetime.now()
+    
+    # 初始化统计结果
+    message_count = 0
+    user_set = set()
+    
+    try:
+        # 查询最近15分钟的消息
+        messages = Messages.select().where(
+            (Messages.time >= fifteen_min_ago_timestamp) &
+            (Messages.chat_id == chat_id)
+        )
+        
+        # 统计消息数量和用户
+        for message in messages:
+            message_count += 1
+            if message.user_id:
+                user_set.add(message.user_id)
+                
+    except Exception as e:
+        # 如果查询失败，返回空结果
+        print(f"Error getting recent 15min stats for chat {chat_id}: {e}")
+        return {
+            "message_count": 0,
+            "user_count": 0,
+            "time_range": f"{fifteen_min_ago.strftime('%Y-%m-%d %H:%M:%S')} - {current_time.strftime('%Y-%m-%d %H:%M:%S')}"
+        }
+    
+    return {
+        "message_count": message_count,
+        "user_count": len(user_set),
+        "time_range": f"{fifteen_min_ago.strftime('%Y-%m-%d %H:%M:%S')} - {current_time.strftime('%Y-%m-%d %H:%M:%S')}"
+    }

src/chat/heart_flow/heartFC_chat.py

@@ -18,7 +18,6 @@ from src.chat.planner_actions.action_modifier import ActionModifier
 from src.chat.planner_actions.action_manager import ActionManager
 from src.chat.heart_flow.hfc_utils import CycleDetail
 from src.chat.heart_flow.hfc_utils import send_typing, stop_typing
-from src.chat.frequency_control.frequency_control import frequency_control_manager
 from src.chat.express.expression_learner import expression_learner_manager
 from src.person_info.person_info import Person
 from src.plugin_system.base.component_types import ChatMode, EventType, ActionInfo
@@ -52,6 +51,16 @@ ERROR_LOOP_INFO = {
     },
 }
 
+# ?什么时候发言：
+# 1.聊天频率较低：与过去该时段发言频率进行比较
+# 2.感兴趣的话题：暂时使用Emb计算
+# 3.感兴趣的人：认识次数
+# 4.直接提及
+
+# 什么时候不发言：
+# 1.敏感话题：判断较难
+# 2.发言频率太高：近时判断，例如发言频率> 1/人数 *2
+# 3.明确被拒绝：planner判断
 
 install(extra_lines=3)
 
@@ -85,8 +94,6 @@ class HeartFChatting:
 
         self.expression_learner = expression_learner_manager.get_expression_learner(self.stream_id)
 
-        self.frequency_control = frequency_control_manager.get_or_create_frequency_control(self.stream_id)
-
         self.action_manager = ActionManager()
         self.action_planner = ActionPlanner(chat_id=self.stream_id, action_manager=self.action_manager)
         self.action_modifier = ActionModifier(action_manager=self.action_manager, chat_id=self.stream_id)
@@ -101,6 +108,10 @@ class HeartFChatting:
         self._current_cycle_detail: CycleDetail = None  # type: ignore
 
         self.last_read_time = time.time() - 10
+        
+        
+        
+        self.no_reply_until_call = False
 
     async def start(self):
         """检查是否需要启动主循环，如果未激活则启动。"""
@@ -156,38 +167,12 @@ class HeartFChatting:
             formatted_time = f"{elapsed * 1000:.2f}毫秒" if elapsed < 1 else f"{elapsed:.2f}秒"
             timer_strings.append(f"{name}: {formatted_time}")
 
-        # 获取动作类型，兼容新旧格式
-        # 移除无用代码
-        # action_type = "未知动作"
-        # if hasattr(self, "_current_cycle_detail") and self._current_cycle_detail:
-        #     loop_plan_info = self._current_cycle_detail.loop_plan_info
-        #     if isinstance(loop_plan_info, dict):
-        #         action_result = loop_plan_info.get("action_result", {})
-        #         if isinstance(action_result, dict):
-        #             # 旧格式：action_result是字典
-        #             action_type = action_result.get("action_type", "未知动作")
-        #         elif isinstance(action_result, list) and action_result:
-        #             # 新格式：action_result是actions列表
-        #             # TODO: 把这里写明白
-        #             action_type = action_result[0].action_type or "未知动作"
-        #     elif isinstance(loop_plan_info, list) and loop_plan_info:
-        #         # 直接是actions列表的情况
-        #         action_type = loop_plan_info[0].get("action_type", "未知动作")
-
         logger.info(
             f"{self.log_prefix} 第{self._current_cycle_detail.cycle_id}次思考,"
             f"耗时: {self._current_cycle_detail.end_time - self._current_cycle_detail.start_time:.1f}秒"  # type: ignore
             + (f"\n详情: {'; '.join(timer_strings)}" if timer_strings else "")
         )
 
-    async def calculate_interest_value(self, recent_messages_list: List["DatabaseMessages"]) -> float:
-        total_interest = 0.0
-        for msg in recent_messages_list:
-            interest_value = msg.interest_value
-            if interest_value is not None and msg.processed_plain_text:
-                total_interest += float(interest_value)
-        return total_interest / len(recent_messages_list)
-
     async def _loopbody(self):
         recent_messages_list = message_api.get_messages_by_time_in_chat(
             chat_id=self.stream_id,
@@ -200,9 +185,22 @@ class HeartFChatting:
         )
 
         if recent_messages_list:
+            
+            # !处理no_reply_until_call逻辑
+            if self.no_reply_until_call:
+                for message in recent_messages_list:
+                    if message.is_mentioned or message.is_at:
+                        self.no_reply_until_call = False
+                        break
+                # 没有提到，继续保持沉默
+                if self.no_reply_until_call:
+                    logger.info(f"{self.log_prefix} 没有提到，继续保持沉默")
+                    await asyncio.sleep(1)
+                    return True
+                    
+            
             self.last_read_time = time.time()
             await self._observe(
-                interest_value=await self.calculate_interest_value(recent_messages_list),
                 recent_messages_list=recent_messages_list,
             )
         else:
@@ -262,190 +260,140 @@ class HeartFChatting:
         return loop_info, reply_text, cycle_timers
 
     async def _observe(
-        self, interest_value: float = 0.0, recent_messages_list: Optional[List["DatabaseMessages"]] = None
+        self, # interest_value: float = 0.0, 
+        recent_messages_list: Optional[List["DatabaseMessages"]] = None
     ) -> bool:
         if recent_messages_list is None:
             recent_messages_list = []
         reply_text = ""  # 初始化reply_text变量，避免UnboundLocalError
 
-        # 使用sigmoid函数将interest_value转换为概率
-        # 当interest_value为0时，概率接近0（使用Focus模式）
-        # 当interest_value很高时，概率接近1（使用Normal模式）
-        def calculate_normal_mode_probability(interest_val: float) -> float:
-            # 使用sigmoid函数，调整参数使概率分布更合理
-            # 当interest_value = 0时，概率约为0.1
-            # 当interest_value = 1时，概率约为0.5
-            # 当interest_value = 2时，概率约为0.8
-            # 当interest_value = 3时，概率约为0.95
-            k = 2.0  # 控制曲线陡峭程度
-            x0 = 1.0  # 控制曲线中心点
-            return 1.0 / (1.0 + math.exp(-k * (interest_val - x0)))
-
-        normal_mode_probability = (
-            calculate_normal_mode_probability(interest_value) * 2 * self.frequency_control.get_final_talk_frequency()
-        )
-
-        # 对呼唤名字进行增幅
-        for msg in recent_messages_list:
-            if msg.reply_probability_boost is not None and msg.reply_probability_boost > 0.0:
-                normal_mode_probability += msg.reply_probability_boost
-            if global_config.chat.mentioned_bot_reply and msg.is_mentioned:
-                normal_mode_probability += global_config.chat.mentioned_bot_reply
-            if global_config.chat.at_bot_inevitable_reply and msg.is_at:
-                normal_mode_probability += global_config.chat.at_bot_inevitable_reply
-
-        # 根据概率决定使用直接回复
-        interest_triggered = False
-        focus_triggered = False
-
-        if random.random() < normal_mode_probability:
-            interest_triggered = True
-
-            logger.info(f"{self.log_prefix} 有新消息，在{normal_mode_probability * 100:.0f}%概率下选择回复")
-
         if s4u_config.enable_s4u:
             await send_typing()
 
         async with global_prompt_manager.async_message_scope(self.chat_stream.context.get_template_name()):
             await self.expression_learner.trigger_learning_for_chat()
+            
+            cycle_timers, thinking_id = self.start_cycle()
+            logger.info(f"{self.log_prefix} 开始第{self._cycle_counter}次思考")
 
+            # 第一步：动作检查
             available_actions: Dict[str, ActionInfo] = {}
+            try:
+                await self.action_modifier.modify_actions()
+                available_actions = self.action_manager.get_using_actions()
+            except Exception as e:
+                logger.error(f"{self.log_prefix} 动作修改失败: {e}")
 
-            # 如果兴趣度不足以激活
-            if not interest_triggered:
-                # 看看专注值够不够
-                if random.random() < self.frequency_control.get_final_focus_value():
-                    # 专注值足够，仍然进入正式思考
-                    focus_triggered = True  # 都没触发，路边
+            # 执行planner
+            is_group_chat, chat_target_info, _ = self.action_planner.get_necessary_info()
 
-            # 任意一种触发都行
-            if interest_triggered or focus_triggered:
-                # 进入正式思考模式
-                cycle_timers, thinking_id = self.start_cycle()
-                logger.info(f"{self.log_prefix} 开始第{self._cycle_counter}次思考")
+            message_list_before_now = get_raw_msg_before_timestamp_with_chat(
+                chat_id=self.stream_id,
+                timestamp=time.time(),
+                limit=int(global_config.chat.max_context_size * 0.6),
+            )
+            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,
+            )
 
-                # 第一步：动作检查
-                try:
-                    await self.action_modifier.modify_actions()
-                    available_actions = self.action_manager.get_using_actions()
-                except Exception as e:
-                    logger.error(f"{self.log_prefix} 动作修改失败: {e}")
-
-                # 执行planner
-                is_group_chat, chat_target_info, _ = self.action_planner.get_necessary_info()
-
-                message_list_before_now = get_raw_msg_before_timestamp_with_chat(
-                    chat_id=self.stream_id,
-                    timestamp=time.time(),
-                    limit=int(global_config.chat.max_context_size * 0.6),
-                )
-                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_info = await self.action_planner.build_planner_prompt(
+                is_group_chat=is_group_chat,
+                chat_target_info=chat_target_info,
+                current_available_actions=available_actions,
+                chat_content_block=chat_content_block,
+                message_id_list=message_id_list,
+                interest=global_config.personality.interest,
+            )
+            continue_flag, modified_message = await events_manager.handle_mai_events(
+                EventType.ON_PLAN, None, prompt_info[0], None, self.chat_stream.stream_id
+            )
+            if not continue_flag:
+                return False
+            if modified_message and modified_message._modify_flags.modify_llm_prompt:
+                prompt_info = (modified_message.llm_prompt, prompt_info[1])
+                
+                
+            with Timer("规划器", cycle_timers):
+                action_to_use_info, _ = await self.action_planner.plan(
+                    loop_start_time=self.last_read_time,
+                    available_actions=available_actions,
                 )
 
-                prompt_info = await self.action_planner.build_planner_prompt(
-                    is_group_chat=is_group_chat,
-                    chat_target_info=chat_target_info,
-                    # current_available_actions=planner_info[2],
-                    chat_content_block=chat_content_block,
-                    # actions_before_now_block=actions_before_now_block,
-                    message_id_list=message_id_list,
+            # 3. 并行执行所有动作
+            action_tasks = [
+                asyncio.create_task(
+                    self._execute_action(action, action_to_use_info, thinking_id, available_actions, cycle_timers)
                 )
-                continue_flag, modified_message = await events_manager.handle_mai_events(
-                    EventType.ON_PLAN, None, prompt_info[0], None, self.chat_stream.stream_id
-                )
-                if not continue_flag:
-                    return False
-                if modified_message and modified_message._modify_flags.modify_llm_prompt:
-                    prompt_info = (modified_message.llm_prompt, prompt_info[1])
-                with Timer("规划器", cycle_timers):
-                    # 根据不同触发，进入不同plan
-                    if focus_triggered:
-                        mode = ChatMode.FOCUS
+                for action in action_to_use_info
+            ]
+
+            # 并行执行所有任务
+            results = await asyncio.gather(*action_tasks, return_exceptions=True)
+
+            # 处理执行结果
+            reply_loop_info = None
+            reply_text_from_reply = ""
+            action_success = False
+            action_reply_text = ""
+            action_command = ""
+
+            for i, result in enumerate(results):
+                if isinstance(result, BaseException):
+                    logger.error(f"{self.log_prefix} 动作执行异常: {result}")
+                    continue
+
+                _cur_action = action_to_use_info[i]
+                if result["action_type"] != "reply":
+                    action_success = result["success"]
+                    action_reply_text = result["reply_text"]
+                    action_command = result.get("command", "")
+                elif result["action_type"] == "reply":
+                    if result["success"]:
+                        reply_loop_info = result["loop_info"]
+                        reply_text_from_reply = result["reply_text"]
                     else:
-                        mode = ChatMode.NORMAL
+                        logger.warning(f"{self.log_prefix} 回复动作执行失败")
 
-                    action_to_use_info, _ = await self.action_planner.plan(
-                        mode=mode,
-                        loop_start_time=self.last_read_time,
-                        available_actions=available_actions,
-                    )
-
-                # 3. 并行执行所有动作
-                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
-                ]
-
-                # 并行执行所有任务
-                results = await asyncio.gather(*action_tasks, return_exceptions=True)
-
-                # 处理执行结果
-                reply_loop_info = None
-                reply_text_from_reply = ""
-                action_success = False
-                action_reply_text = ""
-                action_command = ""
-
-                for i, result in enumerate(results):
-                    if isinstance(result, BaseException):
-                        logger.error(f"{self.log_prefix} 动作执行异常: {result}")
-                        continue
-
-                    _cur_action = action_to_use_info[i]
-                    if result["action_type"] != "reply":
-                        action_success = result["success"]
-                        action_reply_text = result["reply_text"]
-                        action_command = result.get("command", "")
-                    elif result["action_type"] == "reply":
-                        if result["success"]:
-                            reply_loop_info = result["loop_info"]
-                            reply_text_from_reply = result["reply_text"]
-                        else:
-                            logger.warning(f"{self.log_prefix} 回复动作执行失败")
-
-                # 构建最终的循环信息
-                if reply_loop_info:
-                    # 如果有回复信息，使用回复的loop_info作为基础
-                    loop_info = reply_loop_info
-                    # 更新动作执行信息
-                    loop_info["loop_action_info"].update(
-                        {
-                            "action_taken": action_success,
-                            "command": action_command,
-                            "taken_time": time.time(),
-                        }
-                    )
-                    reply_text = reply_text_from_reply
-                else:
-                    # 没有回复信息，构建纯动作的loop_info
-                    loop_info = {
-                        "loop_plan_info": {
-                            "action_result": action_to_use_info,
-                        },
-                        "loop_action_info": {
-                            "action_taken": action_success,
-                            "reply_text": action_reply_text,
-                            "command": action_command,
-                            "taken_time": time.time(),
-                        },
+            # 构建最终的循环信息
+            if reply_loop_info:
+                # 如果有回复信息，使用回复的loop_info作为基础
+                loop_info = reply_loop_info
+                # 更新动作执行信息
+                loop_info["loop_action_info"].update(
+                    {
+                        "action_taken": action_success,
+                        "command": action_command,
+                        "taken_time": time.time(),
                     }
-                    reply_text = action_reply_text
+                )
+                reply_text = reply_text_from_reply
+            else:
+                # 没有回复信息，构建纯动作的loop_info
+                loop_info = {
+                    "loop_plan_info": {
+                        "action_result": action_to_use_info,
+                    },
+                    "loop_action_info": {
+                        "action_taken": action_success,
+                        "reply_text": action_reply_text,
+                        "command": action_command,
+                        "taken_time": time.time(),
+                    },
+                }
+                reply_text = action_reply_text
 
-                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)
 
-                """S4U内容，暂时保留"""
-                if s4u_config.enable_s4u:
-                    await stop_typing()
-                    await mai_thinking_manager.get_mai_think(self.stream_id).do_think_after_response(reply_text)
-                """S4U内容，暂时保留"""
+            """S4U内容，暂时保留"""
+            if s4u_config.enable_s4u:
+                await stop_typing()
+                await mai_thinking_manager.get_mai_think(self.stream_id).do_think_after_response(reply_text)
+            """S4U内容，暂时保留"""
 
             return True
 
@@ -579,7 +527,7 @@ class HeartFChatting:
     ):
         """执行单个动作的通用函数"""
         try:
-            if action_planner_info.action_type == "no_action":
+            if action_planner_info.action_type == "no_reply":
                 # 直接处理no_action逻辑，不再通过动作系统
                 reason = action_planner_info.reasoning or "选择不回复"
                 logger.info(f"{self.log_prefix} 选择不回复，原因: {reason}")
@@ -594,26 +542,19 @@ class HeartFChatting:
                     action_data={"reason": reason},
                     action_name="no_action",
                 )
-
                 return {"action_type": "no_action", "success": True, "reply_text": "", "command": ""}
-            elif action_planner_info.action_type != "reply":
-                # 执行普通动作
-                with Timer("动作执行", cycle_timers):
-                    success, reply_text, command = await self._handle_action(
-                        action_planner_info.action_type,
-                        action_planner_info.reasoning or "",
-                        action_planner_info.action_data or {},
-                        cycle_timers,
-                        thinking_id,
-                        action_planner_info.action_message,
-                    )
-                return {
-                    "action_type": action_planner_info.action_type,
-                    "success": success,
-                    "reply_text": reply_text,
-                    "command": command,
-                }
-            else:
+            
+            elif action_planner_info.action_type == "wait_time":
+                logger.info(f"{self.log_prefix} 等待{action_planner_info.action_data['time']}秒后回复")
+                await asyncio.sleep(action_planner_info.action_data["time"])
+                return {"action_type": "wait_time", "success": True, "reply_text": "", "command": ""}
+            
+            elif action_planner_info.action_type == "no_reply_until_call":
+                logger.info(f"{self.log_prefix} 保持沉默，直到有人直接叫的名字")
+                self.no_reply_until_call = True
+                return {"action_type": "no_reply_until_call", "success": True, "reply_text": "", "command": ""}
+            
+            elif action_planner_info.action_type == "reply":
                 try:
                     success, llm_response = await generator_api.generate_reply(
                         chat_stream=self.chat_stream,
@@ -652,6 +593,26 @@ class HeartFChatting:
                     "reply_text": reply_text,
                     "loop_info": loop_info,
                 }
+                
+            # 其他动作
+            else:
+                # 执行普通动作
+                with Timer("动作执行", cycle_timers):
+                    success, reply_text, command = await self._handle_action(
+                        action_planner_info.action_type,
+                        action_planner_info.reasoning or "",
+                        action_planner_info.action_data or {},
+                        cycle_timers,
+                        thinking_id,
+                        action_planner_info.action_message,
+                    )
+                return {
+                    "action_type": action_planner_info.action_type,
+                    "success": success,
+                    "reply_text": reply_text,
+                    "command": command,
+                }
+                
         except Exception as e:
             logger.error(f"{self.log_prefix} 执行动作时出错: {e}")
             logger.error(f"{self.log_prefix} 错误信息: {traceback.format_exc()}")

src/config/config.py

@@ -56,7 +56,7 @@ TEMPLATE_DIR = os.path.join(PROJECT_ROOT, "template")
 
 # 考虑到，实际上配置文件中的mai_version是不会自动更新的,所以采用硬编码
 # 对该字段的更新，请严格参照语义化版本规范：https://semver.org/lang/zh-CN/
-MMC_VERSION = "0.10.3-snapshot.1"
+MMC_VERSION = "0.10.3-snapshot.2"
 
 
 def get_key_comment(toml_table, key):

src/llm_models/model_client/openai_client.py

@@ -277,10 +277,12 @@ async def _default_stream_response_handler(
         # 空 choices / usage-only 帧的防御
         if not hasattr(event, "choices") or not event.choices:
             if hasattr(event, "usage") and event.usage:
+                # 安全地获取usage属性，处理不同API版本的差异
+                usage_obj = event.usage
                 _usage_record = (
-                    event.usage.prompt_tokens or 0,
-                    event.usage.completion_tokens or 0,
-                    event.usage.total_tokens or 0,
+                    getattr(usage_obj, 'prompt_tokens', 0) or 0,
+                    getattr(usage_obj, 'completion_tokens', 0) or 0,
+                    getattr(usage_obj, 'total_tokens', 0) or 0,
                 )
             continue  # 跳过本帧，避免访问 choices[0]
         delta = event.choices[0].delta  # 获取当前块的delta内容
@@ -300,10 +302,12 @@ async def _default_stream_response_handler(
 
         if event.usage:
             # 如果有使用情况，则将其存储在APIResponse对象中
+            # 安全地获取usage属性，处理不同API版本的差异
+            usage_obj = event.usage
             _usage_record = (
-                event.usage.prompt_tokens or 0,
-                event.usage.completion_tokens or 0,
-                event.usage.total_tokens or 0,
+                getattr(usage_obj, 'prompt_tokens', 0) or 0,
+                getattr(usage_obj, 'completion_tokens', 0) or 0,
+                getattr(usage_obj, 'total_tokens', 0) or 0,
             )
 
     try:
@@ -370,10 +374,12 @@ def _default_normal_response_parser(
 
     # 提取Usage信息
     if resp.usage:
+        # 安全地获取usage属性，处理不同API版本的差异
+        usage_obj = resp.usage
         _usage_record = (
-            resp.usage.prompt_tokens or 0,
-            resp.usage.completion_tokens or 0,
-            resp.usage.total_tokens or 0,
+            getattr(usage_obj, 'prompt_tokens', 0) or 0,
+            getattr(usage_obj, 'completion_tokens', 0) or 0,
+            getattr(usage_obj, 'total_tokens', 0) or 0,
         )
     else:
         _usage_record = None

src/llm_models/utils_model.py

@@ -5,6 +5,7 @@ import time
 from enum import Enum
 from rich.traceback import install
 from typing import Tuple, List, Dict, Optional, Callable, Any
+import traceback
 
 from src.common.logger import get_logger
 from src.config.config import model_config
@@ -391,6 +392,7 @@ class LLMRequest:
             logger.debug(f"附加内容: {str(e.ext_info)}")
             return -1, None  # 不再重试请求该模型
         else:
+            print(traceback.format_exc())
             logger.error(f"任务-'{task_name}' 模型-'{model_name}': 未知异常，错误信息-{str(e)}")
             return -1, None  # 不再重试请求该模型