mirror of https://github.com/Mai-with-u/MaiBot.git
443 lines
17 KiB
Python
443 lines
17 KiB
Python
from typing import Optional
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import asyncio
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from src.llm_models.utils_model import LLMRequest
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from .personality import Personality
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from .identity import Identity
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from .expression_style import PersonalityExpression
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import random
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import json
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import os
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import hashlib
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from rich.traceback import install
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from src.common.logger import get_logger
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from src.person_info.person_info import get_person_info_manager
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from src.config.config import global_config
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install(extra_lines=3)
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logger = get_logger("individuality")
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class Individuality:
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"""个体特征管理类"""
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def __init__(self):
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# 正常初始化实例属性
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self.personality: Optional[Personality] = None
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self.identity: Optional[Identity] = None
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self.express_style: PersonalityExpression = PersonalityExpression()
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self.name = ""
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self.bot_person_id = ""
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self.meta_info_file_path = "data/personality/meta.json"
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self.model = LLMRequest(
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model=global_config.model.utils,
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request_type="individuality.compress",
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)
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async def initialize(
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self,
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bot_nickname: str,
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personality_core: str,
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personality_sides: list,
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identity_detail: list,
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) -> None:
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"""初始化个体特征
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Args:
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bot_nickname: 机器人昵称
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personality_core: 人格核心特点
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personality_sides: 人格侧面描述
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identity_detail: 身份细节描述
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"""
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logger.info("正在初始化个体特征")
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person_info_manager = get_person_info_manager()
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self.bot_person_id = person_info_manager.get_person_id("system", "bot_id")
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self.name = bot_nickname
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# 检查配置变化，如果变化则清空
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await self._check_config_and_clear_if_changed(
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bot_nickname, personality_core, personality_sides, identity_detail
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)
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# 初始化人格
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self.personality = Personality.initialize(
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bot_nickname=bot_nickname, personality_core=personality_core, personality_sides=personality_sides
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)
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# 初始化身份
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self.identity = Identity(identity_detail=identity_detail)
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logger.info("正在将所有人设写入impression")
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# 将所有人设写入impression
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impression_parts = []
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if personality_core:
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impression_parts.append(f"核心人格: {personality_core}")
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if personality_sides:
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impression_parts.append(f"人格侧面: {'、'.join(personality_sides)}")
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if identity_detail:
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impression_parts.append(f"身份: {'、'.join(identity_detail)}")
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logger.info(f"impression_parts: {impression_parts}")
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impression_text = "。".join(impression_parts)
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if impression_text:
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impression_text += "。"
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if impression_text:
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update_data = {
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"platform": "system",
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"user_id": "bot_id",
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"person_name": self.name,
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"nickname": self.name,
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}
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await person_info_manager.update_one_field(
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self.bot_person_id, "impression", impression_text, data=update_data
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)
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logger.info("已将完整人设更新到bot的impression中")
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# 创建压缩版本的short_impression
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asyncio.create_task(self._create_compressed_impression(personality_core, personality_sides, identity_detail))
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asyncio.create_task(self.express_style.extract_and_store_personality_expressions())
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def to_dict(self) -> dict:
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"""将个体特征转换为字典格式"""
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return {
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"personality": self.personality.to_dict() if self.personality else None,
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"identity": self.identity.to_dict() if self.identity else None,
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}
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@classmethod
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def from_dict(cls, data: dict) -> "Individuality":
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"""从字典创建个体特征实例"""
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instance = cls()
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if data.get("personality"):
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instance.personality = Personality.from_dict(data["personality"])
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if data.get("identity"):
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instance.identity = Identity.from_dict(data["identity"])
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return instance
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def get_personality_prompt(self, level: int, x_person: int = 2) -> str:
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"""
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获取人格特征的prompt
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Args:
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level (int): 详细程度 (1: 核心, 2: 核心+随机侧面, 3: 核心+所有侧面)
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x_person (int, optional): 人称代词 (0: 无人称, 1: 我, 2: 你). 默认为 2.
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Returns:
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str: 生成的人格prompt字符串
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"""
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if x_person not in [0, 1, 2]:
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return "无效的人称代词，请使用 0 (无人称), 1 (我) 或 2 (你)。"
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if not self.personality:
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return "人格特征尚未初始化。"
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if x_person == 2:
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p_pronoun = "你"
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prompt_personality = f"{p_pronoun}{self.personality.personality_core}"
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elif x_person == 1:
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p_pronoun = "我"
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prompt_personality = f"{p_pronoun}{self.personality.personality_core}"
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else: # x_person == 0
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# 对于无人称，直接描述核心特征
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prompt_personality = f"{self.personality.personality_core}"
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# 根据level添加人格侧面
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if level >= 2 and self.personality.personality_sides:
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personality_sides = list(self.personality.personality_sides)
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random.shuffle(personality_sides)
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if level == 2:
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prompt_personality += f"，有时也会{personality_sides[0]}"
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elif level == 3:
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sides_str = "、".join(personality_sides)
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prompt_personality += f"，有时也会{sides_str}"
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prompt_personality += "。"
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return prompt_personality
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def get_identity_prompt(self, level: int, x_person: int = 2) -> str:
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"""
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获取身份特征的prompt
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Args:
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level (int): 详细程度 (1: 随机细节, 2: 所有细节, 3: 同2)
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x_person (int, optional): 人称代词 (0: 无人称, 1: 我, 2: 你). 默认为 2.
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Returns:
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str: 生成的身份prompt字符串
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"""
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if x_person not in [0, 1, 2]:
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return "无效的人称代词，请使用 0 (无人称), 1 (我) 或 2 (你)。"
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if not self.identity:
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return "身份特征尚未初始化。"
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if x_person == 2:
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i_pronoun = "你"
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elif x_person == 1:
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i_pronoun = "我"
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else: # x_person == 0
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i_pronoun = "" # 无人称
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identity_parts = []
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# 根据level添加身份细节
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if level >= 1 and self.identity.identity_detail:
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identity_detail = list(self.identity.identity_detail)
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random.shuffle(identity_detail)
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if level == 1:
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identity_parts.append(f"{identity_detail[0]}")
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elif level >= 2:
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details_str = "、".join(identity_detail)
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identity_parts.append(f"{details_str}")
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if identity_parts:
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details_str = "，".join(identity_parts)
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if x_person in [1, 2]:
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return f"{i_pronoun}，{details_str}。"
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else: # x_person == 0
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# 无人称时，直接返回细节，不加代词和开头的逗号
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return f"{details_str}。"
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else:
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if x_person in [1, 2]:
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return f"{i_pronoun}的身份信息不完整。"
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else: # x_person == 0
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return "身份信息不完整。"
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def get_prompt(self, level: int, x_person: int = 2) -> str:
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"""
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获取合并的个体特征prompt
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Args:
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level (int): 详细程度 (1: 核心/随机细节, 2: 核心+随机侧面/全部细节, 3: 全部)
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x_person (int, optional): 人称代词 (0: 无人称, 1: 我, 2: 你). 默认为 2.
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Returns:
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str: 生成的合并prompt字符串
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"""
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if x_person not in [0, 1, 2]:
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return "无效的人称代词，请使用 0 (无人称), 1 (我) 或 2 (你)。"
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if not self.personality or not self.identity:
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return "个体特征尚未完全初始化。"
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# 调用新的独立方法
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prompt_personality = self.get_personality_prompt(level, x_person)
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prompt_identity = self.get_identity_prompt(level, x_person)
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# 移除可能存在的错误信息，只合并有效的 prompt
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valid_prompts = []
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if "尚未初始化" not in prompt_personality and "无效的人称" not in prompt_personality:
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valid_prompts.append(prompt_personality)
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if (
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"尚未初始化" not in prompt_identity
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and "无效的人称" not in prompt_identity
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and "信息不完整" not in prompt_identity
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):
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# 从身份 prompt 中移除代词和句号，以便更好地合并
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identity_content = prompt_identity
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if x_person == 2 and identity_content.startswith("你，"):
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identity_content = identity_content[2:]
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elif x_person == 1 and identity_content.startswith("我，"):
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identity_content = identity_content[2:]
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# 对于 x_person == 0，身份提示不带前缀，无需移除
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if identity_content.endswith("。"):
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identity_content = identity_content[:-1]
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valid_prompts.append(identity_content)
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# --- 合并 Prompt ---
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final_prompt = " ".join(valid_prompts)
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return final_prompt.strip()
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def get_traits(self, factor):
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"""
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获取个体特征的特质
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"""
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if factor == "openness":
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return self.personality.openness
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elif factor == "conscientiousness":
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return self.personality.conscientiousness
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elif factor == "extraversion":
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return self.personality.extraversion
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elif factor == "agreeableness":
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return self.personality.agreeableness
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elif factor == "neuroticism":
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return self.personality.neuroticism
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return None
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def _get_config_hash(
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self, bot_nickname: str, personality_core: str, personality_sides: list, identity_detail: list
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) -> str:
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"""获取当前personality和identity配置的哈希值"""
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config_data = {
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"nickname": bot_nickname,
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"personality_core": personality_core,
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"personality_sides": sorted(personality_sides),
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"identity_detail": sorted(identity_detail),
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}
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config_str = json.dumps(config_data, sort_keys=True)
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return hashlib.md5(config_str.encode("utf-8")).hexdigest()
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async def _check_config_and_clear_if_changed(
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self, bot_nickname: str, personality_core: str, personality_sides: list, identity_detail: list
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):
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"""检查配置是否发生变化，如果变化则清空info_list"""
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person_info_manager = get_person_info_manager()
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current_hash = self._get_config_hash(bot_nickname, personality_core, personality_sides, identity_detail)
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meta_info = self._load_meta_info()
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stored_hash = meta_info.get("config_hash")
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if current_hash != stored_hash:
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logger.info("检测到人格配置发生变化，将清空原有的关键词缓存。")
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# 清空数据库中的info_list
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update_data = {
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"platform": "system",
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"user_id": "bot_id",
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"person_name": self.name,
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"nickname": self.name,
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}
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await person_info_manager.update_one_field(self.bot_person_id, "info_list", [], data=update_data)
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# 更新元信息文件，重置计数器
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new_meta_info = {"config_hash": current_hash}
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self._save_meta_info(new_meta_info)
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def _load_meta_info(self) -> dict:
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"""从JSON文件中加载元信息"""
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if os.path.exists(self.meta_info_file_path):
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try:
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with open(self.meta_info_file_path, "r", encoding="utf-8") as f:
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return json.load(f)
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except (json.JSONDecodeError, IOError) as e:
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logger.error(f"读取meta_info文件失败: {e}, 将创建新文件。")
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return {}
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return {}
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def _save_meta_info(self, meta_info: dict):
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"""将元信息保存到JSON文件"""
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try:
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os.makedirs(os.path.dirname(self.meta_info_file_path), exist_ok=True)
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with open(self.meta_info_file_path, "w", encoding="utf-8") as f:
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json.dump(meta_info, f, ensure_ascii=False, indent=2)
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except IOError as e:
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logger.error(f"保存meta_info文件失败: {e}")
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async def get_keyword_info(self, keyword: str) -> str:
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"""获取指定关键词的信息
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Args:
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keyword: 关键词
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Returns:
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str: 随机选择的一条信息，如果没有则返回空字符串
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"""
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person_info_manager = get_person_info_manager()
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info_list_json = await person_info_manager.get_value(self.bot_person_id, "info_list")
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if info_list_json:
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try:
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# get_value might return a pre-deserialized list if it comes from a cache,
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# or a JSON string if it comes from DB.
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info_list = json.loads(info_list_json) if isinstance(info_list_json, str) else info_list_json
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for item in info_list:
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if isinstance(item, dict) and item.get("info_type") == keyword:
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return item.get("info_content", "")
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except (json.JSONDecodeError, TypeError):
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logger.error(f"解析info_list失败: {info_list_json}")
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return ""
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return ""
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async def get_all_keywords(self) -> list:
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"""获取所有已缓存的关键词列表"""
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person_info_manager = get_person_info_manager()
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info_list_json = await person_info_manager.get_value(self.bot_person_id, "info_list")
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keywords = []
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if info_list_json:
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try:
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info_list = json.loads(info_list_json) if isinstance(info_list_json, str) else info_list_json
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for item in info_list:
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if isinstance(item, dict) and "info_type" in item:
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keywords.append(item["info_type"])
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except (json.JSONDecodeError, TypeError):
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logger.error(f"解析info_list失败: {info_list_json}")
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return keywords
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async def _create_compressed_impression(
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self, personality_core: str, personality_sides: list, identity_detail: list
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) -> str:
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"""使用LLM创建压缩版本的impression
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Args:
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personality_core: 核心人格
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personality_sides: 人格侧面列表
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identity_detail: 身份细节列表
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Returns:
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str: 压缩后的impression文本
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"""
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# 核心人格保持不变
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compressed_parts = []
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if personality_core:
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compressed_parts.append(f"{personality_core}")
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# 准备需要压缩的内容
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content_to_compress = []
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if personality_sides:
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content_to_compress.append(f"人格特质: {'、'.join(personality_sides)}")
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if identity_detail:
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content_to_compress.append(f"身份背景: {'、'.join(identity_detail)}")
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if not content_to_compress:
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# 如果没有需要压缩的内容，直接返回核心人格
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result = "。".join(compressed_parts)
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return result + "。" if result else ""
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# 使用LLM压缩其他内容
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try:
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compress_content = "、".join(content_to_compress)
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prompt = f"""请将以下人设信息进行简洁压缩，保留主要内容，用简练的中文表达：
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{compress_content}
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要求：
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1. 保持原意不变，尽量使用原文
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2. 尽量简洁，不超过30字
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3. 直接输出压缩后的内容，不要解释"""
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response, (_, _) = await self.model.generate_response_async(
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prompt=prompt,
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)
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if response.strip():
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compressed_parts.append(response.strip())
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logger.info(f"精简人格侧面: {response.strip()}")
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else:
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logger.error(f"使用LLM压缩人设时出错: {response}")
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except Exception as e:
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logger.error(f"使用LLM压缩人设时出错: {e}")
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result = "。".join(compressed_parts)
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# 更新short_impression字段
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if result:
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person_info_manager = get_person_info_manager()
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await person_info_manager.update_one_field(self.bot_person_id, "short_impression", result)
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logger.info("已将压缩人设更新到bot的short_impression中")
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individuality = None
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def get_individuality():
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global individuality
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if individuality is None:
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individuality = Individuality()
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return individuality
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