mirror of https://github.com/Mai-with-u/MaiBot.git
增加调试信息
Bakadax
parent
b468c2b2ec
commit
7a226ccb18
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@ -15,7 +15,7 @@ if TYPE_CHECKING:
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logger = get_logger("pfc_loop")
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# 时区配置 (从 conversation.py 移过来，或者考虑放到更全局的配置模块)
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# 时区配置
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configured_tz = getattr(global_config, "TIME_ZONE", "Asia/Shanghai")
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TIME_ZONE = tz.gettz(configured_tz)
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if TIME_ZONE is None:
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@ -26,7 +26,6 @@ if TIME_ZONE is None:
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async def run_conversation_loop(conversation_instance: "Conversation"):
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"""
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核心的规划与行动循环 (PFC Loop)。
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之前是 Conversation 类中的 _plan_and_action_loop 方法。
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"""
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logger.debug(f"[私聊][{conversation_instance.private_name}] 进入 run_conversation_loop 循环。")
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@ -34,16 +33,22 @@ async def run_conversation_loop(conversation_instance: "Conversation"):
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logger.error(f"[私聊][{conversation_instance.private_name}] 尝试在未初始化状态下运行规划循环，退出。")
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return
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force_reflect_and_act = False # 用于强制使用反思 prompt 的标志
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# 注意：force_reflect_and_act 是在主循环的每次迭代开始前确定的，
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# 它在 action_planner.plan 使用后会被重置为 False。
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# 如果在一次迭代中被设为 True (例如因为LLM任务中断)，它会影响下一次迭代的 plan 调用。
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_force_reflect_and_act_next_iter = False
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while conversation_instance.should_continue:
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loop_iter_start_time = time.time()
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logger.debug(f"[私聊][{conversation_instance.private_name}] 开始新一轮循环迭代 ({loop_iter_start_time:.2f})")
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current_force_reflect_and_act = _force_reflect_and_act_next_iter
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_force_reflect_and_act_next_iter = False # 默认下一轮迭代不强制反思
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logger.debug(f"[私聊][{conversation_instance.private_name}] 开始新一轮循环迭代 ({loop_iter_start_time:.2f}), force_reflect_next_iter: {current_force_reflect_and_act}")
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# 更新当前时间
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try:
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global TIME_ZONE # 引用全局 TIME_ZONE
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if TIME_ZONE is None: # 如果还未加载成功
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global TIME_ZONE
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if TIME_ZONE is None:
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configured_tz_loop = getattr(global_config, "TIME_ZONE", "Asia/Shanghai")
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TIME_ZONE = tz.gettz(configured_tz_loop)
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if TIME_ZONE is None:
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@ -54,7 +59,6 @@ async def run_conversation_loop(conversation_instance: "Conversation"):
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if conversation_instance.observation_info:
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time_str = current_time_dt.strftime("%Y-%m-%d %H:%M:%S %Z%z")
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conversation_instance.observation_info.current_time_str = time_str
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logger.debug(f"[私聊][{conversation_instance.private_name}] 更新 ObservationInfo 当前时间: {time_str}")
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else:
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logger.warning(
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f"[私聊][{conversation_instance.private_name}] ObservationInfo 未初始化，无法更新当前时间。"
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@ -89,7 +93,6 @@ async def run_conversation_loop(conversation_instance: "Conversation"):
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# 核心规划与行动逻辑
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try:
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# 更新关系和情绪文本 (在每次循环开始时进行)
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if conversation_instance.conversation_info and conversation_instance._initialized:
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if (
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conversation_instance.conversation_info.person_id
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@ -119,7 +122,6 @@ async def run_conversation_loop(conversation_instance: "Conversation"):
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conversation_instance.mood_mng.get_prompt()
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)
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# 检查核心组件
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if not all(
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[
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conversation_instance.action_planner,
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@ -133,8 +135,7 @@ async def run_conversation_loop(conversation_instance: "Conversation"):
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await asyncio.sleep(5)
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continue
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# 规划
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planning_start_time = time.time() # 这是 ActionPlanner.plan 开始的时间
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planning_start_time = time.time()
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logger.debug(
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f"[私聊][{conversation_instance.private_name}] --- (Loop) 开始规划 ({planning_start_time:.2f}) ---"
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)
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@ -147,15 +148,14 @@ async def run_conversation_loop(conversation_instance: "Conversation"):
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conversation_instance.conversation_info.last_successful_reply_action
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if conversation_instance.conversation_info
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else None,
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use_reflect_prompt=force_reflect_and_act,
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use_reflect_prompt=current_force_reflect_and_act, # 使用当前迭代的强制反思标志
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)
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force_reflect_and_act = False # 重置反思标志
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# current_force_reflect_and_act 已经被用于本次plan, _force_reflect_and_act_next_iter 默认为 False
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logger.debug(
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f"[私聊][{conversation_instance.private_name}] (Loop) ActionPlanner.plan 完成，初步规划动作: {action}"
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)
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# 检查在 ActionPlanner.plan 期间是否有中断 (这部分逻辑保持不变)
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# 注意：这里的 planning_start_time 是 action_planner.plan 开始的时间
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current_unprocessed_messages_after_plan = getattr(conversation_instance.observation_info, "unprocessed_messages", [])
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new_messages_during_action_planning: List[Dict[str, Any]] = []
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other_new_messages_during_action_planning: List[Dict[str, Any]] = []
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@ -164,7 +164,7 @@ async def run_conversation_loop(conversation_instance: "Conversation"):
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msg_time_ap = msg_ap.get("time")
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sender_id_info_ap = msg_ap.get("user_info", {})
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sender_id_ap = str(sender_id_info_ap.get("user_id")) if sender_id_info_ap else None
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if msg_time_ap and msg_time_ap >= planning_start_time: # 使用 action_planner.plan 的开始时间
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if msg_time_ap and msg_time_ap >= planning_start_time:
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new_messages_during_action_planning.append(msg_ap)
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if sender_id_ap != conversation_instance.bot_qq_str:
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other_new_messages_during_action_planning.append(msg_ap)
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@ -172,12 +172,8 @@ async def run_conversation_loop(conversation_instance: "Conversation"):
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new_msg_count_action_planning = len(new_messages_during_action_planning)
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other_new_msg_count_action_planning = len(other_new_messages_during_action_planning)
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# 更新因 ActionPlanner.plan 期间新消息而产生的计数和状态 (这部分逻辑也基本保持)
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if conversation_instance.conversation_info and other_new_msg_count_action_planning > 0:
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# (如果需要，这里可以更新实例消息计数、关系、情绪等，但通常这些在消息实际处理后更新更合适)
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# conversation_instance.conversation_info.current_instance_message_count += other_new_msg_count_action_planning
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pass
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pass # 计数更新等通常在消息实际处理后
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should_interrupt_action_planning: bool = False
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interrupt_reason_action_planning: str = ""
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@ -192,7 +188,6 @@ async def run_conversation_loop(conversation_instance: "Conversation"):
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logger.info(
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f"[私聊][{conversation_instance.private_name}] (Loop) 中断 '{action}' (在ActionPlanner.plan后)，原因: {interrupt_reason_action_planning}。重新规划..."
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)
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# 记录中断的动作
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cancel_record_ap = {
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"action": action,
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"plan_reason": reason,
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@ -206,21 +201,16 @@ async def run_conversation_loop(conversation_instance: "Conversation"):
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conversation_instance.conversation_info.done_action.append(cancel_record_ap)
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conversation_instance.conversation_info.last_successful_reply_action = None
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conversation_instance.state = ConversationState.ANALYZING
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await asyncio.sleep(0.1) # 短暂休眠再开始下一轮
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continue # 跳过本轮的 actions.handle_action，直接进入下一轮循环重新规划
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await asyncio.sleep(0.1)
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continue
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# 如果 ActionPlanner.plan 后没有中断，则准备执行动作
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# 【核心修改点】对于需要LLM生成回复的动作，进行特殊处理
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if action in ["direct_reply", "send_new_message"]:
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logger.debug(
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f"[私聊][{conversation_instance.private_name}] (Loop) 动作 '{action}' 需要LLM生成，进入监控执行模式..."
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)
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llm_call_start_time = time.time() # LLM实际调用开始的时间
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llm_call_start_time = time.time()
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# 将 conversation_info 中用于 action_planner 中断的计数值传递或更新，以供 handle_action 使用
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# actions.handle_action 内部可能也需要知道这些信息
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if conversation_instance.conversation_info:
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# 注意：这个字段可能在 actions.handle_action 中被使用和重置
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conversation_instance.conversation_info.other_new_messages_during_planning_count = other_new_msg_count_action_planning
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llm_action_task = asyncio.create_task(
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@ -234,95 +224,72 @@ async def run_conversation_loop(conversation_instance: "Conversation"):
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)
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interrupted_during_llm = False
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llm_task_cancelled_by_us = False
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while not llm_action_task.done():
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try:
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await asyncio.wait_for(llm_action_task, timeout=5) # 每1.5秒检查一次
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await asyncio.wait_for(llm_action_task, timeout=1.5)
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except asyncio.TimeoutError:
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# LLM任务仍在运行，检查新消息
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current_time_for_check = time.time()
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logger.debug(f"[私聊][{conversation_instance.private_name}] (Loop) LLM Monitor Timeout. llm_call_start_time: {llm_call_start_time:.2f}, current_check_time: {current_time_for_check:.2f}")
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current_unprocessed_messages_during_llm = getattr(conversation_instance.observation_info, "unprocessed_messages", [])
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other_new_messages_this_check: List[Dict[str, Any]] = []
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# 打印调试信息，与用户提供的一致
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# print(111111111111111111111111) # 和用户调试信息一致
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logger.debug(f"[私聊][{conversation_instance.private_name}] (Loop) Checking unprocessed_messages (count: {len(current_unprocessed_messages_during_llm)}):")
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for msg_llm in current_unprocessed_messages_during_llm:
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# print(msg_llm) # 和用户调试信息一致
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msg_time_llm = msg_llm.get("time")
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sender_id_info_llm = msg_llm.get("user_info", {})
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sender_id_llm = str(sender_id_info_llm.get("user_id")) if sender_id_info_llm else None
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is_new_enough = msg_time_llm and msg_time_llm >= llm_call_start_time
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is_other_sender = sender_id_llm != conversation_instance.bot_qq_str
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if msg_time_llm and msg_time_llm >= llm_call_start_time: # 注意这里用 llm_call_start_time
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if sender_id_llm != conversation_instance.bot_qq_str:
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other_new_messages_this_check.append(msg_llm)
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# print("添加成功！\n") # 和用户调试信息一致
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logger.debug(f" - Msg ID: {msg_llm.get('message_id')}, Time: {msg_time_llm:.2f if msg_time_llm else 'N/A'}, Sender: {sender_id_llm}. New enough? {is_new_enough}. Other sender? {is_other_sender}.")
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if is_new_enough and is_other_sender:
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other_new_messages_this_check.append(msg_llm)
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# print(other_new_messages_this_check) # 和用户调试信息一致
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# print(len(other_new_messages_this_check)) # 和用户调试信息一致
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logger.debug(f"[私聊][{conversation_instance.private_name}] (Loop) Found {len(other_new_messages_this_check)} 'other_new_messages_this_check'.")
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if len(other_new_messages_this_check) > 2: # 用户的重新规划条件
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if len(other_new_messages_this_check) > 2:
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logger.info(
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f"[私聊][{conversation_instance.private_name}] (Loop) LLM动作 '{action}' 执行期间收到 {len(other_new_messages_this_check)} 条来自他人的新消息，中断并重新规划。"
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f"[私聊][{conversation_instance.private_name}] (Loop) LLM动作 '{action}' 执行期间收到 {len(other_new_messages_this_check)} 条来自他人的新消息，发起中断。"
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)
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llm_action_task.cancel()
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interrupted_during_llm = True
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# 记录中断的动作到 history
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cancel_record_llm = {
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"action": action,
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"plan_reason": reason, # 使用规划时得到的 reason
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"status": "cancelled_due_to_new_messages_during_llm",
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"time": datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
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"final_reason": f"LLM处理期间收到{len(other_new_messages_this_check)}条新用户消息",
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}
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if conversation_instance.conversation_info:
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if not hasattr(conversation_instance.conversation_info, "done_action") or conversation_instance.conversation_info.done_action is None:
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conversation_instance.conversation_info.done_action = []
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conversation_instance.conversation_info.done_action.append(cancel_record_llm)
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conversation_instance.conversation_info.last_successful_reply_action = None # 因为没有成功回复
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# 可以在这里也更新 current_instance_message_count 和相关情绪/关系，如果这些新消息确实是用户的
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conversation_instance.conversation_info.current_instance_message_count += len(other_new_messages_this_check)
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# (此处可以添加调用关系/情绪更新的逻辑，如果需要的话)
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if not llm_action_task.done():
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llm_action_task.cancel()
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llm_task_cancelled_by_us = True
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break # 从监控循环中断
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# except asyncio.CancelledError: # 这个由外部的 await llm_action_task 捕获
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# pass
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# 监控循环结束后，等待任务的最终结果
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try:
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await llm_action_task
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logger.debug(f"[私聊][{conversation_instance.private_name}] (Loop) LLM动作 '{action}' 任务最终完成 (未被取消或未发生错误)。")
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except asyncio.CancelledError:
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logger.info(f"[私聊][{conversation_instance.private_name}] (Loop) LLM动作 '{action}' 任务最终确认被取消。")
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interrupted_during_llm = True
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# actions.handle_action 内部的finally块会更新done_action状态为cancelled
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except Exception as e_llm_final:
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logger.error(f"[私聊][{conversation_instance.private_name}] (Loop) LLM动作 '{action}' 任务执行时发生最终错误: {e_llm_final}")
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logger.error(traceback.format_exc())
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interrupted_during_llm = True
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conversation_instance.state = ConversationState.ERROR
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# actions.handle_action 内部的finally块会更新done_action状态为error
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conversation_instance.state = ConversationState.ANALYZING # 准备重新规划
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force_reflect_and_act = True # 下一轮强制使用初始/反思型规划
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break # 跳出监控循环
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except asyncio.CancelledError:
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logger.info(f"[私聊][{conversation_instance.private_name}] (Loop) LLM动作 '{action}' 任务被取消。")
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interrupted_during_llm = True # 标记为中断
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# conversation_instance.state 和 force_reflect_and_act 已在上面处理 cancellation 的地方设置
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break # 跳出监控循环
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except Exception as e_llm_task:
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logger.error(f"[私聊][{conversation_instance.private_name}] (Loop) LLM动作 '{action}' 任务执行时出错: {e_llm_task}")
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logger.error(traceback.format_exc())
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interrupted_during_llm = True # 标记为中断，按错误处理
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conversation_instance.state = ConversationState.ERROR
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# 记录错误的动作到 history
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error_record_llm = {
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"action": action,
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"plan_reason": reason,
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"status": "error_during_llm_action",
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"time": datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"),
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"final_reason": f"LLM动作执行时发生错误: {str(e_llm_task)}",
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}
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if conversation_instance.conversation_info:
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if not hasattr(conversation_instance.conversation_info, "done_action") or conversation_instance.conversation_info.done_action is None:
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conversation_instance.conversation_info.done_action = []
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conversation_instance.conversation_info.done_action.append(error_record_llm)
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conversation_instance.conversation_info.last_successful_reply_action = None
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break # 跳出监控循环
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if interrupted_during_llm:
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await asyncio.sleep(0.1) # 短暂休眠
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continue # 如果LLM任务被中断，则直接进入下一轮PFC主循环以重新规划
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# 如果LLM任务正常完成 (没有被中断或出错跳出)
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# actions.handle_action 内部会处理其结果和状态更新
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logger.debug(f"[私聊][{conversation_instance.private_name}] (Loop) LLM动作 '{action}' 任务正常完成。")
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else: # 对于非LLM生成类的动作，直接执行
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conversation_instance.state = ConversationState.ANALYZING
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# 如果是我们因为新消息主动取消的，下一轮不强制反思，正常规划
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# 如果是其他原因（例如LLM内部错误导致任务提前结束并被视为中断），也可以考虑不强制反思
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# _force_reflect_and_act_next_iter 保持其默认的 False
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logger.info(f"[私聊][{conversation_instance.private_name}] (Loop) LLM动作中断，准备重新规划。llm_task_cancelled_by_us: {llm_task_cancelled_by_us}")
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await asyncio.sleep(0.1)
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continue
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else:
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logger.debug(
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f"[私聊][{conversation_instance.private_name}] (Loop) 执行非LLM类动作 '{action}'..."
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)
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if conversation_instance.conversation_info: # 确保传递最新的计数值
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if conversation_instance.conversation_info:
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conversation_instance.conversation_info.other_new_messages_during_planning_count = other_new_msg_count_action_planning
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await actions.handle_action(
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||||
|
|
@ -334,18 +301,19 @@ async def run_conversation_loop(conversation_instance: "Conversation"):
|
|||
)
|
||||
logger.debug(f"[私聊][{conversation_instance.private_name}] (Loop) 非LLM类动作 '{action}' 完成。")
|
||||
|
||||
# 检查是否需要反思 (这部分逻辑保持不变)
|
||||
last_action_record = {}
|
||||
if conversation_instance.conversation_info and conversation_instance.conversation_info.done_action:
|
||||
last_action_record = conversation_instance.conversation_info.done_action[-1]
|
||||
|
||||
# 只有当 ReplyGenerator 明确决定不发送时，才强制下一轮反思
|
||||
if (
|
||||
last_action_record.get("action") == "send_new_message"
|
||||
and last_action_record.get("status") == "done_no_reply"
|
||||
and last_action_record.get("status") == "done_no_reply"
|
||||
):
|
||||
logger.info(f"[私聊][{conversation_instance.private_name}] (Loop) 检测到需反思，设置标志。")
|
||||
force_reflect_and_act = True
|
||||
logger.info(f"[私聊][{conversation_instance.private_name}] (Loop) 检测到 ReplyGenerator 决定不发送消息，下一轮将强制反思。")
|
||||
_force_reflect_and_act_next_iter = True
|
||||
|
||||
|
||||
# 检查结束条件 (这部分逻辑保持不变)
|
||||
goal_ended: bool = False
|
||||
if (
|
||||
conversation_instance.conversation_info
|
||||
|
|
@ -361,7 +329,7 @@ async def run_conversation_loop(conversation_instance: "Conversation"):
|
|||
if current_goal == "结束对话":
|
||||
goal_ended = True
|
||||
|
||||
last_action_record_for_end_check = {}
|
||||
last_action_record_for_end_check = {} # 重新获取最新的记录
|
||||
if conversation_instance.conversation_info and conversation_instance.conversation_info.done_action:
|
||||
last_action_record_for_end_check = conversation_instance.conversation_info.done_action[-1]
|
||||
action_ended: bool = (
|
||||
|
|
@ -382,15 +350,14 @@ async def run_conversation_loop(conversation_instance: "Conversation"):
|
|||
logger.error(f"[私聊][{conversation_instance.private_name}] (Loop) PFC 主循环出错: {loop_err}")
|
||||
logger.error(f"[私聊][{conversation_instance.private_name}] (Loop) {traceback.format_exc()}")
|
||||
conversation_instance.state = ConversationState.ERROR
|
||||
await asyncio.sleep(5) # 出错后等待一段时间
|
||||
await asyncio.sleep(5)
|
||||
|
||||
# 控制循环频率
|
||||
loop_duration = time.time() - loop_iter_start_time
|
||||
min_loop_interval = 0.1 # 最小循环间隔，避免过于频繁的空转
|
||||
min_loop_interval = 0.1
|
||||
logger.debug(f"[私聊][{conversation_instance.private_name}] (Loop) 循环迭代耗时: {loop_duration:.3f} 秒。")
|
||||
if loop_duration < min_loop_interval:
|
||||
await asyncio.sleep(min_loop_interval - loop_duration)
|
||||
|
||||
logger.info(
|
||||
f"[私聊][{conversation_instance.private_name}] (Loop) PFC 循环已退出 for stream_id: {conversation_instance.stream_id}"
|
||||
)
|
||||
)
|
||||
|
|
|
|||
Loading…
Reference in New Issue