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