mirror of https://github.com/Mai-with-u/MaiBot.git
better：优化planner，提及时消耗更少，连续no_reply时降低敏感度
SengokuCola
parent
250919f892
commit
82a87f4926
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@ -111,6 +111,9 @@ class HeartFChatting:
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self.question_probability_multiplier = 1
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self.questioned = False
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# 跟踪连续 no_reply 次数，用于动态调整阈值
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self.consecutive_no_reply_count = 0
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# 聊天内容概括器
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self.chat_history_summarizer = ChatHistorySummarizer(chat_id=self.stream_id)
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@ -192,43 +195,21 @@ class HeartFChatting:
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filter_command=True,
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)
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question_probability = 0
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if time.time() - self.last_active_time > 7200:
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question_probability = 0.0003
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elif time.time() - self.last_active_time > 3600:
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question_probability = 0.0001
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# 根据连续 no_reply 次数动态调整阈值
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# 3次 no_reply 时，阈值调高到 1.5（50%概率为1，50%概率为2）
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# 5次 no_reply 时，提高到 2（大于等于两条消息的阈值）
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if self.consecutive_no_reply_count >= 5:
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threshold = 2
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elif self.consecutive_no_reply_count >= 3:
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# 1.5 的含义：50%概率为1，50%概率为2
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threshold = 2 if random.random() < 0.5 else 1
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else:
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question_probability = 0.00003
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question_probability = question_probability * global_config.chat.get_auto_chat_value(self.stream_id) * self.question_probability_multiplier
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threshold = 1
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#暂时禁用
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# print(f"{self.log_prefix} questioned: {self.questioned},len: {len(global_conflict_tracker.get_questions_by_chat_id(self.stream_id))}")
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# if question_probability > 0 and not self.questioned and len(global_conflict_tracker.get_questions_by_chat_id(self.stream_id)) == 0: #长久没有回复，可以试试主动发言，提问概率随着时间增加
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# # logger.info(f"{self.log_prefix} 长久没有回复，可以试试主动发言，概率: {question_probability}")
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# if random.random() < question_probability: # 30%概率主动发言
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# try:
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# self.questioned = True
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# self.last_active_time = time.time()
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# # print(f"{self.log_prefix} 长久没有回复，可以试试主动发言，开始生成问题")
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# logger.info(f"{self.log_prefix} 长久没有回复，可以试试主动发言，开始生成问题")
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# cycle_timers, thinking_id = self.start_cycle()
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# question_maker = QuestionMaker(self.stream_id)
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# question, context,conflict_context = await question_maker.make_question()
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# if question:
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# logger.info(f"{self.log_prefix} 问题: {question}")
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# await global_conflict_tracker.track_conflict(question, conflict_context, True, self.stream_id)
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# await self._lift_question_reply(question,context,thinking_id)
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# else:
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# logger.info(f"{self.log_prefix} 无问题")
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# # self.end_cycle(cycle_timers, thinking_id)
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# except Exception as e:
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# logger.error(f"{self.log_prefix} 主动提问失败: {e}")
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# print(traceback.format_exc())
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if len(recent_messages_list) >= 1:
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if len(recent_messages_list) >= threshold:
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# for message in recent_messages_list:
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# print(message.processed_plain_text)
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# !处理no_reply_until_call逻辑
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@ -332,14 +313,15 @@ class HeartFChatting:
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available_actions: Dict[str, ActionInfo],
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cycle_timers: Dict[str, float],
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) -> List[ActionPlannerInfo]:
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"""执行planner，但不包含reply动作（用于并行执行场景）"""
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"""执行planner，但不包含reply动作（用于并行执行场景，提及时使用简化版提示词）"""
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try:
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with Timer("规划器", cycle_timers):
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action_to_use_info = await self.action_planner.plan(
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loop_start_time=self.last_read_time,
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available_actions=available_actions,
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is_mentioned=True, # 标记为提及时，使用简化版提示词
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)
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# 过滤掉reply动作
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# 过滤掉reply动作（虽然提及时不应该有reply，但为了安全还是过滤一下）
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return [action for action in action_to_use_info if action.action_type != "reply"]
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except Exception as e:
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logger.error(f"{self.log_prefix} Planner执行失败: {e}")
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@ -356,6 +338,8 @@ class HeartFChatting:
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"""当被提及时，独立生成回复的任务"""
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try:
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self.questioned = False
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# 重置连续 no_reply 计数
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self.consecutive_no_reply_count = 0
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reason = "有人提到了你，进行回复"
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await database_api.store_action_info(
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@ -675,76 +659,6 @@ class HeartFChatting:
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traceback.print_exc()
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return False, ""
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async def _lift_question_reply(self, question: str, question_context: str, thinking_id: str):
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reason = f"在聊天中：\n{question_context}\n你对问题\"{question}\"感到好奇，想要和群友讨论"
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new_msg = get_raw_msg_before_timestamp_with_chat(
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chat_id=self.stream_id,
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timestamp=time.time(),
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limit=1,
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)
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reply_action_info = ActionPlannerInfo(
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action_type="reply",
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reasoning= "",
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action_data={},
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action_message=new_msg[0],
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available_actions=None,
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loop_start_time=time.time(),
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action_reasoning=reason)
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self.action_planner.add_plan_log(reasoning=f"你对问题\"{question}\"感到好奇，想要和群友讨论", actions=[reply_action_info])
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success, llm_response = await generator_api.rewrite_reply(
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chat_stream=self.chat_stream,
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reply_data={
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"raw_reply": f"我对这个问题感到好奇：{question}",
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"reason": reason,
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},
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)
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if not success or not llm_response or not llm_response.reply_set:
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logger.info("主动提问发言失败")
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self.action_planner.add_plan_excute_log(result="主动回复生成失败")
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return {"action_type": "reply", "success": False, "result": "主动回复生成失败", "loop_info": None}
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if success:
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for reply_seg in llm_response.reply_set.reply_data:
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send_data = reply_seg.content
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await send_api.text_to_stream(
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text=send_data,
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stream_id=self.stream_id,
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)
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await database_api.store_action_info(
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chat_stream=self.chat_stream,
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action_build_into_prompt=False,
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action_prompt_display=reason,
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action_done=True,
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thinking_id=thinking_id,
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action_data={"reply_text": llm_response.reply_set.reply_data[0].content},
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action_name="reply",
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)
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# 构建循环信息
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loop_info: Dict[str, Any] = {
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"loop_plan_info": {
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"action_result": [reply_action_info],
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},
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"loop_action_info": {
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"action_taken": True,
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"reply_text": llm_response.reply_set.reply_data[0].content,
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"command": "",
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"taken_time": time.time(),
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},
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}
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self.last_active_time = time.time()
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self.action_planner.add_plan_excute_log(result=f"你提问：{question}")
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return {
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"action_type": "reply",
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"success": True,
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"result": f"你提问：{question}",
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"loop_info": loop_info,
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}
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async def _send_response(
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@ -808,6 +722,9 @@ class HeartFChatting:
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reason = action_planner_info.reasoning or "选择不回复"
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# logger.info(f"{self.log_prefix} 选择不回复，原因: {reason}")
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# 增加连续 no_reply 计数
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self.consecutive_no_reply_count += 1
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await database_api.store_action_info(
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chat_stream=self.chat_stream,
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action_build_into_prompt=False,
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@ -827,6 +744,8 @@ class HeartFChatting:
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logger.info(f"{self.log_prefix} 保持沉默，直到有人直接叫的名字")
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reason = action_planner_info.reasoning or "选择不回复"
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# 增加连续 no_reply 计数
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self.consecutive_no_reply_count += 1
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self.no_reply_until_call = True
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await database_api.store_action_info(
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chat_stream=self.chat_stream,
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@ -844,6 +763,8 @@ class HeartFChatting:
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# 直接当场执行reply逻辑
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self.questioned = False
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# 刷新主动发言状态
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# 重置连续 no_reply 计数
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self.consecutive_no_reply_count = 0
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reason = action_planner_info.reasoning or "选择回复"
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await database_api.store_action_info(
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@ -83,6 +83,42 @@ no_reply
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"planner_prompt",
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)
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Prompt(
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"""{time_block}
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{name_block}
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{chat_context_description}，以下是具体的聊天内容
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**聊天内容**
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{chat_content_block}
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**可选的action**
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no_reply
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动作描述：
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没有合适的可以使用的动作，不使用action
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{{"action":"no_reply"}}
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{action_options_text}
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**你之前的action执行和思考记录**
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{actions_before_now_block}
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请选择**可选的**且符合使用条件的action，并说明触发action的消息id(消息id格式:m+数字)
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先输出你的简短的选择思考理由，再输出你选择的action，理由不要分点，精简。
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**动作选择要求**
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请你根据聊天内容,用户的最新消息和以下标准选择合适的动作:
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1.思考**所有**的可用的action中的**每个动作**是否符合当下条件，如果动作使用条件符合聊天内容就使用
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2.如果相同的内容已经被执行，请不要重复执行
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{moderation_prompt}
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请选择所有符合使用要求的action，动作用json格式输出，用```json包裹，如果输出多个json，每个json都要单独一行放在同一个```json代码块内，你可以重复使用同一个动作或不同动作:
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**示例**
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// 理由文本（简短）
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```json
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{{"action":"动作名", "target_message_id":"m123", "reason":"原因"}}
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{{"action":"动作名", "target_message_id":"m456", "reason":"原因"}}
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```""",
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"planner_prompt_mentioned",
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)
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Prompt(
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"""
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{action_name}
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@ -205,6 +241,7 @@ class ActionPlanner:
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self,
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available_actions: Dict[str, ActionInfo],
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loop_start_time: float = 0.0,
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is_mentioned: bool = False,
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) -> List[ActionPlannerInfo]:
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# sourcery skip: use-named-expression
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"""
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@ -244,6 +281,11 @@ class ActionPlanner:
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logger.debug(f"{self.log_prefix}过滤后有{len(filtered_actions)}个可用动作")
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# 如果是提及时且没有可用动作，直接返回空列表，不调用LLM以节省token
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if is_mentioned and not filtered_actions:
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logger.info(f"{self.log_prefix}提及时没有可用动作，跳过plan调用")
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return []
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# 构建包含所有动作的提示词
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prompt, message_id_list = await self.build_planner_prompt(
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is_group_chat=is_group_chat,
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@ -252,6 +294,7 @@ class ActionPlanner:
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chat_content_block=chat_content_block,
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message_id_list=message_id_list,
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interest=global_config.personality.interest,
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is_mentioned=is_mentioned,
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)
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# 调用LLM获取决策
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@ -355,6 +398,7 @@ class ActionPlanner:
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message_id_list: List[Tuple[str, "DatabaseMessages"]],
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chat_content_block: str = "",
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interest: str = "",
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is_mentioned: bool = False,
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) -> tuple[str, List[Tuple[str, "DatabaseMessages"]]]:
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"""构建 Planner LLM 的提示词 (获取模板并填充数据)"""
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try:
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@ -367,17 +411,6 @@ class ActionPlanner:
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# 构建动作选项块
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action_options_block = await self._build_action_options_block(current_available_actions)
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# 检查是否有连续3次以上no_reply，如果有则添加no_reply_until_call选项
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no_reply_until_call_block = ""
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if self._has_consecutive_no_reply(min_count=3):
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no_reply_until_call_block = """no_reply_until_call
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动作描述：
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保持沉默，直到有人直接叫你的名字
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当前话题不感兴趣时使用，或有人不喜欢你的发言时使用
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当你频繁选择no_reply时使用，表示话题暂时与你无关
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{{"action":"no_reply_until_call"}}
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"""
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# 其他信息
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moderation_prompt_block = "请不要输出违法违规内容，不要输出色情，暴力，政治相关内容，如有敏感内容，请规避。"
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time_block = f"当前时间：{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}"
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@ -387,20 +420,47 @@ class ActionPlanner:
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)
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name_block = f"你的名字是{bot_name}{bot_nickname}，请注意哪些是你自己的发言。"
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# 获取主规划器模板并填充
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planner_prompt_template = await global_prompt_manager.get_prompt_async("planner_prompt")
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prompt = planner_prompt_template.format(
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time_block=time_block,
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chat_context_description=chat_context_description,
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chat_content_block=chat_content_block,
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actions_before_now_block=actions_before_now_block,
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action_options_text=action_options_block,
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no_reply_until_call_block=no_reply_until_call_block,
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moderation_prompt=moderation_prompt_block,
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name_block=name_block,
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interest=interest,
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plan_style=global_config.personality.plan_style,
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)
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# 根据是否是提及时选择不同的模板
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if is_mentioned:
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# 提及时使用简化版提示词，不需要reply、no_reply、no_reply_until_call
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planner_prompt_template = await global_prompt_manager.get_prompt_async("planner_prompt_mentioned")
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prompt = planner_prompt_template.format(
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time_block=time_block,
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chat_context_description=chat_context_description,
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chat_content_block=chat_content_block,
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actions_before_now_block=actions_before_now_block,
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action_options_text=action_options_block,
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moderation_prompt=moderation_prompt_block,
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name_block=name_block,
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interest=interest,
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plan_style=global_config.personality.plan_style,
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)
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else:
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# 正常流程使用完整版提示词
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# 检查是否有连续3次以上no_reply，如果有则添加no_reply_until_call选项
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no_reply_until_call_block = ""
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if self._has_consecutive_no_reply(min_count=3):
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no_reply_until_call_block = """no_reply_until_call
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动作描述：
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保持沉默，直到有人直接叫你的名字
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当前话题不感兴趣时使用，或有人不喜欢你的发言时使用
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当你频繁选择no_reply时使用，表示话题暂时与你无关
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{{"action":"no_reply_until_call"}}
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"""
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planner_prompt_template = await global_prompt_manager.get_prompt_async("planner_prompt")
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prompt = planner_prompt_template.format(
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time_block=time_block,
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chat_context_description=chat_context_description,
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chat_content_block=chat_content_block,
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actions_before_now_block=actions_before_now_block,
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action_options_text=action_options_block,
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no_reply_until_call_block=no_reply_until_call_block,
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moderation_prompt=moderation_prompt_block,
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name_block=name_block,
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interest=interest,
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plan_style=global_config.personality.plan_style,
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)
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return prompt, message_id_list
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except Exception as e:
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