chore: format code and remove redundant blank lines
This commit applies automated code formatting across the project. The changes primarily involve removing unnecessary blank lines and ensuring consistent code style, improving readability and maintainability without altering functionality.
This commit is contained in:
committed by
Windpicker-owo
parent
0172cf7b8b
commit
d66e04baff
@@ -188,15 +188,12 @@ class ActionPlanner:
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param_text = ""
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if action_info.action_parameters:
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param_text = "\n" + "\n".join(
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f' "{p_name}":"{p_desc}"'
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for p_name, p_desc in action_info.action_parameters.items()
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f' "{p_name}":"{p_desc}"' for p_name, p_desc in action_info.action_parameters.items()
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)
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require_text = "\n".join(f"- {req}" for req in action_info.action_require)
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using_action_prompt = await global_prompt_manager.get_prompt_async(
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"action_prompt"
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)
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using_action_prompt = await global_prompt_manager.get_prompt_async("action_prompt")
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action_options_block += using_action_prompt.format(
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action_name=action_name,
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action_description=action_info.description,
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@@ -205,9 +202,7 @@ class ActionPlanner:
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)
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return action_options_block
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def find_message_by_id(
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self, message_id: str, message_id_list: list
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) -> Optional[Dict[str, Any]]:
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def find_message_by_id(self, message_id: str, message_id_list: list) -> Optional[Dict[str, Any]]:
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# sourcery skip: use-next
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"""
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根据message_id从message_id_list中查找对应的原始消息
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@@ -245,7 +240,7 @@ class ActionPlanner:
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async def plan(
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self,
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mode: ChatMode = ChatMode.FOCUS,
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loop_start_time:float = 0.0,
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loop_start_time: float = 0.0,
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available_actions: Optional[Dict[str, ActionInfo]] = None,
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) -> Tuple[List[Dict[str, Any]], Optional[Dict[str, Any]]]:
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"""
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@@ -324,11 +319,15 @@ class ActionPlanner:
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# 如果获取的target_message为None,输出warning并重新plan
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if target_message is None:
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self.plan_retry_count += 1
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logger.warning(f"{self.log_prefix}无法找到target_message_id '{target_message_id}' 对应的消息,重试次数: {self.plan_retry_count}/{self.max_plan_retries}")
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logger.warning(
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f"{self.log_prefix}无法找到target_message_id '{target_message_id}' 对应的消息,重试次数: {self.plan_retry_count}/{self.max_plan_retries}"
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)
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# 如果连续三次plan均为None,输出error并选取最新消息
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if self.plan_retry_count >= self.max_plan_retries:
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logger.error(f"{self.log_prefix}连续{self.max_plan_retries}次plan获取target_message失败,选择最新消息作为target_message")
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logger.error(
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f"{self.log_prefix}连续{self.max_plan_retries}次plan获取target_message失败,选择最新消息作为target_message"
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)
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target_message = self.get_latest_message(message_id_list)
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self.plan_retry_count = 0 # 重置计数器
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else:
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@@ -339,8 +338,7 @@ class ActionPlanner:
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self.plan_retry_count = 0
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else:
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logger.warning(f"{self.log_prefix}动作'{action}'缺少target_message_id")
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if action != "no_reply" and action != "reply" and action not in current_available_actions:
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logger.warning(
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f"{self.log_prefix}LLM 返回了当前不可用或无效的动作: '{action}' (可用: {list(current_available_actions.keys())}),将强制使用 'no_reply'"
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@@ -363,36 +361,35 @@ class ActionPlanner:
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is_parallel = False
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if mode == ChatMode.NORMAL and action in current_available_actions:
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is_parallel = current_available_actions[action].parallel_action
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action_data["loop_start_time"] = loop_start_time
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actions = []
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# 1. 添加Planner取得的动作
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actions.append({
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"action_type": action,
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"reasoning": reasoning,
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"action_data": action_data,
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"action_message": target_message,
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"available_actions": available_actions # 添加这个字段
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})
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if action != "reply" and is_parallel:
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actions.append({
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"action_type": "reply",
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actions.append(
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{
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"action_type": action,
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"reasoning": reasoning,
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"action_data": action_data,
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"action_message": target_message,
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"available_actions": available_actions
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})
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return actions,target_message
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"available_actions": available_actions, # 添加这个字段
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}
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)
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if action != "reply" and is_parallel:
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actions.append(
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{"action_type": "reply", "action_message": target_message, "available_actions": available_actions}
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)
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return actions, target_message
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async def build_planner_prompt(
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self,
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is_group_chat: bool, # Now passed as argument
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chat_target_info: Optional[dict], # Now passed as argument
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current_available_actions: Dict[str, ActionInfo],
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refresh_time :bool = False,
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refresh_time: bool = False,
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mode: ChatMode = ChatMode.FOCUS,
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) -> tuple[str, list]: # sourcery skip: use-join
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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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@@ -401,21 +398,15 @@ class ActionPlanner:
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time_block = f"当前时间:{datetime.now().strftime('%Y-%m-%d %H:%M:%S')}"
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bot_name = global_config.bot.nickname
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bot_nickname = (
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f",也有人叫你{','.join(global_config.bot.alias_names)}"
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if global_config.bot.alias_names
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else ""
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f",也有人叫你{','.join(global_config.bot.alias_names)}" if global_config.bot.alias_names else ""
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)
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bot_core_personality = global_config.personality.personality_core
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identity_block = (
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f"你的名字是{bot_name}{bot_nickname},你{bot_core_personality}:"
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)
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identity_block = f"你的名字是{bot_name}{bot_nickname},你{bot_core_personality}:"
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schedule_block = ""
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if global_config.schedule.enable:
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if current_activity := schedule_manager.get_current_activity():
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schedule_block = (
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f"你当前正在:{current_activity},但注意它与群聊的聊天无关。"
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)
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schedule_block = f"你当前正在:{current_activity},但注意它与群聊的聊天无关。"
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mood_block = ""
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if global_config.mood.enable_mood:
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@@ -425,13 +416,9 @@ class ActionPlanner:
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# --- 根据模式构建不同的Prompt ---
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if mode == ChatMode.PROACTIVE:
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long_term_memory_block = await self._get_long_term_memory_context()
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action_options_text = await self._build_action_options(
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current_available_actions, mode
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)
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action_options_text = await self._build_action_options(current_available_actions, mode)
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prompt_template = await global_prompt_manager.get_prompt_async(
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"proactive_planner_prompt"
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)
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prompt_template = await global_prompt_manager.get_prompt_async("proactive_planner_prompt")
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prompt = prompt_template.format(
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time_block=time_block,
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identity_block=identity_block,
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@@ -464,12 +451,8 @@ class ActionPlanner:
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limit=5,
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)
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actions_before_now_block = build_readable_actions(
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actions=actions_before_now
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)
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actions_before_now_block = (
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f"你刚刚选择并执行过的action是:\n{actions_before_now_block}"
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)
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actions_before_now_block = build_readable_actions(actions=actions_before_now)
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actions_before_now_block = f"你刚刚选择并执行过的action是:\n{actions_before_now_block}"
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if refresh_time:
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self.last_obs_time_mark = time.time()
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@@ -505,30 +488,22 @@ class ActionPlanner:
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}}"""
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chat_context_description = "你现在正在一个群聊中"
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chat_target_name = None
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chat_target_name = None
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if not is_group_chat and chat_target_info:
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chat_target_name = (
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chat_target_info.get("person_name")
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or chat_target_info.get("user_nickname")
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or "对方"
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chat_target_info.get("person_name") or chat_target_info.get("user_nickname") or "对方"
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)
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chat_context_description = f"你正在和 {chat_target_name} 私聊"
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action_options_block = await self._build_action_options(
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current_available_actions, mode
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)
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action_options_block = await self._build_action_options(current_available_actions, mode)
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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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custom_prompt_block = ""
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if global_config.custom_prompt.planner_custom_prompt_content:
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custom_prompt_block = (
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global_config.custom_prompt.planner_custom_prompt_content
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)
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custom_prompt_block = global_config.custom_prompt.planner_custom_prompt_content
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planner_prompt_template = await global_prompt_manager.get_prompt_async(
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"planner_prompt"
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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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schedule_block=schedule_block,
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mood_block=mood_block,
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@@ -557,9 +532,7 @@ class ActionPlanner:
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"""
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is_group_chat = True
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is_group_chat, chat_target_info = get_chat_type_and_target_info(self.chat_id)
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logger.debug(
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f"{self.log_prefix}获取到聊天信息 - 群聊: {is_group_chat}, 目标信息: {chat_target_info}"
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)
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logger.debug(f"{self.log_prefix}获取到聊天信息 - 群聊: {is_group_chat}, 目标信息: {chat_target_info}")
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current_available_actions_dict = self.action_manager.get_using_actions()
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@@ -570,13 +543,9 @@ class ActionPlanner:
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current_available_actions = {}
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for action_name in current_available_actions_dict:
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if action_name in all_registered_actions:
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current_available_actions[action_name] = all_registered_actions[
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action_name
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]
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current_available_actions[action_name] = all_registered_actions[action_name]
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else:
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logger.warning(
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f"{self.log_prefix}使用中的动作 {action_name} 未在已注册动作中找到"
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)
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logger.warning(f"{self.log_prefix}使用中的动作 {action_name} 未在已注册动作中找到")
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# 将no_reply作为系统级特殊动作添加到可用动作中
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# no_reply虽然是系统级决策,但需要让规划器认为它是可用的
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