feat:处理器处理时间上限,处理并行模式,planner和思考prompt,循环观察器大优化
feat:增加了处理器处理时间上限,记忆处理并行模式,优化了planner和思考prompt,优化了循环观察器
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@@ -34,3 +34,13 @@ class ActionObservation:
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action_info_block += "\n注意,除了上面动作选项之外,你在群聊里不能做其他任何事情,这是你能力的边界\n"
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self.observe_info = action_info_block
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def to_dict(self) -> dict:
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"""将观察对象转换为可序列化的字典"""
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return {
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"observe_info": self.observe_info,
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"observe_id": self.observe_id,
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"last_observe_time": self.last_observe_time,
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"all_actions": self.all_actions,
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"all_using_actions": self.all_using_actions
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}
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@@ -66,6 +66,24 @@ class ChattingObservation(Observation):
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self.oldest_messages_str = ""
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self.compressor_prompt = ""
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def to_dict(self) -> dict:
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"""将观察对象转换为可序列化的字典"""
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return {
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"chat_id": self.chat_id,
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"platform": self.platform,
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"is_group_chat": self.is_group_chat,
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"chat_target_info": self.chat_target_info,
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"talking_message_str": self.talking_message_str,
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"talking_message_str_truncate": self.talking_message_str_truncate,
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"name": self.name,
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"nick_name": self.nick_name,
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"mid_memory_info": self.mid_memory_info,
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"person_list": self.person_list,
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"oldest_messages_str": self.oldest_messages_str,
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"compressor_prompt": self.compressor_prompt,
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"last_observe_time": self.last_observe_time
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}
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async def initialize(self):
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self.is_group_chat, self.chat_target_info = await get_chat_type_and_target_info(self.chat_id)
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logger.debug(f"初始化observation: self.is_group_chat: {self.is_group_chat}")
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@@ -27,40 +27,62 @@ class HFCloopObservation:
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recent_active_cycles: List[CycleDetail] = []
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for cycle in reversed(self.history_loop):
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# 只关心实际执行了动作的循环
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action_taken = cycle.loop_action_info["action_taken"]
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if action_taken:
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recent_active_cycles.append(cycle)
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if len(recent_active_cycles) == 5:
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break
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# action_taken = cycle.loop_action_info["action_taken"]
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# if action_taken:
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recent_active_cycles.append(cycle)
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if len(recent_active_cycles) == 5:
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break
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cycle_info_block = ""
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action_detailed_str = ""
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consecutive_text_replies = 0
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responses_for_prompt = []
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# 检查这最近的活动循环中有多少是连续的文本回复 (从最近的开始看)
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for cycle in recent_active_cycles:
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action_type = cycle.loop_plan_info["action_result"]["action_type"]
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action_reasoning = cycle.loop_plan_info["action_result"]["reasoning"]
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is_taken = cycle.loop_action_info["action_taken"]
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action_taken_time = cycle.loop_action_info["taken_time"]
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action_taken_time_str = datetime.fromtimestamp(action_taken_time).strftime("%H:%M:%S")
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# print(action_type)
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# print(action_reasoning)
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# print(is_taken)
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# print(action_taken_time_str)
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# print("--------------------------------")
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if action_type == "reply":
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consecutive_text_replies += 1
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response_text = cycle.loop_plan_info["action_result"]["action_data"].get("text", "[空回复]")
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responses_for_prompt.append(response_text)
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if is_taken:
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action_detailed_str += f"{action_taken_time_str}时,你选择回复(action:{action_type},内容是:'{response_text}')。你选择这个action的原因是:{action_reasoning}\n"
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else:
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action_detailed_str += f"{action_taken_time_str}时,你选择回复(action:{action_type},内容是:'{response_text}'),但是动作失败了。你选择这个action的原因是:{action_reasoning}\n"
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elif action_type == "no_reply":
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action_detailed_str += f"{action_taken_time_str}时,你选择不回复(action:{action_type}),你选择了沉默,原因是:{action_reasoning}\n"
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else:
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break
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if is_taken:
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action_detailed_str += f"{action_taken_time_str}时,你选择执行了(action:{action_type}),你选择这个action的原因是:{action_reasoning}\n"
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else:
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action_detailed_str += f"{action_taken_time_str}时,你选择执行了(action:{action_type}),但是动作失败了。你选择这个action的原因是:{action_reasoning}\n"
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if action_detailed_str:
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cycle_info_block = f"\n你最近做的事:\n{action_detailed_str}\n"
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else:
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cycle_info_block = "\n"
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# 根据连续文本回复的数量构建提示信息
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# 注意: responses_for_prompt 列表是从最近到最远排序的
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if consecutive_text_replies >= 3: # 如果最近的三个活动都是文本回复
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cycle_info_block = f'你已经连续回复了三条消息(最近: "{responses_for_prompt[0]}",第二近: "{responses_for_prompt[1]}",第三近: "{responses_for_prompt[2]}")。你回复的有点多了,请注意'
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elif consecutive_text_replies == 2: # 如果最近的两个活动是文本回复
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cycle_info_block = f'你已经连续回复了两条消息(最近: "{responses_for_prompt[0]}",第二近: "{responses_for_prompt[1]}"),请注意'
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elif consecutive_text_replies == 1: # 如果最近的一个活动是文本回复
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cycle_info_block = f'你刚刚已经回复一条消息(内容: "{responses_for_prompt[0]}")'
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# 包装提示块,增加可读性,即使没有连续回复也给个标记
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if cycle_info_block:
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cycle_info_block = f"\n你最近的回复\n{cycle_info_block}\n"
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else:
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cycle_info_block = "\n"
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# if cycle_info_block:
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# cycle_info_block = f"\n你最近的回复\n{cycle_info_block}\n"
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# else:
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# cycle_info_block = "\n"
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# 获取history_loop中最新添加的
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if self.history_loop:
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@@ -70,10 +92,19 @@ class HFCloopObservation:
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if start_time is not None and end_time is not None:
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time_diff = int(end_time - start_time)
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if time_diff > 60:
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cycle_info_block += f"\n距离你上一次阅读消息已经过去了{time_diff / 60}分钟\n"
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cycle_info_block += f"距离你上一次阅读消息并思考和规划,已经过去了{int(time_diff / 60)}分钟\n"
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else:
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cycle_info_block += f"\n距离你上一次阅读消息已经过去了{time_diff}秒\n"
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cycle_info_block += f"距离你上一次阅读消息并思考和规划,已经过去了{time_diff}秒\n"
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else:
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cycle_info_block += "\n你还没看过消息\n"
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cycle_info_block += "你还没看过消息\n"
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self.observe_info = cycle_info_block
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def to_dict(self) -> dict:
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"""将观察对象转换为可序列化的字典"""
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return {
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"observe_info": self.observe_info,
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"observe_id": self.observe_id,
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"last_observe_time": self.last_observe_time,
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"history_loop": [cycle.to_dict() for cycle in self.history_loop]
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}
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@@ -13,5 +13,13 @@ class Observation:
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self.observe_id = observe_id
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self.last_observe_time = datetime.now().timestamp() # 初始化为当前时间
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def to_dict(self) -> dict:
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"""将观察对象转换为可序列化的字典"""
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return {
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"observe_info": self.observe_info,
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"observe_id": self.observe_id,
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"last_observe_time": self.last_observe_time
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}
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async def observe(self):
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pass
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@@ -15,6 +15,16 @@ class StructureObservation:
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self.history_loop = []
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self.structured_info = []
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def to_dict(self) -> dict:
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"""将观察对象转换为可序列化的字典"""
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return {
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"observe_info": self.observe_info,
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"observe_id": self.observe_id,
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"last_observe_time": self.last_observe_time,
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"history_loop": self.history_loop,
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"structured_info": self.structured_info
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}
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def get_observe_info(self):
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return self.structured_info
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@@ -32,3 +32,13 @@ class WorkingMemoryObservation:
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async def observe(self):
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pass
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def to_dict(self) -> dict:
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"""将观察对象转换为可序列化的字典"""
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return {
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"observe_info": self.observe_info,
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"observe_id": self.observe_id,
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"last_observe_time": self.last_observe_time,
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"working_memory": self.working_memory.to_dict() if hasattr(self.working_memory, 'to_dict') else str(self.working_memory),
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"retrieved_working_memory": [item.to_dict() if hasattr(item, 'to_dict') else str(item) for item in self.retrieved_working_memory]
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}
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@@ -278,10 +278,6 @@ class SubHeartflow:
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self.update_last_chat_state_time()
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self.history_chat_state.append((current_state, self.chat_state_last_time))
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# logger.info(
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# f"{log_prefix} 麦麦的聊天状态从 {current_state.value} (持续了 {int(self.chat_state_last_time)} 秒) 变更为 {new_state.value}"
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# )
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self.chat_state.chat_status = new_state
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self.chat_state_last_time = 0
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self.chat_state_changed_time = time.time()
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