mirror of https://github.com/Mai-with-u/MaiBot.git
125 lines
5.8 KiB
Python
125 lines
5.8 KiB
Python
# 定义了来自外部世界的信息
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# 外部世界可以是某个聊天 不同平台的聊天 也可以是任意媒体
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from datetime import datetime
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from src.common.logger_manager import get_logger
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from src.chat.focus_chat.heartFC_Cycleinfo import CycleDetail
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from typing import List
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# Import the new utility function
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logger = get_logger("observation")
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# 所有观察的基类
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class HFCloopObservation:
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def __init__(self, observe_id):
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self.observe_info = ""
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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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self.history_loop: List[CycleDetail] = []
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def get_observe_info(self):
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return self.observe_info
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def add_loop_info(self, loop_info: CycleDetail):
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self.history_loop.append(loop_info)
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async def observe(self):
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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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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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cycle_last_reason = ""
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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_reasoning != cycle_last_reason:
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cycle_last_reason = action_reasoning
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action_reasoning_str = f"你选择这个action的原因是:{action_reasoning}"
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else:
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action_reasoning_str = ""
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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}')。{action_reasoning_str}\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。{action_reasoning_str}\n"
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elif action_type == "no_reply":
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action_detailed_str += (
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f"{action_taken_time_str}时，你选择不回复(action:{action_type})，{action_reasoning_str}\n"
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)
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else:
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if is_taken:
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action_detailed_str += (
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f"{action_taken_time_str}时，你选择执行了(action:{action_type})，{action_reasoning_str}\n"
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)
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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。{action_reasoning_str}\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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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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# 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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# 获取history_loop中最新添加的
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if self.history_loop:
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last_loop = self.history_loop[0]
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start_time = last_loop.start_time
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end_time = last_loop.end_time
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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"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"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 += "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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# 只序列化基本信息，避免循环引用
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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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# 不序列化history_loop，避免循环引用
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"history_loop_count": len(self.history_loop),
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}
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