remove：无用代码
This commit is contained in:
SengokuCola
@@ -1,15 +1,10 @@
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from datetime import datetime
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from typing import Dict, Optional, Union
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from typing import Optional, Union
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import asyncio
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import hashlib
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import json
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import math
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import random
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import time
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from json_repair import repair_json
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from sqlmodel import col, select
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from src.chat.message_receive.chat_manager import chat_manager as _chat_manager
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@@ -19,15 +14,10 @@ from src.common.database.database_model import PersonInfo
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from src.common.logger import get_logger
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from src.config.config import global_config
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from src.services.memory_service import memory_service
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from src.services.llm_service import LLMServiceClient
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logger = get_logger("person_info")
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relation_selection_model = LLMServiceClient(
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task_name="utils", request_type="relation_selection"
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)
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def _to_group_cardname_records(group_cardname_json: Optional[str]) -> list[dict[str, str]]:
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"""将数据库中的群名片 JSON 转换为 `Person` 内部使用的结构。
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@@ -133,50 +123,6 @@ def is_person_known(
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return False
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def get_category_from_memory(memory_point: str) -> Optional[str]:
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"""从记忆点中获取分类"""
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# 按照最左边的:符号进行分割，返回分割后的第一个部分作为分类
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if not isinstance(memory_point, str):
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return None
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parts = memory_point.split(":", 1)
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return parts[0].strip() if len(parts) > 1 else None
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def get_weight_from_memory(memory_point: str) -> float:
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"""从记忆点中获取权重"""
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# 按照最右边的:符号进行分割，返回分割后的最后一个部分作为权重
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if not isinstance(memory_point, str):
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return -math.inf
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parts = memory_point.rsplit(":", 1)
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if len(parts) <= 1:
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return -math.inf
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try:
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return float(parts[-1].strip())
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except Exception:
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return -math.inf
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def get_memory_content_from_memory(memory_point: str) -> str:
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"""从记忆点中获取记忆内容"""
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# 按:进行分割，去掉第一段和最后一段，返回中间部分作为记忆内容
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if not isinstance(memory_point, str):
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return ""
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parts = memory_point.split(":")
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return ":".join(parts[1:-1]).strip() if len(parts) > 2 else ""
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def extract_categories_from_response(response: str) -> list[str]:
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"""从response中提取所有<>包裹的内容"""
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if not isinstance(response, str):
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return []
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import re
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pattern = r"<([^<>]+)>"
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matches = re.findall(pattern, response)
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return matches
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def calculate_string_similarity(s1: str, s2: str) -> float:
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"""
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计算两个字符串的相似度
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@@ -430,31 +376,6 @@ class Person:
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return deleted_count
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def get_all_category(self):
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category_list = []
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for memory in self.memory_points:
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if memory is None:
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continue
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category = get_category_from_memory(memory)
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if category and category not in category_list:
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category_list.append(category)
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return category_list
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def get_memory_list_by_category(self, category: str):
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memory_list = []
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for memory in self.memory_points:
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if memory is None:
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continue
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if get_category_from_memory(memory) == category:
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memory_list.append(memory)
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return memory_list
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def get_random_memory_by_category(self, category: str, num: int = 1):
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memory_list = self.get_memory_list_by_category(category)
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if len(memory_list) < num:
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return memory_list
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return random.sample(memory_list, num)
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def add_group_nick_name(self, group_id: str, group_nick_name: str):
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"""
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添加或更新群昵称
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@@ -584,251 +505,6 @@ class Person:
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except Exception as e:
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logger.error(f"同步用户 {self.person_id} 信息到数据库时出错: {e}")
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async def build_relationship(self, chat_content: str = "", info_type=""):
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if not self.is_known:
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return ""
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# 构建points文本
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nickname_str = ""
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if self.person_name != self.nickname:
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nickname_str = f"(ta在{self.platform}上的昵称是{self.nickname})"
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relation_info = ""
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points_text = ""
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category_list = self.get_all_category()
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if chat_content:
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prompt = f"""当前聊天内容：
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{chat_content}
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分类列表：
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{category_list}
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**要求**：请你根据当前聊天内容，从以下分类中选择一个与聊天内容相关的分类，并用<>包裹输出，不要输出其他内容，不要输出引号或[]，严格用<>包裹：
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例如:
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<分类1><分类2><分类3>......
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如果没有相关的分类，请输出<none>"""
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generation_result = await relation_selection_model.generate_response(prompt)
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response = generation_result.response
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# print(prompt)
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# print(response)
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category_list = extract_categories_from_response(response)
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if "none" not in category_list:
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for category in category_list:
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random_memory = self.get_random_memory_by_category(category, 2)
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if random_memory:
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random_memory_str = "\n".join(
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[get_memory_content_from_memory(memory) for memory in random_memory]
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)
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points_text = f"有关 {category} 的内容：{random_memory_str}"
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break
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elif info_type:
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prompt = f"""你需要获取用户{self.person_name}的 **{info_type}** 信息。
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现有信息类别列表：
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{category_list}
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**要求**：请你根据**{info_type}**，从以下分类中选择一个与**{info_type}**相关的分类，并用<>包裹输出，不要输出其他内容，不要输出引号或[]，严格用<>包裹：
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例如:
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<分类1><分类2><分类3>......
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如果没有相关的分类，请输出<none>"""
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generation_result = await relation_selection_model.generate_response(prompt)
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response = generation_result.response
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# print(prompt)
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# print(response)
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category_list = extract_categories_from_response(response)
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if "none" not in category_list:
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for category in category_list:
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random_memory = self.get_random_memory_by_category(category, 3)
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if random_memory:
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random_memory_str = "\n".join(
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[get_memory_content_from_memory(memory) for memory in random_memory]
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)
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points_text = f"有关 {category} 的内容：{random_memory_str}"
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break
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else:
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for category in category_list:
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random_memory = self.get_random_memory_by_category(category, 1)[0]
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if random_memory:
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points_text = f"有关 {category} 的内容：{get_memory_content_from_memory(random_memory)}"
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break
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points_info = ""
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if points_text:
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points_info = f"你还记得有关{self.person_name}的内容：{points_text}"
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if not (nickname_str or points_info):
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return ""
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relation_info = f"{self.person_name}:{nickname_str}{points_info}"
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return relation_info
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class PersonInfoManager:
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def __init__(self):
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self.person_name_list = {}
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self.qv_name_llm = LLMServiceClient(
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task_name="utils", request_type="relation.qv_name"
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)
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try:
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with get_db_session() as _:
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pass
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except Exception as e:
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logger.error(f"数据库连接或 PersonInfo 表创建失败: {e}")
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# 初始化时读取所有person_name
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try:
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with get_db_session() as session:
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statement = select(PersonInfo.person_id, PersonInfo.person_name).where(
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col(PersonInfo.person_name).is_not(None)
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)
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for person_id, person_name in session.exec(statement).all():
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if person_name:
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self.person_name_list[person_id] = person_name
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logger.debug(f"已加载 {len(self.person_name_list)} 个用户名称")
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except Exception as e:
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logger.error(f"加载 person_name_list 失败: {e}")
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@staticmethod
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def _extract_json_from_text(text: str) -> Dict[str, str]:
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"""从文本中提取JSON数据的高容错方法"""
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try:
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fixed_json = repair_json(text)
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if isinstance(fixed_json, str):
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parsed_json = json.loads(fixed_json)
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else:
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parsed_json = fixed_json
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if isinstance(parsed_json, list) and parsed_json:
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parsed_json = parsed_json[0]
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if isinstance(parsed_json, dict):
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return parsed_json
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except Exception as e:
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logger.warning(f"JSON提取失败: {e}")
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logger.warning(f"无法从文本中提取有效的JSON字典: {text}")
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logger.info(f"文本: {text}")
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return {"nickname": "", "reason": ""}
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async def _generate_unique_person_name(self, base_name: str) -> str:
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"""生成唯一的 person_name，如果存在重复则添加数字后缀"""
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# 处理空昵称的情况
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if not base_name or base_name.isspace():
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base_name = "空格"
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# 检查基础名称是否已存在
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if base_name not in self.person_name_list.values():
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return base_name
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# 如果存在，添加数字后缀
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counter = 1
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while True:
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new_name = f"{base_name}[{counter}]"
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if new_name not in self.person_name_list.values():
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return new_name
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counter += 1
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async def qv_person_name(
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self, person_id: str, user_nickname: str, user_cardname: str, user_avatar: str, request: str = ""
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):
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"""给某个用户取名"""
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if not person_id:
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logger.debug("取名失败：person_id不能为空")
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return None
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person = Person(person_id=person_id)
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old_name = person.person_name
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old_reason = person.name_reason
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max_retries = 8
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current_try = 0
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existing_names_str = ""
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current_name_set = set(self.person_name_list.values())
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while current_try < max_retries:
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bot_name = global_config.bot.nickname
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qv_name_prompt = f"你是{bot_name}，一个伪装成人类的AI，你不能让别人发现这一点，"
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qv_name_prompt += f"现在你想给一个用户取一个昵称，用户的昵称是{user_nickname}，"
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qv_name_prompt += f"用户的群昵称名是{user_cardname}，"
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if user_avatar:
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qv_name_prompt += f"用户的头像是{user_avatar}，"
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if old_name:
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qv_name_prompt += f"你之前叫他{old_name}，是因为{old_reason}，"
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qv_name_prompt += f"\n其他取名的要求是：{request}，不要太浮夸，简短，"
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qv_name_prompt += "\n请根据以上用户信息，想想你叫他什么比较好，不要太浮夸，请最好使用用户的昵称或群昵称原文，可以稍作修改，优先使用原文。优先使用用户的昵称或者群昵称原文。"
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if existing_names_str:
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qv_name_prompt += f"\n请注意，以下名称已被你尝试过或已知存在，请避免：{existing_names_str}。\n"
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if len(current_name_set) < 50 and current_name_set:
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qv_name_prompt += f"已知的其他昵称有: {', '.join(list(current_name_set)[:10])}等。\n"
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qv_name_prompt += "请用json给出你的想法，并给出理由，示例如下："
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qv_name_prompt += """{
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"nickname": "昵称",
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"reason": "理由"
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}"""
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generation_result = await self.qv_name_llm.generate_response(qv_name_prompt)
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response = generation_result.response
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# logger.info(f"取名提示词：{qv_name_prompt}\n取名回复：{response}")
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result = self._extract_json_from_text(response)
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if not result or not result.get("nickname"):
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logger.error("生成的昵称为空或结果格式不正确，重试中...")
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current_try += 1
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continue
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generated_nickname = result["nickname"]
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is_duplicate = False
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if generated_nickname in current_name_set:
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is_duplicate = True
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logger.info(f"尝试给用户{user_nickname} {person_id} 取名，但是 {generated_nickname} 已存在，重试中...")
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else:
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def _db_check_name_exists_sync(name_to_check):
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with get_db_session() as session:
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statement = select(PersonInfo.person_id).where(col(PersonInfo.person_name) == name_to_check)
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return session.exec(statement).first() is not None
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if await asyncio.to_thread(_db_check_name_exists_sync, generated_nickname):
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is_duplicate = True
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current_name_set.add(generated_nickname)
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if not is_duplicate:
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person.person_name = generated_nickname
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person.name_reason = result.get("reason", "未提供理由")
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person.sync_to_database()
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logger.info(
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f"成功给用户{user_nickname} {person_id} 取名 {generated_nickname}，理由：{result.get('reason', '未提供理由')}"
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)
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self.person_name_list[person_id] = generated_nickname
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return result
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else:
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if existing_names_str:
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existing_names_str += "、"
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existing_names_str += generated_nickname
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logger.debug(f"生成的昵称 {generated_nickname} 已存在，重试中...")
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current_try += 1
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# 如果多次尝试后仍未成功，使用唯一的 user_nickname 作为默认值
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unique_nickname = await self._generate_unique_person_name(user_nickname)
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logger.warning(f"在{max_retries}次尝试后未能生成唯一昵称，使用默认昵称 {unique_nickname}")
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person.person_name = unique_nickname
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person.name_reason = "使用用户原始昵称作为默认值"
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person.sync_to_database()
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self.person_name_list[person_id] = unique_nickname
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return {"nickname": unique_nickname, "reason": "使用用户原始昵称作为默认值"}
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person_info_manager = PersonInfoManager()
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async def store_person_memory_from_answer(person_name: str, memory_content: str, chat_id: str) -> None:
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"""将人物事实写入长期记忆系统。
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Block a user