refactor: 清理项目结构并修复类型注解问题

修复 SQLAlchemy 模型的类型注解，使用 Mapped 类型避免类型检查器错误
- 修正异步数据库操作中缺少 await 的问题
- 优化反注入统计系统的数值字段处理逻辑
- 添加缺失的导入语句修复模块依赖问题

bot.py

@@ -543,7 +543,7 @@ class MaiBotMain:
         """设置时区"""
         try:
             if platform.system().lower() != "windows":
-                time.tzset()
+                time.tzset() # type: ignore
                 logger.info("时区设置完成")
             else:
                 logger.info("Windows系统，跳过时区设置")

plugins/echo_example/__init__.py

@@ -1,10 +0,0 @@
-from src.plugin_system.base.plugin_metadata import PluginMetadata
-
-__plugin_meta__ = PluginMetadata(
-    name="Echo Example Plugin",
-    description="An example plugin that echoes messages.",
-    usage="!echo [message]",
-    version="1.0.0",
-    author="Your Name",
-    license="MIT",
-)

plugins/echo_example/_manifest.json

@@ -1,53 +0,0 @@
-{
-    "manifest_version": 1,
-    "format_version": "1.0.0",
-    "name": "Echo 示例插件",
-    "description": "展示增强命令系统的Echo命令示例插件",
-    "version": "1.0.0",
-    "author": {
-        "name": "MoFox"
-    },
-    "license": "MIT",
-    "keywords": ["echo", "example", "command"],
-    "categories": ["utility", "example"],
-    "host_application": {
-        "name": "MaiBot",
-        "min_version": "0.10.0"
-    },
-    "entry_points": {
-        "main": "plugin.py"
-    },
-    "plugin_info": {
-        "is_built_in": false,
-        "plugin_type": "example",
-        "components": [
-            {
-                "type": "command",
-                "name": "echo",
-                "description": "回显命令，支持别名 say, repeat"
-            },
-            {
-                "type": "command", 
-                "name": "hello",
-                "description": "问候命令，支持别名 hi, greet"
-            },
-            {
-                "type": "command",
-                "name": "info", 
-                "description": "显示插件信息，支持别名 about"
-            },
-            {
-                "type": "command",
-                "name": "test",
-                "description": "测试命令，展示参数解析功能"
-            }
-        ],
-        "features": [
-            "增强命令系统示例",
-            "无需正则表达式的命令定义",
-            "命令别名支持",
-            "参数解析功能",
-            "聊天类型限制"
-        ]
-    }
-}

plugins/echo_example/plugin.py

@@ -1,204 +0,0 @@
-"""
-Echo 示例插件
-
-展示增强命令系统的使用方法
-"""
-
-from typing import Union
-
-from src.plugin_system import (
-    BasePlugin,
-    ChatType,
-    CommandArgs,
-    ConfigField,
-    PlusCommand,
-    PlusCommandInfo,
-    register_plugin,
-)
-from src.plugin_system.base.component_types import PythonDependency
-
-
-class EchoCommand(PlusCommand):
-    """Echo命令示例"""
-
-    command_name = "echo"
-    command_description = "回显命令"
-    command_aliases = ["say", "repeat"]
-    priority = 5
-    chat_type_allow = ChatType.ALL
-    intercept_message = True
-
-    async def execute(self, args: CommandArgs) -> tuple[bool, str | None, bool]:
-        """执行echo命令"""
-        if args.is_empty():
-            await self.send_text("❓ 请提供要回显的内容\n用法: /echo <内容>")
-            return True, "参数不足", True
-
-        content = args.get_raw()
-
-        # 检查内容长度限制
-        max_length = self.get_config("commands.max_content_length", 500)
-        if len(content) > max_length:
-            await self.send_text(f"❌ 内容过长，最大允许 {max_length} 字符")
-            return True, "内容过长", True
-
-        await self.send_text(f"🔊 {content}")
-
-        return True, "Echo命令执行成功", True
-
-
-class HelloCommand(PlusCommand):
-    """Hello命令示例"""
-
-    command_name = "hello"
-    command_description = "问候命令"
-    command_aliases = ["hi", "greet"]
-    priority = 3
-    chat_type_allow = ChatType.ALL
-    intercept_message = True
-
-    async def execute(self, args: CommandArgs) -> tuple[bool, str | None, bool]:
-        """执行hello命令"""
-        if args.is_empty():
-            await self.send_text("👋 Hello! 很高兴见到你！")
-        else:
-            name = args.get_first()
-            await self.send_text(f"👋 Hello, {name}! 很高兴见到你！")
-
-        return True, "Hello命令执行成功", True
-
-
-class InfoCommand(PlusCommand):
-    """信息命令示例"""
-
-    command_name = "info"
-    command_description = "显示插件信息"
-    command_aliases = ["about"]
-    priority = 1
-    chat_type_allow = ChatType.ALL
-    intercept_message = True
-
-    async def execute(self, args: CommandArgs) -> tuple[bool, str | None, bool]:
-        """执行info命令"""
-        info_text = (
-            "📋 Echo 示例插件信息\n"
-            "版本: 1.0.0\n"
-            "作者: MaiBot Team\n"
-            "描述: 展示增强命令系统的使用方法\n\n"
-            "🎯 可用命令:\n"
-            "• /echo|/say|/repeat <内容> - 回显内容\n"
-            "• /hello|/hi|/greet [名字] - 问候\n"
-            "• /info|/about - 显示此信息\n"
-            "• /test <子命令> [参数] - 测试各种功能"
-        )
-        await self.send_text(info_text)
-
-        return True, "Info命令执行成功", True
-
-
-class TestCommand(PlusCommand):
-    """测试命令示例，展示参数解析功能"""
-
-    command_name = "test"
-    command_description = "测试命令，展示参数解析功能"
-    command_aliases = ["t"]
-    priority = 2
-    chat_type_allow = ChatType.ALL
-    intercept_message = True
-
-    async def execute(self, args: CommandArgs) -> tuple[bool, str | None, bool]:
-        """执行test命令"""
-        if args.is_empty():
-            help_text = (
-                "🧪 测试命令帮助\n"
-                "用法: /test <子命令> [参数]\n\n"
-                "可用子命令:\n"
-                "• args - 显示参数解析结果\n"
-                "• flags - 测试标志参数\n"
-                "• count - 计算参数数量\n"
-                "• join - 连接所有参数"
-            )
-            await self.send_text(help_text)
-            return True, "显示帮助", True
-
-        subcommand = args.get_first().lower()
-
-        if subcommand == "args":
-            result = (
-                f"🔍 参数解析结果:\n"
-                f"原始字符串: '{args.get_raw()}'\n"
-                f"解析后参数: {args.get_args()}\n"
-                f"参数数量: {args.count()}\n"
-                f"第一个参数: '{args.get_first()}'\n"
-                f"剩余参数: '{args.get_remaining()}'"
-            )
-            await self.send_text(result)
-
-        elif subcommand == "flags":
-            result = (
-                f"🏴 标志测试结果:\n"
-                f"包含 --verbose: {args.has_flag('--verbose')}\n"
-                f"包含 -v: {args.has_flag('-v')}\n"
-                f"--output 的值: '{args.get_flag_value('--output', '未设置')}'\n"
-                f"--name 的值: '{args.get_flag_value('--name', '未设置')}'"
-            )
-            await self.send_text(result)
-
-        elif subcommand == "count":
-            count = args.count() - 1  # 减去子命令本身
-            await self.send_text(f"📊 除子命令外的参数数量: {count}")
-
-        elif subcommand == "join":
-            remaining = args.get_remaining()
-            if remaining:
-                await self.send_text(f"🔗 连接结果: {remaining}")
-            else:
-                await self.send_text("❌ 没有可连接的参数")
-
-        else:
-            await self.send_text(f"❓ 未知的子命令: {subcommand}")
-
-        return True, "Test命令执行成功", True
-
-
-@register_plugin
-class EchoExamplePlugin(BasePlugin):
-    """Echo 示例插件"""
-
-    plugin_name: str = "echo_example_plugin"
-    enable_plugin: bool = True
-    dependencies: list[str] = []
-    python_dependencies: list[Union[str, "PythonDependency"]] = []
-    config_file_name: str = "config.toml"
-
-    config_schema = {
-        "plugin": {
-            "enabled": ConfigField(bool, default=True, description="是否启用插件"),
-            "config_version": ConfigField(str, default="1.0.0", description="配置文件版本"),
-        },
-        "commands": {
-            "echo_enabled": ConfigField(bool, default=True, description="是否启用 Echo 命令"),
-            "cooldown": ConfigField(int, default=0, description="命令冷却时间（秒）"),
-            "max_content_length": ConfigField(int, default=500, description="最大回显内容长度"),
-        },
-    }
-
-    config_section_descriptions = {
-        "plugin": "插件基本配置",
-        "commands": "命令相关配置",
-    }
-
-    def get_plugin_components(self) -> list[tuple[PlusCommandInfo, type]]:
-        """获取插件组件"""
-        components = []
-
-        if self.get_config("plugin.enabled", True):
-            # 添加所有命令，直接使用PlusCommand类
-            if self.get_config("commands.echo_enabled", True):
-                components.append((EchoCommand.get_plus_command_info(), EchoCommand))
-
-            components.append((HelloCommand.get_plus_command_info(), HelloCommand))
-            components.append((InfoCommand.get_plus_command_info(), InfoCommand))
-            components.append((TestCommand.get_plus_command_info(), TestCommand))
-
-        return components

plugins/hello_world_plugin/plugin.py

@@ -107,7 +107,7 @@ class HelloWorldPlugin(BasePlugin):
         components.append((GetSystemInfoTool.get_tool_info(), GetSystemInfoTool))
 
         if self.get_config("components.hello_command_enabled", True):
-            components.append((HelloCommand.get_command_info(), HelloCommand))
+            components.append((HelloCommand.get_plus_command_info(), HelloCommand))
 
         if self.get_config("components.random_emoji_action_enabled", True):
             components.append((RandomEmojiAction.get_action_info(), RandomEmojiAction))

pyrightconfig.json

@@ -0,0 +1,31 @@
+{
+  "$schema": "https://raw.githubusercontent.com/microsoft/pyright/main/packages/vscode-pyright/schemas/pyrightconfig.schema.json",
+  "include": [
+    "src",
+    "bot.py",
+    "__main__.py"
+  ],
+  "exclude": [
+    "**/__pycache__",
+    "data",
+    "logs",
+    "tests",
+    "target",
+    "*.egg-info"
+  ],
+  "typeCheckingMode": "standard",
+  "reportMissingImports": false,
+  "reportMissingTypeStubs": false,
+  "reportMissingModuleSource": false,
+  "diagnosticSeverityOverrides": {
+    "reportMissingImports": "none",
+    "reportMissingTypeStubs": "none",
+    "reportMissingModuleSource": "none"
+  },
+  "pythonVersion": "3.12",
+  "venvPath": ".",
+  "venv": ".venv",
+  "executionEnvironments": [
+    {"root": "src"}
+  ]
+}

scripts/convert_sqlalchemy_models.py

@@ -0,0 +1,220 @@
+"""批量将经典 SQLAlchemy 模型字段写法
+
+    field = Column(Integer, nullable=False, default=0)
+
+转换为 2.0 推荐的带类型注解写法：
+
+    field: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
+
+脚本特点:
+1. 仅处理指定文件(默认: src/common/database/sqlalchemy_models.py)。
+2. 自动识别多行 Column(...) 定义 (括号未闭合会继续合并)。
+3. 已经是 Mapped 写法的行会跳过。
+4. 根据类型名 (Integer / Float / Boolean / Text / String / DateTime / get_string_field) 推断 Python 类型。
+5. nullable=True 时自动添加 "| None"。
+6. 保留 Column(...) 内的原始参数顺序与内容。
+7. 生成 .bak 备份文件，确保可回滚。
+8. 支持 --dry-run 查看差异，不写回文件。
+
+局限/注意:
+- 简单基于正则/括号计数，不解析完整 AST；非常规写法(例如变量中构造 Column 再赋值)不会处理。
+- 复杂工厂/自定义类型未在映射表中的，统一映射为 Any。
+- 不自动添加 from __future__ import annotations；如需 Python 3.10 以下更先进类型表达式，请自行处理。
+
+使用方式: (在项目根目录执行)
+
+    python scripts/convert_sqlalchemy_models.py \
+        --file src/common/database/sqlalchemy_models.py --dry-run
+
+确认无误后去掉 --dry-run 真实写入。
+"""
+
+from __future__ import annotations
+
+import argparse
+import re
+import shutil
+from pathlib import Path
+from typing import Any
+
+
+TYPE_MAP = {
+    "Integer": "int",
+    "Float": "float",
+    "Boolean": "bool",
+    "Text": "str",
+    "String": "str",
+    "DateTime": "datetime.datetime",
+    # 自定义帮助函数 get_string_field(...) 也返回字符串类型
+    "get_string_field": "str",
+}
+
+
+COLUMN_ASSIGN_RE = re.compile(r"^(?P<indent>\s+)(?P<name>[A-Za-z_][A-Za-z0-9_]*)\s*=\s*Column\(")
+ALREADY_MAPPED_RE = re.compile(r"^[ \t]*[A-Za-z_][A-Za-z0-9_]*\s*:\s*Mapped\[")
+
+
+def detect_column_block(lines: list[str], start_index: int) -> tuple[int, int] | None:
+    """检测从 start_index 开始的 Column(...) 语句跨越的行范围 (包含结束行)。
+
+    使用括号计数法处理多行。
+    返回 (start, end) 行号 (包含 end)。"""
+    line = lines[start_index]
+    if "Column(" not in line:
+        return None
+    open_parens = line.count("(") - line.count(")")
+    i = start_index
+    while open_parens > 0 and i + 1 < len(lines):
+        i += 1
+        l2 = lines[i]
+        open_parens += l2.count("(") - l2.count(")")
+    return (start_index, i)
+
+
+def extract_column_body(block_lines: list[str]) -> str:
+    """提取 Column(...) 内部参数文本 (去掉首尾 Column( 和 最后一个 ) )。"""
+    joined = "\n".join(block_lines)
+    # 找到第一次出现 Column(
+    start_pos = joined.find("Column(")
+    if start_pos == -1:
+        return ""
+    inner = joined[start_pos + len("Column(") :]
+    # 去掉最后一个 ) —— 简单方式: 找到最后一个 ) 并截断
+    last_paren = inner.rfind(")")
+    if last_paren != -1:
+        inner = inner[:last_paren]
+    return inner.strip()
+
+
+def guess_python_type(column_body: str) -> str:
+    # 简单取第一个类型标识符 (去掉前导装饰/空格)
+    # 可能形式: Integer, Text, get_string_field(50), DateTime, Boolean
+    # 利用正则抓取第一个标识符
+    m = re.search(r"([A-Za-z_][A-Za-z0-9_]*)", column_body)
+    if not m:
+        return "Any"
+    type_token = m.group(1)
+    py_type = TYPE_MAP.get(type_token, "Any")
+    # nullable 检测
+    if "nullable=True" in column_body or "nullable = True" in column_body:
+        # 避免重复 Optional
+        if py_type != "Any" and not py_type.endswith(" | None"):
+            py_type = f"{py_type} | None"
+        elif py_type == "Any":
+            py_type = "Any | None"
+    return py_type
+
+
+def convert_block(block_lines: list[str]) -> list[str]:
+    first_line = block_lines[0]
+    m_name = re.match(r"^(?P<indent>\s+)(?P<name>[A-Za-z_][A-Za-z0-9_]*)\s*=", first_line)
+    if not m_name:
+        return block_lines
+    indent = m_name.group("indent")
+    name = m_name.group("name")
+    body = extract_column_body(block_lines)
+    py_type = guess_python_type(body)
+    # 构造新的多行 mapped_column 写法
+    # 保留内部参数的换行缩进: 重新缩进为 indent + 4 空格 (延续原风格: 在 indent 基础上再加 4 空格)
+    inner_lines = body.split("\n")
+    if len(inner_lines) == 1:
+        new_line = f"{indent}{name}: Mapped[{py_type}] = mapped_column({inner_lines[0].strip()})\n"
+        return [new_line]
+    else:
+        # 多行情况
+        ind2 = indent + "    "
+        rebuilt = [f"{indent}{name}: Mapped[{py_type}] = mapped_column(",]
+        for il in inner_lines:
+            if il.strip():
+                rebuilt.append(f"{ind2}{il.rstrip()}")
+        rebuilt.append(f"{indent})\n")
+        return [l + ("\n" if not l.endswith("\n") else "") for l in rebuilt]
+
+
+def ensure_imports(content: str) -> str:
+    if "Mapped," in content or "Mapped[" in content:
+        # 已经可能存在导入
+        if "from sqlalchemy.orm import Mapped, mapped_column" not in content:
+            # 简单插到第一个 import sqlalchemy 之后
+            lines = content.splitlines()
+            for i, line in enumerate(lines):
+                if "sqlalchemy" in line and line.startswith("from sqlalchemy"):
+                    lines.insert(i + 1, "from sqlalchemy.orm import Mapped, mapped_column")
+                    return "\n".join(lines)
+    return content
+
+
+def process_file(path: Path) -> tuple[str, str]:
+    original = path.read_text(encoding="utf-8")
+    lines = original.splitlines(keepends=True)
+    i = 0
+    out: list[str] = []
+    changed = 0
+    while i < len(lines):
+        line = lines[i]
+        # 跳过已是 Mapped 风格
+        if ALREADY_MAPPED_RE.match(line):
+            out.append(line)
+            i += 1
+            continue
+        if "= Column(" in line and re.match(r"^\s+[A-Za-z_][A-Za-z0-9_]*\s*=", line):
+            start, end = detect_column_block(lines, i) or (i, i)
+            block = lines[start : end + 1]
+            converted = convert_block(block)
+            out.extend(converted)
+            i = end + 1
+            # 如果转换结果与原始不同，计数
+            if "".join(converted) != "".join(block):
+                changed += 1
+        else:
+            out.append(line)
+            i += 1
+    new_content = "".join(out)
+    new_content = ensure_imports(new_content)
+    # 在文件末尾或头部预留统计信息打印(不写入文件，只返回)
+    return original, new_content if changed else original
+
+
+def main():
+    parser = argparse.ArgumentParser(description="批量转换 SQLAlchemy 模型字段为 2.0 Mapped 写法")
+    parser.add_argument("--file", default="src/common/database/sqlalchemy_models.py", help="目标模型文件")
+    parser.add_argument("--dry-run", action="store_true", help="仅显示差异，不写回")
+    parser.add_argument("--write", action="store_true", help="执行写回 (与 --dry-run 互斥)")
+    args = parser.parse_args()
+
+    target = Path(args.file)
+    if not target.exists():
+        raise SystemExit(f"文件不存在: {target}")
+
+    original, new_content = process_file(target)
+
+    if original == new_content:
+        print("[INFO] 没有需要转换的内容或转换后无差异。")
+        return
+
+    # 简单差异输出 (行对比)
+    if args.dry_run or not args.write:
+        print("[DRY-RUN] 以下为转换后预览 (仅显示不同段落):")
+        import difflib
+
+        diff = difflib.unified_diff(
+            original.splitlines(), new_content.splitlines(), fromfile="original", tofile="converted", lineterm=""
+        )
+        count = 0
+        for d in diff:
+            print(d)
+            count += 1
+        if count == 0:
+            print("[INFO] 差异为空 (可能未匹配到 Column 定义)。")
+        if not args.write:
+            print("\n未写回。若确认无误，添加 --write 执行替换。")
+        return
+
+    backup = target.with_suffix(target.suffix + ".bak")
+    shutil.copyfile(target, backup)
+    target.write_text(new_content, encoding="utf-8")
+    print(f"[DONE] 已写回: {target}，备份文件: {backup.name}")
+
+
+if __name__ == "__main__":  # pragma: no cover
+    main()

scripts/interest_value_analysis.py

@@ -1,284 +0,0 @@
-import os
-import sys
-import time
-from datetime import datetime
-
-# Add project root to Python path
-project_root = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
-sys.path.insert(0, project_root)
-from src.common.database.database_model import Messages, ChatStreams  # noqa
-
-
-def get_chat_name(chat_id: str) -> str:
-    """Get chat name from chat_id by querying ChatStreams table directly"""
-    try:
-        chat_stream = ChatStreams.get_or_none(ChatStreams.stream_id == chat_id)
-        if chat_stream is None:
-            return f"未知聊天 ({chat_id})"
-
-        if chat_stream.group_name:
-            return f"{chat_stream.group_name} ({chat_id})"
-        elif chat_stream.user_nickname:
-            return f"{chat_stream.user_nickname}的私聊 ({chat_id})"
-        else:
-            return f"未知聊天 ({chat_id})"
-    except Exception:
-        return f"查询失败 ({chat_id})"
-
-
-def format_timestamp(timestamp: float) -> str:
-    """Format timestamp to readable date string"""
-    try:
-        return datetime.fromtimestamp(timestamp).strftime("%Y-%m-%d %H:%M:%S")
-    except (ValueError, OSError):
-        return "未知时间"
-
-
-def calculate_interest_value_distribution(messages) -> dict[str, int]:
-    """Calculate distribution of interest_value"""
-    distribution = {
-        "0.000-0.010": 0,
-        "0.010-0.050": 0,
-        "0.050-0.100": 0,
-        "0.100-0.500": 0,
-        "0.500-1.000": 0,
-        "1.000-2.000": 0,
-        "2.000-5.000": 0,
-        "5.000-10.000": 0,
-        "10.000+": 0,
-    }
-
-    for msg in messages:
-        if msg.interest_value is None or msg.interest_value == 0.0:
-            continue
-
-        value = float(msg.interest_value)
-        if value < 0.010:
-            distribution["0.000-0.010"] += 1
-        elif value < 0.050:
-            distribution["0.010-0.050"] += 1
-        elif value < 0.100:
-            distribution["0.050-0.100"] += 1
-        elif value < 0.500:
-            distribution["0.100-0.500"] += 1
-        elif value < 1.000:
-            distribution["0.500-1.000"] += 1
-        elif value < 2.000:
-            distribution["1.000-2.000"] += 1
-        elif value < 5.000:
-            distribution["2.000-5.000"] += 1
-        elif value < 10.000:
-            distribution["5.000-10.000"] += 1
-        else:
-            distribution["10.000+"] += 1
-
-    return distribution
-
-
-def get_interest_value_stats(messages) -> dict[str, float]:
-    """Calculate basic statistics for interest_value"""
-    values = [
-        float(msg.interest_value) for msg in messages if msg.interest_value is not None and msg.interest_value != 0.0
-    ]
-
-    if not values:
-        return {"count": 0, "min": 0, "max": 0, "avg": 0, "median": 0}
-
-    values.sort()
-    count = len(values)
-
-    return {
-        "count": count,
-        "min": min(values),
-        "max": max(values),
-        "avg": sum(values) / count,
-        "median": values[count // 2] if count % 2 == 1 else (values[count // 2 - 1] + values[count // 2]) / 2,
-    }
-
-
-def get_available_chats() -> list[tuple[str, str, int]]:
-    """Get all available chats with message counts"""
-    try:
-        # 获取所有有消息的chat_id
-        chat_counts = {}
-        for msg in Messages.select(Messages.chat_id).distinct():
-            chat_id = msg.chat_id
-            count = (
-                Messages.select()
-                .where(
-                    (Messages.chat_id == chat_id)
-                    & (Messages.interest_value.is_null(False))
-                    & (Messages.interest_value != 0.0)
-                )
-                .count()
-            )
-            if count > 0:
-                chat_counts[chat_id] = count
-
-        # 获取聊天名称
-        result = []
-        for chat_id, count in chat_counts.items():
-            chat_name = get_chat_name(chat_id)
-            result.append((chat_id, chat_name, count))
-
-        # 按消息数量排序
-        result.sort(key=lambda x: x[2], reverse=True)
-        return result
-    except Exception as e:
-        print(f"获取聊天列表失败: {e}")
-        return []
-
-
-def get_time_range_input() -> tuple[float | None, float | None]:
-    """Get time range input from user"""
-    print("\n时间范围选择:")
-    print("1. 最近1天")
-    print("2. 最近3天")
-    print("3. 最近7天")
-    print("4. 最近30天")
-    print("5. 自定义时间范围")
-    print("6. 不限制时间")
-
-    choice = input("请选择时间范围 (1-6): ").strip()
-
-    now = time.time()
-
-    if choice == "1":
-        return now - 24 * 3600, now
-    elif choice == "2":
-        return now - 3 * 24 * 3600, now
-    elif choice == "3":
-        return now - 7 * 24 * 3600, now
-    elif choice == "4":
-        return now - 30 * 24 * 3600, now
-    elif choice == "5":
-        print("请输入开始时间 (格式: YYYY-MM-DD HH:MM:SS):")
-        start_str = input().strip()
-        print("请输入结束时间 (格式: YYYY-MM-DD HH:MM:SS):")
-        end_str = input().strip()
-
-        try:
-            start_time = datetime.strptime(start_str, "%Y-%m-%d %H:%M:%S").timestamp()
-            end_time = datetime.strptime(end_str, "%Y-%m-%d %H:%M:%S").timestamp()
-            return start_time, end_time
-        except ValueError:
-            print("时间格式错误，将不限制时间范围")
-            return None, None
-    else:
-        return None, None
-
-
-def analyze_interest_values(
-    chat_id: str | None = None, start_time: float | None = None, end_time: float | None = None
-) -> None:
-    """Analyze interest values with optional filters"""
-
-    # 构建查询条件
-    query = Messages.select().where((Messages.interest_value.is_null(False)) & (Messages.interest_value != 0.0))
-
-    if chat_id:
-        query = query.where(Messages.chat_id == chat_id)
-
-    if start_time:
-        query = query.where(Messages.time >= start_time)
-
-    if end_time:
-        query = query.where(Messages.time <= end_time)
-
-    messages = list(query)
-
-    if not messages:
-        print("没有找到符合条件的消息")
-        return
-
-    # 计算统计信息
-    distribution = calculate_interest_value_distribution(messages)
-    stats = get_interest_value_stats(messages)
-
-    # 显示结果
-    print("\n=== Interest Value 分析结果 ===")
-    if chat_id:
-        print(f"聊天: {get_chat_name(chat_id)}")
-    else:
-        print("聊天: 全部聊天")
-
-    if start_time and end_time:
-        print(f"时间范围: {format_timestamp(start_time)} 到 {format_timestamp(end_time)}")
-    elif start_time:
-        print(f"时间范围: {format_timestamp(start_time)} 之后")
-    elif end_time:
-        print(f"时间范围: {format_timestamp(end_time)} 之前")
-    else:
-        print("时间范围: 不限制")
-
-    print("\n基本统计:")
-    print(f"有效消息数量: {stats['count']} (排除null和0值)")
-    print(f"最小值: {stats['min']:.3f}")
-    print(f"最大值: {stats['max']:.3f}")
-    print(f"平均值: {stats['avg']:.3f}")
-    print(f"中位数: {stats['median']:.3f}")
-
-    print("\nInterest Value 分布:")
-    total = stats["count"]
-    for range_name, count in distribution.items():
-        if count > 0:
-            percentage = count / total * 100
-            print(f"{range_name}: {count} ({percentage:.2f}%)")
-
-
-def interactive_menu() -> None:
-    """Interactive menu for interest value analysis"""
-
-    while True:
-        print("\n" + "=" * 50)
-        print("Interest Value 分析工具")
-        print("=" * 50)
-        print("1. 分析全部聊天")
-        print("2. 选择特定聊天分析")
-        print("q. 退出")
-
-        choice = input("\n请选择分析模式 (1-2, q): ").strip()
-
-        if choice.lower() == "q":
-            print("再见！")
-            break
-
-        chat_id = None
-
-        if choice == "2":
-            # 显示可用的聊天列表
-            chats = get_available_chats()
-            if not chats:
-                print("没有找到有interest_value数据的聊天")
-                continue
-
-            print(f"\n可用的聊天 (共{len(chats)}个):")
-            for i, (_cid, name, count) in enumerate(chats, 1):
-                print(f"{i}. {name} ({count}条有效消息)")
-
-            try:
-                chat_choice = int(input(f"\n请选择聊天 (1-{len(chats)}): ").strip())
-                if 1 <= chat_choice <= len(chats):
-                    chat_id = chats[chat_choice - 1][0]
-                else:
-                    print("无效选择")
-                    continue
-            except ValueError:
-                print("请输入有效数字")
-                continue
-
-        elif choice != "1":
-            print("无效选择")
-            continue
-
-        # 获取时间范围
-        start_time, end_time = get_time_range_input()
-
-        # 执行分析
-        analyze_interest_values(chat_id, start_time, end_time)
-
-        input("\n按回车键继续...")
-
-
-if __name__ == "__main__":
-    interactive_menu()

scripts/manifest_tool.py

@@ -1,239 +0,0 @@
-"""
-插件Manifest管理命令行工具
-
-提供插件manifest文件的创建、验证和管理功能
-"""
-
-import argparse
-import os
-import sys
-from pathlib import Path
-
-import orjson
-
-from src.common.logger import get_logger
-from src.plugin_system.utils.manifest_utils import (
-    ManifestValidator,
-)
-
-# 添加项目根目录到Python路径
-project_root = Path(__file__).parent.parent.parent.parent
-sys.path.insert(0, str(project_root))
-
-
-logger = get_logger("manifest_tool")
-
-
-def create_minimal_manifest(plugin_dir: str, plugin_name: str, description: str = "", author: str = "") -> bool:
-    """创建最小化的manifest文件
-
-    Args:
-        plugin_dir: 插件目录
-        plugin_name: 插件名称
-        description: 插件描述
-        author: 插件作者
-
-    Returns:
-        bool: 是否创建成功
-    """
-    manifest_path = os.path.join(plugin_dir, "_manifest.json")
-
-    if os.path.exists(manifest_path):
-        print(f"❌ Manifest文件已存在: {manifest_path}")
-        return False
-
-    # 创建最小化manifest
-    minimal_manifest = {
-        "manifest_version": 1,
-        "name": plugin_name,
-        "version": "1.0.0",
-        "description": description or f"{plugin_name}插件",
-        "author": {"name": author or "Unknown"},
-    }
-
-    try:
-        with open(manifest_path, "w", encoding="utf-8") as f:
-            f.write(orjson.dumps(minimal_manifest, option=orjson.OPT_INDENT_2).decode("utf-8"))
-        print(f"✅ 已创建最小化manifest文件: {manifest_path}")
-        return True
-    except Exception as e:
-        print(f"❌ 创建manifest文件失败: {e}")
-        return False
-
-
-def create_complete_manifest(plugin_dir: str, plugin_name: str) -> bool:
-    """创建完整的manifest模板文件
-
-    Args:
-        plugin_dir: 插件目录
-        plugin_name: 插件名称
-
-    Returns:
-        bool: 是否创建成功
-    """
-    manifest_path = os.path.join(plugin_dir, "_manifest.json")
-
-    if os.path.exists(manifest_path):
-        print(f"❌ Manifest文件已存在: {manifest_path}")
-        return False
-
-    # 创建完整模板
-    complete_manifest = {
-        "manifest_version": 1,
-        "name": plugin_name,
-        "version": "1.0.0",
-        "description": f"{plugin_name}插件描述",
-        "author": {"name": "插件作者", "url": "https://github.com/your-username"},
-        "license": "MIT",
-        "host_application": {"min_version": "1.0.0", "max_version": "4.0.0"},
-        "homepage_url": "https://github.com/your-repo",
-        "repository_url": "https://github.com/your-repo",
-        "keywords": ["keyword1", "keyword2"],
-        "categories": ["Category1"],
-        "default_locale": "zh-CN",
-        "locales_path": "_locales",
-        "plugin_info": {
-            "is_built_in": False,
-            "plugin_type": "general",
-            "components": [{"type": "action", "name": "sample_action", "description": "示例动作组件"}],
-        },
-    }
-
-    try:
-        with open(manifest_path, "w", encoding="utf-8") as f:
-            f.write(orjson.dumps(complete_manifest, option=orjson.OPT_INDENT_2).decode("utf-8"))
-        print(f"✅ 已创建完整manifest模板: {manifest_path}")
-        print("💡 请根据实际情况修改manifest文件中的内容")
-        return True
-    except Exception as e:
-        print(f"❌ 创建manifest文件失败: {e}")
-        return False
-
-
-def validate_manifest_file(plugin_dir: str) -> bool:
-    """验证manifest文件
-
-    Args:
-        plugin_dir: 插件目录
-
-    Returns:
-        bool: 是否验证通过
-    """
-    manifest_path = os.path.join(plugin_dir, "_manifest.json")
-
-    if not os.path.exists(manifest_path):
-        print(f"❌ 未找到manifest文件: {manifest_path}")
-        return False
-
-    try:
-        with open(manifest_path, encoding="utf-8") as f:
-            manifest_data = orjson.loads(f.read())
-
-        validator = ManifestValidator()
-        is_valid = validator.validate_manifest(manifest_data)
-
-        # 显示验证结果
-        print("📋 Manifest验证结果:")
-        print(validator.get_validation_report())
-
-        if is_valid:
-            print("✅ Manifest文件验证通过")
-        else:
-            print("❌ Manifest文件验证失败")
-
-        return is_valid
-
-    except orjson.JSONDecodeError as e:
-        print(f"❌ Manifest文件格式错误: {e}")
-        return False
-    except Exception as e:
-        print(f"❌ 验证过程中发生错误: {e}")
-        return False
-
-
-def scan_plugins_without_manifest(root_dir: str) -> None:
-    """扫描缺少manifest文件的插件
-
-    Args:
-        root_dir: 扫描的根目录
-    """
-    print(f"🔍 扫描目录: {root_dir}")
-
-    plugins_without_manifest = []
-
-    for root, dirs, files in os.walk(root_dir):
-        # 跳过隐藏目录和__pycache__
-        dirs[:] = [d for d in dirs if not d.startswith(".") and d != "__pycache__"]
-
-        # 检查是否包含plugin.py文件（标识为插件目录）
-        if "plugin.py" in files:
-            manifest_path = os.path.join(root, "_manifest.json")
-            if not os.path.exists(manifest_path):
-                plugins_without_manifest.append(root)
-
-    if plugins_without_manifest:
-        print(f"❌ 发现 {len(plugins_without_manifest)} 个插件缺少manifest文件:")
-        for plugin_dir in plugins_without_manifest:
-            plugin_name = os.path.basename(plugin_dir)
-            print(f"  - {plugin_name}: {plugin_dir}")
-        print("💡 使用 'python manifest_tool.py create-minimal <插件目录>' 创建manifest文件")
-    else:
-        print("✅ 所有插件都有manifest文件")
-
-
-def main():
-    """主函数"""
-    parser = argparse.ArgumentParser(description="插件Manifest管理工具")
-    subparsers = parser.add_subparsers(dest="command", help="可用命令")
-
-    # 创建最小化manifest命令
-    create_minimal_parser = subparsers.add_parser("create-minimal", help="创建最小化manifest文件")
-    create_minimal_parser.add_argument("plugin_dir", help="插件目录路径")
-    create_minimal_parser.add_argument("--name", help="插件名称")
-    create_minimal_parser.add_argument("--description", help="插件描述")
-    create_minimal_parser.add_argument("--author", help="插件作者")
-
-    # 创建完整manifest命令
-    create_complete_parser = subparsers.add_parser("create-complete", help="创建完整manifest模板")
-    create_complete_parser.add_argument("plugin_dir", help="插件目录路径")
-    create_complete_parser.add_argument("--name", help="插件名称")
-
-    # 验证manifest命令
-    validate_parser = subparsers.add_parser("validate", help="验证manifest文件")
-    validate_parser.add_argument("plugin_dir", help="插件目录路径")
-
-    # 扫描插件命令
-    scan_parser = subparsers.add_parser("scan", help="扫描缺少manifest的插件")
-    scan_parser.add_argument("root_dir", help="扫描的根目录路径")
-
-    args = parser.parse_args()
-
-    if not args.command:
-        parser.print_help()
-        return
-
-    try:
-        if args.command == "create-minimal":
-            plugin_name = args.name or os.path.basename(os.path.abspath(args.plugin_dir))
-            success = create_minimal_manifest(args.plugin_dir, plugin_name, args.description or "", args.author or "")
-            sys.exit(0 if success else 1)
-
-        elif args.command == "create-complete":
-            plugin_name = args.name or os.path.basename(os.path.abspath(args.plugin_dir))
-            success = create_complete_manifest(args.plugin_dir, plugin_name)
-            sys.exit(0 if success else 1)
-
-        elif args.command == "validate":
-            success = validate_manifest_file(args.plugin_dir)
-            sys.exit(0 if success else 1)
-
-        elif args.command == "scan":
-            scan_plugins_without_manifest(args.root_dir)
-
-    except Exception as e:
-        print(f"❌ 执行命令时发生错误: {e}")
-        sys.exit(1)
-
-
-if __name__ == "__main__":
-    main()

scripts/mongodb_to_sqlite.py

@@ -1,922 +0,0 @@
-import os
-
-# import time
-import pickle
-import sys  # 新增系统模块导入
-from pathlib import Path
-
-import orjson
-
-sys.path.append(os.path.abspath(os.path.join(os.path.dirname(__file__), "..")))
-from dataclasses import dataclass, field
-from datetime import datetime
-from typing import Any
-
-from peewee import Field, IntegrityError, Model
-from pymongo import MongoClient
-from pymongo.errors import ConnectionFailure
-
-# Rich 进度条和显示组件
-from rich.console import Console
-from rich.panel import Panel
-from rich.progress import (
-    BarColumn,
-    Progress,
-    SpinnerColumn,
-    TaskProgressColumn,
-    TextColumn,
-    TimeElapsedColumn,
-    TimeRemainingColumn,
-)
-from rich.table import Table
-
-# from rich.text import Text
-from src.common.database.database import db
-from src.common.database.sqlalchemy_models import (
-    ChatStreams,
-    Emoji,
-    GraphEdges,
-    GraphNodes,
-    ImageDescriptions,
-    Images,
-    Knowledges,
-    Messages,
-    PersonInfo,
-    ThinkingLog,
-)
-from src.common.logger import get_logger
-
-logger = get_logger("mongodb_to_sqlite")
-
-ROOT_PATH = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
-
-
-@dataclass
-class MigrationConfig:
-    """迁移配置类"""
-
-    mongo_collection: str
-    target_model: type[Model]
-    field_mapping: dict[str, str]
-    batch_size: int = 500
-    enable_validation: bool = True
-    skip_duplicates: bool = True
-    unique_fields: list[str] = field(default_factory=list)  # 用于重复检查的字段
-
-
-# 数据验证相关类已移除 - 用户要求不要数据验证
-
-
-@dataclass
-class MigrationCheckpoint:
-    """迁移断点数据"""
-
-    collection_name: str
-    processed_count: int
-    last_processed_id: Any
-    timestamp: datetime
-    batch_errors: list[dict[str, Any]] = field(default_factory=list)
-
-
-@dataclass
-class MigrationStats:
-    """迁移统计信息"""
-
-    total_documents: int = 0
-    processed_count: int = 0
-    success_count: int = 0
-    error_count: int = 0
-    skipped_count: int = 0
-    duplicate_count: int = 0
-    validation_errors: int = 0
-    batch_insert_count: int = 0
-    errors: list[dict[str, Any]] = field(default_factory=list)
-    start_time: datetime | None = None
-    end_time: datetime | None = None
-
-    def add_error(self, doc_id: Any, error: str, doc_data: dict | None = None):
-        """添加错误记录"""
-        self.errors.append(
-            {"doc_id": str(doc_id), "error": error, "timestamp": datetime.now().isoformat(), "doc_data": doc_data}
-        )
-        self.error_count += 1
-
-    def add_validation_error(self, doc_id: Any, field: str, error: str):
-        """添加验证错误"""
-        self.add_error(doc_id, f"验证失败 - {field}: {error}")
-        self.validation_errors += 1
-
-
-class MongoToSQLiteMigrator:
-    """MongoDB到SQLite数据迁移器 - 使用Peewee ORM"""
-
-    def __init__(self, mongo_uri: str | None = None, database_name: str | None = None):
-        self.database_name = database_name or os.getenv("DATABASE_NAME", "MegBot")
-        self.mongo_uri = mongo_uri or self._build_mongo_uri()
-        self.mongo_client: MongoClient | None = None
-        self.mongo_db = None
-
-        # 迁移配置
-        self.migration_configs = self._initialize_migration_configs()
-
-        # 进度条控制台
-        self.console = Console()
-        # 检查点目录
-        self.checkpoint_dir = Path(os.path.join(ROOT_PATH, "data", "checkpoints"))
-        self.checkpoint_dir.mkdir(exist_ok=True)
-
-        # 验证规则已禁用
-        self.validation_rules = self._initialize_validation_rules()
-
-    def _build_mongo_uri(self) -> str:
-        """构建MongoDB连接URI"""
-        if mongo_uri := os.getenv("MONGODB_URI"):
-            return mongo_uri
-
-        user = os.getenv("MONGODB_USER")
-        password = os.getenv("MONGODB_PASS")
-        host = os.getenv("MONGODB_HOST", "localhost")
-        port = os.getenv("MONGODB_PORT", "27017")
-        auth_source = os.getenv("MONGODB_AUTH_SOURCE", "admin")
-
-        if user and password:
-            return f"mongodb://{user}:{password}@{host}:{port}/{self.database_name}?authSource={auth_source}"
-        else:
-            return f"mongodb://{host}:{port}/{self.database_name}"
-
-    def _initialize_migration_configs(self) -> list[MigrationConfig]:
-        """初始化迁移配置"""
-        return [  # 表情包迁移配置
-            MigrationConfig(
-                mongo_collection="emoji",
-                target_model=Emoji,
-                field_mapping={
-                    "full_path": "full_path",
-                    "format": "format",
-                    "hash": "emoji_hash",
-                    "description": "description",
-                    "emotion": "emotion",
-                    "usage_count": "usage_count",
-                    "last_used_time": "last_used_time",
-                    # record_time字段将在转换时自动设置为当前时间
-                },
-                enable_validation=False,  # 禁用数据验证
-                unique_fields=["full_path", "emoji_hash"],
-            ),
-            # 聊天流迁移配置
-            MigrationConfig(
-                mongo_collection="chat_streams",
-                target_model=ChatStreams,
-                field_mapping={
-                    "stream_id": "stream_id",
-                    "create_time": "create_time",
-                    "group_info.platform": "group_platform",  # 由于Mongodb处理私聊时会让group_info值为null，而新的数据库不允许为null，所以私聊聊天流是没法迁移的，等更新吧。
-                    "group_info.group_id": "group_id",  # 同上
-                    "group_info.group_name": "group_name",  # 同上
-                    "last_active_time": "last_active_time",
-                    "platform": "platform",
-                    "user_info.platform": "user_platform",
-                    "user_info.user_id": "user_id",
-                    "user_info.user_nickname": "user_nickname",
-                    "user_info.user_cardname": "user_cardname",
-                },
-                enable_validation=False,  # 禁用数据验证
-                unique_fields=["stream_id"],
-            ),
-            # 消息迁移配置
-            MigrationConfig(
-                mongo_collection="messages",
-                target_model=Messages,
-                field_mapping={
-                    "message_id": "message_id",
-                    "time": "time",
-                    "chat_id": "chat_id",
-                    "chat_info.stream_id": "chat_info_stream_id",
-                    "chat_info.platform": "chat_info_platform",
-                    "chat_info.user_info.platform": "chat_info_user_platform",
-                    "chat_info.user_info.user_id": "chat_info_user_id",
-                    "chat_info.user_info.user_nickname": "chat_info_user_nickname",
-                    "chat_info.user_info.user_cardname": "chat_info_user_cardname",
-                    "chat_info.group_info.platform": "chat_info_group_platform",
-                    "chat_info.group_info.group_id": "chat_info_group_id",
-                    "chat_info.group_info.group_name": "chat_info_group_name",
-                    "chat_info.create_time": "chat_info_create_time",
-                    "chat_info.last_active_time": "chat_info_last_active_time",
-                    "user_info.platform": "user_platform",
-                    "user_info.user_id": "user_id",
-                    "user_info.user_nickname": "user_nickname",
-                    "user_info.user_cardname": "user_cardname",
-                    "processed_plain_text": "processed_plain_text",
-                    "memorized_times": "memorized_times",
-                },
-                enable_validation=False,  # 禁用数据验证
-                unique_fields=["message_id"],
-            ),
-            # 图片迁移配置
-            MigrationConfig(
-                mongo_collection="images",
-                target_model=Images,
-                field_mapping={
-                    "hash": "emoji_hash",
-                    "description": "description",
-                    "path": "path",
-                    "timestamp": "timestamp",
-                    "type": "type",
-                },
-                unique_fields=["path"],
-            ),
-            # 图片描述迁移配置
-            MigrationConfig(
-                mongo_collection="image_descriptions",
-                target_model=ImageDescriptions,
-                field_mapping={
-                    "type": "type",
-                    "hash": "image_description_hash",
-                    "description": "description",
-                    "timestamp": "timestamp",
-                },
-                unique_fields=["image_description_hash", "type"],
-            ),
-            # 个人信息迁移配置
-            MigrationConfig(
-                mongo_collection="person_info",
-                target_model=PersonInfo,
-                field_mapping={
-                    "person_id": "person_id",
-                    "person_name": "person_name",
-                    "name_reason": "name_reason",
-                    "platform": "platform",
-                    "user_id": "user_id",
-                    "nickname": "nickname",
-                    "relationship_value": "relationship_value",
-                    "konw_time": "know_time",
-                },
-                unique_fields=["person_id"],
-            ),
-            # 知识库迁移配置
-            MigrationConfig(
-                mongo_collection="knowledges",
-                target_model=Knowledges,
-                field_mapping={"content": "content", "embedding": "embedding"},
-                unique_fields=["content"],  # 假设内容唯一
-            ),
-            # 思考日志迁移配置
-            MigrationConfig(
-                mongo_collection="thinking_log",
-                target_model=ThinkingLog,
-                field_mapping={
-                    "chat_id": "chat_id",
-                    "trigger_text": "trigger_text",
-                    "response_text": "response_text",
-                    "trigger_info": "trigger_info_json",
-                    "response_info": "response_info_json",
-                    "timing_results": "timing_results_json",
-                    "chat_history": "chat_history_json",
-                    "chat_history_in_thinking": "chat_history_in_thinking_json",
-                    "chat_history_after_response": "chat_history_after_response_json",
-                    "heartflow_data": "heartflow_data_json",
-                    "reasoning_data": "reasoning_data_json",
-                },
-                unique_fields=["chat_id", "trigger_text"],
-            ),
-            # 图节点迁移配置
-            MigrationConfig(
-                mongo_collection="graph_data.nodes",
-                target_model=GraphNodes,
-                field_mapping={
-                    "concept": "concept",
-                    "memory_items": "memory_items",
-                    "hash": "hash",
-                    "created_time": "created_time",
-                    "last_modified": "last_modified",
-                },
-                unique_fields=["concept"],
-            ),
-            # 图边迁移配置
-            MigrationConfig(
-                mongo_collection="graph_data.edges",
-                target_model=GraphEdges,
-                field_mapping={
-                    "source": "source",
-                    "target": "target",
-                    "strength": "strength",
-                    "hash": "hash",
-                    "created_time": "created_time",
-                    "last_modified": "last_modified",
-                },
-                unique_fields=["source", "target"],  # 组合唯一性
-            ),
-        ]
-
-    def _initialize_validation_rules(self) -> dict[str, Any]:
-        """数据验证已禁用 - 返回空字典"""
-        return {}
-
-    def connect_mongodb(self) -> bool:
-        """连接到MongoDB"""
-        try:
-            self.mongo_client = MongoClient(
-                self.mongo_uri, serverSelectionTimeoutMS=5000, connectTimeoutMS=10000, maxPoolSize=10
-            )
-
-            # 测试连接
-            self.mongo_client.admin.command("ping")
-            self.mongo_db = self.mongo_client[self.database_name]
-
-            logger.info(f"成功连接到MongoDB: {self.database_name}")
-            return True
-
-        except ConnectionFailure as e:
-            logger.error(f"MongoDB连接失败: {e}")
-            return False
-        except Exception as e:
-            logger.error(f"MongoDB连接异常: {e}")
-            return False
-
-    def disconnect_mongodb(self):
-        """断开MongoDB连接"""
-        if self.mongo_client:
-            self.mongo_client.close()
-            logger.info("MongoDB连接已关闭")
-
-    def _get_nested_value(self, document: dict[str, Any], field_path: str) -> Any:
-        """获取嵌套字段的值"""
-        if "." not in field_path:
-            return document.get(field_path)
-
-        parts = field_path.split(".")
-        value = document
-
-        for part in parts:
-            if isinstance(value, dict):
-                value = value.get(part)
-            else:
-                return None
-
-            if value is None:
-                break
-
-        return value
-
-    def _convert_field_value(self, value: Any, target_field: Field) -> Any:
-        """根据目标字段类型转换值"""
-        if value is None:
-            return None
-
-        field_type = target_field.__class__.__name__
-
-        try:
-            if target_field.name == "record_time" and field_type == "DateTimeField":
-                return datetime.now()
-
-            if field_type in ["CharField", "TextField"]:
-                if isinstance(value, list | dict):
-                    return orjson.dumps(value, ensure_ascii=False)
-                return str(value) if value is not None else ""
-
-            elif field_type == "IntegerField":
-                if isinstance(value, str):
-                    # 处理字符串数字
-                    clean_value = value.strip()
-                    if clean_value.replace(".", "").replace("-", "").isdigit():
-                        return int(float(clean_value))
-                    return 0
-                return int(value) if value is not None else 0
-
-            elif field_type in ["FloatField", "DoubleField"]:
-                return float(value) if value is not None else 0.0
-
-            elif field_type == "BooleanField":
-                if isinstance(value, str):
-                    return value.lower() in ("true", "1", "yes", "on")
-                return bool(value)
-
-            elif field_type == "DateTimeField":
-                if isinstance(value, int | float):
-                    return datetime.fromtimestamp(value)
-                elif isinstance(value, str):
-                    try:
-                        # 尝试解析ISO格式日期
-                        return datetime.fromisoformat(value.replace("Z", "+00:00"))
-                    except ValueError:
-                        try:
-                            # 尝试解析时间戳字符串
-                            return datetime.fromtimestamp(float(value))
-                        except ValueError:
-                            return datetime.now()
-                return datetime.now()
-
-            return value
-
-        except (ValueError, TypeError) as e:
-            logger.warning(f"字段值转换失败 ({field_type}): {value} -> {e}")
-            return self._get_default_value_for_field(target_field)
-
-    def _get_default_value_for_field(self, field: Field) -> Any:
-        """获取字段的默认值"""
-        field_type = field.__class__.__name__
-
-        if hasattr(field, "default") and field.default is not None:
-            return field.default
-
-        if field.null:
-            return None
-
-        # 根据字段类型返回默认值
-        if field_type in ["CharField", "TextField"]:
-            return ""
-        elif field_type == "IntegerField":
-            return 0
-        elif field_type in ["FloatField", "DoubleField"]:
-            return 0.0
-        elif field_type == "BooleanField":
-            return False
-        elif field_type == "DateTimeField":
-            return datetime.now()
-
-        return None
-
-    def _validate_data(self, collection_name: str, data: dict[str, Any], doc_id: Any, stats: MigrationStats) -> bool:
-        """数据验证已禁用 - 始终返回True"""
-        return True
-
-    def _save_checkpoint(self, collection_name: str, processed_count: int, last_id: Any):
-        """保存迁移断点"""
-        checkpoint = MigrationCheckpoint(
-            collection_name=collection_name,
-            processed_count=processed_count,
-            last_processed_id=last_id,
-            timestamp=datetime.now(),
-        )
-
-        checkpoint_file = self.checkpoint_dir / f"{collection_name}_checkpoint.pkl"
-        try:
-            with open(checkpoint_file, "wb") as f:
-                pickle.dump(checkpoint, f)
-        except Exception as e:
-            logger.warning(f"保存断点失败: {e}")
-
-    def _load_checkpoint(self, collection_name: str) -> MigrationCheckpoint | None:
-        """加载迁移断点"""
-        checkpoint_file = self.checkpoint_dir / f"{collection_name}_checkpoint.pkl"
-        if not checkpoint_file.exists():
-            return None
-
-        try:
-            with open(checkpoint_file, "rb") as f:
-                return pickle.load(f)
-        except Exception as e:
-            logger.warning(f"加载断点失败: {e}")
-            return None
-
-    def _batch_insert(self, model: type[Model], data_list: list[dict[str, Any]]) -> int:
-        """批量插入数据"""
-        if not data_list:
-            return 0
-
-        success_count = 0
-        try:
-            with db.atomic():
-                # 分批插入，避免SQL语句过长
-                batch_size = 100
-                for i in range(0, len(data_list), batch_size):
-                    batch = data_list[i : i + batch_size]
-                    model.insert_many(batch).execute()
-                    success_count += len(batch)
-        except Exception as e:
-            logger.error(f"批量插入失败: {e}")
-            # 如果批量插入失败，尝试逐个插入
-            for data in data_list:
-                try:
-                    model.create(**data)
-                    success_count += 1
-                except Exception:
-                    pass  # 忽略单个插入失败
-
-        return success_count
-
-    def _check_duplicate_by_unique_fields(
-        self, model: type[Model], data: dict[str, Any], unique_fields: list[str]
-    ) -> bool:
-        """根据唯一字段检查重复"""
-        if not unique_fields:
-            return False
-
-        try:
-            query = model.select()
-            for field_name in unique_fields:
-                if field_name in data and data[field_name] is not None:
-                    field_obj = getattr(model, field_name)
-                    query = query.where(field_obj == data[field_name])
-
-            return query.exists()
-        except Exception as e:
-            logger.debug(f"重复检查失败: {e}")
-            return False
-
-    def _create_model_instance(self, model: type[Model], data: dict[str, Any]) -> Model | None:
-        """使用ORM创建模型实例"""
-        try:
-            # 过滤掉不存在的字段
-            valid_data = {}
-            for field_name, value in data.items():
-                if hasattr(model, field_name):
-                    valid_data[field_name] = value
-                else:
-                    logger.debug(f"跳过未知字段: {field_name}")
-
-            # 创建实例
-            instance = model.create(**valid_data)
-            return instance
-
-        except IntegrityError as e:
-            # 处理唯一约束冲突等完整性错误
-            logger.debug(f"完整性约束冲突: {e}")
-            return None
-        except Exception as e:
-            logger.error(f"创建模型实例失败: {e}")
-            return None
-
-    def migrate_collection(self, config: MigrationConfig) -> MigrationStats:
-        """迁移单个集合 - 使用优化的批量插入和进度条"""
-        stats = MigrationStats()
-        stats.start_time = datetime.now()
-
-        # 检查是否有断点
-        checkpoint = self._load_checkpoint(config.mongo_collection)
-        start_from_id = checkpoint.last_processed_id if checkpoint else None
-        if checkpoint:
-            stats.processed_count = checkpoint.processed_count
-            logger.info(f"从断点恢复: 已处理 {checkpoint.processed_count} 条记录")
-
-        logger.info(f"开始迁移: {config.mongo_collection} -> {config.target_model._meta.table_name}")
-
-        try:
-            # 获取MongoDB集合
-            mongo_collection = self.mongo_db[config.mongo_collection]
-
-            # 构建查询条件（用于断点恢复）
-            query = {}
-            if start_from_id:
-                query = {"_id": {"$gt": start_from_id}}
-
-            stats.total_documents = mongo_collection.count_documents(query)
-
-            if stats.total_documents == 0:
-                logger.warning(f"集合 {config.mongo_collection} 为空，跳过迁移")
-                return stats
-
-            logger.info(f"待迁移文档数量: {stats.total_documents}")
-
-            # 创建Rich进度条
-            with Progress(
-                SpinnerColumn(),
-                TextColumn("[progress.description]{task.description}"),
-                BarColumn(),
-                TaskProgressColumn(),
-                TimeElapsedColumn(),
-                TimeRemainingColumn(),
-                console=self.console,
-                refresh_per_second=10,
-            ) as progress:
-                task = progress.add_task(f"迁移 {config.mongo_collection}", total=stats.total_documents)
-                # 批量处理数据
-                batch_data = []
-                batch_count = 0
-                last_processed_id = None
-
-                for mongo_doc in mongo_collection.find(query).batch_size(config.batch_size):
-                    try:
-                        doc_id = mongo_doc.get("_id", "unknown")
-                        last_processed_id = doc_id
-
-                        # 构建目标数据
-                        target_data = {}
-                        for mongo_field, sqlite_field in config.field_mapping.items():
-                            value = self._get_nested_value(mongo_doc, mongo_field)
-
-                            # 获取目标字段对象并转换类型
-                            if hasattr(config.target_model, sqlite_field):
-                                field_obj = getattr(config.target_model, sqlite_field)
-                                converted_value = self._convert_field_value(value, field_obj)
-                                target_data[sqlite_field] = converted_value
-
-                        # 数据验证已禁用
-                        # if config.enable_validation:
-                        #     if not self._validate_data(config.mongo_collection, target_data, doc_id, stats):
-                        #         stats.skipped_count += 1
-                        #         continue
-
-                        # 重复检查
-                        if config.skip_duplicates and self._check_duplicate_by_unique_fields(
-                            config.target_model, target_data, config.unique_fields
-                        ):
-                            stats.duplicate_count += 1
-                            stats.skipped_count += 1
-                            logger.debug(f"跳过重复记录: {doc_id}")
-                            continue
-
-                        # 添加到批量数据
-                        batch_data.append(target_data)
-                        stats.processed_count += 1
-
-                        # 执行批量插入
-                        if len(batch_data) >= config.batch_size:
-                            success_count = self._batch_insert(config.target_model, batch_data)
-                            stats.success_count += success_count
-                            stats.batch_insert_count += 1
-
-                            # 保存断点
-                            self._save_checkpoint(config.mongo_collection, stats.processed_count, last_processed_id)
-
-                            batch_data.clear()
-                            batch_count += 1
-
-                            # 更新进度条
-                            progress.update(task, advance=config.batch_size)
-
-                    except Exception as e:
-                        doc_id = mongo_doc.get("_id", "unknown")
-                        stats.add_error(doc_id, f"处理文档异常: {e}", mongo_doc)
-                        logger.error(f"处理文档失败 (ID: {doc_id}): {e}")
-
-                # 处理剩余的批量数据
-                if batch_data:
-                    success_count = self._batch_insert(config.target_model, batch_data)
-                    stats.success_count += success_count
-                    stats.batch_insert_count += 1
-                    progress.update(task, advance=len(batch_data))
-
-                # 完成进度条
-                progress.update(task, completed=stats.total_documents)
-
-            stats.end_time = datetime.now()
-            duration = stats.end_time - stats.start_time
-
-            logger.info(
-                f"迁移完成: {config.mongo_collection} -> {config.target_model._meta.table_name}\n"
-                f"总计: {stats.total_documents}, 成功: {stats.success_count}, "
-                f"错误: {stats.error_count}, 跳过: {stats.skipped_count}, 重复: {stats.duplicate_count}\n"
-                f"耗时: {duration.total_seconds():.2f}秒, 批量插入次数: {stats.batch_insert_count}"
-            )
-
-            # 清理断点文件
-            checkpoint_file = self.checkpoint_dir / f"{config.mongo_collection}_checkpoint.pkl"
-            if checkpoint_file.exists():
-                checkpoint_file.unlink()
-
-        except Exception as e:
-            logger.error(f"迁移集合 {config.mongo_collection} 时发生异常: {e}")
-            stats.add_error("collection_error", str(e))
-
-        return stats
-
-    def migrate_all(self) -> dict[str, MigrationStats]:
-        """执行所有迁移任务"""
-        logger.info("开始执行数据库迁移...")
-
-        if not self.connect_mongodb():
-            logger.error("无法连接到MongoDB，迁移终止")
-            return {}
-
-        all_stats = {}
-
-        try:
-            # 创建总体进度表格
-            total_collections = len(self.migration_configs)
-            self.console.print(
-                Panel(
-                    f"[bold blue]MongoDB 到 SQLite 数据迁移[/bold blue]\n"
-                    f"[yellow]总集合数: {total_collections}[/yellow]",
-                    title="迁移开始",
-                    expand=False,
-                )
-            )
-            for idx, config in enumerate(self.migration_configs, 1):
-                self.console.print(
-                    f"\n[bold green]正在处理集合 {idx}/{total_collections}: {config.mongo_collection}[/bold green]"
-                )
-                stats = self.migrate_collection(config)
-                all_stats[config.mongo_collection] = stats
-
-                # 显示单个集合的快速统计
-                if stats.processed_count > 0:
-                    success_rate = stats.success_count / stats.processed_count * 100
-                    if success_rate >= 95:
-                        status_emoji = "✅"
-                        status_color = "bright_green"
-                    elif success_rate >= 80:
-                        status_emoji = "⚠️"
-                        status_color = "yellow"
-                    else:
-                        status_emoji = "❌"
-                        status_color = "red"
-
-                    self.console.print(
-                        f"   {status_emoji} [{status_color}]完成: {stats.success_count}/{stats.processed_count} "
-                        f"({success_rate:.1f}%) 错误: {stats.error_count}[/{status_color}]"
-                    )
-
-                # 错误率检查
-                if stats.processed_count > 0:
-                    error_rate = stats.error_count / stats.processed_count
-                    if error_rate > 0.1:  # 错误率超过10%
-                        self.console.print(
-                            f"   [red]⚠️  警告: 错误率较高 {error_rate:.1%} "
-                            f"({stats.error_count}/{stats.processed_count})[/red]"
-                        )
-
-        finally:
-            self.disconnect_mongodb()
-
-        self._print_migration_summary(all_stats)
-        return all_stats
-
-    def _print_migration_summary(self, all_stats: dict[str, MigrationStats]):
-        """使用Rich打印美观的迁移汇总信息"""
-        # 计算总体统计
-        total_processed = sum(stats.processed_count for stats in all_stats.values())
-        total_success = sum(stats.success_count for stats in all_stats.values())
-        total_errors = sum(stats.error_count for stats in all_stats.values())
-        total_skipped = sum(stats.skipped_count for stats in all_stats.values())
-        total_duplicates = sum(stats.duplicate_count for stats in all_stats.values())
-        total_validation_errors = sum(stats.validation_errors for stats in all_stats.values())
-        total_batch_inserts = sum(stats.batch_insert_count for stats in all_stats.values())
-
-        # 计算总耗时
-        total_duration_seconds = 0
-        for stats in all_stats.values():
-            if stats.start_time and stats.end_time:
-                duration = stats.end_time - stats.start_time
-                total_duration_seconds += duration.total_seconds()
-
-        # 创建详细统计表格
-        table = Table(title="[bold blue]数据迁移汇总报告[/bold blue]", show_header=True, header_style="bold magenta")
-        table.add_column("集合名称", style="cyan", width=20)
-        table.add_column("文档总数", justify="right", style="blue")
-        table.add_column("处理数量", justify="right", style="green")
-        table.add_column("成功数量", justify="right", style="green")
-        table.add_column("错误数量", justify="right", style="red")
-        table.add_column("跳过数量", justify="right", style="yellow")
-        table.add_column("重复数量", justify="right", style="bright_yellow")
-        table.add_column("验证错误", justify="right", style="red")
-        table.add_column("批次数", justify="right", style="purple")
-        table.add_column("成功率", justify="right", style="bright_green")
-        table.add_column("耗时(秒)", justify="right", style="blue")
-
-        for collection_name, stats in all_stats.items():
-            success_rate = (stats.success_count / stats.processed_count * 100) if stats.processed_count > 0 else 0
-            duration = 0
-            if stats.start_time and stats.end_time:
-                duration = (stats.end_time - stats.start_time).total_seconds()
-
-            # 根据成功率设置颜色
-            if success_rate >= 95:
-                success_rate_style = "[bright_green]"
-            elif success_rate >= 80:
-                success_rate_style = "[yellow]"
-            else:
-                success_rate_style = "[red]"
-
-            table.add_row(
-                collection_name,
-                str(stats.total_documents),
-                str(stats.processed_count),
-                str(stats.success_count),
-                f"[red]{stats.error_count}[/red]" if stats.error_count > 0 else "0",
-                f"[yellow]{stats.skipped_count}[/yellow]" if stats.skipped_count > 0 else "0",
-                f"[bright_yellow]{stats.duplicate_count}[/bright_yellow]" if stats.duplicate_count > 0 else "0",
-                f"[red]{stats.validation_errors}[/red]" if stats.validation_errors > 0 else "0",
-                str(stats.batch_insert_count),
-                f"{success_rate_style}{success_rate:.1f}%[/{success_rate_style[1:]}",
-                f"{duration:.2f}",
-            )
-
-        # 添加总计行
-        total_success_rate = (total_success / total_processed * 100) if total_processed > 0 else 0
-        if total_success_rate >= 95:
-            total_rate_style = "[bright_green]"
-        elif total_success_rate >= 80:
-            total_rate_style = "[yellow]"
-        else:
-            total_rate_style = "[red]"
-
-        table.add_section()
-        table.add_row(
-            "[bold]总计[/bold]",
-            f"[bold]{sum(stats.total_documents for stats in all_stats.values())}[/bold]",
-            f"[bold]{total_processed}[/bold]",
-            f"[bold]{total_success}[/bold]",
-            f"[bold red]{total_errors}[/bold red]" if total_errors > 0 else "[bold]0[/bold]",
-            f"[bold yellow]{total_skipped}[/bold yellow]" if total_skipped > 0 else "[bold]0[/bold]",
-            f"[bold bright_yellow]{total_duplicates}[/bold bright_yellow]"
-            if total_duplicates > 0
-            else "[bold]0[/bold]",
-            f"[bold red]{total_validation_errors}[/bold red]" if total_validation_errors > 0 else "[bold]0[/bold]",
-            f"[bold]{total_batch_inserts}[/bold]",
-            f"[bold]{total_rate_style}{total_success_rate:.1f}%[/{total_rate_style[1:]}[/bold]",
-            f"[bold]{total_duration_seconds:.2f}[/bold]",
-        )
-
-        self.console.print(table)
-
-        # 创建状态面板
-        status_items = []
-        if total_errors > 0:
-            status_items.append(f"[red]⚠️  发现 {total_errors} 个错误，请检查日志详情[/red]")
-
-        if total_validation_errors > 0:
-            status_items.append(f"[red]🔍 数据验证失败: {total_validation_errors} 条记录[/red]")
-
-        if total_duplicates > 0:
-            status_items.append(f"[yellow]📋 跳过重复记录: {total_duplicates} 条[/yellow]")
-
-        if total_success_rate >= 95:
-            status_items.append(f"[bright_green]✅ 迁移成功率优秀: {total_success_rate:.1f}%[/bright_green]")
-        elif total_success_rate >= 80:
-            status_items.append(f"[yellow]⚡ 迁移成功率良好: {total_success_rate:.1f}%[/yellow]")
-        else:
-            status_items.append(f"[red]❌ 迁移成功率较低: {total_success_rate:.1f}%，需要检查[/red]")
-
-        if status_items:
-            status_panel = Panel(
-                "\n".join(status_items), title="[bold yellow]迁移状态总结[/bold yellow]", border_style="yellow"
-            )
-            self.console.print(status_panel)
-
-        # 性能统计面板
-        avg_speed = total_processed / total_duration_seconds if total_duration_seconds > 0 else 0
-        performance_info = (
-            f"[cyan]总处理时间:[/cyan] {total_duration_seconds:.2f} 秒\n"
-            f"[cyan]平均处理速度:[/cyan] {avg_speed:.1f} 条记录/秒\n"
-            f"[cyan]批量插入优化:[/cyan] 执行了 {total_batch_inserts} 次批量操作"
-        )
-
-        performance_panel = Panel(performance_info, title="[bold green]性能统计[/bold green]", border_style="green")
-        self.console.print(performance_panel)
-
-    def add_migration_config(self, config: MigrationConfig):
-        """添加新的迁移配置"""
-        self.migration_configs.append(config)
-
-    def migrate_single_collection(self, collection_name: str) -> MigrationStats | None:
-        """迁移单个指定的集合"""
-        config = next((c for c in self.migration_configs if c.mongo_collection == collection_name), None)
-        if not config:
-            logger.error(f"未找到集合 {collection_name} 的迁移配置")
-            return None
-
-        if not self.connect_mongodb():
-            logger.error("无法连接到MongoDB")
-            return None
-
-        try:
-            stats = self.migrate_collection(config)
-            self._print_migration_summary({collection_name: stats})
-            return stats
-        finally:
-            self.disconnect_mongodb()
-
-    def export_error_report(self, all_stats: dict[str, MigrationStats], filepath: str):
-        """导出错误报告"""
-        error_report = {
-            "timestamp": datetime.now().isoformat(),
-            "summary": {
-                collection: {
-                    "total": stats.total_documents,
-                    "processed": stats.processed_count,
-                    "success": stats.success_count,
-                    "errors": stats.error_count,
-                    "skipped": stats.skipped_count,
-                    "duplicates": stats.duplicate_count,
-                }
-                for collection, stats in all_stats.items()
-            },
-            "errors": {collection: stats.errors for collection, stats in all_stats.items() if stats.errors},
-        }
-
-        try:
-            with open(filepath, "w", encoding="utf-8") as f:
-                orjson.dumps(error_report, f, ensure_ascii=False, indent=2)
-            logger.info(f"错误报告已导出到: {filepath}")
-        except Exception as e:
-            logger.error(f"导出错误报告失败: {e}")
-
-
-def main():
-    """主程序入口"""
-    migrator = MongoToSQLiteMigrator()
-
-    # 执行迁移
-    migration_results = migrator.migrate_all()
-
-    # 导出错误报告（如果有错误）
-    if any(stats.error_count > 0 for stats in migration_results.values()):
-        error_report_path = f"migration_errors_{datetime.now().strftime('%Y%m%d_%H%M%S')}.json"
-        migrator.export_error_report(migration_results, error_report_path)
-
-    logger.info("数据迁移完成！")
-
-
-if __name__ == "__main__":
-    main()

scripts/run.sh

@@ -1,556 +0,0 @@
-#!/bin/bash
-
-# MaiCore & NapCat Adapter一键安装脚本 by Cookie_987
-# 适用于Arch/Ubuntu 24.10/Debian 12/CentOS 9
-# 请小心使用任何一键脚本！
-
-INSTALLER_VERSION="0.0.5-refactor"
-LANG=C.UTF-8
-
-# 如无法访问GitHub请修改此处镜像地址
-GITHUB_REPO="https://ghfast.top/https://github.com"
-
-# 颜色输出
-GREEN="\e[32m"
-RED="\e[31m"
-RESET="\e[0m"
-
-# 需要的基本软件包
-
-declare -A REQUIRED_PACKAGES=(
-    ["common"]="git sudo python3 curl gnupg"
-    ["debian"]="python3-venv python3-pip build-essential"
-    ["ubuntu"]="python3-venv python3-pip build-essential"
-    ["centos"]="epel-release python3-pip python3-devel gcc gcc-c++ make"
-    ["arch"]="python-virtualenv python-pip base-devel"
-)
-
-# 默认项目目录
-DEFAULT_INSTALL_DIR="/opt/maicore"
-
-# 服务名称
-SERVICE_NAME="maicore"
-SERVICE_NAME_WEB="maicore-web"
-SERVICE_NAME_NBADAPTER="maibot-napcat-adapter"
-
-IS_INSTALL_NAPCAT=false
-IS_INSTALL_DEPENDENCIES=false
-
-# 检查是否已安装
-check_installed() {
-    [[ -f /etc/systemd/system/${SERVICE_NAME}.service ]]
-}
-
-# 加载安装信息
-load_install_info() {
-    if [[ -f /etc/maicore_install.conf ]]; then
-        source /etc/maicore_install.conf
-    else
-        INSTALL_DIR="$DEFAULT_INSTALL_DIR"
-        BRANCH="refactor"
-    fi
-}
-
-# 显示管理菜单
-show_menu() {
-    while true; do
-        choice=$(whiptail --title "MaiCore管理菜单" --menu "请选择要执行的操作：" 15 60 7 \
-            "1" "启动MaiCore" \
-            "2" "停止MaiCore" \
-            "3" "重启MaiCore" \
-            "4" "启动NapCat Adapter" \
-            "5" "停止NapCat Adapter" \
-            "6" "重启NapCat Adapter" \
-            "7" "拉取最新MaiCore仓库" \
-            "8" "切换分支" \
-            "9" "退出" 3>&1 1>&2 2>&3)
-
-        [[ $? -ne 0 ]] && exit 0
-
-        case "$choice" in
-            1)
-                systemctl start ${SERVICE_NAME}
-                whiptail --msgbox "✅MaiCore已启动" 10 60
-                ;;
-            2)
-                systemctl stop ${SERVICE_NAME}
-                whiptail --msgbox "🛑MaiCore已停止" 10 60
-                ;;
-            3)
-                systemctl restart ${SERVICE_NAME}
-                whiptail --msgbox "🔄MaiCore已重启" 10 60
-                ;;
-            4)
-                systemctl start ${SERVICE_NAME_NBADAPTER}
-                whiptail --msgbox "✅NapCat Adapter已启动" 10 60
-                ;;
-            5)
-                systemctl stop ${SERVICE_NAME_NBADAPTER}
-                whiptail --msgbox "🛑NapCat Adapter已停止" 10 60
-                ;;
-            6)
-                systemctl restart ${SERVICE_NAME_NBADAPTER}
-                whiptail --msgbox "🔄NapCat Adapter已重启" 10 60
-                ;;
-            7)
-                update_dependencies
-                ;;
-            8)
-                switch_branch
-                ;;
-            9)
-                exit 0
-                ;;
-            *)
-                whiptail --msgbox "无效选项！" 10 60
-                ;;
-        esac
-    done
-}
-
-# 更新依赖
-update_dependencies() {
-    whiptail --title "⚠" --msgbox "更新后请阅读教程" 10 60
-    systemctl stop ${SERVICE_NAME}
-    cd "${INSTALL_DIR}/MaiBot" || {
-        whiptail --msgbox "🚫 无法进入安装目录！" 10 60
-        return 1
-    }
-    if ! git pull origin "${BRANCH}"; then
-        whiptail --msgbox "🚫 代码更新失败！" 10 60
-        return 1
-    fi
-    source "${INSTALL_DIR}/venv/bin/activate"
-    if ! pip install -r requirements.txt; then
-        whiptail --msgbox "🚫 依赖安装失败！" 10 60
-        deactivate
-        return 1
-    fi
-    deactivate
-    whiptail --msgbox "✅ 已停止服务并拉取最新仓库提交" 10 60
-}
-
-# 切换分支
-switch_branch() {
-    new_branch=$(whiptail --inputbox "请输入要切换的分支名称：" 10 60 "${BRANCH}" 3>&1 1>&2 2>&3)
-    [[ -z "$new_branch" ]] && {
-        whiptail --msgbox "🚫 分支名称不能为空！" 10 60
-        return 1
-    }
-
-    cd "${INSTALL_DIR}/MaiBot" || {
-        whiptail --msgbox "🚫 无法进入安装目录！" 10 60
-        return 1
-    }
-
-    if ! git ls-remote --exit-code --heads origin "${new_branch}" >/dev/null 2>&1; then
-        whiptail --msgbox "🚫 分支 ${new_branch} 不存在！" 10 60
-        return 1
-    fi
-
-    if ! git checkout "${new_branch}"; then
-        whiptail --msgbox "🚫 分支切换失败！" 10 60
-        return 1
-    fi
-
-    if ! git pull origin "${new_branch}"; then
-        whiptail --msgbox "🚫 代码拉取失败！" 10 60
-        return 1
-    fi
-    systemctl stop ${SERVICE_NAME}
-    source "${INSTALL_DIR}/venv/bin/activate"
-    pip install -r requirements.txt
-    deactivate
-
-    sed -i "s/^BRANCH=.*/BRANCH=${new_branch}/" /etc/maicore_install.conf
-    BRANCH="${new_branch}"
-    check_eula
-    whiptail --msgbox "✅ 已停止服务并切换到分支 ${new_branch} ！" 10 60
-}
-
-check_eula() {
-    # 首先计算当前EULA的MD5值
-    current_md5=$(md5sum "${INSTALL_DIR}/MaiBot/EULA.md" | awk '{print $1}')
-
-    # 首先计算当前隐私条款文件的哈希值
-    current_md5_privacy=$(md5sum "${INSTALL_DIR}/MaiBot/PRIVACY.md" | awk '{print $1}')
-
-    # 如果当前的md5值为空，则直接返回
-    if [[ -z $current_md5 || -z $current_md5_privacy ]]; then
-        whiptail --msgbox "🚫 未找到使用协议\n 请检查PRIVACY.md和EULA.md是否存在" 10 60
-    fi
-
-    # 检查eula.confirmed文件是否存在
-    if [[ -f ${INSTALL_DIR}/MaiBot/eula.confirmed ]]; then
-        # 如果存在则检查其中包含的md5与current_md5是否一致
-        confirmed_md5=$(cat ${INSTALL_DIR}/MaiBot/eula.confirmed)
-    else
-        confirmed_md5=""
-    fi
-
-    # 检查privacy.confirmed文件是否存在
-    if [[ -f ${INSTALL_DIR}/MaiBot/privacy.confirmed ]]; then
-        # 如果存在则检查其中包含的md5与current_md5是否一致
-        confirmed_md5_privacy=$(cat ${INSTALL_DIR}/MaiBot/privacy.confirmed)
-    else
-        confirmed_md5_privacy=""
-    fi
-
-    # 如果EULA或隐私条款有更新，提示用户重新确认
-    if [[ $current_md5 != $confirmed_md5 || $current_md5_privacy != $confirmed_md5_privacy ]]; then
-        whiptail --title "📜 使用协议更新" --yesno "检测到MaiCore EULA或隐私条款已更新。\nhttps://github.com/MaiM-with-u/MaiBot/blob/refactor/EULA.md\nhttps://github.com/MaiM-with-u/MaiBot/blob/refactor/PRIVACY.md\n\n您是否同意上述协议？ \n\n " 12 70
-        if [[ $? -eq 0 ]]; then
-            echo -n $current_md5 > ${INSTALL_DIR}/MaiBot/eula.confirmed
-            echo -n $current_md5_privacy > ${INSTALL_DIR}/MaiBot/privacy.confirmed
-        else
-            exit 1
-        fi
-    fi
-
-}
-
-# ----------- 主安装流程 -----------
-run_installation() {
-    # 1/6: 检测是否安装 whiptail
-    if ! command -v whiptail &>/dev/null; then
-        echo -e "${RED}[1/6] whiptail 未安装，正在安装...${RESET}"
-
-        if command -v apt-get &>/dev/null; then
-            apt-get update && apt-get install -y whiptail
-        elif command -v pacman &>/dev/null; then
-            pacman -Syu --noconfirm whiptail
-        elif command -v yum &>/dev/null; then
-            yum install -y whiptail
-        else
-            echo -e "${RED}[Error] 无受支持的包管理器，无法安装 whiptail!${RESET}"
-            exit 1
-        fi
-    fi
-
-    whiptail --title "ℹ️ 提示" --msgbox "如果您没有特殊需求，请优先使用docker方式部署。" 10 60
-
-    # 协议确认
-    if ! (whiptail --title "ℹ️ [1/6] 使用协议" --yes-button "我同意" --no-button "我拒绝" --yesno "使用MaiCore及此脚本前请先阅读EULA协议及隐私协议\nhttps://github.com/MaiM-with-u/MaiBot/blob/refactor/EULA.md\nhttps://github.com/MaiM-with-u/MaiBot/blob/refactor/PRIVACY.md\n\n您是否同意上述协议？" 12 70); then
-        exit 1
-    fi
-
-    # 欢迎信息
-    whiptail --title "[2/6] 欢迎使用MaiCore一键安装脚本 by Cookie987" --msgbox "检测到您未安装MaiCore，将自动进入安装流程，安装完成后再次运行此脚本即可进入管理菜单。\n\n项目处于活跃开发阶段，代码可能随时更改\n文档未完善，有问题可以提交 Issue 或者 Discussion\nQQ机器人存在被限制风险，请自行了解，谨慎使用\n由于持续迭代，可能存在一些已知或未知的bug\n由于开发中，可能消耗较多token\n\n本脚本可能更新不及时，如遇到bug请优先尝试手动部署以确定是否为脚本问题" 17 60
-
-    # 系统检查
-    check_system() {
-        if [[ "$(id -u)" -ne 0 ]]; then
-            whiptail --title "🚫 权限不足" --msgbox "请使用 root 用户运行此脚本！\n执行方式: sudo bash $0" 10 60
-            exit 1
-        fi
-
-        if [[ -f /etc/os-release ]]; then
-            source /etc/os-release
-            if [[ "$ID" == "debian" && "$VERSION_ID" == "12" ]]; then
-                return
-            elif [[ "$ID" == "ubuntu" && "$VERSION_ID" == "24.10" ]]; then
-                return
-            elif [[ "$ID" == "centos" && "$VERSION_ID" == "9" ]]; then
-                return
-            elif [[ "$ID" == "arch" ]]; then
-                whiptail --title "⚠️ 兼容性警告" --msgbox "NapCat无可用的 Arch Linux 官方安装方法，将无法自动安装NapCat。\n\n您可尝试在AUR中搜索相关包。" 10 60
-                return
-            else
-                whiptail --title "🚫 不支持的系统" --msgbox "此脚本仅支持 Arch/Debian 12 (Bookworm)/Ubuntu 24.10 (Oracular Oriole)/CentOS9！\n当前系统: $PRETTY_NAME\n安装已终止。" 10 60
-                exit 1
-            fi
-        else
-            whiptail --title "⚠️ 无法检测系统" --msgbox "无法识别系统版本，安装已终止。" 10 60
-            exit 1
-        fi
-    }
-    check_system
-
-    # 设置包管理器
-    case "$ID" in
-        debian|ubuntu)
-            PKG_MANAGER="apt"
-            ;;
-        centos)
-            PKG_MANAGER="yum"
-            ;;
-        arch)  
-            # 添加arch包管理器
-            PKG_MANAGER="pacman"
-            ;;
-    esac
-
-    # 检查NapCat
-    check_napcat() {
-        if command -v napcat &>/dev/null; then
-            NAPCAT_INSTALLED=true
-        else
-            NAPCAT_INSTALLED=false
-        fi
-    }
-    check_napcat
-
-    # 安装必要软件包
-    install_packages() {
-        missing_packages=()
-        # 检查 common 及当前系统专属依赖
-        for package in ${REQUIRED_PACKAGES["common"]} ${REQUIRED_PACKAGES["$ID"]}; do
-            case "$PKG_MANAGER" in
-            apt)
-                dpkg -s "$package" &>/dev/null || missing_packages+=("$package")
-                ;;
-            yum)
-                rpm -q "$package" &>/dev/null || missing_packages+=("$package")
-                ;;
-            pacman)
-                pacman -Qi "$package" &>/dev/null || missing_packages+=("$package")
-                ;;
-            esac
-        done
-
-        if [[ ${#missing_packages[@]} -gt 0 ]]; then
-            whiptail --title "📦 [3/6] 依赖检查" --yesno "以下软件包缺失:\n${missing_packages[*]}\n\n是否自动安装？" 10 60
-            if [[ $? -eq 0 ]]; then
-                IS_INSTALL_DEPENDENCIES=true
-            else
-                whiptail --title "⚠️ 注意" --yesno "未安装某些依赖，可能影响运行！\n是否继续？" 10 60 || exit 1
-            fi
-        fi
-    }
-    install_packages
-       
-    # 安装NapCat
-    install_napcat() {
-        [[ $NAPCAT_INSTALLED == true ]] && return
-        whiptail --title "📦 [3/6] 软件包检查" --yesno "检测到未安装NapCat，是否安装？\n如果您想使用远程NapCat，请跳过此步。" 10 60 && {
-            IS_INSTALL_NAPCAT=true
-        }
-    }
-
-    # 仅在非Arch系统上安装NapCat
-    [[ "$ID" != "arch" ]] && install_napcat
-
-    # Python版本检查
-    check_python() {
-        PYTHON_VERSION=$(python3 -c 'import sys; print(f"{sys.version_info.major}.{sys.version_info.minor}")')
-        if ! python3 -c "import sys; exit(0) if sys.version_info >= (3,10) else exit(1)"; then
-            whiptail --title "⚠️ [4/6] Python 版本过低" --msgbox "检测到 Python 版本为 $PYTHON_VERSION，需要 3.10 或以上！\n请升级 Python 后重新运行本脚本。" 10 60
-            exit 1
-        fi
-    }
-
-    # 如果没安装python则不检查python版本
-    if command -v python3 &>/dev/null; then
-        check_python
-    fi
-    
-
-    # 选择分支
-    choose_branch() {
-    BRANCH=$(whiptail --title "🔀 选择分支" --radiolist "请选择要安装的分支：" 15 60 4 \
-        "main" "稳定版本（推荐）" ON \
-        "dev" "开发版（不知道什么意思就别选）" OFF \
-        "classical" "经典版（0.6.0以前的版本）" OFF \
-        "custom" "自定义分支" OFF 3>&1 1>&2 2>&3)
-    RETVAL=$?
-    if [ $RETVAL -ne 0 ]; then
-        whiptail --msgbox "🚫 操作取消！" 10 60
-        exit 1
-    fi
-
-    if [[ "$BRANCH" == "custom" ]]; then
-        BRANCH=$(whiptail --title "🔀 自定义分支" --inputbox "请输入自定义分支名称：" 10 60 "refactor" 3>&1 1>&2 2>&3)
-        RETVAL=$?
-        if [ $RETVAL -ne 0 ]; then
-            whiptail --msgbox "🚫 输入取消！" 10 60
-            exit 1
-        fi
-        if [[ -z "$BRANCH" ]]; then
-            whiptail --msgbox "🚫 分支名称不能为空！" 10 60
-            exit 1
-        fi
-    fi
-    }
-    choose_branch
-
-    # 选择安装路径
-    choose_install_dir() {
-        INSTALL_DIR=$(whiptail --title "📂 [6/6] 选择安装路径" --inputbox "请输入MaiCore的安装目录：" 10 60 "$DEFAULT_INSTALL_DIR" 3>&1 1>&2 2>&3)
-        [[ -z "$INSTALL_DIR" ]] && {
-            whiptail --title "⚠️ 取消输入" --yesno "未输入安装路径，是否退出安装？" 10 60 && exit 1
-            INSTALL_DIR="$DEFAULT_INSTALL_DIR"
-        }
-    }
-    choose_install_dir
-
-    # 确认安装
-    confirm_install() {
-        local confirm_msg="请确认以下更改：\n\n"
-        confirm_msg+="📂 安装MaiCore、NapCat Adapter到: $INSTALL_DIR\n"
-        confirm_msg+="🔀 分支: $BRANCH\n"
-        [[ $IS_INSTALL_DEPENDENCIES == true ]] && confirm_msg+="📦 安装依赖：${missing_packages[@]}\n"
-        [[ $IS_INSTALL_NAPCAT == true ]] && confirm_msg+="📦 安装额外组件：\n"
-
-        [[ $IS_INSTALL_NAPCAT == true ]] && confirm_msg+="  - NapCat\n"
-        confirm_msg+="\n注意：本脚本默认使用ghfast.top为GitHub进行加速，如不想使用请手动修改脚本开头的GITHUB_REPO变量。"
-
-        whiptail --title "🔧 安装确认" --yesno "$confirm_msg" 20 60 || exit 1
-    }
-    confirm_install
-
-    # 开始安装
-    echo -e "${GREEN}安装${missing_packages[@]}...${RESET}"
-    
-    if [[ $IS_INSTALL_DEPENDENCIES == true ]]; then
-        case "$PKG_MANAGER" in
-        apt)
-            apt update && apt install -y "${missing_packages[@]}"
-            ;;
-        yum)
-            yum install -y "${missing_packages[@]}" --nobest
-            ;;
-        pacman)
-            pacman -S --noconfirm "${missing_packages[@]}"
-            ;;
-        esac
-    fi
-
-    if [[ $IS_INSTALL_NAPCAT == true ]]; then
-        echo -e "${GREEN}安装 NapCat...${RESET}"
-        curl -o napcat.sh https://nclatest.znin.net/NapNeko/NapCat-Installer/main/script/install.sh && bash napcat.sh --cli y --docker n
-    fi
-
-    echo -e "${GREEN}创建安装目录...${RESET}"
-    mkdir -p "$INSTALL_DIR"
-    cd "$INSTALL_DIR" || exit 1
-
-    echo -e "${GREEN}设置Python虚拟环境...${RESET}"
-    python3 -m venv venv
-    source venv/bin/activate
-
-    echo -e "${GREEN}克隆MaiCore仓库...${RESET}"
-    git clone -b "$BRANCH" "$GITHUB_REPO/MaiM-with-u/MaiBot" MaiBot || {
-        echo -e "${RED}克隆MaiCore仓库失败！${RESET}"
-        exit 1
-    }
-
-    echo -e "${GREEN}克隆 maim_message 包仓库...${RESET}"
-    git clone $GITHUB_REPO/MaiM-with-u/maim_message.git || {
-        echo -e "${RED}克隆 maim_message 包仓库失败！${RESET}"
-        exit 1
-    }
-
-    echo -e "${GREEN}克隆 nonebot-plugin-maibot-adapters 仓库...${RESET}"
-    git clone $GITHUB_REPO/MaiM-with-u/MaiBot-Napcat-Adapter.git || {
-        echo -e "${RED}克隆 MaiBot-Napcat-Adapter.git 仓库失败！${RESET}"
-        exit 1
-    }
-
-
-    echo -e "${GREEN}安装Python依赖...${RESET}"
-    pip install -r MaiBot/requirements.txt
-    cd MaiBot
-    pip install uv
-    uv pip install -i https://mirrors.aliyun.com/pypi/simple -r requirements.txt   
-    cd ..
-
-    echo -e "${GREEN}安装maim_message依赖...${RESET}"
-    cd maim_message
-    uv pip install -i https://mirrors.aliyun.com/pypi/simple -e .
-    cd ..
-
-    echo -e "${GREEN}部署MaiBot Napcat Adapter...${RESET}"
-    cd MaiBot-Napcat-Adapter
-    uv pip install -i https://mirrors.aliyun.com/pypi/simple -r requirements.txt
-    cd ..
-
-    echo -e "${GREEN}同意协议...${RESET}"
-
-    # 首先计算当前EULA的MD5值
-    current_md5=$(md5sum "MaiBot/EULA.md" | awk '{print $1}')
-
-    # 首先计算当前隐私条款文件的哈希值
-    current_md5_privacy=$(md5sum "MaiBot/PRIVACY.md" | awk '{print $1}')
-
-    echo -n $current_md5 > MaiBot/eula.confirmed
-    echo -n $current_md5_privacy > MaiBot/privacy.confirmed
-
-    echo -e "${GREEN}创建系统服务...${RESET}"
-    cat > /etc/systemd/system/${SERVICE_NAME}.service <<EOF
-[Unit]
-Description=MaiCore
-After=network.target ${SERVICE_NAME_NBADAPTER}.service
-
-[Service]
-Type=simple
-WorkingDirectory=${INSTALL_DIR}/MaiBot
-ExecStart=$INSTALL_DIR/venv/bin/python3 bot.py
-Restart=always
-RestartSec=10s
-
-[Install]
-WantedBy=multi-user.target
-EOF
-
-#     cat > /etc/systemd/system/${SERVICE_NAME_WEB}.service <<EOF
-# [Unit]
-# Description=MaiCore WebUI
-# After=network.target ${SERVICE_NAME}.service
-
-# [Service]
-# Type=simple
-# WorkingDirectory=${INSTALL_DIR}/MaiBot
-# ExecStart=$INSTALL_DIR/venv/bin/python3 webui.py
-# Restart=always
-# RestartSec=10s
-
-# [Install]
-# WantedBy=multi-user.target
-# EOF
-
-    cat > /etc/systemd/system/${SERVICE_NAME_NBADAPTER}.service <<EOF
-[Unit]
-Description=MaiBot Napcat Adapter
-After=network.target mongod.service ${SERVICE_NAME}.service
-
-[Service]
-Type=simple
-WorkingDirectory=${INSTALL_DIR}/MaiBot-Napcat-Adapter
-ExecStart=$INSTALL_DIR/venv/bin/python3 main.py
-Restart=always
-RestartSec=10s
-
-[Install]
-WantedBy=multi-user.target
-EOF
-
-    systemctl daemon-reload
-
-    # 保存安装信息
-    echo "INSTALLER_VERSION=${INSTALLER_VERSION}" > /etc/maicore_install.conf
-    echo "INSTALL_DIR=${INSTALL_DIR}" >> /etc/maicore_install.conf
-    echo "BRANCH=${BRANCH}" >> /etc/maicore_install.conf
-
-    whiptail --title "🎉 安装完成" --msgbox "MaiCore安装完成！\n已创建系统服务：${SERVICE_NAME}、${SERVICE_NAME_WEB}、${SERVICE_NAME_NBADAPTER}\n\n使用以下命令管理服务：\n启动服务：systemctl start ${SERVICE_NAME}\n查看状态：systemctl status ${SERVICE_NAME}" 14 60
-}
-
-# ----------- 主执行流程 -----------
-# 检查root权限
-[[ $(id -u) -ne 0 ]] && {
-    echo -e "${RED}请使用root用户运行此脚本！${RESET}"
-    exit 1
-}
-
-# 如果已安装显示菜单，并检查协议是否更新
-if check_installed; then
-    load_install_info
-    check_eula
-    show_menu
-else
-    run_installation
-    # 安装完成后询问是否启动
-    if whiptail --title "安装完成" --yesno "是否立即启动MaiCore服务？" 10 60; then
-        systemctl start ${SERVICE_NAME}
-        whiptail --msgbox "✅ 服务已启动！\n使用 systemctl status ${SERVICE_NAME} 查看状态" 10 60
-    fi
-fi

src/chat/antipromptinjector/anti_injector.py

@@ -265,7 +265,8 @@ class AntiPromptInjector:
             async with get_db_session() as session:
                 # 删除对应的消息记录
                 stmt = delete(Messages).where(Messages.message_id == message_id)
-                result = session.execute(stmt)
+                # 注意: 异步会话需要 await 执行，否则 result 是 coroutine，无法获取 rowcount
+                result = await session.execute(stmt)
                 await session.commit()
 
                 if result.rowcount > 0:
@@ -296,7 +297,7 @@ class AntiPromptInjector:
                     .where(Messages.message_id == message_id)
                     .values(processed_plain_text=new_content, display_message=new_content)
                 )
-                result = session.execute(stmt)
+                result = await session.execute(stmt)
                 await session.commit()
 
                 if result.rowcount > 0:

src/chat/antipromptinjector/management/statistics.py

@@ -5,9 +5,9 @@
 """
 
 import datetime
-from typing import Any
+from typing import Any, Optional, TypedDict, Literal, Union, Callable, TypeVar, cast
 
-from sqlalchemy import select
+from sqlalchemy import select, delete
 
 from src.common.database.sqlalchemy_models import AntiInjectionStats, get_db_session
 from src.common.logger import get_logger
@@ -16,8 +16,30 @@ from src.config.config import global_config
 logger = get_logger("anti_injector.statistics")
 
 
+TNum = TypeVar("TNum", int, float)
+
+
+def _add_optional(a: Optional[TNum], b: TNum) -> TNum:
+    """安全相加：左值可能为 None。
+
+    Args:
+        a: 可能为 None 的当前值
+        b: 要累加的增量（非 None）
+    Returns:
+        新的累加结果（与 b 同类型）
+    """
+    if a is None:
+        return b
+    return cast(TNum, a + b)  # a 不为 None，此处显式 cast 便于类型检查
+
+
 class AntiInjectionStatistics:
-    """反注入系统统计管理类"""
+    """反注入系统统计管理类
+
+    主要改进：
+    - 对 "可能为 None" 的数值字段做集中安全处理，减少在业务逻辑里反复判空。
+    - 补充类型注解，便于静态检查器（Pylance/Pyright）识别。
+    """
 
     def __init__(self):
         """初始化统计管理器"""
@@ -25,8 +47,12 @@ class AntiInjectionStatistics:
         """当前会话开始时间"""
 
     @staticmethod
-    async def get_or_create_stats():
-        """获取或创建统计记录"""
+    async def get_or_create_stats() -> Optional[AntiInjectionStats]:  # type: ignore[name-defined]
+        """获取或创建统计记录
+
+        Returns:
+            AntiInjectionStats | None: 成功返回模型实例，否则 None
+        """
         try:
             async with get_db_session() as session:
                 # 获取最新的统计记录，如果没有则创建
@@ -46,8 +72,15 @@ class AntiInjectionStatistics:
             return None
 
     @staticmethod
-    async def update_stats(**kwargs):
-        """更新统计数据"""
+    async def update_stats(**kwargs: Any) -> None:
+        """更新统计数据（批量可选字段）
+
+        支持字段：
+            - processing_time_delta: float 累加到 processing_time_total
+            - last_processing_time: float 设置 last_process_time
+            - total_messages / detected_injections / blocked_messages / shielded_messages / error_count: 累加
+            - 其他任意字段：直接赋值（若模型存在该属性）
+        """
         try:
             async with get_db_session() as session:
                 stats = (
@@ -63,13 +96,12 @@ class AntiInjectionStatistics:
                 for key, value in kwargs.items():
                     if key == "processing_time_delta":
                         # 处理时间累加 - 确保不为 None
-                        if stats.processing_time_total is None:
-                            stats.processing_time_total = 0.0
-                        stats.processing_time_total += value
+                        delta = float(value)
+                        stats.processing_time_total = _add_optional(stats.processing_time_total, delta)  # type: ignore[attr-defined]
                         continue
                     elif key == "last_processing_time":
                         # 直接设置最后处理时间
-                        stats.last_process_time = value
+                        stats.last_process_time = float(value)
                         continue
                     elif hasattr(stats, key):
                         if key in [
@@ -79,12 +111,10 @@ class AntiInjectionStatistics:
                             "shielded_messages",
                             "error_count",
                         ]:
-                            # 累加类型的字段 - 确保不为None
-                            current_value = getattr(stats, key)
-                            if current_value is None:
-                                setattr(stats, key, value)
-                            else:
-                                setattr(stats, key, current_value + value)
+                            # 累加类型的字段 - 统一用辅助函数
+                            current_value = cast(Optional[int], getattr(stats, key))
+                            increment = int(value)
+                            setattr(stats, key, _add_optional(current_value, increment))
                         else:
                             # 直接设置的字段
                             setattr(stats, key, value)
@@ -114,10 +144,11 @@ class AntiInjectionStatistics:
 
             stats = await self.get_or_create_stats()
 
+
             # 计算派生统计信息 - 处理 None 值
-            total_messages = stats.total_messages or 0
-            detected_injections = stats.detected_injections or 0
-            processing_time_total = stats.processing_time_total or 0.0
+            total_messages = stats.total_messages or 0  # type: ignore[attr-defined]
+            detected_injections = stats.detected_injections or 0  # type: ignore[attr-defined]
+            processing_time_total = stats.processing_time_total or 0.0  # type: ignore[attr-defined]
 
             detection_rate = (detected_injections / total_messages * 100) if total_messages > 0 else 0
             avg_processing_time = (processing_time_total / total_messages) if total_messages > 0 else 0
@@ -127,17 +158,22 @@ class AntiInjectionStatistics:
             current_time = datetime.datetime.now()
             uptime = current_time - self.session_start_time
 
+            last_proc = stats.last_process_time  # type: ignore[attr-defined]
+            blocked_messages = stats.blocked_messages or 0  # type: ignore[attr-defined]
+            shielded_messages = stats.shielded_messages or 0  # type: ignore[attr-defined]
+            error_count = stats.error_count or 0  # type: ignore[attr-defined]
+
             return {
                 "status": "enabled",
                 "uptime": str(uptime),
                 "total_messages": total_messages,
                 "detected_injections": detected_injections,
-                "blocked_messages": stats.blocked_messages or 0,
-                "shielded_messages": stats.shielded_messages or 0,
+                "blocked_messages": blocked_messages,
+                "shielded_messages": shielded_messages,
                 "detection_rate": f"{detection_rate:.2f}%",
                 "average_processing_time": f"{avg_processing_time:.3f}s",
-                "last_processing_time": f"{stats.last_process_time:.3f}s" if stats.last_process_time else "0.000s",
-                "error_count": stats.error_count or 0,
+                "last_processing_time": f"{last_proc:.3f}s" if last_proc else "0.000s",
+                "error_count": error_count,
             }
         except Exception as e:
             logger.error(f"获取统计信息失败: {e}")
@@ -149,7 +185,7 @@ class AntiInjectionStatistics:
         try:
             async with get_db_session() as session:
                 # 删除现有统计记录
-                await session.execute(select(AntiInjectionStats).delete())
+                await session.execute(delete(AntiInjectionStats))
                 await session.commit()
                 logger.info("统计信息已重置")
         except Exception as e:

src/chat/antipromptinjector/management/user_ban.py

@@ -51,7 +51,7 @@ class UserBanManager:
                             remaining_time = ban_duration - (datetime.datetime.now() - ban_record.created_at)
                             return False, None, f"用户被封禁中，剩余时间: {remaining_time}"
                         else:
-                            # 封禁已过期，重置违规次数
+                            # 封禁已过期，重置违规次数与时间（模型已使用 Mapped 类型，可直接赋值）
                             ban_record.violation_num = 0
                             ban_record.created_at = datetime.datetime.now()
                             await session.commit()
@@ -92,7 +92,6 @@ class UserBanManager:
 
                 await session.commit()
 
-                # 检查是否需要自动封禁
                 if ban_record.violation_num >= self.config.auto_ban_violation_threshold:
                     logger.warning(f"用户 {platform}:{user_id} 违规次数达到 {ban_record.violation_num}，触发自动封禁")
                     # 只有在首次达到阈值时才更新封禁开始时间

src/chat/emoji_system/emoji_manager.py

@@ -377,11 +377,12 @@ async def clean_unused_emojis(emoji_dir: str, emoji_objects: list["MaiEmoji"], r
 
 class EmojiManager:
     _instance = None
+    _initialized: bool = False  # 显式声明，避免属性未定义错误
 
     def __new__(cls) -> "EmojiManager":
         if cls._instance is None:
             cls._instance = super().__new__(cls)
-            cls._instance._initialized = False
+            # 类属性已声明，无需再次赋值
         return cls._instance
 
     def __init__(self) -> None:
@@ -399,7 +400,8 @@ class EmojiManager:
         self.emoji_num_max = global_config.emoji.max_reg_num
         self.emoji_num_max_reach_deletion = global_config.emoji.do_replace
         self.emoji_objects: list[MaiEmoji] = []  # 存储MaiEmoji对象的列表，使用类型注解明确列表元素类型
-
+        logger.info("启动表情包管理器")
+        self._initialized = True
         logger.info("启动表情包管理器")
 
     def shutdown(self) -> None:
@@ -752,8 +754,8 @@ class EmojiManager:
             try:
                 emoji_record = await self.get_emoji_from_db(emoji_hash)
                 if emoji_record and emoji_record[0].emotion:
-                    logger.info(f"[缓存命中] 从数据库获取表情包描述: {emoji_record.emotion[:50]}...")
-                    return emoji_record.emotion
+                    logger.info(f"[缓存命中] 从数据库获取表情包描述: {emoji_record.emotion[:50]}...")  # type: ignore # type: ignore
+                    return emoji_record.emotion # type: ignore
             except Exception as e:
                 logger.error(f"从数据库查询表情包描述时出错: {e}")
 

src/chat/message_manager/distribution_manager.py

@@ -7,6 +7,7 @@ import asyncio
 import time
 from typing import Any
 
+from chat.message_manager.adaptive_stream_manager import StreamPriority
 from src.chat.chatter_manager import ChatterManager
 from src.chat.energy_system import energy_manager
 from src.common.data_models.message_manager_data_model import StreamContext

src/common/database/sqlalchemy_models.py

@@ -1,6 +1,14 @@
 """SQLAlchemy数据库模型定义
 
 替换Peewee ORM，使用SQLAlchemy提供更好的连接池管理和错误恢复能力
+
+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
+SQLAlchemy 2.0 推荐的带类型注解的声明式风格：
+
+    field_name: Mapped[PyType] = mapped_column(Type, ...)
+
+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。
+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。
 """
 
 import datetime
@@ -103,31 +111,31 @@ class ChatStreams(Base):
 
     __tablename__ = "chat_streams"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    stream_id = Column(get_string_field(64), nullable=False, unique=True, index=True)
-    create_time = Column(Float, nullable=False)
-    group_platform = Column(Text, nullable=True)
-    group_id = Column(get_string_field(100), nullable=True, index=True)
-    group_name = Column(Text, nullable=True)
-    last_active_time = Column(Float, nullable=False)
-    platform = Column(Text, nullable=False)
-    user_platform = Column(Text, nullable=False)
-    user_id = Column(get_string_field(100), nullable=False, index=True)
-    user_nickname = Column(Text, nullable=False)
-    user_cardname = Column(Text, nullable=True)
-    energy_value = Column(Float, nullable=True, default=5.0)
-    sleep_pressure = Column(Float, nullable=True, default=0.0)
-    focus_energy = Column(Float, nullable=True, default=0.5)
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
+    stream_id: Mapped[str] = mapped_column(get_string_field(64), nullable=False, unique=True, index=True)
+    create_time: Mapped[float] = mapped_column(Float, nullable=False)
+    group_platform: Mapped[str | None] = mapped_column(Text, nullable=True)
+    group_id: Mapped[str | None] = mapped_column(get_string_field(100), nullable=True, index=True)
+    group_name: Mapped[str | None] = mapped_column(Text, nullable=True)
+    last_active_time: Mapped[float] = mapped_column(Float, nullable=False)
+    platform: Mapped[str] = mapped_column(Text, nullable=False)
+    user_platform: Mapped[str] = mapped_column(Text, nullable=False)
+    user_id: Mapped[str] = mapped_column(get_string_field(100), nullable=False, index=True)
+    user_nickname: Mapped[str] = mapped_column(Text, nullable=False)
+    user_cardname: Mapped[str | None] = mapped_column(Text, nullable=True)
+    energy_value: Mapped[float | None] = mapped_column(Float, nullable=True, default=5.0)
+    sleep_pressure: Mapped[float | None] = mapped_column(Float, nullable=True, default=0.0)
+    focus_energy: Mapped[float | None] = mapped_column(Float, nullable=True, default=0.5)
     # 动态兴趣度系统字段
-    base_interest_energy = Column(Float, nullable=True, default=0.5)
-    message_interest_total = Column(Float, nullable=True, default=0.0)
-    message_count = Column(Integer, nullable=True, default=0)
-    action_count = Column(Integer, nullable=True, default=0)
-    reply_count = Column(Integer, nullable=True, default=0)
-    last_interaction_time = Column(Float, nullable=True, default=None)
-    consecutive_no_reply = Column(Integer, nullable=True, default=0)
+    base_interest_energy: Mapped[float | None] = mapped_column(Float, nullable=True, default=0.5)
+    message_interest_total: Mapped[float | None] = mapped_column(Float, nullable=True, default=0.0)
+    message_count: Mapped[int | None] = mapped_column(Integer, nullable=True, default=0)
+    action_count: Mapped[int | None] = mapped_column(Integer, nullable=True, default=0)
+    reply_count: Mapped[int | None] = mapped_column(Integer, nullable=True, default=0)
+    last_interaction_time: Mapped[float | None] = mapped_column(Float, nullable=True, default=None)
+    consecutive_no_reply: Mapped[int | None] = mapped_column(Integer, nullable=True, default=0)
     # 消息打断系统字段
-    interruption_count = Column(Integer, nullable=True, default=0)
+    interruption_count: Mapped[int | None] = mapped_column(Integer, nullable=True, default=0)
 
     __table_args__ = (
         Index("idx_chatstreams_stream_id", "stream_id"),
@@ -141,20 +149,20 @@ class LLMUsage(Base):
 
     __tablename__ = "llm_usage"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    model_name = Column(get_string_field(100), nullable=False, index=True)
-    model_assign_name = Column(get_string_field(100), index=True)  # 添加索引
-    model_api_provider = Column(get_string_field(100), index=True)  # 添加索引
-    user_id = Column(get_string_field(50), nullable=False, index=True)
-    request_type = Column(get_string_field(50), nullable=False, index=True)
-    endpoint = Column(Text, nullable=False)
-    prompt_tokens = Column(Integer, nullable=False)
-    completion_tokens = Column(Integer, nullable=False)
-    time_cost = Column(Float, nullable=True)
-    total_tokens = Column(Integer, nullable=False)
-    cost = Column(Float, nullable=False)
-    status = Column(Text, nullable=False)
-    timestamp = Column(DateTime, nullable=False, index=True, default=datetime.datetime.now)
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
+    model_name: Mapped[str] = mapped_column(get_string_field(100), nullable=False, index=True)
+    model_assign_name: Mapped[str] = mapped_column(get_string_field(100), index=True)
+    model_api_provider: Mapped[str] = mapped_column(get_string_field(100), index=True)
+    user_id: Mapped[str] = mapped_column(get_string_field(50), nullable=False, index=True)
+    request_type: Mapped[str] = mapped_column(get_string_field(50), nullable=False, index=True)
+    endpoint: Mapped[str] = mapped_column(Text, nullable=False)
+    prompt_tokens: Mapped[int] = mapped_column(Integer, nullable=False)
+    completion_tokens: Mapped[int] = mapped_column(Integer, nullable=False)
+    time_cost: Mapped[float | None] = mapped_column(Float, nullable=True)
+    total_tokens: Mapped[int] = mapped_column(Integer, nullable=False)
+    cost: Mapped[float] = mapped_column(Float, nullable=False)
+    status: Mapped[str] = mapped_column(Text, nullable=False)
+    timestamp: Mapped[datetime.datetime] = mapped_column(DateTime, nullable=False, index=True, default=datetime.datetime.now)
 
     __table_args__ = (
         Index("idx_llmusage_model_name", "model_name"),
@@ -172,19 +180,19 @@ class Emoji(Base):
 
     __tablename__ = "emoji"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    full_path = Column(get_string_field(500), nullable=False, unique=True, index=True)
-    format = Column(Text, nullable=False)
-    emoji_hash = Column(get_string_field(64), nullable=False, index=True)
-    description = Column(Text, nullable=False)
-    query_count = Column(Integer, nullable=False, default=0)
-    is_registered = Column(Boolean, nullable=False, default=False)
-    is_banned = Column(Boolean, nullable=False, default=False)
-    emotion = Column(Text, nullable=True)
-    record_time = Column(Float, nullable=False)
-    register_time = Column(Float, nullable=True)
-    usage_count = Column(Integer, nullable=False, default=0)
-    last_used_time = Column(Float, nullable=True)
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
+    full_path: Mapped[str] = mapped_column(get_string_field(500), nullable=False, unique=True, index=True)
+    format: Mapped[str] = mapped_column(Text, nullable=False)
+    emoji_hash: Mapped[str] = mapped_column(get_string_field(64), nullable=False, index=True)
+    description: Mapped[str] = mapped_column(Text, nullable=False)
+    query_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
+    is_registered: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
+    is_banned: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
+    emotion: Mapped[str | None] = mapped_column(Text, nullable=True)
+    record_time: Mapped[float] = mapped_column(Float, nullable=False)
+    register_time: Mapped[float | None] = mapped_column(Float, nullable=True)
+    usage_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
+    last_used_time: Mapped[float | None] = mapped_column(Float, nullable=True)
 
     __table_args__ = (
         Index("idx_emoji_full_path", "full_path"),
@@ -197,50 +205,50 @@ class Messages(Base):
 
     __tablename__ = "messages"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    message_id = Column(get_string_field(100), nullable=False, index=True)
-    time = Column(Float, nullable=False)
-    chat_id = Column(get_string_field(64), nullable=False, index=True)
-    reply_to = Column(Text, nullable=True)
-    interest_value = Column(Float, nullable=True)
-    key_words = Column(Text, nullable=True)
-    key_words_lite = Column(Text, nullable=True)
-    is_mentioned = Column(Boolean, nullable=True)
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
+    message_id: Mapped[str] = mapped_column(get_string_field(100), nullable=False, index=True)
+    time: Mapped[float] = mapped_column(Float, nullable=False)
+    chat_id: Mapped[str] = mapped_column(get_string_field(64), nullable=False, index=True)
+    reply_to: Mapped[str | None] = mapped_column(Text, nullable=True)
+    interest_value: Mapped[float | None] = mapped_column(Float, nullable=True)
+    key_words: Mapped[str | None] = mapped_column(Text, nullable=True)
+    key_words_lite: Mapped[str | None] = mapped_column(Text, nullable=True)
+    is_mentioned: Mapped[bool | None] = mapped_column(Boolean, nullable=True)
 
     # 从 chat_info 扁平化而来的字段
-    chat_info_stream_id = Column(Text, nullable=False)
-    chat_info_platform = Column(Text, nullable=False)
-    chat_info_user_platform = Column(Text, nullable=False)
-    chat_info_user_id = Column(Text, nullable=False)
-    chat_info_user_nickname = Column(Text, nullable=False)
-    chat_info_user_cardname = Column(Text, nullable=True)
-    chat_info_group_platform = Column(Text, nullable=True)
-    chat_info_group_id = Column(Text, nullable=True)
-    chat_info_group_name = Column(Text, nullable=True)
-    chat_info_create_time = Column(Float, nullable=False)
-    chat_info_last_active_time = Column(Float, nullable=False)
+    chat_info_stream_id: Mapped[str] = mapped_column(Text, nullable=False)
+    chat_info_platform: Mapped[str] = mapped_column(Text, nullable=False)
+    chat_info_user_platform: Mapped[str] = mapped_column(Text, nullable=False)
+    chat_info_user_id: Mapped[str] = mapped_column(Text, nullable=False)
+    chat_info_user_nickname: Mapped[str] = mapped_column(Text, nullable=False)
+    chat_info_user_cardname: Mapped[str | None] = mapped_column(Text, nullable=True)
+    chat_info_group_platform: Mapped[str | None] = mapped_column(Text, nullable=True)
+    chat_info_group_id: Mapped[str | None] = mapped_column(Text, nullable=True)
+    chat_info_group_name: Mapped[str | None] = mapped_column(Text, nullable=True)
+    chat_info_create_time: Mapped[float] = mapped_column(Float, nullable=False)
+    chat_info_last_active_time: Mapped[float] = mapped_column(Float, nullable=False)
 
     # 从顶层 user_info 扁平化而来的字段
-    user_platform = Column(Text, nullable=True)
-    user_id = Column(get_string_field(100), nullable=True, index=True)
-    user_nickname = Column(Text, nullable=True)
-    user_cardname = Column(Text, nullable=True)
+    user_platform: Mapped[str | None] = mapped_column(Text, nullable=True)
+    user_id: Mapped[str | None] = mapped_column(get_string_field(100), nullable=True, index=True)
+    user_nickname: Mapped[str | None] = mapped_column(Text, nullable=True)
+    user_cardname: Mapped[str | None] = mapped_column(Text, nullable=True)
 
-    processed_plain_text = Column(Text, nullable=True)
-    display_message = Column(Text, nullable=True)
-    memorized_times = Column(Integer, nullable=False, default=0)
-    priority_mode = Column(Text, nullable=True)
-    priority_info = Column(Text, nullable=True)
-    additional_config = Column(Text, nullable=True)
-    is_emoji = Column(Boolean, nullable=False, default=False)
-    is_picid = Column(Boolean, nullable=False, default=False)
-    is_command = Column(Boolean, nullable=False, default=False)
-    is_notify = Column(Boolean, nullable=False, default=False)
+    processed_plain_text: Mapped[str | None] = mapped_column(Text, nullable=True)
+    display_message: Mapped[str | None] = mapped_column(Text, nullable=True)
+    memorized_times: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
+    priority_mode: Mapped[str | None] = mapped_column(Text, nullable=True)
+    priority_info: Mapped[str | None] = mapped_column(Text, nullable=True)
+    additional_config: Mapped[str | None] = mapped_column(Text, nullable=True)
+    is_emoji: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
+    is_picid: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
+    is_command: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
+    is_notify: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
 
     # 兴趣度系统字段
-    actions = Column(Text, nullable=True)  # JSON格式存储动作列表
-    should_reply = Column(Boolean, nullable=True, default=False)
-    should_act = Column(Boolean, nullable=True, default=False)
+    actions: Mapped[str | None] = mapped_column(Text, nullable=True)
+    should_reply: Mapped[bool | None] = mapped_column(Boolean, nullable=True, default=False)
+    should_act: Mapped[bool | None] = mapped_column(Boolean, nullable=True, default=False)
 
     __table_args__ = (
         Index("idx_messages_message_id", "message_id"),
@@ -257,17 +265,17 @@ class ActionRecords(Base):
 
     __tablename__ = "action_records"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    action_id = Column(get_string_field(100), nullable=False, index=True)
-    time = Column(Float, nullable=False)
-    action_name = Column(Text, nullable=False)
-    action_data = Column(Text, nullable=False)
-    action_done = Column(Boolean, nullable=False, default=False)
-    action_build_into_prompt = Column(Boolean, nullable=False, default=False)
-    action_prompt_display = Column(Text, nullable=False)
-    chat_id = Column(get_string_field(64), nullable=False, index=True)
-    chat_info_stream_id = Column(Text, nullable=False)
-    chat_info_platform = Column(Text, nullable=False)
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
+    action_id: Mapped[str] = mapped_column(get_string_field(100), nullable=False, index=True)
+    time: Mapped[float] = mapped_column(Float, nullable=False)
+    action_name: Mapped[str] = mapped_column(Text, nullable=False)
+    action_data: Mapped[str] = mapped_column(Text, nullable=False)
+    action_done: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
+    action_build_into_prompt: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
+    action_prompt_display: Mapped[str] = mapped_column(Text, nullable=False)
+    chat_id: Mapped[str] = mapped_column(get_string_field(64), nullable=False, index=True)
+    chat_info_stream_id: Mapped[str] = mapped_column(Text, nullable=False)
+    chat_info_platform: Mapped[str] = mapped_column(Text, nullable=False)
 
     __table_args__ = (
         Index("idx_actionrecords_action_id", "action_id"),
@@ -281,15 +289,15 @@ class Images(Base):
 
     __tablename__ = "images"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    image_id = Column(Text, nullable=False, default="")
-    emoji_hash = Column(get_string_field(64), nullable=False, index=True)
-    description = Column(Text, nullable=True)
-    path = Column(get_string_field(500), nullable=False, unique=True)
-    count = Column(Integer, nullable=False, default=1)
-    timestamp = Column(Float, nullable=False)
-    type = Column(Text, nullable=False)
-    vlm_processed = Column(Boolean, nullable=False, default=False)
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
+    image_id: Mapped[str] = mapped_column(Text, nullable=False, default="")
+    emoji_hash: Mapped[str] = mapped_column(get_string_field(64), nullable=False, index=True)
+    description: Mapped[str | None] = mapped_column(Text, nullable=True)
+    path: Mapped[str] = mapped_column(get_string_field(500), nullable=False, unique=True)
+    count: Mapped[int] = mapped_column(Integer, nullable=False, default=1)
+    timestamp: Mapped[float] = mapped_column(Float, nullable=False)
+    type: Mapped[str] = mapped_column(Text, nullable=False)
+    vlm_processed: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
 
     __table_args__ = (
         Index("idx_images_emoji_hash", "emoji_hash"),
@@ -302,11 +310,11 @@ class ImageDescriptions(Base):
 
     __tablename__ = "image_descriptions"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    type = Column(Text, nullable=False)
-    image_description_hash = Column(get_string_field(64), nullable=False, index=True)
-    description = Column(Text, nullable=False)
-    timestamp = Column(Float, nullable=False)
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
+    type: Mapped[str] = mapped_column(Text, nullable=False)
+    image_description_hash: Mapped[str] = mapped_column(get_string_field(64), nullable=False, index=True)
+    description: Mapped[str] = mapped_column(Text, nullable=False)
+    timestamp: Mapped[float] = mapped_column(Float, nullable=False)
 
     __table_args__ = (Index("idx_imagedesc_hash", "image_description_hash"),)
 
@@ -316,20 +324,20 @@ class Videos(Base):
 
     __tablename__ = "videos"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    video_id = Column(Text, nullable=False, default="")
-    video_hash = Column(get_string_field(64), nullable=False, index=True, unique=True)
-    description = Column(Text, nullable=True)
-    count = Column(Integer, nullable=False, default=1)
-    timestamp = Column(Float, nullable=False)
-    vlm_processed = Column(Boolean, nullable=False, default=False)
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
+    video_id: Mapped[str] = mapped_column(Text, nullable=False, default="")
+    video_hash: Mapped[str] = mapped_column(get_string_field(64), nullable=False, index=True, unique=True)
+    description: Mapped[str | None] = mapped_column(Text, nullable=True)
+    count: Mapped[int] = mapped_column(Integer, nullable=False, default=1)
+    timestamp: Mapped[float] = mapped_column(Float, nullable=False)
+    vlm_processed: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
 
     # 视频特有属性
-    duration = Column(Float, nullable=True)  # 视频时长（秒）
-    frame_count = Column(Integer, nullable=True)  # 总帧数
-    fps = Column(Float, nullable=True)  # 帧率
-    resolution = Column(Text, nullable=True)  # 分辨率
-    file_size = Column(Integer, nullable=True)  # 文件大小（字节）
+    duration: Mapped[float | None] = mapped_column(Float, nullable=True)
+    frame_count: Mapped[int | None] = mapped_column(Integer, nullable=True)
+    fps: Mapped[float | None] = mapped_column(Float, nullable=True)
+    resolution: Mapped[str | None] = mapped_column(Text, nullable=True)
+    file_size: Mapped[int | None] = mapped_column(Integer, nullable=True)
 
     __table_args__ = (
         Index("idx_videos_video_hash", "video_hash"),
@@ -342,11 +350,11 @@ class OnlineTime(Base):
 
     __tablename__ = "online_time"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    timestamp = Column(Text, nullable=False, default=str(datetime.datetime.now))
-    duration = Column(Integer, nullable=False)
-    start_timestamp = Column(DateTime, nullable=False, default=datetime.datetime.now)
-    end_timestamp = Column(DateTime, nullable=False, index=True)
+    id: Mapped[int] = mapped_column(Integer, primary_key=True, autoincrement=True)
+    timestamp: Mapped[str] = mapped_column(Text, nullable=False, default=str(datetime.datetime.now))
+    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"),)
 
@@ -356,22 +364,22 @@ class PersonInfo(Base):
 
     __tablename__ = "person_info"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    person_id = Column(get_string_field(100), nullable=False, unique=True, index=True)
-    person_name = Column(Text, nullable=True)
-    name_reason = Column(Text, nullable=True)
-    platform = Column(Text, nullable=False)
-    user_id = Column(get_string_field(50), nullable=False, index=True)
-    nickname = Column(Text, nullable=True)
-    impression = Column(Text, nullable=True)
-    short_impression = Column(Text, nullable=True)
-    points = Column(Text, nullable=True)
-    forgotten_points = Column(Text, nullable=True)
-    info_list = Column(Text, nullable=True)
-    know_times = Column(Float, nullable=True)
-    know_since = Column(Float, nullable=True)
-    last_know = Column(Float, nullable=True)
-    attitude = Column(Integer, nullable=True, default=50)
+    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"),
@@ -384,13 +392,13 @@ class BotPersonalityInterests(Base):
 
     __tablename__ = "bot_personality_interests"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    personality_id = Column(get_string_field(100), nullable=False, index=True)
-    personality_description = Column(Text, nullable=False)
-    interest_tags = Column(Text, nullable=False)  # JSON格式存储的兴趣标签列表
-    embedding_model = Column(get_string_field(100), nullable=False, default="text-embedding-ada-002")
-    version = Column(Integer, nullable=False, default=1)
-    last_updated = Column(DateTime, nullable=False, default=datetime.datetime.now, index=True)
+    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"),
@@ -404,13 +412,13 @@ class Memory(Base):
 
     __tablename__ = "memory"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    memory_id = Column(get_string_field(64), nullable=False, index=True)
-    chat_id = Column(Text, nullable=True)
-    memory_text = Column(Text, nullable=True)
-    keywords = Column(Text, nullable=True)
-    create_time = Column(Float, nullable=True)
-    last_view_time = Column(Float, nullable=True)
+    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"),)
 
@@ -437,19 +445,19 @@ class ThinkingLog(Base):
 
     __tablename__ = "thinking_logs"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    chat_id = Column(get_string_field(64), nullable=False, index=True)
-    trigger_text = Column(Text, nullable=True)
-    response_text = Column(Text, nullable=True)
-    trigger_info_json = Column(Text, nullable=True)
-    response_info_json = Column(Text, nullable=True)
-    timing_results_json = Column(Text, nullable=True)
-    chat_history_json = Column(Text, nullable=True)
-    chat_history_in_thinking_json = Column(Text, nullable=True)
-    chat_history_after_response_json = Column(Text, nullable=True)
-    heartflow_data_json = Column(Text, nullable=True)
-    reasoning_data_json = Column(Text, nullable=True)
-    created_at = Column(DateTime, nullable=False, default=datetime.datetime.now)
+    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"),)
 
@@ -459,13 +467,13 @@ class GraphNodes(Base):
 
     __tablename__ = "graph_nodes"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    concept = Column(get_string_field(255), nullable=False, unique=True, index=True)
-    memory_items = Column(Text, nullable=False)
-    hash = Column(Text, nullable=False)
-    weight = Column(Float, nullable=False, default=1.0)
-    created_time = Column(Float, nullable=False)
-    last_modified = Column(Float, nullable=False)
+    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"),)
 
@@ -475,13 +483,13 @@ class GraphEdges(Base):
 
     __tablename__ = "graph_edges"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    source = Column(get_string_field(255), nullable=False, index=True)
-    target = Column(get_string_field(255), nullable=False, index=True)
-    strength = Column(Integer, nullable=False)
-    hash = Column(Text, nullable=False)
-    created_time = Column(Float, nullable=False)
-    last_modified = Column(Float, nullable=False)
+    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"),
@@ -494,11 +502,11 @@ class Schedule(Base):
 
     __tablename__ = "schedule"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    date = Column(get_string_field(10), nullable=False, unique=True, index=True)  # YYYY-MM-DD格式
-    schedule_data = Column(Text, nullable=False)  # JSON格式的日程数据
-    created_at = Column(DateTime, nullable=False, default=datetime.datetime.now)
-    updated_at = Column(DateTime, nullable=False, default=datetime.datetime.now, onupdate=datetime.datetime.now)
+    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"),)
 
@@ -508,17 +516,15 @@ class MaiZoneScheduleStatus(Base):
 
     __tablename__ = "maizone_schedule_status"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    datetime_hour = Column(
-        get_string_field(13), nullable=False, unique=True, index=True
-    )  # YYYY-MM-DD HH格式，精确到小时
-    activity = Column(Text, nullable=False)  # 该小时的活动内容
-    is_processed = Column(Boolean, nullable=False, default=False)  # 是否已处理
-    processed_at = Column(DateTime, nullable=True)  # 处理时间
-    story_content = Column(Text, nullable=True)  # 生成的说说内容
-    send_success = Column(Boolean, nullable=False, default=False)  # 是否发送成功
-    created_at = Column(DateTime, nullable=False, default=datetime.datetime.now)
-    updated_at = Column(DateTime, nullable=False, default=datetime.datetime.now, onupdate=datetime.datetime.now)
+    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"),
@@ -527,16 +533,20 @@ class MaiZoneScheduleStatus(Base):
 
 
 class BanUser(Base):
-    """被禁用用户模型"""
+    """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 = Column(Integer, primary_key=True, autoincrement=True)
-    platform = Column(Text, nullable=False)
-    user_id = Column(get_string_field(50), nullable=False, index=True)
-    violation_num = Column(Integer, nullable=False, default=0)
-    reason = Column(Text, nullable=False)
-    created_at = Column(DateTime, nullable=False, default=datetime.datetime.now)
+    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"),
@@ -551,38 +561,38 @@ class AntiInjectionStats(Base):
 
     __tablename__ = "anti_injection_stats"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    total_messages = Column(Integer, nullable=False, default=0)
+    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 = Column(Integer, nullable=False, default=0)
+    detected_injections: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
     """检测到的注入攻击数"""
 
-    blocked_messages = Column(Integer, nullable=False, default=0)
+    blocked_messages: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
     """被阻止的消息数"""
 
-    shielded_messages = Column(Integer, nullable=False, default=0)
+    shielded_messages: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
     """被加盾的消息数"""
 
-    processing_time_total = Column(Float, nullable=False, default=0.0)
+    processing_time_total: Mapped[float] = mapped_column(Float, nullable=False, default=0.0)
     """总处理时间"""
 
-    total_process_time = Column(Float, nullable=False, default=0.0)
+    total_process_time: Mapped[float] = mapped_column(Float, nullable=False, default=0.0)
     """累计总处理时间"""
 
-    last_process_time = Column(Float, nullable=False, default=0.0)
+    last_process_time: Mapped[float] = mapped_column(Float, nullable=False, default=0.0)
     """最近一次处理时间"""
 
-    error_count = Column(Integer, nullable=False, default=0)
+    error_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
     """错误计数"""
 
-    start_time = Column(DateTime, nullable=False, default=datetime.datetime.now)
+    start_time: Mapped[datetime.datetime] = mapped_column(DateTime, nullable=False, default=datetime.datetime.now)
     """统计开始时间"""
 
-    created_at = Column(DateTime, nullable=False, default=datetime.datetime.now)
+    created_at: Mapped[datetime.datetime] = mapped_column(DateTime, nullable=False, default=datetime.datetime.now)
     """记录创建时间"""
 
-    updated_at = Column(DateTime, nullable=False, default=datetime.datetime.now, onupdate=datetime.datetime.now)
+    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__ = (
@@ -596,26 +606,26 @@ class CacheEntries(Base):
 
     __tablename__ = "cache_entries"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    cache_key = Column(get_string_field(500), nullable=False, unique=True, index=True)
+    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 = Column(Text, nullable=False)
+    cache_value: Mapped[str] = mapped_column(Text, nullable=False)
     """缓存的数据，JSON格式"""
 
-    expires_at = Column(Float, nullable=False, index=True)
+    expires_at: Mapped[float] = mapped_column(Float, nullable=False, index=True)
     """过期时间戳"""
 
-    tool_name = Column(get_string_field(100), nullable=False, index=True)
+    tool_name: Mapped[str] = mapped_column(get_string_field(100), nullable=False, index=True)
     """工具名称"""
 
-    created_at = Column(Float, nullable=False, default=lambda: time.time())
+    created_at: Mapped[float] = mapped_column(Float, nullable=False, default=lambda: time.time())
     """创建时间戳"""
 
-    last_accessed = Column(Float, nullable=False, default=lambda: time.time())
+    last_accessed: Mapped[float] = mapped_column(Float, nullable=False, default=lambda: time.time())
     """最后访问时间戳"""
 
-    access_count = Column(Integer, nullable=False, default=0)
+    access_count: Mapped[int] = mapped_column(Integer, nullable=False, default=0)
     """访问次数"""
 
     __table_args__ = (
@@ -631,18 +641,16 @@ class MonthlyPlan(Base):
 
     __tablename__ = "monthly_plans"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    plan_text = Column(Text, nullable=False)
-    target_month = Column(String(7), nullable=False, index=True)  # "YYYY-MM"
-    status = Column(
-        get_string_field(20), nullable=False, default="active", index=True
-    )  # 'active', 'completed', 'archived'
-    usage_count = Column(Integer, nullable=False, default=0)
-    last_used_date = Column(String(10), nullable=True, index=True)  # "YYYY-MM-DD" format
-    created_at = Column(DateTime, nullable=False, default=datetime.datetime.now)
+    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)
 
     # 保留 is_deleted 字段以兼容现有数据，但标记为已弃用
-    is_deleted = Column(Boolean, nullable=False, default=False)
+    is_deleted: Mapped[bool] = mapped_column(Boolean, nullable=False, default=False)
 
     __table_args__ = (
         Index("idx_monthlyplan_target_month_status", "target_month", "status"),
@@ -807,12 +815,12 @@ class PermissionNodes(Base):
 
     __tablename__ = "permission_nodes"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    node_name = Column(get_string_field(255), nullable=False, unique=True, index=True)  # 权限节点名称
-    description = Column(Text, nullable=False)  # 权限描述
-    plugin_name = Column(get_string_field(100), nullable=False, index=True)  # 所属插件
-    default_granted = Column(Boolean, default=False, nullable=False)  # 默认是否授权
-    created_at = Column(DateTime, default=datetime.datetime.utcnow, nullable=False)  # 创建时间
+    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"),
@@ -825,13 +833,13 @@ class UserPermissions(Base):
 
     __tablename__ = "user_permissions"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    platform = Column(get_string_field(50), nullable=False, index=True)  # 平台类型
-    user_id = Column(get_string_field(100), nullable=False, index=True)  # 用户ID
-    permission_node = Column(get_string_field(255), nullable=False, index=True)  # 权限节点名称
-    granted = Column(Boolean, default=True, nullable=False)  # 是否授权
-    granted_at = Column(DateTime, default=datetime.datetime.utcnow, nullable=False)  # 授权时间
-    granted_by = Column(get_string_field(100), nullable=True)  # 授权者信息
+    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"),
@@ -845,13 +853,13 @@ class UserRelationships(Base):
 
     __tablename__ = "user_relationships"
 
-    id = Column(Integer, primary_key=True, autoincrement=True)
-    user_id = Column(get_string_field(100), nullable=False, unique=True, index=True)  # 用户ID
-    user_name = Column(get_string_field(100), nullable=True)  # 用户名
-    relationship_text = Column(Text, nullable=True)  # 关系印象描述
-    relationship_score = Column(Float, nullable=False, default=0.3)  # 关系分数(0-1)
-    last_updated = Column(Float, nullable=False, default=time.time)  # 最后更新时间
-    created_at = Column(DateTime, default=datetime.datetime.utcnow, nullable=False)  # 创建时间
+    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"),

src/common/database/sqlalchemy_models.py.bak

@@ -0,0 +1,872 @@
+"""SQLAlchemy数据库模型定义
+
+替换Peewee ORM，使用SQLAlchemy提供更好的连接池管理和错误恢复能力
+
+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
+SQLAlchemy 2.0 推荐的带类型注解的声明式风格：
+
+    field_name: Mapped[PyType] = mapped_column(Type, ...)
+
+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。
+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。
+"""
+
+import datetime
+import os
+import time
+from collections.abc import AsyncGenerator
+from contextlib import asynccontextmanager
+from typing import Any
+
+from sqlalchemy import Boolean, Column, DateTime, Float, Index, Integer, String, Text, text
+from sqlalchemy.ext.asyncio import AsyncSession, async_sessionmaker, create_async_engine
+from sqlalchemy.ext.declarative import declarative_base
+from sqlalchemy.orm import Mapped, mapped_column
+
+from src.common.database.connection_pool_manager import get_connection_pool_manager
+from src.common.logger import get_logger
+
+logger = get_logger("sqlalchemy_models")
+
+# 创建基类
+Base = declarative_base()
+
+
+async def enable_sqlite_wal_mode(engine):
+    """为 SQLite 启用 WAL 模式以提高并发性能"""
+    try:
+        async with engine.begin() as conn:
+            # 启用 WAL 模式
+            await conn.execute(text("PRAGMA journal_mode = WAL"))
+            # 设置适中的同步级别，平衡性能和安全性
+            await conn.execute(text("PRAGMA synchronous = NORMAL"))
+            # 启用外键约束
+            await conn.execute(text("PRAGMA foreign_keys = ON"))
+            # 设置 busy_timeout，避免锁定错误
+            await conn.execute(text("PRAGMA busy_timeout = 60000"))  # 60秒
+
+        logger.info("[SQLite] WAL 模式已启用，并发性能已优化")
+    except Exception as e:
+        logger.warning(f"[SQLite] 启用 WAL 模式失败: {e}，将使用默认配置")
+
+
+async def maintain_sqlite_database():
+    """定期维护 SQLite 数据库性能"""
+    try:
+        engine, SessionLocal = await initialize_database()
+        if not engine:
+            return
+
+        async with engine.begin() as conn:
+            # 检查并确保 WAL 模式仍然启用
+            result = await conn.execute(text("PRAGMA journal_mode"))
+            journal_mode = result.scalar()
+
+            if journal_mode != "wal":
+                await conn.execute(text("PRAGMA journal_mode = WAL"))
+                logger.info("[SQLite] WAL 模式已重新启用")
+
+            # 优化数据库性能
+            await conn.execute(text("PRAGMA synchronous = NORMAL"))
+            await conn.execute(text("PRAGMA busy_timeout = 60000"))
+            await conn.execute(text("PRAGMA foreign_keys = ON"))
+
+            # 定期清理（可选，根据需要启用）
+            # await conn.execute(text("PRAGMA optimize"))
+
+        logger.info("[SQLite] 数据库维护完成")
+    except Exception as e:
+        logger.warning(f"[SQLite] 数据库维护失败: {e}")
+
+
+def get_sqlite_performance_config():
+    """获取 SQLite 性能优化配置"""
+    return {
+        "journal_mode": "WAL",  # 提高并发性能
+        "synchronous": "NORMAL",  # 平衡性能和安全性
+        "busy_timeout": 60000,  # 60秒超时
+        "foreign_keys": "ON",  # 启用外键约束
+        "cache_size": -10000,  # 10MB 缓存
+        "temp_store": "MEMORY",  # 临时存储使用内存
+        "mmap_size": 268435456,  # 256MB 内存映射
+    }
+
+
+# MySQL兼容的字段类型辅助函数
+def get_string_field(max_length=255, **kwargs):
+    """
+    根据数据库类型返回合适的字符串字段
+    MySQL需要指定长度的VARCHAR用于索引，SQLite可以使用Text
+    """
+    from src.config.config import global_config
+
+    if global_config.database.database_type == "mysql":
+        return String(max_length, **kwargs)
+    else:
+        return Text(**kwargs)
+
+
+class ChatStreams(Base):
+    """聊天流模型"""
+
+    __tablename__ = "chat_streams"
+
+    id = Column(Integer, primary_key=True, autoincrement=True)
+    stream_id = Column(get_string_field(64), nullable=False, unique=True, index=True)
+    create_time = Column(Float, nullable=False)
+    group_platform = Column(Text, nullable=True)
+    group_id = Column(get_string_field(100), nullable=True, index=True)
+    group_name = Column(Text, nullable=True)
+    last_active_time = Column(Float, nullable=False)
+    platform = Column(Text, nullable=False)
+    user_platform = Column(Text, nullable=False)
+    user_id = Column(get_string_field(100), nullable=False, index=True)
+    user_nickname = Column(Text, nullable=False)
+    user_cardname = Column(Text, nullable=True)
+    energy_value = Column(Float, nullable=True, default=5.0)
+    sleep_pressure = Column(Float, nullable=True, default=0.0)
+    focus_energy = Column(Float, nullable=True, default=0.5)
+    # 动态兴趣度系统字段
+    base_interest_energy = Column(Float, nullable=True, default=0.5)
+    message_interest_total = Column(Float, nullable=True, default=0.0)
+    message_count = Column(Integer, nullable=True, default=0)
+    action_count = Column(Integer, nullable=True, default=0)
+    reply_count = Column(Integer, nullable=True, default=0)
+    last_interaction_time = Column(Float, nullable=True, default=None)
+    consecutive_no_reply = Column(Integer, nullable=True, default=0)
+    # 消息打断系统字段
+    interruption_count = Column(Integer, nullable=True, default=0)
+
+    __table_args__ = (
+        Index("idx_chatstreams_stream_id", "stream_id"),
+        Index("idx_chatstreams_user_id", "user_id"),
+        Index("idx_chatstreams_group_id", "group_id"),
+    )
+
+
+class LLMUsage(Base):
+    """LLM使用记录模型"""
+
+    __tablename__ = "llm_usage"
+
+    id = Column(Integer, primary_key=True, autoincrement=True)
+    model_name = Column(get_string_field(100), nullable=False, index=True)
+    model_assign_name = Column(get_string_field(100), index=True)  # 添加索引
+    model_api_provider = Column(get_string_field(100), index=True)  # 添加索引
+    user_id = Column(get_string_field(50), nullable=False, index=True)
+    request_type = Column(get_string_field(50), nullable=False, index=True)
+    endpoint = Column(Text, nullable=False)
+    prompt_tokens = Column(Integer, nullable=False)
+    completion_tokens = Column(Integer, nullable=False)
+    time_cost = Column(Float, nullable=True)
+    total_tokens = Column(Integer, nullable=False)
+    cost = Column(Float, nullable=False)
+    status = Column(Text, nullable=False)
+    timestamp = Column(DateTime, nullable=False, index=True, default=datetime.datetime.now)
+
+    __table_args__ = (
+        Index("idx_llmusage_model_name", "model_name"),
+        Index("idx_llmusage_model_assign_name", "model_assign_name"),
+        Index("idx_llmusage_model_api_provider", "model_api_provider"),
+        Index("idx_llmusage_time_cost", "time_cost"),
+        Index("idx_llmusage_user_id", "user_id"),
+        Index("idx_llmusage_request_type", "request_type"),
+        Index("idx_llmusage_timestamp", "timestamp"),
+    )
+
+
+class Emoji(Base):
+    """表情包模型"""
+
+    __tablename__ = "emoji"
+
+    id = Column(Integer, primary_key=True, autoincrement=True)
+    full_path = Column(get_string_field(500), nullable=False, unique=True, index=True)
+    format = Column(Text, nullable=False)
+    emoji_hash = Column(get_string_field(64), nullable=False, index=True)
+    description = Column(Text, nullable=False)
+    query_count = Column(Integer, nullable=False, default=0)
+    is_registered = Column(Boolean, nullable=False, default=False)
+    is_banned = Column(Boolean, nullable=False, default=False)
+    emotion = Column(Text, nullable=True)
+    record_time = Column(Float, nullable=False)
+    register_time = Column(Float, nullable=True)
+    usage_count = Column(Integer, nullable=False, default=0)
+    last_used_time = Column(Float, nullable=True)
+
+    __table_args__ = (
+        Index("idx_emoji_full_path", "full_path"),
+        Index("idx_emoji_hash", "emoji_hash"),
+    )
+
+
+class Messages(Base):
+    """消息模型"""
+
+    __tablename__ = "messages"
+
+    id = Column(Integer, primary_key=True, autoincrement=True)
+    message_id = Column(get_string_field(100), nullable=False, index=True)
+    time = Column(Float, nullable=False)
+    chat_id = Column(get_string_field(64), nullable=False, index=True)
+    reply_to = Column(Text, nullable=True)
+    interest_value = Column(Float, nullable=True)
+    key_words = Column(Text, nullable=True)
+    key_words_lite = Column(Text, nullable=True)
+    is_mentioned = Column(Boolean, nullable=True)
+
+    # 从 chat_info 扁平化而来的字段
+    chat_info_stream_id = Column(Text, nullable=False)
+    chat_info_platform = Column(Text, nullable=False)
+    chat_info_user_platform = Column(Text, nullable=False)
+    chat_info_user_id = Column(Text, nullable=False)
+    chat_info_user_nickname = Column(Text, nullable=False)
+    chat_info_user_cardname = Column(Text, nullable=True)
+    chat_info_group_platform = Column(Text, nullable=True)
+    chat_info_group_id = Column(Text, nullable=True)
+    chat_info_group_name = Column(Text, nullable=True)
+    chat_info_create_time = Column(Float, nullable=False)
+    chat_info_last_active_time = Column(Float, nullable=False)
+
+    # 从顶层 user_info 扁平化而来的字段
+    user_platform = Column(Text, nullable=True)
+    user_id = Column(get_string_field(100), nullable=True, index=True)
+    user_nickname = Column(Text, nullable=True)
+    user_cardname = Column(Text, nullable=True)
+
+    processed_plain_text = Column(Text, nullable=True)
+    display_message = Column(Text, nullable=True)
+    memorized_times = Column(Integer, nullable=False, default=0)
+    priority_mode = Column(Text, nullable=True)
+    priority_info = Column(Text, nullable=True)
+    additional_config = Column(Text, nullable=True)
+    is_emoji = Column(Boolean, nullable=False, default=False)
+    is_picid = Column(Boolean, nullable=False, default=False)
+    is_command = Column(Boolean, nullable=False, default=False)
+    is_notify = Column(Boolean, nullable=False, default=False)
+
+    # 兴趣度系统字段
+    actions = Column(Text, nullable=True)  # JSON格式存储动作列表
+    should_reply = Column(Boolean, nullable=True, default=False)
+    should_act = Column(Boolean, nullable=True, default=False)
+
+    __table_args__ = (
+        Index("idx_messages_message_id", "message_id"),
+        Index("idx_messages_chat_id", "chat_id"),
+        Index("idx_messages_time", "time"),
+        Index("idx_messages_user_id", "user_id"),
+        Index("idx_messages_should_reply", "should_reply"),
+        Index("idx_messages_should_act", "should_act"),
+    )
+
+
+class ActionRecords(Base):
+    """动作记录模型"""
+
+    __tablename__ = "action_records"
+
+    id = Column(Integer, primary_key=True, autoincrement=True)
+    action_id = Column(get_string_field(100), nullable=False, index=True)
+    time = Column(Float, nullable=False)
+    action_name = Column(Text, nullable=False)
+    action_data = Column(Text, nullable=False)
+    action_done = Column(Boolean, nullable=False, default=False)
+    action_build_into_prompt = Column(Boolean, nullable=False, default=False)
+    action_prompt_display = Column(Text, nullable=False)
+    chat_id = Column(get_string_field(64), nullable=False, index=True)
+    chat_info_stream_id = Column(Text, nullable=False)
+    chat_info_platform = Column(Text, nullable=False)
+
+    __table_args__ = (
+        Index("idx_actionrecords_action_id", "action_id"),
+        Index("idx_actionrecords_chat_id", "chat_id"),
+        Index("idx_actionrecords_time", "time"),
+    )
+
+
+class Images(Base):
+    """图像信息模型"""
+
+    __tablename__ = "images"
+
+    id = Column(Integer, primary_key=True, autoincrement=True)
+    image_id = Column(Text, nullable=False, default="")
+    emoji_hash = Column(get_string_field(64), nullable=False, index=True)
+    description = Column(Text, nullable=True)
+    path = Column(get_string_field(500), nullable=False, unique=True)
+    count = Column(Integer, nullable=False, default=1)
+    timestamp = Column(Float, nullable=False)
+    type = Column(Text, nullable=False)
+    vlm_processed = Column(Boolean, nullable=False, default=False)
+
+    __table_args__ = (
+        Index("idx_images_emoji_hash", "emoji_hash"),
+        Index("idx_images_path", "path"),
+    )
+
+
+class ImageDescriptions(Base):
+    """图像描述信息模型"""
+
+    __tablename__ = "image_descriptions"
+
+    id = Column(Integer, primary_key=True, autoincrement=True)
+    type = Column(Text, nullable=False)
+    image_description_hash = Column(get_string_field(64), nullable=False, index=True)
+    description = Column(Text, nullable=False)
+    timestamp = Column(Float, nullable=False)
+
+    __table_args__ = (Index("idx_imagedesc_hash", "image_description_hash"),)
+
+
+class Videos(Base):
+    """视频信息模型"""
+
+    __tablename__ = "videos"
+
+    id = Column(Integer, primary_key=True, autoincrement=True)
+    video_id = Column(Text, nullable=False, default="")
+    video_hash = Column(get_string_field(64), nullable=False, index=True, unique=True)
+    description = Column(Text, nullable=True)
+    count = Column(Integer, nullable=False, default=1)
+    timestamp = Column(Float, nullable=False)
+    vlm_processed = Column(Boolean, nullable=False, default=False)
+
+    # 视频特有属性
+    duration = Column(Float, nullable=True)  # 视频时长（秒）
+    frame_count = Column(Integer, nullable=True)  # 总帧数
+    fps = Column(Float, nullable=True)  # 帧率
+    resolution = Column(Text, nullable=True)  # 分辨率
+    file_size = Column(Integer, nullable=True)  # 文件大小（字节）
+
+    __table_args__ = (
+        Index("idx_videos_video_hash", "video_hash"),
+        Index("idx_videos_timestamp", "timestamp"),
+    )
+
+
+class OnlineTime(Base):
+    """在线时长记录模型"""
+
+    __tablename__ = "online_time"
+
+    id = Column(Integer, primary_key=True, autoincrement=True)
+    timestamp = Column(Text, nullable=False, default=str(datetime.datetime.now))
+    duration = Column(Integer, nullable=False)
+    start_timestamp = Column(DateTime, nullable=False, default=datetime.datetime.now)
+    end_timestamp = 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 = Column(Integer, primary_key=True, autoincrement=True)
+    person_id = Column(get_string_field(100), nullable=False, unique=True, index=True)
+    person_name = Column(Text, nullable=True)
+    name_reason = Column(Text, nullable=True)
+    platform = Column(Text, nullable=False)
+    user_id = Column(get_string_field(50), nullable=False, index=True)
+    nickname = Column(Text, nullable=True)
+    impression = Column(Text, nullable=True)
+    short_impression = Column(Text, nullable=True)
+    points = Column(Text, nullable=True)
+    forgotten_points = Column(Text, nullable=True)
+    info_list = Column(Text, nullable=True)
+    know_times = Column(Float, nullable=True)
+    know_since = Column(Float, nullable=True)
+    last_know = Column(Float, nullable=True)
+    attitude = 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 = Column(Integer, primary_key=True, autoincrement=True)
+    personality_id = Column(get_string_field(100), nullable=False, index=True)
+    personality_description = Column(Text, nullable=False)
+    interest_tags = Column(Text, nullable=False)  # JSON格式存储的兴趣标签列表
+    embedding_model = Column(get_string_field(100), nullable=False, default="text-embedding-ada-002")
+    version = Column(Integer, nullable=False, default=1)
+    last_updated = 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 = Column(Integer, primary_key=True, autoincrement=True)
+    memory_id = Column(get_string_field(64), nullable=False, index=True)
+    chat_id = Column(Text, nullable=True)
+    memory_text = Column(Text, nullable=True)
+    keywords = Column(Text, nullable=True)
+    create_time = Column(Float, nullable=True)
+    last_view_time = 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 = Column(Integer, primary_key=True, autoincrement=True)
+    chat_id = Column(get_string_field(64), nullable=False, index=True)
+    trigger_text = Column(Text, nullable=True)
+    response_text = Column(Text, nullable=True)
+    trigger_info_json = Column(Text, nullable=True)
+    response_info_json = Column(Text, nullable=True)
+    timing_results_json = Column(Text, nullable=True)
+    chat_history_json = Column(Text, nullable=True)
+    chat_history_in_thinking_json = Column(Text, nullable=True)
+    chat_history_after_response_json = Column(Text, nullable=True)
+    heartflow_data_json = Column(Text, nullable=True)
+    reasoning_data_json = Column(Text, nullable=True)
+    created_at = 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 = Column(Integer, primary_key=True, autoincrement=True)
+    concept = Column(get_string_field(255), nullable=False, unique=True, index=True)
+    memory_items = Column(Text, nullable=False)
+    hash = Column(Text, nullable=False)
+    weight = Column(Float, nullable=False, default=1.0)
+    created_time = Column(Float, nullable=False)
+    last_modified = Column(Float, nullable=False)
+
+    __table_args__ = (Index("idx_graphnodes_concept", "concept"),)
+
+
+class GraphEdges(Base):
+    """记忆图边模型"""
+
+    __tablename__ = "graph_edges"
+
+    id = Column(Integer, primary_key=True, autoincrement=True)
+    source = Column(get_string_field(255), nullable=False, index=True)
+    target = Column(get_string_field(255), nullable=False, index=True)
+    strength = Column(Integer, nullable=False)
+    hash = Column(Text, nullable=False)
+    created_time = Column(Float, nullable=False)
+    last_modified = 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 = Column(Integer, primary_key=True, autoincrement=True)
+    date = Column(get_string_field(10), nullable=False, unique=True, index=True)  # YYYY-MM-DD格式
+    schedule_data = Column(Text, nullable=False)  # JSON格式的日程数据
+    created_at = Column(DateTime, nullable=False, default=datetime.datetime.now)
+    updated_at = 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 = Column(Integer, primary_key=True, autoincrement=True)
+    datetime_hour = Column(
+        get_string_field(13), nullable=False, unique=True, index=True
+    )  # YYYY-MM-DD HH格式，精确到小时
+    activity = Column(Text, nullable=False)  # 该小时的活动内容
+    is_processed = Column(Boolean, nullable=False, default=False)  # 是否已处理
+    processed_at = Column(DateTime, nullable=True)  # 处理时间
+    story_content = Column(Text, nullable=True)  # 生成的说说内容
+    send_success = Column(Boolean, nullable=False, default=False)  # 是否发送成功
+    created_at = Column(DateTime, nullable=False, default=datetime.datetime.now)
+    updated_at = 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 = Column(Integer, primary_key=True, autoincrement=True)
+    total_messages = Column(Integer, nullable=False, default=0)
+    """总处理消息数"""
+
+    detected_injections = Column(Integer, nullable=False, default=0)
+    """检测到的注入攻击数"""
+
+    blocked_messages = Column(Integer, nullable=False, default=0)
+    """被阻止的消息数"""
+
+    shielded_messages = Column(Integer, nullable=False, default=0)
+    """被加盾的消息数"""
+
+    processing_time_total = Column(Float, nullable=False, default=0.0)
+    """总处理时间"""
+
+    total_process_time = Column(Float, nullable=False, default=0.0)
+    """累计总处理时间"""
+
+    last_process_time = Column(Float, nullable=False, default=0.0)
+    """最近一次处理时间"""
+
+    error_count = Column(Integer, nullable=False, default=0)
+    """错误计数"""
+
+    start_time = Column(DateTime, nullable=False, default=datetime.datetime.now)
+    """统计开始时间"""
+
+    created_at = Column(DateTime, nullable=False, default=datetime.datetime.now)
+    """记录创建时间"""
+
+    updated_at = 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 = Column(Integer, primary_key=True, autoincrement=True)
+    cache_key = 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 = Column(Text, nullable=False)
+    """缓存的数据，JSON格式"""
+
+    expires_at = Column(Float, nullable=False, index=True)
+    """过期时间戳"""
+
+    tool_name = Column(get_string_field(100), nullable=False, index=True)
+    """工具名称"""
+
+    created_at = Column(Float, nullable=False, default=lambda: time.time())
+    """创建时间戳"""
+
+    last_accessed = Column(Float, nullable=False, default=lambda: time.time())
+    """最后访问时间戳"""
+
+    access_count = 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 = Column(Integer, primary_key=True, autoincrement=True)
+    plan_text = Column(Text, nullable=False)
+    target_month = Column(String(7), nullable=False, index=True)  # "YYYY-MM"
+    status = Column(
+        get_string_field(20), nullable=False, default="active", index=True
+    )  # 'active', 'completed', 'archived'
+    usage_count = Column(Integer, nullable=False, default=0)
+    last_used_date = Column(String(10), nullable=True, index=True)  # "YYYY-MM-DD" format
+    created_at = Column(DateTime, nullable=False, default=datetime.datetime.now)
+
+    # 保留 is_deleted 字段以兼容现有数据，但标记为已弃用
+    is_deleted = Column(Boolean, nullable=False, default=False)
+
+    __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"),
+        # 保留旧索引以兼容
+        Index("idx_monthlyplan_target_month_is_deleted", "target_month", "is_deleted"),
+    )
+
+
+# 数据库引擎和会话管理
+_engine = None
+_SessionLocal = None
+
+
+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}"
+
+
+async def initialize_database():
+    """初始化异步数据库引擎和会话"""
+    global _engine, _SessionLocal
+
+    if _engine is not None:
+        return _engine, _SessionLocal
+
+    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":
+        # MySQL连接池配置 - 异步引擎使用默认连接池
+        engine_kwargs.update(
+            {
+                "pool_size": config.connection_pool_size,
+                "max_overflow": config.connection_pool_size * 2,
+                "pool_timeout": config.connection_timeout,
+                "pool_recycle": 3600,  # 1小时回收连接
+                "pool_pre_ping": True,  # 连接前ping检查
+                "connect_args": {
+                    "autocommit": config.mysql_autocommit,
+                    "charset": config.mysql_charset,
+                    "connect_timeout": config.connection_timeout,
+                },
+            }
+        )
+    else:
+        # SQLite配置 - aiosqlite不支持连接池参数
+        engine_kwargs.update(
+            {
+                "connect_args": {
+                    "check_same_thread": False,
+                    "timeout": 60,  # 增加超时时间
+                },
+            }
+        )
+
+    _engine = create_async_engine(database_url, **engine_kwargs)
+    _SessionLocal = async_sessionmaker(bind=_engine, class_=AsyncSession, expire_on_commit=False)
+
+    # 调用新的迁移函数，它会处理表的创建和列的添加
+    from src.common.database.db_migration import check_and_migrate_database
+
+    await check_and_migrate_database()
+
+    # 如果是 SQLite，启用 WAL 模式以提高并发性能
+    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
+
+
+@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 = Column(Integer, primary_key=True, autoincrement=True)
+    node_name = Column(get_string_field(255), nullable=False, unique=True, index=True)  # 权限节点名称
+    description = Column(Text, nullable=False)  # 权限描述
+    plugin_name = Column(get_string_field(100), nullable=False, index=True)  # 所属插件
+    default_granted = Column(Boolean, default=False, nullable=False)  # 默认是否授权
+    created_at = Column(DateTime, default=datetime.datetime.utcnow, nullable=False)  # 创建时间
+
+    __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 = Column(Integer, primary_key=True, autoincrement=True)
+    platform = Column(get_string_field(50), nullable=False, index=True)  # 平台类型
+    user_id = Column(get_string_field(100), nullable=False, index=True)  # 用户ID
+    permission_node = Column(get_string_field(255), nullable=False, index=True)  # 权限节点名称
+    granted = Column(Boolean, default=True, nullable=False)  # 是否授权
+    granted_at = Column(DateTime, default=datetime.datetime.utcnow, nullable=False)  # 授权时间
+    granted_by = Column(get_string_field(100), nullable=True)  # 授权者信息
+
+    __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 = Column(Integer, primary_key=True, autoincrement=True)
+    user_id = Column(get_string_field(100), nullable=False, unique=True, index=True)  # 用户ID
+    user_name = Column(get_string_field(100), nullable=True)  # 用户名
+    relationship_text = Column(Text, nullable=True)  # 关系印象描述
+    relationship_score = Column(Float, nullable=False, default=0.3)  # 关系分数(0-1)
+    last_updated = Column(Float, nullable=False, default=time.time)  # 最后更新时间
+    created_at = Column(DateTime, default=datetime.datetime.utcnow, nullable=False)  # 创建时间
+
+    __table_args__ = (
+        Index("idx_user_relationship_id", "user_id"),
+        Index("idx_relationship_score", "relationship_score"),
+        Index("idx_relationship_updated", "last_updated"),
+    )