mirror of https://github.com/Mai-with-u/MaiBot.git
379 lines
14 KiB
Python
379 lines
14 KiB
Python
from src.common.logger_manager import get_logger
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from src.chat.message_receive.chat_stream import ChatStream
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import math
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from src.person_info.person_info import person_info_manager
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import time
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import random
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from src.llm_models.utils_model import LLMRequest
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from src.config.config import global_config
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from src.chat.utils.chat_message_builder import get_raw_msg_by_timestamp_with_chat_users
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from src.chat.utils.chat_message_builder import build_readable_messages
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from src.manager.mood_manager import mood_manager
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logger = get_logger("relation")
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class RelationshipManager:
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def __init__(self):
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self.positive_feedback_value = 0 # 正反馈系统
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self.gain_coefficient = [1.0, 1.0, 1.1, 1.2, 1.4, 1.7, 1.9, 2.0]
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self._mood_manager = None
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self.relationship_llm = LLMRequest(
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model=global_config.model.normal_chat_1,
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max_tokens=1000,
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request_type="relationship", # 用于动作规划
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)
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@property
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def mood_manager(self):
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if self._mood_manager is None:
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self._mood_manager = mood_manager
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return self._mood_manager
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def positive_feedback_sys(self, label: str, stance: str):
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"""正反馈系统，通过正反馈系数增益情绪变化，根据情绪再影响关系变更"""
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positive_list = [
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"开心",
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"惊讶",
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"害羞",
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]
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negative_list = [
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"愤怒",
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"悲伤",
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"恐惧",
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"厌恶",
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]
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if label in positive_list:
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if 7 > self.positive_feedback_value >= 0:
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self.positive_feedback_value += 1
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elif self.positive_feedback_value < 0:
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self.positive_feedback_value = 0
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elif label in negative_list:
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if -7 < self.positive_feedback_value <= 0:
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self.positive_feedback_value -= 1
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elif self.positive_feedback_value > 0:
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self.positive_feedback_value = 0
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if abs(self.positive_feedback_value) > 1:
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logger.debug(f"触发mood变更增益，当前增益系数：{self.gain_coefficient[abs(self.positive_feedback_value)]}")
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def mood_feedback(self, value):
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"""情绪反馈"""
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mood_manager = self.mood_manager
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mood_gain = mood_manager.current_mood.valence**2 * math.copysign(1, value * mood_manager.current_mood.valence)
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value += value * mood_gain
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logger.debug(f"当前relationship增益系数：{mood_gain:.3f}")
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return value
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def feedback_to_mood(self, mood_value):
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"""对情绪的反馈"""
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coefficient = self.gain_coefficient[abs(self.positive_feedback_value)]
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if mood_value > 0 and self.positive_feedback_value > 0 or mood_value < 0 and self.positive_feedback_value < 0:
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return mood_value * coefficient
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else:
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return mood_value / coefficient
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@staticmethod
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async def is_known_some_one(platform, user_id):
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"""判断是否认识某人"""
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is_known = await person_info_manager.is_person_known(platform, user_id)
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return is_known
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@staticmethod
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async def is_qved_name(platform, user_id):
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"""判断是否认识某人"""
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person_id = person_info_manager.get_person_id(platform, user_id)
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is_qved = await person_info_manager.has_one_field(person_id, "person_name")
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old_name = await person_info_manager.get_value(person_id, "person_name")
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# print(f"old_name: {old_name}")
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# print(f"is_qved: {is_qved}")
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if is_qved and old_name is not None:
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return True
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else:
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return False
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@staticmethod
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async def first_knowing_some_one(
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platform: str, user_id: str, user_nickname: str, user_cardname: str, user_avatar: str
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):
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"""判断是否认识某人"""
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person_id = person_info_manager.get_person_id(platform, user_id)
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data = {
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"platform": platform,
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"user_id": user_id,
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"nickname": user_nickname,
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"konw_time": int(time.time()),
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}
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await person_info_manager.update_one_field(
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person_id=person_id, field_name="nickname", value=user_nickname, data=data
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)
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await person_info_manager.qv_person_name(
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person_id=person_id, user_nickname=user_nickname, user_cardname=user_cardname, user_avatar=user_avatar
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)
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async def calculate_update_relationship_value_with_reason(
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self, chat_stream: ChatStream, label: str, stance: str, reason: str
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) -> tuple:
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"""计算并变更关系值
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新的关系值变更计算方式：
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将关系值限定在-1000到1000
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对于关系值的变更，期望：
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1.向两端逼近时会逐渐减缓
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2.关系越差，改善越难，关系越好，恶化越容易
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3.人维护关系的精力往往有限，所以当高关系值用户越多，对于中高关系值用户增长越慢
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4.连续正面或负面情感会正反馈
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返回：
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用户昵称，变更值，变更后关系等级
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"""
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stancedict = {
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"支持": 0,
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"中立": 1,
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"反对": 2,
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}
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valuedict = {
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"开心": 1.5,
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"愤怒": -2.0,
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"悲伤": -0.5,
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"惊讶": 0.6,
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"害羞": 2.0,
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"平静": 0.3,
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"恐惧": -1.5,
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"厌恶": -1.0,
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"困惑": 0.5,
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}
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person_id = person_info_manager.get_person_id(chat_stream.user_info.platform, chat_stream.user_info.user_id)
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data = {
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"platform": chat_stream.user_info.platform,
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"user_id": chat_stream.user_info.user_id,
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"nickname": chat_stream.user_info.user_nickname,
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"konw_time": int(time.time()),
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}
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old_value = await person_info_manager.get_value(person_id, "relationship_value")
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old_value = self.ensure_float(old_value, person_id)
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if old_value > 1000:
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old_value = 1000
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elif old_value < -1000:
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old_value = -1000
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value = valuedict[label]
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if old_value >= 0:
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if valuedict[label] >= 0 and stancedict[stance] != 2:
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value = value * math.cos(math.pi * old_value / 2000)
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if old_value > 500:
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rdict = await person_info_manager.get_specific_value_list("relationship_value", lambda x: x > 700)
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high_value_count = len(rdict)
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if old_value > 700:
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value *= 3 / (high_value_count + 2) # 排除自己
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else:
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value *= 3 / (high_value_count + 3)
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elif valuedict[label] < 0 and stancedict[stance] != 0:
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value = value * math.exp(old_value / 2000)
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else:
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value = 0
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elif old_value < 0:
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if valuedict[label] >= 0 and stancedict[stance] != 2:
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value = value * math.exp(old_value / 2000)
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elif valuedict[label] < 0 and stancedict[stance] != 0:
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value = value * math.cos(math.pi * old_value / 2000)
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else:
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value = 0
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self.positive_feedback_sys(label, stance)
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value = self.mood_feedback(value)
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level_num = self.calculate_level_num(old_value + value)
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relationship_level = ["厌恶", "冷漠", "一般", "友好", "喜欢", "暧昧"]
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logger.info(
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f"用户: {chat_stream.user_info.user_nickname}"
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f"当前关系: {relationship_level[level_num]}, "
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f"关系值: {old_value:.2f}, "
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f"当前立场情感: {stance}-{label}, "
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f"变更: {value:+.5f}"
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)
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await person_info_manager.update_one_field(person_id, "relationship_value", old_value + value, data)
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return chat_stream.user_info.user_nickname, value, relationship_level[level_num]
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async def build_relationship_info(self, person, is_id: bool = False) -> str:
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if is_id:
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person_id = person
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else:
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# print(f"person: {person}")
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person_id = person_info_manager.get_person_id(person[0], person[1])
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person_name = await person_info_manager.get_value(person_id, "person_name")
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# print(f"person_name: {person_name}")
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relationship_value = await person_info_manager.get_value(person_id, "relationship_value")
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level_num = self.calculate_level_num(relationship_value)
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relation_value_prompt = ""
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if level_num == 0 or level_num == 5:
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relationship_level = ["厌恶", "冷漠以对", "认识", "友好对待", "喜欢", "暧昧"]
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relation_prompt2_list = [
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"忽视的回应",
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"冷淡回复",
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"保持理性",
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"愿意回复",
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"积极回复",
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"友善和包容的回复",
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]
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relation_value_prompt = (
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f"你{relationship_level[level_num]}{person_name}，打算{relation_prompt2_list[level_num]}。"
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)
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elif level_num == 2:
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relation_value_prompt = ""
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else:
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if random.random() < 0.6:
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relationship_level = ["厌恶", "冷漠以对", "认识", "友好对待", "喜欢", "暧昧"]
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relation_prompt2_list = [
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"忽视的回应",
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"冷淡回复",
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"保持理性",
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"愿意回复",
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"积极回复",
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"友善和包容的回复",
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]
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relation_value_prompt = (
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f"你{relationship_level[level_num]}{person_name}，打算{relation_prompt2_list[level_num]}。"
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)
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else:
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relation_value_prompt = ""
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if relation_value_prompt:
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nickname_str = await person_info_manager.get_value(person_id, "nickname")
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platform = await person_info_manager.get_value(person_id, "platform")
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relation_prompt = f"{relation_value_prompt}，ta在{platform}上的昵称是{nickname_str}。\n"
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else:
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relation_prompt = ""
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person_name_reason = await person_info_manager.get_value(person_id, "person_name_reason")
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if person_name_reason:
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relation_prompt += f"ta的昵称{person_name}的由来是：{person_name_reason}。\n"
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person_impression = await person_info_manager.get_value(person_id, "person_impression")
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if person_impression:
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relation_prompt += f"ta的印象是：{person_impression}。\n"
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return relation_prompt
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@staticmethod
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def calculate_level_num(relationship_value) -> int:
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"""关系等级计算"""
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if -1000 <= relationship_value < -227:
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level_num = 0
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elif -227 <= relationship_value < -73:
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level_num = 1
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elif -73 <= relationship_value < 227:
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level_num = 2
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elif 227 <= relationship_value < 587:
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level_num = 3
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elif 587 <= relationship_value < 900:
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level_num = 4
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elif 900 <= relationship_value <= 1000:
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level_num = 5
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else:
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level_num = 5 if relationship_value > 1000 else 0
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return level_num
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async def update_person_impression(self, person_id, chat_id, reason, timestamp):
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"""更新用户印象
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Args:
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person_id: 用户ID
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chat_id: 聊天ID
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reason: 更新原因
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timestamp: 时间戳
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"""
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# 获取现有印象和用户信息
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person_name = await person_info_manager.get_value(person_id, "person_name")
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nickname = await person_info_manager.get_value(person_id, "nickname")
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old_impression = await person_info_manager.get_value(person_id, "person_impression")
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user_id = await person_info_manager.get_value(person_id, "user_id")
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logger.debug(f"更新印象的person_id: {person_id}, chat_id: {chat_id}, reason: {reason}, timestamp: {timestamp}, user_id: {user_id}")
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# 获取时间戳前后的消息
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messages_before = get_raw_msg_by_timestamp_with_chat_users(
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chat_id=chat_id,
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timestamp_start=timestamp - 3600, # 前1小时
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timestamp_end=timestamp,
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person_ids=[user_id],
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limit=30,
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limit_mode="latest"
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)
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messages_after = get_raw_msg_by_timestamp_with_chat_users(
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chat_id=chat_id,
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timestamp_start=timestamp,
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timestamp_end=timestamp + 3600, # 后1小时
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person_ids=[user_id],
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limit=30,
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limit_mode="earliest"
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)
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# 合并消息并按时间排序
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user_messages = messages_before + messages_after
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user_messages.sort(key=lambda x: x["time"])
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# print(f"user_messages: {user_messages}")
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# 构建可读消息
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readable_messages = await build_readable_messages(
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messages=user_messages,
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replace_bot_name=True,
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timestamp_mode="relative",
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truncate=False
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)
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# 使用LLM总结印象
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prompt = f"""基于以下信息，总结对{person_name}(昵称:{nickname})的印象：
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原因：{reason}
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历史印象：{old_impression if old_impression else '无'}
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最近发言：
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{readable_messages}
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请用简洁的语言总结对这个人的印象，不超过200字。"""
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new_impression, _ = await self.relationship_llm.generate_response_async(prompt=prompt)
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logger.debug(f"新印象prompt：{prompt}")
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logger.info(f"新印象：{new_impression}")
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# 合并新旧印象
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if old_impression:
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merge_prompt = f"""请将以下两段印象合并，形成一段连贯的描述：
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旧印象：{old_impression}
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新印象：{new_impression}
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请用简洁的语言合并这两段印象，不超过200字。"""
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final_impression, _ = await self.relationship_llm.generate_response_async(prompt=merge_prompt)
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logger.debug(f"合并印象prompt：{merge_prompt}")
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logger.info(f"合并印象：{final_impression}")
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else:
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final_impression = new_impression
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# 更新到数据库
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await person_info_manager.update_one_field(person_id, "person_impression", final_impression)
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return final_impression
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relationship_manager = RelationshipManager()
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