6659c60799
- 重构数据库初始化逻辑，添加防重入保护和更好的错误处理 - 优化插件组件注册系统的类型注解和代码结构 - 简化统计模块异常处理逻辑 - 移除插件管理器中的重载功能以简化代码 - 更新Pyright配置排除内置插件目录 - 修复权限管理器异步方法调用
887 lines
39 KiB
Python
887 lines
39 KiB
Python
"""SQLAlchemy数据库模型定义
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替换Peewee ORM，使用SQLAlchemy提供更好的连接池管理和错误恢复能力
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说明: 部分旧模型仍使用 `Column = Column(Type, ...)` 的经典风格。本文件开始逐步迁移到
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SQLAlchemy 2.0 推荐的带类型注解的声明式风格：
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field_name: Mapped[PyType] = mapped_column(Type, ...)
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这样 IDE / Pylance 能正确推断实例属性的真实 Python 类型，避免将其视为不可赋值的 Column 对象。
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当前仅对产生类型检查问题的模型 (BanUser) 进行了迁移，其余模型保持不变以减少一次性改动范围。
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"""
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import datetime
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import os
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import time
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from collections.abc import AsyncGenerator
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from contextlib import asynccontextmanager
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from typing import Any
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from sqlalchemy import Boolean, Column, DateTime, Float, Index, Integer, String, Text, text
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from sqlalchemy.ext.asyncio import AsyncSession, AsyncEngine, async_sessionmaker, create_async_engine
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from sqlalchemy.ext.declarative import declarative_base
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from sqlalchemy.orm import Mapped, mapped_column
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from src.common.database.connection_pool_manager import get_connection_pool_manager
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from src.common.logger import get_logger
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logger = get_logger("sqlalchemy_models")
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# 创建基类
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Base = declarative_base()
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# 全局异步引擎与会话工厂占位（延迟初始化）
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_engine: AsyncEngine | None = None
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_SessionLocal: async_sessionmaker[AsyncSession] | None = None
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async def enable_sqlite_wal_mode(engine):
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"""为 SQLite 启用 WAL 模式以提高并发性能"""
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try:
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async with engine.begin() as conn:
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# 启用 WAL 模式
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await conn.execute(text("PRAGMA journal_mode = WAL"))
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# 设置适中的同步级别，平衡性能和安全性
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await conn.execute(text("PRAGMA synchronous = NORMAL"))
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# 启用外键约束
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await conn.execute(text("PRAGMA foreign_keys = ON"))
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# 设置 busy_timeout，避免锁定错误
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await conn.execute(text("PRAGMA busy_timeout = 60000")) # 60秒
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logger.info("[SQLite] WAL 模式已启用，并发性能已优化")
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except Exception as e:
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logger.warning(f"[SQLite] 启用 WAL 模式失败: {e}，将使用默认配置")
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async def maintain_sqlite_database():
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"""定期维护 SQLite 数据库性能"""
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try:
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engine, SessionLocal = await initialize_database()
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if not engine:
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return
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async with engine.begin() as conn:
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# 检查并确保 WAL 模式仍然启用
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result = await conn.execute(text("PRAGMA journal_mode"))
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journal_mode = result.scalar()
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if journal_mode != "wal":
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await conn.execute(text("PRAGMA journal_mode = WAL"))
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logger.info("[SQLite] WAL 模式已重新启用")
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# 优化数据库性能
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await conn.execute(text("PRAGMA synchronous = NORMAL"))
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await conn.execute(text("PRAGMA busy_timeout = 60000"))
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await conn.execute(text("PRAGMA foreign_keys = ON"))
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# 定期清理（可选，根据需要启用）
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# await conn.execute(text("PRAGMA optimize"))
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logger.info("[SQLite] 数据库维护完成")
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except Exception as e:
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logger.warning(f"[SQLite] 数据库维护失败: {e}")
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def get_sqlite_performance_config():
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"""获取 SQLite 性能优化配置"""
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return {
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"journal_mode": "WAL", # 提高并发性能
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"synchronous": "NORMAL", # 平衡性能和安全性
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"busy_timeout": 60000, # 60秒超时
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"foreign_keys": "ON", # 启用外键约束
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"cache_size": -10000, # 10MB 缓存
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"temp_store": "MEMORY", # 临时存储使用内存
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"mmap_size": 268435456, # 256MB 内存映射
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}
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# MySQL兼容的字段类型辅助函数
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def get_string_field(max_length=255, **kwargs):
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"""
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根据数据库类型返回合适的字符串字段
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MySQL需要指定长度的VARCHAR用于索引，SQLite可以使用Text
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"""
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from src.config.config import global_config
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if global_config.database.database_type == "mysql":
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return String(max_length, **kwargs)
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else:
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return Text(**kwargs)
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class ChatStreams(Base):
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"""聊天流模型"""
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__tablename__ = "chat_streams"
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id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
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stream_id: Mapped[str] = mapped_column(get_string_field(64), nullable=False, unique=True, index=True)
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create_time: Mapped[float] = mapped_column(Float, nullable=False)
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group_platform: Mapped[str | None] = mapped_column(Text, nullable=True)
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group_id: Mapped[str | None] = mapped_column(get_string_field(100), nullable=True, index=True)
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group_name: Mapped[str | None] = mapped_column(Text, nullable=True)
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last_active_time: Mapped[float] = mapped_column(Float, nullable=False)
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platform: Mapped[str] = mapped_column(Text, nullable=False)
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user_platform: Mapped[str] = mapped_column(Text, nullable=False)
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user_id: Mapped[str] = mapped_column(get_string_field(100), nullable=False, index=True)
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user_nickname: Mapped[str] = mapped_column(Text, nullable=False)
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user_cardname: Mapped[str | None] = mapped_column(Text, nullable=True)
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energy_value: Mapped[float | None] = mapped_column(Float, nullable=True, default=5.0)
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sleep_pressure: Mapped[float | None] = mapped_column(Float, nullable=True, default=0.0)
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focus_energy: Mapped[float | None] = mapped_column(Float, nullable=True, default=0.5)
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# 动态兴趣度系统字段
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base_interest_energy: Mapped[float | None] = mapped_column(Float, nullable=True, default=0.5)
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message_interest_total: Mapped[float | None] = mapped_column(Float, nullable=True, default=0.0)
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message_count: Mapped[int | None] = mapped_column(Integer, nullable=True, default=0)
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action_count: Mapped[int | None] = mapped_column(Integer, nullable=True, default=0)
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reply_count: Mapped[int | None] = mapped_column(Integer, nullable=True, default=0)
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last_interaction_time: Mapped[float | None] = mapped_column(Float, nullable=True, default=None)
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consecutive_no_reply: Mapped[int | None] = mapped_column(Integer, nullable=True, default=0)
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# 消息打断系统字段
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interruption_count: Mapped[int | None] = mapped_column(Integer, nullable=True, default=0)
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__table_args__ = (
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Index("idx_chatstreams_stream_id", "stream_id"),
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Index("idx_chatstreams_user_id", "user_id"),
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Index("idx_chatstreams_group_id", "group_id"),
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)
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class LLMUsage(Base):
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"""LLM使用记录模型"""
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__tablename__ = "llm_usage"
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id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
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model_name: Mapped[str] = mapped_column(get_string_field(100), nullable=False, index=True)
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model_assign_name: Mapped[str] = mapped_column(get_string_field(100), index=True)
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model_api_provider: Mapped[str] = mapped_column(get_string_field(100), index=True)
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user_id: Mapped[str] = mapped_column(get_string_field(50), nullable=False, index=True)
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request_type: Mapped[str] = mapped_column(get_string_field(50), nullable=False, index=True)
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endpoint: Mapped[str] = mapped_column(Text, nullable=False)
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prompt_tokens: Mapped[int] = mapped_column(Integer, nullable=False)
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completion_tokens: Mapped[int] = mapped_column(Integer, nullable=False)
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time_cost: Mapped[float | None] = mapped_column(Float, nullable=True)
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total_tokens: Mapped[int] = mapped_column(Integer, nullable=False)
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cost: Mapped[float] = mapped_column(Float, nullable=False)
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status: Mapped[str] = mapped_column(Text, nullable=False)
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timestamp: Mapped[datetime.datetime] = mapped_column(DateTime, nullable=False, index=True, default=datetime.datetime.now)
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__table_args__ = (
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Index("idx_llmusage_model_name", "model_name"),
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Index("idx_llmusage_model_assign_name", "model_assign_name"),
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Index("idx_llmusage_model_api_provider", "model_api_provider"),
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Index("idx_llmusage_time_cost", "time_cost"),
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Index("idx_llmusage_user_id", "user_id"),
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Index("idx_llmusage_request_type", "request_type"),
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Index("idx_llmusage_timestamp", "timestamp"),
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)
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class Emoji(Base):
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"""表情包模型"""
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__tablename__ = "emoji"
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id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
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full_path: Mapped[str] = mapped_column(get_string_field(500), nullable=False, unique=True, index=True)
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format: Mapped[str] = mapped_column(Text, nullable=False)
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emoji_hash: Mapped[str] = mapped_column(get_string_field(64), nullable=False, index=True)
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description: Mapped[str] = mapped_column(Text, nullable=False)
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query_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
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is_registered: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
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is_banned: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
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emotion: Mapped[str | None] = mapped_column(Text, nullable=True)
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record_time: Mapped[float] = mapped_column(Float, nullable=False)
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register_time: Mapped[float | None] = mapped_column(Float, nullable=True)
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usage_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
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last_used_time: Mapped[float | None] = mapped_column(Float, nullable=True)
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__table_args__ = (
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Index("idx_emoji_full_path", "full_path"),
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Index("idx_emoji_hash", "emoji_hash"),
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)
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class Messages(Base):
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"""消息模型"""
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__tablename__ = "messages"
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id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
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message_id: Mapped[str] = mapped_column(get_string_field(100), nullable=False, index=True)
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time: Mapped[float] = mapped_column(Float, nullable=False)
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chat_id: Mapped[str] = mapped_column(get_string_field(64), nullable=False, index=True)
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reply_to: Mapped[str | None] = mapped_column(Text, nullable=True)
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interest_value: Mapped[float | None] = mapped_column(Float, nullable=True)
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key_words: Mapped[str | None] = mapped_column(Text, nullable=True)
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key_words_lite: Mapped[str | None] = mapped_column(Text, nullable=True)
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is_mentioned: Mapped[bool | None] = mapped_column(Boolean, nullable=True)
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# 从 chat_info 扁平化而来的字段
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chat_info_stream_id: Mapped[str] = mapped_column(Text, nullable=False)
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chat_info_platform: Mapped[str] = mapped_column(Text, nullable=False)
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chat_info_user_platform: Mapped[str] = mapped_column(Text, nullable=False)
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chat_info_user_id: Mapped[str] = mapped_column(Text, nullable=False)
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chat_info_user_nickname: Mapped[str] = mapped_column(Text, nullable=False)
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chat_info_user_cardname: Mapped[str | None] = mapped_column(Text, nullable=True)
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chat_info_group_platform: Mapped[str | None] = mapped_column(Text, nullable=True)
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chat_info_group_id: Mapped[str | None] = mapped_column(Text, nullable=True)
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chat_info_group_name: Mapped[str | None] = mapped_column(Text, nullable=True)
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chat_info_create_time: Mapped[float] = mapped_column(Float, nullable=False)
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chat_info_last_active_time: Mapped[float] = mapped_column(Float, nullable=False)
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# 从顶层 user_info 扁平化而来的字段
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user_platform: Mapped[str | None] = mapped_column(Text, nullable=True)
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user_id: Mapped[str | None] = mapped_column(get_string_field(100), nullable=True, index=True)
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user_nickname: Mapped[str | None] = mapped_column(Text, nullable=True)
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user_cardname: Mapped[str | None] = mapped_column(Text, nullable=True)
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processed_plain_text: Mapped[str | None] = mapped_column(Text, nullable=True)
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display_message: Mapped[str | None] = mapped_column(Text, nullable=True)
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memorized_times: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
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priority_mode: Mapped[str | None] = mapped_column(Text, nullable=True)
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priority_info: Mapped[str | None] = mapped_column(Text, nullable=True)
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additional_config: Mapped[str | None] = mapped_column(Text, nullable=True)
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is_emoji: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
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is_picid: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
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is_command: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
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is_notify: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
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# 兴趣度系统字段
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actions: Mapped[str | None] = mapped_column(Text, nullable=True)
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should_reply: Mapped[bool | None] = mapped_column(Boolean, nullable=True, default=False)
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should_act: Mapped[bool | None] = mapped_column(Boolean, nullable=True, default=False)
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__table_args__ = (
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Index("idx_messages_message_id", "message_id"),
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Index("idx_messages_chat_id", "chat_id"),
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Index("idx_messages_time", "time"),
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Index("idx_messages_user_id", "user_id"),
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Index("idx_messages_should_reply", "should_reply"),
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Index("idx_messages_should_act", "should_act"),
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)
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class ActionRecords(Base):
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"""动作记录模型"""
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__tablename__ = "action_records"
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id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
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action_id: Mapped[str] = mapped_column(get_string_field(100), nullable=False, index=True)
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time: Mapped[float] = mapped_column(Float, nullable=False)
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action_name: Mapped[str] = mapped_column(Text, nullable=False)
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action_data: Mapped[str] = mapped_column(Text, nullable=False)
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action_done: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
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action_build_into_prompt: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
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action_prompt_display: Mapped[str] = mapped_column(Text, nullable=False)
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chat_id: Mapped[str] = mapped_column(get_string_field(64), nullable=False, index=True)
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chat_info_stream_id: Mapped[str] = mapped_column(Text, nullable=False)
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chat_info_platform: Mapped[str] = mapped_column(Text, nullable=False)
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__table_args__ = (
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Index("idx_actionrecords_action_id", "action_id"),
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Index("idx_actionrecords_chat_id", "chat_id"),
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Index("idx_actionrecords_time", "time"),
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)
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class Images(Base):
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"""图像信息模型"""
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__tablename__ = "images"
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id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
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image_id: Mapped[str] = mapped_column(Text, nullable=False, default="")
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emoji_hash: Mapped[str] = mapped_column(get_string_field(64), nullable=False, index=True)
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description: Mapped[str | None] = mapped_column(Text, nullable=True)
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path: Mapped[str] = mapped_column(get_string_field(500), nullable=False, unique=True)
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count: Mapped[int] = mapped_column(Integer, nullable=False, default=1)
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timestamp: Mapped[float] = mapped_column(Float, nullable=False)
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type: Mapped[str] = mapped_column(Text, nullable=False)
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vlm_processed: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
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__table_args__ = (
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Index("idx_images_emoji_hash", "emoji_hash"),
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Index("idx_images_path", "path"),
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)
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class ImageDescriptions(Base):
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"""图像描述信息模型"""
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__tablename__ = "image_descriptions"
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id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
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type: Mapped[str] = mapped_column(Text, nullable=False)
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image_description_hash: Mapped[str] = mapped_column(get_string_field(64), nullable=False, index=True)
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description: Mapped[str] = mapped_column(Text, nullable=False)
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timestamp: Mapped[float] = mapped_column(Float, nullable=False)
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__table_args__ = (Index("idx_imagedesc_hash", "image_description_hash"),)
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class Videos(Base):
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"""视频信息模型"""
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__tablename__ = "videos"
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id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
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video_id: Mapped[str] = mapped_column(Text, nullable=False, default="")
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video_hash: Mapped[str] = mapped_column(get_string_field(64), nullable=False, index=True, unique=True)
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description: Mapped[str | None] = mapped_column(Text, nullable=True)
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count: Mapped[int] = mapped_column(Integer, nullable=False, default=1)
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timestamp: Mapped[float] = mapped_column(Float, nullable=False)
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vlm_processed: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
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# 视频特有属性
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duration: Mapped[float | None] = mapped_column(Float, nullable=True)
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frame_count: Mapped[int | None] = mapped_column(Integer, nullable=True)
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fps: Mapped[float | None] = mapped_column(Float, nullable=True)
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resolution: Mapped[str | None] = mapped_column(Text, nullable=True)
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file_size: Mapped[int | None] = mapped_column(Integer, nullable=True)
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__table_args__ = (
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Index("idx_videos_video_hash", "video_hash"),
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Index("idx_videos_timestamp", "timestamp"),
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)
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class OnlineTime(Base):
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"""在线时长记录模型"""
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__tablename__ = "online_time"
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id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
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timestamp: Mapped[str] = mapped_column(Text, nullable=False, default=str(datetime.datetime.now))
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duration: Mapped[int] = mapped_column(Integer, nullable=False)
|
||
start_timestamp: Mapped[datetime.datetime] = mapped_column(DateTime, nullable=False, default=datetime.datetime.now)
|
||
end_timestamp: Mapped[datetime.datetime] = mapped_column(DateTime, nullable=False, index=True)
|
||
|
||
__table_args__ = (Index("idx_onlinetime_end_timestamp", "end_timestamp"),)
|
||
|
||
|
||
class PersonInfo(Base):
|
||
"""人物信息模型"""
|
||
|
||
__tablename__ = "person_info"
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
person_id: Mapped[str] = mapped_column(get_string_field(100), nullable=False, unique=True, index=True)
|
||
person_name: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
name_reason: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
platform: Mapped[str] = mapped_column(Text, nullable=False)
|
||
user_id: Mapped[str] = mapped_column(get_string_field(50), nullable=False, index=True)
|
||
nickname: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
impression: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
short_impression: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
points: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
forgotten_points: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
info_list: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
know_times: Mapped[float | None] = mapped_column(Float, nullable=True)
|
||
know_since: Mapped[float | None] = mapped_column(Float, nullable=True)
|
||
last_know: Mapped[float | None] = mapped_column(Float, nullable=True)
|
||
attitude: Mapped[int | None] = mapped_column(Integer, nullable=True, default=50)
|
||
|
||
__table_args__ = (
|
||
Index("idx_personinfo_person_id", "person_id"),
|
||
Index("idx_personinfo_user_id", "user_id"),
|
||
)
|
||
|
||
|
||
class BotPersonalityInterests(Base):
|
||
"""机器人人格兴趣标签模型"""
|
||
|
||
__tablename__ = "bot_personality_interests"
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
personality_id: Mapped[str] = mapped_column(get_string_field(100), nullable=False, index=True)
|
||
personality_description: Mapped[str] = mapped_column(Text, nullable=False)
|
||
interest_tags: Mapped[str] = mapped_column(Text, nullable=False)
|
||
embedding_model: Mapped[str] = mapped_column(get_string_field(100), nullable=False, default="text-embedding-ada-002")
|
||
version: Mapped[int] = mapped_column(Integer, nullable=False, default=1)
|
||
last_updated: Mapped[datetime.datetime] = mapped_column(DateTime, nullable=False, default=datetime.datetime.now, index=True)
|
||
|
||
__table_args__ = (
|
||
Index("idx_botpersonality_personality_id", "personality_id"),
|
||
Index("idx_botpersonality_version", "version"),
|
||
Index("idx_botpersonality_last_updated", "last_updated"),
|
||
)
|
||
|
||
|
||
class Memory(Base):
|
||
"""记忆模型"""
|
||
|
||
__tablename__ = "memory"
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
memory_id: Mapped[str] = mapped_column(get_string_field(64), nullable=False, index=True)
|
||
chat_id: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
memory_text: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
keywords: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
create_time: Mapped[float | None] = mapped_column(Float, nullable=True)
|
||
last_view_time: Mapped[float | None] = mapped_column(Float, nullable=True)
|
||
|
||
__table_args__ = (Index("idx_memory_memory_id", "memory_id"),)
|
||
|
||
|
||
class Expression(Base):
|
||
"""表达风格模型"""
|
||
|
||
__tablename__ = "expression"
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
situation: Mapped[str] = mapped_column(Text, nullable=False)
|
||
style: Mapped[str] = mapped_column(Text, nullable=False)
|
||
count: Mapped[float] = mapped_column(Float, nullable=False)
|
||
last_active_time: Mapped[float] = mapped_column(Float, nullable=False)
|
||
chat_id: Mapped[str] = mapped_column(get_string_field(64), nullable=False, index=True)
|
||
type: Mapped[str] = mapped_column(Text, nullable=False)
|
||
create_date: Mapped[float | None] = mapped_column(Float, nullable=True)
|
||
|
||
__table_args__ = (Index("idx_expression_chat_id", "chat_id"),)
|
||
|
||
|
||
class ThinkingLog(Base):
|
||
"""思考日志模型"""
|
||
|
||
__tablename__ = "thinking_logs"
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
chat_id: Mapped[str] = mapped_column(get_string_field(64), nullable=False, index=True)
|
||
trigger_text: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
response_text: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
trigger_info_json: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
response_info_json: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
timing_results_json: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
chat_history_json: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
chat_history_in_thinking_json: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
chat_history_after_response_json: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
heartflow_data_json: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
reasoning_data_json: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
created_at: Mapped[datetime.datetime] = mapped_column(DateTime, nullable=False, default=datetime.datetime.now)
|
||
|
||
__table_args__ = (Index("idx_thinkinglog_chat_id", "chat_id"),)
|
||
|
||
|
||
class GraphNodes(Base):
|
||
"""记忆图节点模型"""
|
||
|
||
__tablename__ = "graph_nodes"
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
concept: Mapped[str] = mapped_column(get_string_field(255), nullable=False, unique=True, index=True)
|
||
memory_items: Mapped[str] = mapped_column(Text, nullable=False)
|
||
hash: Mapped[str] = mapped_column(Text, nullable=False)
|
||
weight: Mapped[float] = mapped_column(Float, nullable=False, default=1.0)
|
||
created_time: Mapped[float] = mapped_column(Float, nullable=False)
|
||
last_modified: Mapped[float] = mapped_column(Float, nullable=False)
|
||
|
||
__table_args__ = (Index("idx_graphnodes_concept", "concept"),)
|
||
|
||
|
||
class GraphEdges(Base):
|
||
"""记忆图边模型"""
|
||
|
||
__tablename__ = "graph_edges"
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
source: Mapped[str] = mapped_column(get_string_field(255), nullable=False, index=True)
|
||
target: Mapped[str] = mapped_column(get_string_field(255), nullable=False, index=True)
|
||
strength: Mapped[int] = mapped_column(Integer, nullable=False)
|
||
hash: Mapped[str] = mapped_column(Text, nullable=False)
|
||
created_time: Mapped[float] = mapped_column(Float, nullable=False)
|
||
last_modified: Mapped[float] = mapped_column(Float, nullable=False)
|
||
|
||
__table_args__ = (
|
||
Index("idx_graphedges_source", "source"),
|
||
Index("idx_graphedges_target", "target"),
|
||
)
|
||
|
||
|
||
class Schedule(Base):
|
||
"""日程模型"""
|
||
|
||
__tablename__ = "schedule"
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
date: Mapped[str] = mapped_column(get_string_field(10), nullable=False, unique=True, index=True)
|
||
schedule_data: Mapped[str] = mapped_column(Text, nullable=False)
|
||
created_at: Mapped[datetime.datetime] = mapped_column(DateTime, nullable=False, default=datetime.datetime.now)
|
||
updated_at: Mapped[datetime.datetime] = mapped_column(DateTime, nullable=False, default=datetime.datetime.now, onupdate=datetime.datetime.now)
|
||
|
||
__table_args__ = (Index("idx_schedule_date", "date"),)
|
||
|
||
|
||
class MaiZoneScheduleStatus(Base):
|
||
"""麦麦空间日程处理状态模型"""
|
||
|
||
__tablename__ = "maizone_schedule_status"
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
datetime_hour: Mapped[str] = mapped_column(get_string_field(13), nullable=False, unique=True, index=True)
|
||
activity: Mapped[str] = mapped_column(Text, nullable=False)
|
||
is_processed: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
|
||
processed_at: Mapped[datetime.datetime | None] = mapped_column(DateTime, nullable=True)
|
||
story_content: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
send_success: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
|
||
created_at: Mapped[datetime.datetime] = mapped_column(DateTime, nullable=False, default=datetime.datetime.now)
|
||
updated_at: Mapped[datetime.datetime] = mapped_column(DateTime, nullable=False, default=datetime.datetime.now, onupdate=datetime.datetime.now)
|
||
|
||
__table_args__ = (
|
||
Index("idx_maizone_datetime_hour", "datetime_hour"),
|
||
Index("idx_maizone_is_processed", "is_processed"),
|
||
)
|
||
|
||
|
||
class BanUser(Base):
|
||
"""被禁用用户模型
|
||
|
||
使用 SQLAlchemy 2.0 类型标注写法，方便静态类型检查器识别实际字段类型，
|
||
避免在业务代码中对属性赋值时报 `Column[...]` 不可赋值的告警。
|
||
"""
|
||
|
||
__tablename__ = "ban_users"
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
platform: Mapped[str] = mapped_column(Text, nullable=False)
|
||
user_id: Mapped[str] = mapped_column(get_string_field(50), nullable=False, index=True)
|
||
violation_num: Mapped[int] = mapped_column(Integer, nullable=False, default=0, index=True)
|
||
reason: Mapped[str] = mapped_column(Text, nullable=False)
|
||
created_at: Mapped[datetime.datetime] = mapped_column(DateTime, nullable=False, default=datetime.datetime.now)
|
||
|
||
__table_args__ = (
|
||
Index("idx_violation_num", "violation_num"),
|
||
Index("idx_banuser_user_id", "user_id"),
|
||
Index("idx_banuser_platform", "platform"),
|
||
Index("idx_banuser_platform_user_id", "platform", "user_id"),
|
||
)
|
||
|
||
|
||
class AntiInjectionStats(Base):
|
||
"""反注入系统统计模型"""
|
||
|
||
__tablename__ = "anti_injection_stats"
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
total_messages: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
|
||
"""总处理消息数"""
|
||
|
||
detected_injections: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
|
||
"""检测到的注入攻击数"""
|
||
|
||
blocked_messages: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
|
||
"""被阻止的消息数"""
|
||
|
||
shielded_messages: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
|
||
"""被加盾的消息数"""
|
||
|
||
processing_time_total: Mapped[float] = mapped_column(Float, nullable=False, default=0.0)
|
||
"""总处理时间"""
|
||
|
||
total_process_time: Mapped[float] = mapped_column(Float, nullable=False, default=0.0)
|
||
"""累计总处理时间"""
|
||
|
||
last_process_time: Mapped[float] = mapped_column(Float, nullable=False, default=0.0)
|
||
"""最近一次处理时间"""
|
||
|
||
error_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
|
||
"""错误计数"""
|
||
|
||
start_time: Mapped[datetime.datetime] = mapped_column(DateTime, nullable=False, default=datetime.datetime.now)
|
||
"""统计开始时间"""
|
||
|
||
created_at: Mapped[datetime.datetime] = mapped_column(DateTime, nullable=False, default=datetime.datetime.now)
|
||
"""记录创建时间"""
|
||
|
||
updated_at: Mapped[datetime.datetime] = mapped_column(DateTime, nullable=False, default=datetime.datetime.now, onupdate=datetime.datetime.now)
|
||
"""记录更新时间"""
|
||
|
||
__table_args__ = (
|
||
Index("idx_anti_injection_stats_created_at", "created_at"),
|
||
Index("idx_anti_injection_stats_updated_at", "updated_at"),
|
||
)
|
||
|
||
|
||
class CacheEntries(Base):
|
||
"""工具缓存条目模型"""
|
||
|
||
__tablename__ = "cache_entries"
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
cache_key: Mapped[str] = mapped_column(get_string_field(500), nullable=False, unique=True, index=True)
|
||
"""缓存键，包含工具名、参数和代码哈希"""
|
||
|
||
cache_value: Mapped[str] = mapped_column(Text, nullable=False)
|
||
"""缓存的数据，JSON格式"""
|
||
|
||
expires_at: Mapped[float] = mapped_column(Float, nullable=False, index=True)
|
||
"""过期时间戳"""
|
||
|
||
tool_name: Mapped[str] = mapped_column(get_string_field(100), nullable=False, index=True)
|
||
"""工具名称"""
|
||
|
||
created_at: Mapped[float] = mapped_column(Float, nullable=False, default=lambda: time.time())
|
||
"""创建时间戳"""
|
||
|
||
last_accessed: Mapped[float] = mapped_column(Float, nullable=False, default=lambda: time.time())
|
||
"""最后访问时间戳"""
|
||
|
||
access_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
|
||
"""访问次数"""
|
||
|
||
__table_args__ = (
|
||
Index("idx_cache_entries_key", "cache_key"),
|
||
Index("idx_cache_entries_expires_at", "expires_at"),
|
||
Index("idx_cache_entries_tool_name", "tool_name"),
|
||
Index("idx_cache_entries_created_at", "created_at"),
|
||
)
|
||
|
||
|
||
class MonthlyPlan(Base):
|
||
"""月度计划模型"""
|
||
|
||
__tablename__ = "monthly_plans"
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
plan_text: Mapped[str] = mapped_column(Text, nullable=False)
|
||
target_month: Mapped[str] = mapped_column(String(7), nullable=False, index=True)
|
||
status: Mapped[str] = mapped_column(get_string_field(20), nullable=False, default="active", index=True)
|
||
usage_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
|
||
last_used_date: Mapped[str | None] = mapped_column(String(10), nullable=True, index=True)
|
||
created_at: Mapped[datetime.datetime] = mapped_column(DateTime, nullable=False, default=datetime.datetime.now)
|
||
|
||
__table_args__ = (
|
||
Index("idx_monthlyplan_target_month_status", "target_month", "status"),
|
||
Index("idx_monthlyplan_last_used_date", "last_used_date"),
|
||
Index("idx_monthlyplan_usage_count", "usage_count"),
|
||
)
|
||
|
||
|
||
def get_database_url():
|
||
"""获取数据库连接URL"""
|
||
from src.config.config import global_config
|
||
|
||
config = global_config.database
|
||
|
||
if config.database_type == "mysql":
|
||
# 对用户名和密码进行URL编码，处理特殊字符
|
||
from urllib.parse import quote_plus
|
||
|
||
encoded_user = quote_plus(config.mysql_user)
|
||
encoded_password = quote_plus(config.mysql_password)
|
||
|
||
# 检查是否配置了Unix socket连接
|
||
if config.mysql_unix_socket:
|
||
# 使用Unix socket连接
|
||
encoded_socket = quote_plus(config.mysql_unix_socket)
|
||
return (
|
||
f"mysql+aiomysql://{encoded_user}:{encoded_password}"
|
||
f"@/{config.mysql_database}"
|
||
f"?unix_socket={encoded_socket}&charset={config.mysql_charset}"
|
||
)
|
||
else:
|
||
# 使用标准TCP连接
|
||
return (
|
||
f"mysql+aiomysql://{encoded_user}:{encoded_password}"
|
||
f"@{config.mysql_host}:{config.mysql_port}/{config.mysql_database}"
|
||
f"?charset={config.mysql_charset}"
|
||
)
|
||
else: # SQLite
|
||
# 如果是相对路径，则相对于项目根目录
|
||
if not os.path.isabs(config.sqlite_path):
|
||
ROOT_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), "..", "..", ".."))
|
||
db_path = os.path.join(ROOT_PATH, config.sqlite_path)
|
||
else:
|
||
db_path = config.sqlite_path
|
||
|
||
# 确保数据库目录存在
|
||
os.makedirs(os.path.dirname(db_path), exist_ok=True)
|
||
|
||
return f"sqlite+aiosqlite:///{db_path}"
|
||
|
||
|
||
_initializing: bool = False # 防止递归初始化
|
||
|
||
async def initialize_database() -> tuple["AsyncEngine", async_sessionmaker[AsyncSession]]:
|
||
"""初始化异步数据库引擎和会话
|
||
|
||
Returns:
|
||
tuple[AsyncEngine, async_sessionmaker[AsyncSession]]: 创建好的异步引擎与会话工厂。
|
||
|
||
说明:
|
||
显式的返回类型标注有助于 Pyright/Pylance 正确推断调用处的对象，
|
||
避免后续对返回值再次 `await` 时出现 *"tuple[...] 并非 awaitable"* 的误用。
|
||
"""
|
||
global _engine, _SessionLocal, _initializing
|
||
|
||
# 已经初始化直接返回
|
||
if _engine is not None and _SessionLocal is not None:
|
||
return _engine, _SessionLocal
|
||
|
||
# 正在初始化的并发调用等待主初始化完成，避免递归
|
||
if _initializing:
|
||
import asyncio
|
||
for _ in range(1000): # 最多等待约10秒
|
||
await asyncio.sleep(0.01)
|
||
if _engine is not None and _SessionLocal is not None:
|
||
return _engine, _SessionLocal
|
||
raise RuntimeError("等待数据库初始化完成超时 (reentrancy guard)")
|
||
|
||
_initializing = True
|
||
try:
|
||
database_url = get_database_url()
|
||
from src.config.config import global_config
|
||
|
||
config = global_config.database
|
||
|
||
# 配置引擎参数
|
||
engine_kwargs: dict[str, Any] = {
|
||
"echo": False, # 生产环境关闭SQL日志
|
||
"future": True,
|
||
}
|
||
|
||
if config.database_type == "mysql":
|
||
engine_kwargs.update(
|
||
{
|
||
"pool_size": config.connection_pool_size,
|
||
"max_overflow": config.connection_pool_size * 2,
|
||
"pool_timeout": config.connection_timeout,
|
||
"pool_recycle": 3600,
|
||
"pool_pre_ping": True,
|
||
"connect_args": {
|
||
"autocommit": config.mysql_autocommit,
|
||
"charset": config.mysql_charset,
|
||
"connect_timeout": config.connection_timeout,
|
||
},
|
||
}
|
||
)
|
||
else:
|
||
engine_kwargs.update(
|
||
{
|
||
"connect_args": {
|
||
"check_same_thread": False,
|
||
"timeout": 60,
|
||
},
|
||
}
|
||
)
|
||
|
||
_engine = create_async_engine(database_url, **engine_kwargs)
|
||
_SessionLocal = async_sessionmaker(bind=_engine, class_=AsyncSession, expire_on_commit=False)
|
||
|
||
# 迁移
|
||
try:
|
||
from src.common.database.db_migration import check_and_migrate_database
|
||
await check_and_migrate_database(existing_engine=_engine)
|
||
except TypeError:
|
||
from src.common.database.db_migration import check_and_migrate_database as _legacy_migrate
|
||
await _legacy_migrate()
|
||
|
||
if config.database_type == "sqlite":
|
||
await enable_sqlite_wal_mode(_engine)
|
||
|
||
logger.info(f"SQLAlchemy异步数据库初始化成功: {config.database_type}")
|
||
return _engine, _SessionLocal
|
||
finally:
|
||
_initializing = False
|
||
|
||
|
||
@asynccontextmanager
|
||
async def get_db_session() -> AsyncGenerator[AsyncSession]:
|
||
"""
|
||
异步数据库会话上下文管理器。
|
||
在初始化失败时会yield None，调用方需要检查会话是否为None。
|
||
|
||
现在使用透明的连接池管理器来复用现有连接，提高并发性能。
|
||
"""
|
||
SessionLocal = None
|
||
try:
|
||
_, SessionLocal = await initialize_database()
|
||
if not SessionLocal:
|
||
raise RuntimeError("数据库会话工厂 (_SessionLocal) 未初始化。")
|
||
except Exception as e:
|
||
logger.error(f"数据库初始化失败，无法创建会话: {e}")
|
||
raise
|
||
|
||
# 使用连接池管理器获取会话
|
||
pool_manager = get_connection_pool_manager()
|
||
|
||
async with pool_manager.get_session(SessionLocal) as session:
|
||
# 对于 SQLite，在会话开始时设置 PRAGMA（仅对新连接）
|
||
from src.config.config import global_config
|
||
|
||
if global_config.database.database_type == "sqlite":
|
||
try:
|
||
await session.execute(text("PRAGMA busy_timeout = 60000"))
|
||
await session.execute(text("PRAGMA foreign_keys = ON"))
|
||
except Exception as e:
|
||
logger.debug(f"设置 SQLite PRAGMA 时出错（可能是复用连接）: {e}")
|
||
|
||
yield session
|
||
|
||
|
||
async def get_engine():
|
||
"""获取异步数据库引擎"""
|
||
engine, _ = await initialize_database()
|
||
return engine
|
||
|
||
|
||
class PermissionNodes(Base):
|
||
"""权限节点模型"""
|
||
|
||
__tablename__ = "permission_nodes"
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
node_name: Mapped[str] = mapped_column(get_string_field(255), nullable=False, unique=True, index=True)
|
||
description: Mapped[str] = mapped_column(Text, nullable=False)
|
||
plugin_name: Mapped[str] = mapped_column(get_string_field(100), nullable=False, index=True)
|
||
default_granted: Mapped[bool] = mapped_column(Boolean, default=False, nullable=False)
|
||
created_at: Mapped[datetime.datetime] = mapped_column(DateTime, default=datetime.datetime.utcnow, nullable=False)
|
||
|
||
__table_args__ = (
|
||
Index("idx_permission_plugin", "plugin_name"),
|
||
Index("idx_permission_node", "node_name"),
|
||
)
|
||
|
||
|
||
class UserPermissions(Base):
|
||
"""用户权限模型"""
|
||
|
||
__tablename__ = "user_permissions"
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
platform: Mapped[str] = mapped_column(get_string_field(50), nullable=False, index=True)
|
||
user_id: Mapped[str] = mapped_column(get_string_field(100), nullable=False, index=True)
|
||
permission_node: Mapped[str] = mapped_column(get_string_field(255), nullable=False, index=True)
|
||
granted: Mapped[bool] = mapped_column(Boolean, default=True, nullable=False)
|
||
granted_at: Mapped[datetime.datetime] = mapped_column(DateTime, default=datetime.datetime.utcnow, nullable=False)
|
||
granted_by: Mapped[str | None] = mapped_column(get_string_field(100), nullable=True)
|
||
|
||
__table_args__ = (
|
||
Index("idx_user_platform_id", "platform", "user_id"),
|
||
Index("idx_user_permission", "platform", "user_id", "permission_node"),
|
||
Index("idx_permission_granted", "permission_node", "granted"),
|
||
)
|
||
|
||
|
||
class UserRelationships(Base):
|
||
"""用户关系模型 - 存储用户与bot的关系数据"""
|
||
|
||
__tablename__ = "user_relationships"
|
||
|
||
id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
|
||
user_id: Mapped[str] = mapped_column(get_string_field(100), nullable=False, unique=True, index=True)
|
||
user_name: Mapped[str | None] = mapped_column(get_string_field(100), nullable=True)
|
||
relationship_text: Mapped[str | None] = mapped_column(Text, nullable=True)
|
||
relationship_score: Mapped[float] = mapped_column(Float, nullable=False, default=0.3) # 关系分数(0-1)
|
||
last_updated: Mapped[float] = mapped_column(Float, nullable=False, default=time.time)
|
||
created_at: Mapped[datetime.datetime] = mapped_column(DateTime, default=datetime.datetime.utcnow, nullable=False)
|
||
|
||
__table_args__ = (
|
||
Index("idx_user_relationship_id", "user_id"),
|
||
Index("idx_relationship_score", "relationship_score"),
|
||
Index("idx_relationship_updated", "last_updated"),
|
||
)
|