Merge branch 'debug' into Willing_cycles_and_better_response

.github/workflows/ruff.yml

@@ -0,0 +1,8 @@
+name: Ruff
+on: [ push, pull_request ]
+jobs:
+  ruff:
+    runs-on: ubuntu-latest
+    steps:
+      - uses: actions/checkout@v4
+      - uses: astral-sh/ruff-action@v3

.gitignore

@@ -190,7 +190,6 @@ cython_debug/
 
 # PyPI configuration file
 .pypirc
-.env
 
 # jieba
 jieba.cache
@@ -199,4 +198,9 @@ jieba.cache
 !.vscode/settings.json
 
 # direnv
-/.direnv
+/.direnv
+
+# JetBrains
+.idea
+*.iml
+*.ipr

.pre-commit-config.yaml

@@ -0,0 +1,10 @@
+repos:
+- repo: https://github.com/astral-sh/ruff-pre-commit
+  # Ruff version.
+  rev: v0.9.10
+  hooks:
+    # Run the linter.
+    - id: ruff
+      args: [ --fix ]
+    # Run the formatter.
+    - id: ruff-format

README.md

@@ -61,6 +61,7 @@
 
 -  📦 **Windows 一键傻瓜式部署**：请运行项目根目录中的 `run.bat`，部署完成后请参照后续配置指南进行配置
 
+-  📦 Linux 自动部署（实验） ：请下载并运行项目根目录中的`run.sh`并按照提示安装，部署完成后请参照后续配置指南进行配置
 
 - [📦 Windows 手动部署指南 ](docs/manual_deploy_windows.md)
 

bot.py

@@ -12,26 +12,11 @@ from loguru import logger
 from nonebot.adapters.onebot.v11 import Adapter
 import platform
 
-from src.common.database import Database
-
 # 获取没有加载env时的环境变量
 env_mask = {key: os.getenv(key) for key in os.environ}
 
 uvicorn_server = None
 
-# 配置日志
-log_path = os.path.join(os.getcwd(), "logs")
-if not os.path.exists(log_path):
-    os.makedirs(log_path)
-
-# 添加文件日志，启用rotation和retention
-logger.add(
-    os.path.join(log_path, "maimbot_{time:YYYY-MM-DD}.log"),
-    rotation="00:00",  # 每天0点创建新文件
-    retention="30 days",  # 保留30天的日志
-    level="INFO",
-    encoding="utf-8"
-)
 
 def easter_egg():
     # 彩蛋
@@ -78,7 +63,7 @@ def init_env():
 
     # 首先加载基础环境变量.env
     if os.path.exists(".env"):
-        load_dotenv(".env",override=True)
+        load_dotenv(".env", override=True)
         logger.success("成功加载基础环境变量配置")
 
 
@@ -92,10 +77,7 @@ def load_env():
         logger.success("加载开发环境变量配置")
         load_dotenv(".env.dev", override=True)  # override=True 允许覆盖已存在的环境变量
 
-    fn_map = {
+    fn_map = {"prod": prod, "dev": dev}
-        "prod": prod,
-        "dev": dev
-    }
 
     env = os.getenv("ENVIRONMENT")
     logger.info(f"[load_env] 当前的 ENVIRONMENT 变量值：{env}")
@@ -111,40 +93,45 @@ def load_env():
         logger.error(f"ENVIRONMENT 配置错误，请检查 .env 文件中的 ENVIRONMENT 变量及对应 .env.{env} 是否存在")
         RuntimeError(f"ENVIRONMENT 配置错误，请检查 .env 文件中的 ENVIRONMENT 变量及对应 .env.{env} 是否存在")
 
-def init_database():
-    Database.initialize(
-        uri=os.getenv("MONGODB_URI"),
-        host=os.getenv("MONGODB_HOST", "127.0.0.1"),
-        port=int(os.getenv("MONGODB_PORT", "27017")),
-        db_name=os.getenv("DATABASE_NAME", "MegBot"),
-        username=os.getenv("MONGODB_USERNAME"),
-        password=os.getenv("MONGODB_PASSWORD"),
-        auth_source=os.getenv("MONGODB_AUTH_SOURCE"),
-    )
-    
 
 def load_logger():
-    logger.remove()  # 移除默认配置
+    logger.remove()
-    if os.getenv("ENVIRONMENT") == "dev":
-        logger.add(
-            sys.stderr,
-            format="<green>{time:YYYY-MM-DD HH:mm:ss.SSS}</green> <fg #777777>|</> <level>{level: <7}</level> <fg "
-                   "#777777>|</> <cyan>{name:.<8}</cyan>:<cyan>{function:.<8}</cyan>:<cyan>{line: >4}</cyan> <fg "
-                   "#777777>-</> <level>{message}</level>",
-            colorize=True,
-            level=os.getenv("LOG_LEVEL", "DEBUG"),  # 根据环境设置日志级别，默认为DEBUG
-        )
-    else:
-        logger.add(
-            sys.stderr,
-            format="<green>{time:YYYY-MM-DD HH:mm:ss.SSS}</green> <fg #777777>|</> <level>{level: <7}</level> <fg "
-                "#777777>|</> <cyan>{name:.<8}</cyan>:<cyan>{function:.<8}</cyan>:<cyan>{line: >4}</cyan> <fg "
-                "#777777>-</> <level>{message}</level>",
-            colorize=True,
-            level=os.getenv("LOG_LEVEL", "INFO"),  # 根据环境设置日志级别，默认为INFO
-            filter=lambda record: "nonebot" not in record["name"]
-        )
 
+    # 配置日志基础路径
+    log_path = os.path.join(os.getcwd(), "logs")
+    if not os.path.exists(log_path):
+        os.makedirs(log_path)
+
+    current_env = os.getenv("ENVIRONMENT", "dev")
+
+    # 公共配置参数
+    log_level = os.getenv("LOG_LEVEL", "INFO" if current_env == "prod" else "DEBUG")
+    log_filter = lambda record: (
+        ("nonebot" not in record["name"] or record["level"].no >= logger.level("ERROR").no)
+        if current_env == "prod"
+        else True
+    )
+    log_format = (
+        "<green>{time:YYYY-MM-DD HH:mm:ss.SSS}</green> "
+        "<fg #777777>|</> <level>{level: <7}</level> "
+        "<fg #777777>|</> <cyan>{name:.<8}</cyan>:<cyan>{function:.<8}</cyan>:<cyan>{line: >4}</cyan> "
+        "<fg #777777>-</> <level>{message}</level>"
+    )
+
+    # 日志文件储存至/logs
+    logger.add(
+        os.path.join(log_path, "maimbot_{time:YYYY-MM-DD}.log"),
+        rotation="00:00",
+        retention="30 days",
+        format=log_format,
+        colorize=False,
+        level=log_level,
+        filter=log_filter,
+        encoding="utf-8",
+    )
+
+    # 终端输出
+    logger.add(sys.stderr, format=log_format, colorize=True, level=log_level, filter=log_filter)
 
 
 def scan_provider(env_config: dict):
@@ -174,10 +161,7 @@ def scan_provider(env_config: dict):
     # 检查每个 provider 是否同时存在 url 和 key
     for provider_name, config in provider.items():
         if config["url"] is None or config["key"] is None:
-            logger.error(
+            logger.error(f"provider 内容：{config}\nenv_config 内容：{env_config}")
-                f"provider 内容：{config}\n"
-                f"env_config 内容：{env_config}"
-            )
             raise ValueError(f"请检查 '{provider_name}' 提供商配置是否丢失 BASE_URL 或 KEY 环境变量")
 
 
@@ -206,7 +190,7 @@ async def uvicorn_main():
         reload=os.getenv("ENVIRONMENT") == "dev",
         timeout_graceful_shutdown=5,
         log_config=None,
-        access_log=False
+        access_log=False,
     )
     server = uvicorn.Server(config)
     uvicorn_server = server
@@ -216,14 +200,13 @@ async def uvicorn_main():
 def raw_main():
     # 利用 TZ 环境变量设定程序工作的时区
     # 仅保证行为一致，不依赖 localtime()，实际对生产环境几乎没有作用
-    if platform.system().lower() != 'windows':
+    if platform.system().lower() != "windows":
         time.tzset()
 
     easter_egg()
     init_config()
     init_env()
     load_env()
-    init_database() # 加载完成环境后初始化database
     load_logger()
 
     env_config = {key: os.getenv(key) for key in os.environ}

docs/avatars/run.bat

@@ -0,0 +1 @@
+gource gource.log --user-image-dir docs/avatars/ --default-user-image docs/avatars/default.png

docs/manual_deploy_linux.md

@@ -121,6 +121,7 @@ sudo nano /etc/systemd/system/maimbot.service
 输入以下内容：
 
 `<maimbot_directory>`：你的maimbot目录
+
 `<venv_directory>`：你的venv环境（就是上文创建环境后，执行的代码`source maimbot/bin/activate`中source后面的路径的绝对路径）
 
 ```ini

docs/synology_deploy.md

@@ -0,0 +1,67 @@
+# 群晖 NAS 部署指南
+
+**笔者使用的是 DSM 7.2.2，其他 DSM 版本的操作可能不完全一样**
+**需要使用 Container Manager，群晖的部分部分入门级 NAS 可能不支持**
+
+## 部署步骤
+
+### 创建配置文件目录
+
+打开 `DSM ➡️ 控制面板 ➡️ 共享文件夹`，点击 `新增` ，创建一个共享文件夹
+只需要设置名称，其他设置均保持默认即可。如果你已经有 docker 专用的共享文件夹了，就跳过这一步
+
+打开 `DSM ➡️ FileStation`， 在共享文件夹中创建一个 `MaiMBot` 文件夹
+
+### 准备配置文件
+
+docker-compose.yml: https://github.com/SengokuCola/MaiMBot/blob/main/docker-compose.yml
+下载后打开，将 `services-mongodb-image` 修改为 `mongo:4.4.24`。这是因为最新的 MongoDB 强制要求 AVX 指令集，而群晖似乎不支持这个指令集
+![](https://raw.githubusercontent.com/ProperSAMA/MaiMBot/refs/heads/debug/docs/synology_docker-compose.png)
+
+bot_config.toml: https://github.com/SengokuCola/MaiMBot/blob/main/template/bot_config_template.toml
+下载后，重命名为 `bot_config.toml`
+打开它，按自己的需求填写配置文件
+
+.env.prod: https://github.com/SengokuCola/MaiMBot/blob/main/template.env
+下载后，重命名为 `.env.prod`
+按下图修改 mongodb 设置，使用  `MONGODB_URI`
+![](https://raw.githubusercontent.com/ProperSAMA/MaiMBot/refs/heads/debug/docs/synology_.env.prod.png)
+
+把 `bot_config.toml` 和 `.env.prod` 放入之前创建的 `MaiMBot`文件夹
+
+#### 如何下载？
+
+点这里！![](https://raw.githubusercontent.com/ProperSAMA/MaiMBot/refs/heads/debug/docs/synology_how_to_download.png)
+
+### 创建项目
+
+打开 `DSM ➡️ ContainerManager ➡️ 项目`，点击 `新增` 创建项目，填写以下内容：
+
+- 项目名称： `maimbot`
+- 路径：之前创建的 `MaiMBot` 文件夹
+- 来源： `上传 docker-compose.yml`
+- 文件：之前下载的 `docker-compose.yml` 文件
+
+图例：
+
+![](https://raw.githubusercontent.com/ProperSAMA/MaiMBot/refs/heads/debug/docs/synology_create_project.png)
+
+一路点下一步，等待项目创建完成
+
+### 设置 Napcat
+
+1. 登陆 napcat
+   打开 napcat： `http://<你的nas地址>:6099` ，输入token登陆
+   token可以打开 `DSM ➡️ ContainerManager ➡️ 项目 ➡️ MaiMBot ➡️ 容器 ➡️ Napcat ➡️ 日志`，找到类似 `[WebUi] WebUi Local Panel Url: http://127.0.0.1:6099/webui?token=xxxx` 的日志
+   这个 `token=` 后面的就是你的 napcat token
+
+2. 按提示，登陆你给麦麦准备的QQ小号
+
+3. 设置 websocket 客户端
+   `网络配置 -> 新建 -> Websocket客户端`，名称自定，URL栏填入 `ws://maimbot:8080/onebot/v11/ws`，启用并保存即可。
+   若修改过容器名称，则替换 `maimbot` 为你自定的名称
+
+### 部署完成
+
+找个群，发送 `麦麦，你在吗` 之类的
+如果一切正常，应该能正常回复了

run.sh

@@ -0,0 +1,278 @@
+#!/bin/bash
+
+# Maimbot 一键安装脚本 by Cookie987
+# 适用于Debian系
+# 请小心使用任何一键脚本！
+
+# 如无法访问GitHub请修改此处镜像地址
+
+LANG=C.UTF-8
+
+GITHUB_REPO="https://ghfast.top/https://github.com/SengokuCola/MaiMBot.git"
+
+# 颜色输出
+GREEN="\e[32m"
+RED="\e[31m"
+RESET="\e[0m"
+
+# 需要的基本软件包
+REQUIRED_PACKAGES=("git" "sudo" "python3" "python3-venv" "curl" "gnupg" "python3-pip")
+
+# 默认项目目录
+DEFAULT_INSTALL_DIR="/opt/maimbot"
+
+# 服务名称
+SERVICE_NAME="maimbot"
+
+IS_INSTALL_MONGODB=false
+IS_INSTALL_NAPCAT=false
+
+# 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}"
+    apt update && apt install -y whiptail
+fi
+
+get_os_info() {
+    if command -v lsb_release &>/dev/null; then
+        OS_INFO=$(lsb_release -d | cut -f2)
+    elif [[ -f /etc/os-release ]]; then
+        OS_INFO=$(grep "^PRETTY_NAME=" /etc/os-release | cut -d '"' -f2)
+    else
+        OS_INFO="Unknown OS"
+    fi
+    echo "$OS_INFO"
+}
+
+# 检查系统
+check_system() {
+    # 检查是否为 root 用户
+    if [[ "$(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
+            whiptail --title "🚫 不支持的系统" --msgbox "此脚本仅支持 Debian 12 (Bookworm)！\n当前系统: $PRETTY_NAME\n安装已终止。" 10 60
+            exit 1
+        fi
+    else
+        whiptail --title "⚠️ 无法检测系统" --msgbox "无法识别系统版本，安装已终止。" 10 60
+        exit 1
+    fi
+}
+
+# 3/6: 询问用户是否安装缺失的软件包
+install_packages() {
+    missing_packages=()
+    for package in "${REQUIRED_PACKAGES[@]}"; do
+        if ! dpkg -s "$package" &>/dev/null; then
+            missing_packages+=("$package")
+        fi
+    done
+
+    if [[ ${#missing_packages[@]} -gt 0 ]]; then
+        whiptail --title "📦 [3/6] 软件包检查" --yesno "检测到以下必须的依赖项目缺失:\n${missing_packages[*]}\n\n是否要自动安装？" 12 60
+        if [[ $? -eq 0 ]]; then
+            return 0
+        else
+            whiptail --title "⚠️ 注意" --yesno "某些必要的依赖项未安装，可能会影响运行！\n是否继续？" 10 60 || exit 1
+        fi
+    fi
+}
+
+# 4/6: Python 版本检查
+check_python() {
+    PYTHON_VERSION=$(python3 -c 'import sys; print(f"{sys.version_info.major}.{sys.version_info.minor}")')
+
+    python3 -c "import sys; exit(0) if sys.version_info >= (3,9) else exit(1)"
+    if [[ $? -ne 0 ]]; then
+        whiptail --title "⚠️ [4/6] Python 版本过低" --msgbox "检测到 Python 版本为 $PYTHON_VERSION，需要 3.9 或以上！\n请升级 Python 后重新运行本脚本。" 10 60
+        exit 1
+    fi
+}
+
+# 5/6: 选择分支
+choose_branch() {
+    BRANCH=$(whiptail --title "🔀 [5/6] 选择 Maimbot 分支" --menu "请选择要安装的 Maimbot 分支：" 15 60 2 \
+        "main" "稳定版本（推荐）" \
+        "debug" "开发版本（可能不稳定）" 3>&1 1>&2 2>&3)
+
+    if [[ -z "$BRANCH" ]]; then
+        BRANCH="main"
+        whiptail --title "🔀 默认选择" --msgbox "未选择分支，默认安装稳定版本（main）" 10 60
+    fi
+}
+
+# 6/6: 选择安装路径
+choose_install_dir() {
+    INSTALL_DIR=$(whiptail --title "📂 [6/6] 选择安装路径" --inputbox "请输入 Maimbot 的安装目录：" 10 60 "$DEFAULT_INSTALL_DIR" 3>&1 1>&2 2>&3)
+
+    if [[ -z "$INSTALL_DIR" ]]; then
+        whiptail --title "⚠️ 取消输入" --yesno "未输入安装路径，是否退出安装？" 10 60
+        if [[ $? -ne 0 ]]; then
+            INSTALL_DIR="$DEFAULT_INSTALL_DIR"
+        else
+            exit 1
+        fi
+    fi
+}
+
+# 显示确认界面
+confirm_install() {
+    local confirm_message="请确认以下更改:\n\n"
+
+    if [[ ${#missing_packages[@]} -gt 0 ]]; then
+        confirm_message+="📦 安装缺失的依赖项: ${missing_packages[*]}\n"
+    else
+        confirm_message+="✅ 所有依赖项已安装\n"
+    fi
+
+    confirm_message+="📂 安装麦麦Bot到: $INSTALL_DIR\n"
+    confirm_message+="🔀 分支: $BRANCH\n"
+
+    if [[ "$MONGODB_INSTALLED" == "true" ]]; then
+        confirm_message+="✅ MongoDB 已安装\n"
+    else
+        if [[ "$IS_INSTALL_MONGODB" == "true" ]]; then
+            confirm_message+="📦 安装 MongoDB\n"
+        fi
+    fi
+
+    if [[ "$NAPCAT_INSTALLED" == "true" ]]; then
+        confirm_message+="✅ NapCat 已安装\n"
+    else
+        if [[ "$IS_INSTALL_NAPCAT" == "true" ]]; then
+            confirm_message+="📦 安装 NapCat\n"
+        fi
+    fi
+
+    confirm_message+="🛠️ 添加麦麦Bot作为系统服务 ($SERVICE_NAME.service)\n"
+
+    confitm_message+="\n\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_message\n\n是否继续安装？" 15 60
+    if [[ $? -ne 0 ]]; then
+        whiptail --title "🚫 取消安装" --msgbox "安装已取消。" 10 60
+        exit 1
+    fi
+}
+
+check_mongodb() {
+    if command -v mongod &>/dev/null; then
+        MONGO_INSTALLED=true
+    else
+        MONGO_INSTALLED=false
+    fi
+}
+
+# 安装 MongoDB
+install_mongodb() {
+    if [[ "$MONGO_INSTALLED" == "true" ]]; then
+        return 0
+    fi
+
+    whiptail --title "📦 [3/6] 软件包检查" --yesno "检测到未安装MongoDB，是否安装？\n如果您想使用远程数据库，请跳过此步。" 10 60
+    if [[ $? -ne 0 ]]; then
+        return 1
+    fi
+    IS_INSTALL_MONGODB=true
+}
+
+check_napcat() {
+    if command -v napcat &>/dev/null; then
+        NAPCAT_INSTALLED=true
+    else
+        NAPCAT_INSTALLED=false
+    fi
+}
+
+install_napcat() {
+    if [[ "$NAPCAT_INSTALLED" == "true" ]]; then
+        return 0
+    fi
+
+    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
+    if [[ $? -ne 0 ]]; then
+        return 1
+    fi
+    IS_INSTALL_NAPCAT=true
+}
+
+# 运行安装步骤
+check_system
+check_mongodb
+check_napcat
+install_packages
+install_mongodb
+install_napcat
+check_python
+choose_branch
+choose_install_dir
+confirm_install
+
+# 开始安装
+whiptail --title "🚀 开始安装" --msgbox "所有环境检查完毕，即将开始安装麦麦Bot！" 10 60
+
+echo -e "${GREEN}安装依赖项...${RESET}"
+
+apt update && apt install -y "${missing_packages[@]}"
+
+
+if [[ "$IS_INSTALL_MONGODB" == "true" ]]; then
+    echo -e "${GREEN}安装 MongoDB...${RESET}"
+    curl -fsSL https://www.mongodb.org/static/pgp/server-8.0.asc | gpg -o /usr/share/keyrings/mongodb-server-8.0.gpg --dearmor
+    echo "deb [ signed-by=/usr/share/keyrings/mongodb-server-8.0.gpg ] http://repo.mongodb.org/apt/debian bookworm/mongodb-org/8.0 main" | sudo tee /etc/apt/sources.list.d/mongodb-org-8.0.list
+    apt-get update
+    apt-get install -y mongodb-org
+
+    systemctl enable mongod
+    systemctl start mongod
+fi
+
+if [[ "$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
+fi
+
+echo -e "${GREEN}创建 Python 虚拟环境...${RESET}"
+mkdir -p "$INSTALL_DIR"
+cd "$INSTALL_DIR" || exit
+python3 -m venv venv
+source venv/bin/activate
+
+echo -e "${GREEN}克隆仓库...${RESET}"
+# 安装 Maimbot
+mkdir -p "$INSTALL_DIR/repo"
+cd "$INSTALL_DIR/repo" || exit 1
+git clone -b "$BRANCH" $GITHUB_REPO .
+
+echo -e "${GREEN}安装 Python 依赖...${RESET}"
+pip install -r requirements.txt
+
+echo -e "${GREEN}设置服务...${RESET}"
+
+# 设置 Maimbot 服务
+cat <<EOF | tee /etc/systemd/system/$SERVICE_NAME.service
+[Unit]
+Description=MaiMbot 麦麦
+After=network.target mongod.service
+
+[Service]
+Type=simple
+WorkingDirectory=$INSTALL_DIR/repo/
+ExecStart=$INSTALL_DIR/venv/bin/python3 bot.py
+ExecStop=/bin/kill -2 $MAINPID
+Restart=always
+RestartSec=10s
+
+[Install]
+WantedBy=multi-user.target
+EOF
+
+systemctl daemon-reload
+systemctl enable maimbot
+systemctl start maimbot
+
+whiptail --title "🎉 安装完成" --msgbox "麦麦Bot安装完成！\n已经启动麦麦Bot服务。\n\n安装路径: $INSTALL_DIR\n分支: $BRANCH" 12 60

src/common/database.py

@@ -1,73 +1,51 @@
-from typing import Optional
+import os
+from typing import cast
 from pymongo import MongoClient
-from pymongo.database import Database as MongoDatabase
+from pymongo.database import Database
 
-class Database:
+_client = None
-    _instance: Optional["Database"] = None
+_db = None
-    
-    def __init__(
-        self,
-        host: str,
-        port: int,
-        db_name: str,
-        username: Optional[str] = None,
-        password: Optional[str] = None,
-        auth_source: Optional[str] = None,
-        uri: Optional[str] = None,
-    ):
-        if uri and uri.startswith("mongodb://"):
-            # 优先使用URI连接
-            self.client = MongoClient(uri)
-        elif username and password:
-            # 如果有用户名和密码，使用认证连接
-            self.client = MongoClient(
-                host, port, username=username, password=password, authSource=auth_source
-            )
-        else:
-            # 否则使用无认证连接
-            self.client = MongoClient(host, port)
-        self.db: MongoDatabase = self.client[db_name]
-        
-    @classmethod
-    def initialize(
-        cls,
-        host: str,
-        port: int,
-        db_name: str,
-        username: Optional[str] = None,
-        password: Optional[str] = None,
-        auth_source: Optional[str] = None,
-        uri: Optional[str] = None,
-    ) -> MongoDatabase:
-        if cls._instance is None:
-            cls._instance = cls(
-                host, port, db_name, username, password, auth_source, uri
-            )
-        return cls._instance.db
-        
-    @classmethod
-    def get_instance(cls) -> MongoDatabase:
-        if cls._instance is None:
-            raise RuntimeError("Database not initialized")
-        return cls._instance.db
 
 
-    #测试用
+def __create_database_instance():
-    
+    uri = os.getenv("MONGODB_URI")
-    def get_random_group_messages(self, group_id: str, limit: int = 5):
+    host = os.getenv("MONGODB_HOST", "127.0.0.1")
-        # 先随机获取一条消息
+    port = int(os.getenv("MONGODB_PORT", "27017"))
-        random_message = list(self.db.messages.aggregate([
+    db_name = os.getenv("DATABASE_NAME", "MegBot")
-            {"$match": {"group_id": group_id}},
+    username = os.getenv("MONGODB_USERNAME")
-            {"$sample": {"size": 1}}
+    password = os.getenv("MONGODB_PASSWORD")
-        ]))[0]
+    auth_source = os.getenv("MONGODB_AUTH_SOURCE")
-        
+
-        # 获取该消息之后的消息
+    if uri and uri.startswith("mongodb://"):
-        subsequent_messages = list(self.db.messages.find({
+        # 优先使用URI连接
-            "group_id": group_id,
+        return MongoClient(uri)
-            "time": {"$gt": random_message["time"]}
+
-        }).sort("time", 1).limit(limit))
+    if username and password:
-        
+        # 如果有用户名和密码，使用认证连接
-        # 将随机消息和后续消息合并
+        return MongoClient(host, port, username=username, password=password, authSource=auth_source)
-        messages = [random_message] + subsequent_messages
+
-        
+    # 否则使用无认证连接
-        return messages
+    return MongoClient(host, port)
+
+
+def get_db():
+    """获取数据库连接实例，延迟初始化。"""
+    global _client, _db
+    if _client is None:
+        _client = __create_database_instance()
+        _db = _client[os.getenv("DATABASE_NAME", "MegBot")]
+    return _db
+
+
+class DBWrapper:
+    """数据库代理类，保持接口兼容性同时实现懒加载。"""
+
+    def __getattr__(self, name):
+        return getattr(get_db(), name)
+
+    def __getitem__(self, key):
+        return get_db()[key]
+
+
+# 全局数据库访问点
+db: Database = DBWrapper()

src/gui/reasoning_gui.py

@@ -7,7 +7,7 @@ from datetime import datetime
 from typing import Dict, List
 from loguru import logger
 from typing import Optional
-from ..common.database import Database
+
 
 import customtkinter as ctk
 from dotenv import load_dotenv
@@ -16,6 +16,8 @@ from dotenv import load_dotenv
 current_dir = os.path.dirname(os.path.abspath(__file__))
 # 获取项目根目录
 root_dir = os.path.abspath(os.path.join(current_dir, '..', '..'))
+sys.path.insert(0, root_dir)
+from src.common.database import db
 
 # 加载环境变量
 if os.path.exists(os.path.join(root_dir, '.env.dev')):
@@ -44,28 +46,6 @@ class ReasoningGUI:
         self.root.geometry('800x600')
         self.root.protocol("WM_DELETE_WINDOW", self._on_closing)
 
-        # 初始化数据库连接
-        try:
-            self.db = Database.get_instance()
-            logger.success("数据库连接成功")
-        except RuntimeError:
-            logger.warning("数据库未初始化，正在尝试初始化...")
-            try:
-                Database.initialize(
-                    uri=os.getenv("MONGODB_URI"),
-                    host=os.getenv("MONGODB_HOST", "127.0.0.1"),
-                    port=int(os.getenv("MONGODB_PORT", "27017")),
-                    db_name=os.getenv("DATABASE_NAME", "MegBot"),
-                    username=os.getenv("MONGODB_USERNAME"),
-                    password=os.getenv("MONGODB_PASSWORD"),
-                    auth_source=os.getenv("MONGODB_AUTH_SOURCE"),
-                )
-                self.db = Database.get_instance()
-                logger.success("数据库初始化成功")
-            except Exception:
-                logger.exception("数据库初始化失败")
-                sys.exit(1)
-
         # 存储群组数据
         self.group_data: Dict[str, List[dict]] = {}
 
@@ -264,11 +244,11 @@ class ReasoningGUI:
                 logger.debug(f"查询条件: {query}")
 
                 # 先获取一条记录检查时间格式
-                sample = self.db.reasoning_logs.find_one()
+                sample = db.reasoning_logs.find_one()
                 if sample:
                     logger.debug(f"样本记录时间格式: {type(sample['time'])} 值: {sample['time']}")
 
-                cursor = self.db.reasoning_logs.find(query).sort("time", -1)
+                cursor = db.reasoning_logs.find(query).sort("time", -1)
                 new_data = {}
                 total_count = 0
 
@@ -333,17 +313,6 @@ class ReasoningGUI:
 
 
 def main():
-    """主函数"""
-    Database.initialize(
-        uri=os.getenv("MONGODB_URI"),
-        host=os.getenv("MONGODB_HOST", "127.0.0.1"),
-        port=int(os.getenv("MONGODB_PORT", "27017")),
-        db_name=os.getenv("DATABASE_NAME", "MegBot"),
-        username=os.getenv("MONGODB_USERNAME"),
-        password=os.getenv("MONGODB_PASSWORD"),
-        auth_source=os.getenv("MONGODB_AUTH_SOURCE"),
-    )
-
     app = ReasoningGUI()
     app.run()
 

src/plugins/chat/__init__.py

@@ -3,11 +3,11 @@ import time
 import os
 
 from loguru import logger
-from nonebot import get_driver, on_message, require
+from nonebot import get_driver, on_message, on_notice, require
-from nonebot.adapters.onebot.v11 import Bot, GroupMessageEvent, Message, MessageSegment,MessageEvent
+from nonebot.rule import to_me
+from nonebot.adapters.onebot.v11 import Bot, GroupMessageEvent, Message, MessageSegment, MessageEvent, NoticeEvent
 from nonebot.typing import T_State
 
-from ...common.database import Database
 from ..moods.moods import MoodManager  # 导入情绪管理器
 from ..schedule.schedule_generator import bot_schedule
 from ..utils.statistic import LLMStatistics
@@ -40,6 +40,8 @@ logger.debug(f"正在唤醒{global_config.BOT_NICKNAME}......")
 chat_bot = ChatBot()
 # 注册消息处理器
 msg_in = on_message(priority=5)
+# 注册和bot相关的通知处理器
+notice_matcher = on_notice(priority=1)
 # 创建定时任务
 scheduler = require("nonebot_plugin_apscheduler").scheduler
 
@@ -96,19 +98,24 @@ async def _(bot: Bot, event: MessageEvent, state: T_State):
     await chat_bot.handle_message(event, bot)
 
 
+@notice_matcher.handle()
+async def _(bot: Bot, event: NoticeEvent, state: T_State):
+    logger.debug(f"收到通知：{event}")
+    await chat_bot.handle_notice(event, bot)
+
+
 # 添加build_memory定时任务
 @scheduler.scheduled_job("interval", seconds=global_config.build_memory_interval, id="build_memory")
 async def build_memory_task():
     """每build_memory_interval秒执行一次记忆构建"""
-    logger.debug(
+    logger.debug("[记忆构建]------------------------------------开始构建记忆--------------------------------------")
-        "[记忆构建]"
-        "------------------------------------开始构建记忆--------------------------------------")
     start_time = time.time()
     await hippocampus.operation_build_memory(chat_size=20)
     end_time = time.time()
     logger.success(
         f"[记忆构建]--------------------------记忆构建完成：耗时: {end_time - start_time:.2f} "
-        "秒-------------------------------------------")
+        "秒-------------------------------------------"
+    )
 
 
 @scheduler.scheduled_job("interval", seconds=global_config.forget_memory_interval, id="forget_memory")
@@ -132,3 +139,12 @@ async def print_mood_task():
     """每30秒打印一次情绪状态"""
     mood_manager = MoodManager.get_instance()
     mood_manager.print_mood_status()
+
+
+@scheduler.scheduled_job("interval", seconds=7200, id="generate_schedule")
+async def generate_schedule_task():
+    """每2小时尝试生成一次日程"""
+    logger.debug("尝试生成日程")
+    await bot_schedule.initialize()
+    if not bot_schedule.enable_output:
+        bot_schedule.print_schedule()

src/plugins/chat/bot.py

@@ -7,6 +7,8 @@ from nonebot.adapters.onebot.v11 import (
     GroupMessageEvent,
     MessageEvent,
     PrivateMessageEvent,
+    NoticeEvent,
+    PokeNotifyEvent,
 )
 
 from ..memory_system.memory import hippocampus
@@ -25,6 +27,7 @@ from .relationship_manager import relationship_manager
 from .storage import MessageStorage
 from .utils import calculate_typing_time, is_mentioned_bot_in_message
 from .utils_image import image_path_to_base64
+from .utils_user import get_user_nickname, get_user_cardname, get_groupname
 from .willing_manager import willing_manager  # 导入意愿管理器
 from .message_base import UserInfo, GroupInfo, Seg
 
@@ -46,6 +49,69 @@ class ChatBot:
         if not self._started:
             self._started = True
 
+    async def handle_notice(self, event: NoticeEvent, bot: Bot) -> None:
+        """处理收到的通知"""
+        # 戳一戳通知
+        if isinstance(event, PokeNotifyEvent):
+            # 用户屏蔽,不区分私聊/群聊
+            if event.user_id in global_config.ban_user_id:
+                return
+            reply_poke_probability = 1  # 回复戳一戳的概率
+
+            if random() < reply_poke_probability:
+                user_info = UserInfo(
+                    user_id=event.user_id,
+                    user_nickname=get_user_nickname(event.user_id) or None,
+                    user_cardname=get_user_cardname(event.user_id) or None,
+                    platform="qq",
+                )
+                group_info = GroupInfo(group_id=event.group_id, group_name=None, platform="qq")
+                message_cq = MessageRecvCQ(
+                    message_id=None,
+                    user_info=user_info,
+                    raw_message=str("[戳了戳]你"),
+                    group_info=group_info,
+                    reply_message=None,
+                    platform="qq",
+                )
+                message_json = message_cq.to_dict()
+
+                # 进入maimbot
+                message = MessageRecv(message_json)
+                groupinfo = message.message_info.group_info
+                userinfo = message.message_info.user_info
+                messageinfo = message.message_info
+
+                chat = await chat_manager.get_or_create_stream(
+                    platform=messageinfo.platform, user_info=userinfo, group_info=groupinfo
+                )
+                message.update_chat_stream(chat)
+                await message.process()
+
+                bot_user_info = UserInfo(
+                    user_id=global_config.BOT_QQ,
+                    user_nickname=global_config.BOT_NICKNAME,
+                    platform=messageinfo.platform,
+                )
+
+                response, raw_content = await self.gpt.generate_response(message)
+
+                if response:
+                    for msg in response:
+                        message_segment = Seg(type="text", data=msg)
+
+                        bot_message = MessageSending(
+                            message_id=None,
+                            chat_stream=chat,
+                            bot_user_info=bot_user_info,
+                            sender_info=userinfo,
+                            message_segment=message_segment,
+                            reply=None,
+                            is_head=False,
+                            is_emoji=False,
+                        )
+                        message_manager.add_message(bot_message)
+
     async def handle_message(self, event: MessageEvent, bot: Bot) -> None:
         """处理收到的消息"""
 
@@ -54,7 +120,10 @@ class ChatBot:
         # 用户屏蔽,不区分私聊/群聊
         if event.user_id in global_config.ban_user_id:
             return
-
+        
+        if event.reply and hasattr(event.reply, 'sender') and hasattr(event.reply.sender, 'user_id') and event.reply.sender.user_id in global_config.ban_user_id:
+            logger.debug(f"跳过处理回复来自被ban用户 {event.reply.sender.user_id} 的消息")
+            return
         # 处理私聊消息
         if isinstance(event, PrivateMessageEvent):
             if not global_config.enable_friend_chat:  # 私聊过滤
@@ -126,7 +195,7 @@ class ChatBot:
         for word in global_config.ban_words:
             if word in message.processed_plain_text:
                 logger.info(
-                    f"[{chat.group_info.group_name if chat.group_info.group_id else '私聊'}]{userinfo.user_nickname}:{message.processed_plain_text}"
+                    f"[{chat.group_info.group_name if chat.group_info else '私聊'}]{userinfo.user_nickname}:{message.processed_plain_text}"
                 )
                 logger.info(f"[过滤词识别]消息中含有{word}，filtered")
                 return
@@ -135,7 +204,7 @@ class ChatBot:
         for pattern in global_config.ban_msgs_regex:
             if re.search(pattern, message.raw_message):
                 logger.info(
-                    f"[{chat.group_info.group_name if chat.group_info.group_id else '私聊'}]{message.user_nickname}:{message.raw_message}"
+                    f"[{chat.group_info.group_name if chat.group_info else '私聊'}]{userinfo.user_nickname}:{message.raw_message}"
                 )
                 logger.info(f"[正则表达式过滤]消息匹配到{pattern}，filtered")
                 return
@@ -143,7 +212,7 @@ class ChatBot:
         current_time = time.strftime("%Y-%m-%d %H:%M:%S", time.localtime(messageinfo.time))
 
         # topic=await topic_identifier.identify_topic_llm(message.processed_plain_text)
-        
+
         topic = ""
         interested_rate = await hippocampus.memory_activate_value(message.processed_plain_text) / 100
         logger.debug(f"对{message.processed_plain_text}的激活度:{interested_rate}")
@@ -164,7 +233,7 @@ class ChatBot:
         current_willing = willing_manager.get_willing(chat_stream=chat)
 
         logger.info(
-            f"[{current_time}][{chat.group_info.group_name if chat.group_info.group_id else '私聊'}]{chat.user_info.user_nickname}:"
+            f"[{current_time}][{chat.group_info.group_name if chat.group_info else '私聊'}]{chat.user_info.user_nickname}:"
             f"{message.processed_plain_text}[回复意愿:{current_willing:.2f}][概率:{reply_probability * 100:.1f}%]"
         )
 

src/plugins/chat/chat_stream.py

@@ -6,7 +6,7 @@ from typing import Dict, Optional
 
 from loguru import logger
 
-from ...common.database import Database
+from ...common.database import db
 from .message_base import GroupInfo, UserInfo
 
 
@@ -83,7 +83,6 @@ class ChatManager:
     def __init__(self):
         if not self._initialized:
             self.streams: Dict[str, ChatStream] = {}  # stream_id -> ChatStream
-            self.db = Database.get_instance()
             self._ensure_collection()
             self._initialized = True
             # 在事件循环中启动初始化
@@ -111,11 +110,11 @@ class ChatManager:
 
     def _ensure_collection(self):
         """确保数据库集合存在并创建索引"""
-        if "chat_streams" not in self.db.list_collection_names():
+        if "chat_streams" not in db.list_collection_names():
-            self.db.create_collection("chat_streams")
+            db.create_collection("chat_streams")
             # 创建索引
-            self.db.chat_streams.create_index([("stream_id", 1)], unique=True)
+            db.chat_streams.create_index([("stream_id", 1)], unique=True)
-            self.db.chat_streams.create_index(
+            db.chat_streams.create_index(
                 [("platform", 1), ("user_info.user_id", 1), ("group_info.group_id", 1)]
             )
 
@@ -168,7 +167,7 @@ class ChatManager:
             return stream
 
         # 检查数据库中是否存在
-        data = self.db.chat_streams.find_one({"stream_id": stream_id})
+        data = db.chat_streams.find_one({"stream_id": stream_id})
         if data:
             stream = ChatStream.from_dict(data)
             # 更新用户信息和群组信息
@@ -204,7 +203,7 @@ class ChatManager:
     async def _save_stream(self, stream: ChatStream):
         """保存聊天流到数据库"""
         if not stream.saved:
-            self.db.chat_streams.update_one(
+            db.chat_streams.update_one(
                 {"stream_id": stream.stream_id}, {"$set": stream.to_dict()}, upsert=True
             )
             stream.saved = True
@@ -216,7 +215,7 @@ class ChatManager:
 
     async def load_all_streams(self):
         """从数据库加载所有聊天流"""
-        all_streams = self.db.chat_streams.find({})
+        all_streams = db.chat_streams.find({})
         for data in all_streams:
             stream = ChatStream.from_dict(data)
             self.streams[stream.stream_id] = stream

src/plugins/chat/cq_code.py

@@ -86,9 +86,12 @@ class CQCode:
             else:
                 self.translated_segments = Seg(type="text", data="[图片]")
         elif self.type == "at":
-            user_nickname = get_user_nickname(self.params.get("qq", ""))
+            if self.params.get("qq") == "all":
-            self.translated_segments = Seg(
+                self.translated_segments = Seg(type="text", data="@[全体成员]")
-                type="text", data=f"[@{user_nickname or '某人'}]"
+            else:  
+                user_nickname = get_user_nickname(self.params.get("qq", ""))
+                self.translated_segments = Seg(
+                    type="text", data=f"[@{user_nickname or '某人'}]"
             )
         elif self.type == "reply":
             reply_segments = self.translate_reply()

src/plugins/chat/emoji_manager.py

@@ -12,7 +12,7 @@ import io
 from loguru import logger
 from nonebot import get_driver
 
-from ...common.database import Database
+from ...common.database import db
 from ..chat.config import global_config
 from ..chat.utils import get_embedding
 from ..chat.utils_image import ImageManager, image_path_to_base64
@@ -25,22 +25,20 @@ image_manager = ImageManager()
 
 class EmojiManager:
     _instance = None
-    EMOJI_DIR = "data/emoji"  # 表情包存储目录
+    EMOJI_DIR = os.path.join("data", "emoji")  # 表情包存储目录
 
     def __new__(cls):
         if cls._instance is None:
             cls._instance = super().__new__(cls)
-            cls._instance.db = None
             cls._instance._initialized = False
         return cls._instance
 
     def __init__(self):
-        self.db = Database.get_instance()
         self._scan_task = None
         self.vlm = LLM_request(model=global_config.vlm, temperature=0.3, max_tokens=1000)
-        self.llm_emotion_judge = LLM_request(model=global_config.llm_emotion_judge, max_tokens=60,
+        self.llm_emotion_judge = LLM_request(
-                                             temperature=0.8)  # 更高的温度，更少的token（后续可以根据情绪来调整温度）
+            model=global_config.llm_emotion_judge, max_tokens=60, temperature=0.8
-
+        )  # 更高的温度，更少的token（后续可以根据情绪来调整温度）
 
     def _ensure_emoji_dir(self):
         """确保表情存储目录存在"""
@@ -50,7 +48,6 @@ class EmojiManager:
         """初始化数据库连接和表情目录"""
         if not self._initialized:
             try:
-                self.db = Database.get_instance()
                 self._ensure_emoji_collection()
                 self._ensure_emoji_dir()
                 self._initialized = True
@@ -68,42 +65,39 @@ class EmojiManager:
 
     def _ensure_emoji_collection(self):
         """确保emoji集合存在并创建索引
-        
+
         这个函数用于确保MongoDB数据库中存在emoji集合,并创建必要的索引。
-        
+
         索引的作用是加快数据库查询速度:
         - embedding字段的2dsphere索引: 用于加速向量相似度搜索,帮助快速找到相似的表情包
         - tags字段的普通索引: 加快按标签搜索表情包的速度
         - filename字段的唯一索引: 确保文件名不重复,同时加快按文件名查找的速度
-        
+
         没有索引的话,数据库每次查询都需要扫描全部数据,建立索引后可以大大提高查询效率。
         """
-        if 'emoji' not in self.db.list_collection_names():
+        if "emoji" not in db.list_collection_names():
-            self.db.create_collection('emoji')
+            db.create_collection("emoji")
-            self.db.emoji.create_index([('embedding', '2dsphere')])
+            db.emoji.create_index([("embedding", "2dsphere")])
-            self.db.emoji.create_index([('filename', 1)], unique=True)
+            db.emoji.create_index([("filename", 1)], unique=True)
 
     def record_usage(self, emoji_id: str):
         """记录表情使用次数"""
         try:
             self._ensure_db()
-            self.db.emoji.update_one(
+            db.emoji.update_one({"_id": emoji_id}, {"$inc": {"usage_count": 1}})
-                {'_id': emoji_id},
-                {'$inc': {'usage_count': 1}}
-            )
         except Exception as e:
             logger.error(f"记录表情使用失败: {str(e)}")
-            
+
-    async def get_emoji_for_text(self, text: str) -> Optional[Tuple[str,str]]:
+    async def get_emoji_for_text(self, text: str) -> Optional[Tuple[str, str]]:
         """根据文本内容获取相关表情包
         Args:
             text: 输入文本
         Returns:
             Optional[str]: 表情包文件路径，如果没有找到则返回None
-            
+
-        
+
         可不可以通过 配置文件中的指令 来自定义使用表情包的逻辑？
-        我觉得可行    
+        我觉得可行
 
         """
         try:
@@ -121,7 +115,7 @@ class EmojiManager:
 
             try:
                 # 获取所有表情包
-                all_emojis = list(self.db.emoji.find({}, {'_id': 1, 'path': 1, 'embedding': 1, 'description': 1}))
+                all_emojis = list(db.emoji.find({}, {"_id": 1, "path": 1, "embedding": 1, "description": 1}))
 
                 if not all_emojis:
                     logger.warning("数据库中没有任何表情包")
@@ -140,34 +134,31 @@ class EmojiManager:
 
                 # 计算所有表情包与输入文本的相似度
                 emoji_similarities = [
-                    (emoji, cosine_similarity(text_embedding, emoji.get('embedding', [])))
+                    (emoji, cosine_similarity(text_embedding, emoji.get("embedding", []))) for emoji in all_emojis
-                    for emoji in all_emojis
                 ]
 
                 # 按相似度降序排序
                 emoji_similarities.sort(key=lambda x: x[1], reverse=True)
 
                 # 获取前3个最相似的表情包
-                top_10_emojis = emoji_similarities[:10 if len(emoji_similarities) > 10 else len(emoji_similarities)]
+                top_10_emojis = emoji_similarities[: 10 if len(emoji_similarities) > 10 else len(emoji_similarities)]
-                
+
                 if not top_10_emojis:
                     logger.warning("未找到匹配的表情包")
                     return None
 
                 # 从前3个中随机选择一个
                 selected_emoji, similarity = random.choice(top_10_emojis)
-                
+
-                if selected_emoji and 'path' in selected_emoji:
+                if selected_emoji and "path" in selected_emoji:
                     # 更新使用次数
-                    self.db.emoji.update_one(
+                    db.emoji.update_one({"_id": selected_emoji["_id"]}, {"$inc": {"usage_count": 1}})
-                        {'_id': selected_emoji['_id']},
-                        {'$inc': {'usage_count': 1}}
-                    )
 
                     logger.success(
-                        f"找到匹配的表情包: {selected_emoji.get('description', '无描述')} (相似度: {similarity:.4f})")
+                        f"找到匹配的表情包: {selected_emoji.get('description', '无描述')} (相似度: {similarity:.4f})"
+                    )
                     # 稍微改一下文本描述，不然容易产生幻觉，描述已经包含 表情包 了
-                    return selected_emoji['path'], "[ %s ]" % selected_emoji.get('description', '无描述')
+                    return selected_emoji["path"], "[ %s ]" % selected_emoji.get("description", "无描述")
 
             except Exception as search_error:
                 logger.error(f"搜索表情包失败: {str(search_error)}")
@@ -179,7 +170,6 @@ class EmojiManager:
             logger.error(f"获取表情包失败: {str(e)}")
             return None
 
-
     async def _get_emoji_discription(self, image_base64: str) -> str:
         """获取表情包的标签，使用image_manager的描述生成功能"""
 
@@ -187,16 +177,16 @@ class EmojiManager:
             # 使用image_manager获取描述，去掉前后的方括号和"表情包："前缀
             description = await image_manager.get_emoji_description(image_base64)
             # 去掉[表情包：xxx]的格式，只保留描述内容
-            description = description.strip('[]').replace('表情包：', '')
+            description = description.strip("[]").replace("表情包：", "")
             return description
-            
+
         except Exception as e:
             logger.error(f"获取标签失败: {str(e)}")
             return None
 
     async def _check_emoji(self, image_base64: str, image_format: str) -> str:
         try:
-            prompt = f'这是一个表情包，请回答这个表情包是否满足\"{global_config.EMOJI_CHECK_PROMPT}\"的要求，是则回答是，否则回答否，不要出现任何其他内容'
+            prompt = f'这是一个表情包，请回答这个表情包是否满足"{global_config.EMOJI_CHECK_PROMPT}"的要求，是则回答是，否则回答否，不要出现任何其他内容'
 
             content, _ = await self.vlm.generate_response_for_image(prompt, image_base64, image_format)
             logger.debug(f"输出描述: {content}")
@@ -208,9 +198,9 @@ class EmojiManager:
 
     async def _get_kimoji_for_text(self, text: str):
         try:
-            prompt = f'这是{global_config.BOT_NICKNAME}将要发送的消息内容:\n{text}\n若要为其配上表情包，请你输出这个表情包应该表达怎样的情感，应该给人什么样的感觉，不要太简洁也不要太长，注意不要输出任何对消息内容的分析内容，只输出\"一种什么样的感觉\"中间的形容词部分。'
+            prompt = f'这是{global_config.BOT_NICKNAME}将要发送的消息内容:\n{text}\n若要为其配上表情包，请你输出这个表情包应该表达怎样的情感，应该给人什么样的感觉，不要太简洁也不要太长，注意不要输出任何对消息内容的分析内容，只输出"一种什么样的感觉"中间的形容词部分。'
 
-            content, _ = await self.llm_emotion_judge.generate_response_async(prompt,temperature=1.5)
+            content, _ = await self.llm_emotion_judge.generate_response_async(prompt, temperature=1.5)
             logger.info(f"输出描述: {content}")
             return content
 
@@ -221,67 +211,62 @@ class EmojiManager:
     async def scan_new_emojis(self):
         """扫描新的表情包"""
         try:
-            emoji_dir = "data/emoji"
+            emoji_dir = self.EMOJI_DIR
             os.makedirs(emoji_dir, exist_ok=True)
 
             # 获取所有支持的图片文件
-            files_to_process = [f for f in os.listdir(emoji_dir) if
+            files_to_process = [
-                                f.lower().endswith(('.jpg', '.jpeg', '.png', '.gif'))]
+                f for f in os.listdir(emoji_dir) if f.lower().endswith((".jpg", ".jpeg", ".png", ".gif"))
+            ]
 
             for filename in files_to_process:
                 image_path = os.path.join(emoji_dir, filename)
-                
+
                 # 获取图片的base64编码和哈希值
                 image_base64 = image_path_to_base64(image_path)
                 if image_base64 is None:
                     os.remove(image_path)
                     continue
-                
+
                 image_bytes = base64.b64decode(image_base64)
                 image_hash = hashlib.md5(image_bytes).hexdigest()
                 image_format = Image.open(io.BytesIO(image_bytes)).format.lower()
                 # 检查是否已经注册过
-                existing_emoji = self.db['emoji'].find_one({'filename': filename})
+                existing_emoji = db["emoji"].find_one({"hash": image_hash})
                 description = None
-                
+
                 if existing_emoji:
                     # 即使表情包已存在，也检查是否需要同步到images集合
-                    description = existing_emoji.get('discription')
+                    description = existing_emoji.get("discription")
                     # 检查是否在images集合中存在
-                    existing_image = image_manager.db.images.find_one({'hash': image_hash})
+                    existing_image = db.images.find_one({"hash": image_hash})
                     if not existing_image:
                         # 同步到images集合
                         image_doc = {
-                            'hash': image_hash,
+                            "hash": image_hash,
-                            'path': image_path,
+                            "path": image_path,
-                            'type': 'emoji',
+                            "type": "emoji",
-                            'description': description,
+                            "description": description,
-                            'timestamp': int(time.time())
+                            "timestamp": int(time.time()),
                         }
-                        image_manager.db.images.update_one(
+                        db.images.update_one({"hash": image_hash}, {"$set": image_doc}, upsert=True)
-                            {'hash': image_hash},
-                            {'$set': image_doc},
-                            upsert=True
-                        )
                         # 保存描述到image_descriptions集合
-                        image_manager._save_description_to_db(image_hash, description, 'emoji')
+                        image_manager._save_description_to_db(image_hash, description, "emoji")
                         logger.success(f"同步已存在的表情包到images集合: {filename}")
                     continue
-                
+
                 # 检查是否在images集合中已有描述
-                existing_description = image_manager._get_description_from_db(image_hash, 'emoji')
+                existing_description = image_manager._get_description_from_db(image_hash, "emoji")
-                
+
                 if existing_description:
                     description = existing_description
                 else:
                     # 获取表情包的描述
                     description = await self._get_emoji_discription(image_base64)
-                
-
 
                 if global_config.EMOJI_CHECK:
                     check = await self._check_emoji(image_base64, image_format)
-                    if '是' not in check:
+                    if "是" not in check:
                         os.remove(image_path)
                         logger.info(f"描述: {description}")
 
@@ -289,44 +274,39 @@ class EmojiManager:
                         logger.info(f"其不满足过滤规则，被剔除 {check}")
                         continue
                     logger.info(f"check通过 {check}")
-                
+
                 if description is not None:
                     embedding = await get_embedding(description)
-                
+
                 if description is not None:
                     embedding = await get_embedding(description)
 
                     # 准备数据库记录
                     emoji_record = {
-                        'filename': filename,
+                        "filename": filename,
-                        'path': image_path,
+                        "path": image_path,
-                        'embedding': embedding,
+                        "embedding": embedding,
-                        'discription': description,
+                        "discription": description,
-                        'hash': image_hash,
+                        "hash": image_hash,
-                        'timestamp': int(time.time())
+                        "timestamp": int(time.time()),
                     }
-                    
+
                     # 保存到emoji数据库
-                    self.db['emoji'].insert_one(emoji_record)
+                    db["emoji"].insert_one(emoji_record)
                     logger.success(f"注册新表情包: {filename}")
                     logger.info(f"描述: {description}")
 
-                    
                     # 保存到images数据库
                     image_doc = {
-                        'hash': image_hash,
+                        "hash": image_hash,
-                        'path': image_path,
+                        "path": image_path,
-                        'type': 'emoji',
+                        "type": "emoji",
-                        'description': description,
+                        "description": description,
-                        'timestamp': int(time.time())
+                        "timestamp": int(time.time()),
                     }
-                    image_manager.db.images.update_one(
+                    db.images.update_one({"hash": image_hash}, {"$set": image_doc}, upsert=True)
-                        {'hash': image_hash},
-                        {'$set': image_doc},
-                        upsert=True
-                    )
                     # 保存描述到image_descriptions集合
-                    image_manager._save_description_to_db(image_hash, description, 'emoji')
+                    image_manager._save_description_to_db(image_hash, description, "emoji")
                     logger.success(f"同步保存到images集合: {filename}")
                 else:
                     logger.warning(f"跳过表情包: {filename}")
@@ -348,40 +328,47 @@ class EmojiManager:
         try:
             self._ensure_db()
             # 获取所有表情包记录
-            all_emojis = list(self.db.emoji.find())
+            all_emojis = list(db.emoji.find())
             removed_count = 0
             total_count = len(all_emojis)
 
             for emoji in all_emojis:
                 try:
-                    if 'path' not in emoji:
+                    if "path" not in emoji:
                         logger.warning(f"发现无效记录（缺少path字段），ID: {emoji.get('_id', 'unknown')}")
-                        self.db.emoji.delete_one({'_id': emoji['_id']})
+                        db.emoji.delete_one({"_id": emoji["_id"]})
                         removed_count += 1
                         continue
 
-                    if 'embedding' not in emoji:
+                    if "embedding" not in emoji:
                         logger.warning(f"发现过时记录（缺少embedding字段），ID: {emoji.get('_id', 'unknown')}")
-                        self.db.emoji.delete_one({'_id': emoji['_id']})
+                        db.emoji.delete_one({"_id": emoji["_id"]})
                         removed_count += 1
                         continue
 
                     # 检查文件是否存在
-                    if not os.path.exists(emoji['path']):
+                    if not os.path.exists(emoji["path"]):
                         logger.warning(f"表情包文件已被删除: {emoji['path']}")
                         # 从数据库中删除记录
-                        result = self.db.emoji.delete_one({'_id': emoji['_id']})
+                        result = db.emoji.delete_one({"_id": emoji["_id"]})
                         if result.deleted_count > 0:
                             logger.debug(f"成功删除数据库记录: {emoji['_id']}")
                             removed_count += 1
                         else:
                             logger.error(f"删除数据库记录失败: {emoji['_id']}")
+                        continue
+
+                    if "hash" not in emoji:
+                        logger.warning(f"发现缺失记录（缺少hash字段），ID: {emoji.get('_id', 'unknown')}")
+                        hash = hashlib.md5(open(emoji["path"], "rb").read()).hexdigest()
+                        db.emoji.update_one({"_id": emoji["_id"]}, {"$set": {"hash": hash}})
+
                 except Exception as item_error:
                     logger.error(f"处理表情包记录时出错: {str(item_error)}")
                     continue
 
             # 验证清理结果
-            remaining_count = self.db.emoji.count_documents({})
+            remaining_count = db.emoji.count_documents({})
             if removed_count > 0:
                 logger.success(f"已清理 {removed_count} 个失效的表情包记录")
                 logger.info(f"清理前总数: {total_count} | 清理后总数: {remaining_count}")
@@ -401,5 +388,3 @@ class EmojiManager:
 # 创建全局单例
 
 emoji_manager = EmojiManager()
-
-

src/plugins/chat/llm_generator.py

@@ -5,7 +5,7 @@ from typing import List, Optional, Tuple, Union
 from nonebot import get_driver
 from loguru import logger
 
-from ...common.database import Database
+from ...common.database import db
 from ..models.utils_model import LLM_request
 from .config import global_config
 from .message import MessageRecv, MessageThinking, Message
@@ -34,7 +34,6 @@ class ResponseGenerator:
         self.model_v25 = LLM_request(
             model=global_config.llm_normal_minor, temperature=0.7, max_tokens=1000
         )
-        self.db = Database.get_instance()
         self.current_model_type = "r1"  # 默认使用 R1
 
     async def generate_response(
@@ -154,7 +153,7 @@ class ResponseGenerator:
         reasoning_content: str,
     ):
         """保存对话记录到数据库"""
-        self.db.reasoning_logs.insert_one(
+        db.reasoning_logs.insert_one(
             {
                 "time": time.time(),
                 "chat_id": message.chat_stream.stream_id,
@@ -211,7 +210,6 @@ class ResponseGenerator:
 
 class InitiativeMessageGenerate:
     def __init__(self):
-        self.db = Database.get_instance()
         self.model_r1 = LLM_request(model=global_config.llm_reasoning, temperature=0.7)
         self.model_v3 = LLM_request(model=global_config.llm_normal, temperature=0.7)
         self.model_r1_distill = LLM_request(

src/plugins/chat/message.py

@@ -23,8 +23,8 @@ urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
 
 @dataclass
 class Message(MessageBase):
-    chat_stream: ChatStream=None
+    chat_stream: ChatStream = None
-    reply: Optional['Message'] = None
+    reply: Optional["Message"] = None
     detailed_plain_text: str = ""
     processed_plain_text: str = ""
 
@@ -35,7 +35,7 @@ class Message(MessageBase):
         chat_stream: ChatStream,
         user_info: UserInfo,
         message_segment: Optional[Seg] = None,
-        reply: Optional['MessageRecv'] = None,
+        reply: Optional["MessageRecv"] = None,
         detailed_plain_text: str = "",
         processed_plain_text: str = "",
     ):
@@ -45,21 +45,17 @@ class Message(MessageBase):
             message_id=message_id,
             time=time,
             group_info=chat_stream.group_info,
-            user_info=user_info
+            user_info=user_info,
         )
 
         # 调用父类初始化
-        super().__init__(
+        super().__init__(message_info=message_info, message_segment=message_segment, raw_message=None)
-            message_info=message_info,
-            message_segment=message_segment,
-            raw_message=None
-        )
 
         self.chat_stream = chat_stream
         # 文本处理相关属性
         self.processed_plain_text = processed_plain_text
         self.detailed_plain_text = detailed_plain_text
-        
+
         # 回复消息
         self.reply = reply
 
@@ -74,41 +70,38 @@ class MessageRecv(Message):
         Args:
             message_dict: MessageCQ序列化后的字典
         """
-        self.message_info = BaseMessageInfo.from_dict(message_dict.get('message_info', {}))
+        self.message_info = BaseMessageInfo.from_dict(message_dict.get("message_info", {}))
 
-        message_segment = message_dict.get('message_segment', {})
+        message_segment = message_dict.get("message_segment", {})
 
-        if message_segment.get('data','') == '[json]':
+        if message_segment.get("data", "") == "[json]":
             # 提取json消息中的展示信息
-            pattern = r'\[CQ:json,data=(?P<json_data>.+?)\]'
+            pattern = r"\[CQ:json,data=(?P<json_data>.+?)\]"
-            match = re.search(pattern, message_dict.get('raw_message',''))
+            match = re.search(pattern, message_dict.get("raw_message", ""))
-            raw_json = html.unescape(match.group('json_data'))
+            raw_json = html.unescape(match.group("json_data"))
             try:
                 json_message = json.loads(raw_json)
             except json.JSONDecodeError:
                 json_message = {}
-            message_segment['data'] = json_message.get('prompt','')
+            message_segment["data"] = json_message.get("prompt", "")
+
+        self.message_segment = Seg.from_dict(message_dict.get("message_segment", {}))
+        self.raw_message = message_dict.get("raw_message")
 
-        self.message_segment = Seg.from_dict(message_dict.get('message_segment', {}))
-        self.raw_message = message_dict.get('raw_message')
-        
         # 处理消息内容
         self.processed_plain_text = ""  # 初始化为空字符串
-        self.detailed_plain_text = ""   # 初始化为空字符串
+        self.detailed_plain_text = ""  # 初始化为空字符串
-        self.is_emoji=False
+        self.is_emoji = False
-    
+
-    
+    def update_chat_stream(self, chat_stream: ChatStream):
-    def update_chat_stream(self,chat_stream:ChatStream):
+        self.chat_stream = chat_stream
-        self.chat_stream=chat_stream
+
-    
     async def process(self) -> None:
         """处理消息内容，生成纯文本和详细文本
 
         这个方法必须在创建实例后显式调用，因为它包含异步操作。
         """
-        self.processed_plain_text = await self._process_message_segments(
+        self.processed_plain_text = await self._process_message_segments(self.message_segment)
-            self.message_segment
-        )
         self.detailed_plain_text = self._generate_detailed_text()
 
     async def _process_message_segments(self, segment: Seg) -> str:
@@ -157,16 +150,12 @@ class MessageRecv(Message):
             else:
                 return f"[{seg.type}:{str(seg.data)}]"
         except Exception as e:
-            logger.error(
+            logger.error(f"处理消息段失败: {str(e)}, 类型: {seg.type}, 数据: {seg.data}")
-                f"处理消息段失败: {str(e)}, 类型: {seg.type}, 数据: {seg.data}"
-            )
             return f"[处理失败的{seg.type}消息]"
 
     def _generate_detailed_text(self) -> str:
         """生成详细文本，包含时间和用户信息"""
-        time_str = time.strftime(
+        time_str = time.strftime("%m-%d %H:%M:%S", time.localtime(self.message_info.time))
-            "%m-%d %H:%M:%S", time.localtime(self.message_info.time)
-        )
         user_info = self.message_info.user_info
         name = (
             f"{user_info.user_nickname}(ta的昵称:{user_info.user_cardname},ta的id:{user_info.user_id})"
@@ -174,7 +163,7 @@ class MessageRecv(Message):
             else f"{user_info.user_nickname}(ta的id:{user_info.user_id})"
         )
         return f"[{time_str}] {name}: {self.processed_plain_text}\n"
-    
+
 
 @dataclass
 class MessageProcessBase(Message):
@@ -257,16 +246,12 @@ class MessageProcessBase(Message):
             else:
                 return f"[{seg.type}:{str(seg.data)}]"
         except Exception as e:
-            logger.error(
+            logger.error(f"处理消息段失败: {str(e)}, 类型: {seg.type}, 数据: {seg.data}")
-                f"处理消息段失败: {str(e)}, 类型: {seg.type}, 数据: {seg.data}"
-            )
             return f"[处理失败的{seg.type}消息]"
 
     def _generate_detailed_text(self) -> str:
         """生成详细文本，包含时间和用户信息"""
-        time_str = time.strftime(
+        time_str = time.strftime("%m-%d %H:%M:%S", time.localtime(self.message_info.time))
-            "%m-%d %H:%M:%S", time.localtime(self.message_info.time)
-        )
         user_info = self.message_info.user_info
         name = (
             f"{user_info.user_nickname}(ta的昵称:{user_info.user_cardname},ta的id:{user_info.user_id})"
@@ -330,10 +315,11 @@ class MessageSending(MessageProcessBase):
         self.is_head = is_head
         self.is_emoji = is_emoji
 
-    def set_reply(self, reply: Optional["MessageRecv"]) -> None:
+    def set_reply(self, reply: Optional["MessageRecv"] = None) -> None:
         """设置回复消息"""
         if reply:
             self.reply = reply
+        if self.reply:
             self.reply_to_message_id = self.reply.message_info.message_id
             self.message_segment = Seg(
                 type="seglist",
@@ -346,9 +332,7 @@ class MessageSending(MessageProcessBase):
     async def process(self) -> None:
         """处理消息内容，生成纯文本和详细文本"""
         if self.message_segment:
-            self.processed_plain_text = await self._process_message_segments(
+            self.processed_plain_text = await self._process_message_segments(self.message_segment)
-                self.message_segment
-            )
             self.detailed_plain_text = self._generate_detailed_text()
 
     @classmethod
@@ -377,10 +361,7 @@ class MessageSending(MessageProcessBase):
 
     def is_private_message(self) -> bool:
         """判断是否为私聊消息"""
-        return (
+        return self.message_info.group_info is None or self.message_info.group_info.group_id is None
-            self.message_info.group_info is None
-            or self.message_info.group_info.group_id is None
-        )
 
 
 @dataclass

src/plugins/chat/message_base.py

@@ -65,6 +65,8 @@ class GroupInfo:
         Returns:
             GroupInfo: 新的实例
         """
+        if data.get('group_id') is None:
+            return None
         return cls(
             platform=data.get('platform'),
             group_id=data.get('group_id'),
@@ -129,8 +131,8 @@ class BaseMessageInfo:
         Returns:
             BaseMessageInfo: 新的实例
         """
-        group_info = GroupInfo(**data.get('group_info', {}))
+        group_info = GroupInfo.from_dict(data.get('group_info', {}))
-        user_info = UserInfo(**data.get('user_info', {}))
+        user_info = UserInfo.from_dict(data.get('user_info', {}))
         return cls(
             platform=data.get('platform'),
             message_id=data.get('message_id'),
@@ -173,7 +175,7 @@ class MessageBase:
         Returns:
             MessageBase: 新的实例
         """
-        message_info = BaseMessageInfo(**data.get('message_info', {}))
+        message_info = BaseMessageInfo.from_dict(data.get('message_info', {}))
         message_segment = Seg(**data.get('message_segment', {}))
         raw_message = data.get('raw_message',None)
         return cls(

src/plugins/chat/message_cq.py

@@ -8,48 +8,40 @@ from .cq_code import cq_code_tool
 from .utils_cq import parse_cq_code
 from .utils_user import get_groupname
 from .message_base import Seg, GroupInfo, UserInfo, BaseMessageInfo, MessageBase
+
 # 禁用SSL警告
 urllib3.disable_warnings(urllib3.exceptions.InsecureRequestWarning)
 
-#这个类是消息数据类，用于存储和管理消息数据。
+# 这个类是消息数据类，用于存储和管理消息数据。
-#它定义了消息的属性，包括群组ID、用户ID、消息ID、原始消息内容、纯文本内容和时间戳。
+# 它定义了消息的属性，包括群组ID、用户ID、消息ID、原始消息内容、纯文本内容和时间戳。
-#它还定义了两个辅助属性：keywords用于提取消息的关键词，is_plain_text用于判断消息是否为纯文本。
+# 它还定义了两个辅助属性：keywords用于提取消息的关键词，is_plain_text用于判断消息是否为纯文本。
+
 
 @dataclass
 class MessageCQ(MessageBase):
     """QQ消息基类，继承自MessageBase
-    
+
     最小必要参数:
     - message_id: 消息ID
     - user_id: 发送者/接收者ID
     - platform: 平台标识（默认为"qq"）
     """
+
     def __init__(
-        self,
+        self, message_id: int, user_info: UserInfo, group_info: Optional[GroupInfo] = None, platform: str = "qq"
-        message_id: int,
-        user_info: UserInfo,
-        group_info: Optional[GroupInfo] = None,
-        platform: str = "qq"
     ):
         # 构造基础消息信息
         message_info = BaseMessageInfo(
-            platform=platform,
+            platform=platform, message_id=message_id, time=int(time.time()), group_info=group_info, user_info=user_info
-            message_id=message_id,
-            time=int(time.time()),
-            group_info=group_info,
-            user_info=user_info
         )
         # 调用父类初始化，message_segment 由子类设置
-        super().__init__(
+        super().__init__(message_info=message_info, message_segment=None, raw_message=None)
-            message_info=message_info,
+
-            message_segment=None,
-            raw_message=None
-        )
 
 @dataclass
 class MessageRecvCQ(MessageCQ):
     """QQ接收消息类，用于解析raw_message到Seg对象"""
-    
+
     def __init__(
         self,
         message_id: int,
@@ -61,14 +53,14 @@ class MessageRecvCQ(MessageCQ):
     ):
         # 调用父类初始化
         super().__init__(message_id, user_info, group_info, platform)
-        
+
         # 私聊消息不携带group_info
         if group_info is None:
             pass
 
         elif group_info.group_name is None:
             group_info.group_name = get_groupname(group_info.group_id)
-        
+
         # 解析消息段
         self.message_segment = self._parse_message(raw_message, reply_message)
         self.raw_message = raw_message
@@ -77,10 +69,10 @@ class MessageRecvCQ(MessageCQ):
         """解析消息内容为Seg对象"""
         cq_code_dict_list = []
         segments = []
-        
+
         start = 0
         while True:
-            cq_start = message.find('[CQ:', start)
+            cq_start = message.find("[CQ:", start)
             if cq_start == -1:
                 if start < len(message):
                     text = message[start:].strip()
@@ -93,81 +85,80 @@ class MessageRecvCQ(MessageCQ):
                 if text:
                     cq_code_dict_list.append(parse_cq_code(text))
 
-            cq_end = message.find(']', cq_start)
+            cq_end = message.find("]", cq_start)
             if cq_end == -1:
                 text = message[cq_start:].strip()
                 if text:
                     cq_code_dict_list.append(parse_cq_code(text))
                 break
 
-            cq_code = message[cq_start:cq_end + 1]
+            cq_code = message[cq_start : cq_end + 1]
             cq_code_dict_list.append(parse_cq_code(cq_code))
             start = cq_end + 1
 
         # 转换CQ码为Seg对象
         for code_item in cq_code_dict_list:
-            message_obj = cq_code_tool.cq_from_dict_to_class(code_item,msg=self,reply=reply_message)
+            message_obj = cq_code_tool.cq_from_dict_to_class(code_item, msg=self, reply=reply_message)
             if message_obj.translated_segments:
                 segments.append(message_obj.translated_segments)
 
         # 如果只有一个segment，直接返回
         if len(segments) == 1:
             return segments[0]
-        
+
         # 否则返回seglist类型的Seg
-        return Seg(type='seglist', data=segments)
+        return Seg(type="seglist", data=segments)
 
     def to_dict(self) -> Dict:
         """转换为字典格式，包含所有必要信息"""
         base_dict = super().to_dict()
         return base_dict
 
+
 @dataclass
 class MessageSendCQ(MessageCQ):
     """QQ发送消息类，用于将Seg对象转换为raw_message"""
-    
+
-    def __init__(
+    def __init__(self, data: Dict):
-        self,
-        data: Dict
-    ):
         # 调用父类初始化
-        message_info = BaseMessageInfo.from_dict(data.get('message_info', {}))
+        message_info = BaseMessageInfo.from_dict(data.get("message_info", {}))
-        message_segment = Seg.from_dict(data.get('message_segment', {}))
+        message_segment = Seg.from_dict(data.get("message_segment", {}))
         super().__init__(
-            message_info.message_id, 
+            message_info.message_id,
-            message_info.user_info, 
+            message_info.user_info,
-            message_info.group_info if message_info.group_info else None, 
+            message_info.group_info if message_info.group_info else None,
-            message_info.platform
+            message_info.platform,
-            )
+        )
-        
+
         self.message_segment = message_segment
         self.raw_message = self._generate_raw_message()
 
-    def _generate_raw_message(self, ) -> str:
+    def _generate_raw_message(
+        self,
+    ) -> str:
         """将Seg对象转换为raw_message"""
         segments = []
 
         # 处理消息段
-        if self.message_segment.type == 'seglist':
+        if self.message_segment.type == "seglist":
             for seg in self.message_segment.data:
                 segments.append(self._seg_to_cq_code(seg))
         else:
             segments.append(self._seg_to_cq_code(self.message_segment))
 
-        return ''.join(segments)
+        return "".join(segments)
 
     def _seg_to_cq_code(self, seg: Seg) -> str:
         """将单个Seg对象转换为CQ码字符串"""
-        if seg.type == 'text':
+        if seg.type == "text":
             return str(seg.data)
-        elif seg.type == 'image':
+        elif seg.type == "image":
             return cq_code_tool.create_image_cq_base64(seg.data)
-        elif seg.type == 'emoji':
+        elif seg.type == "emoji":
             return cq_code_tool.create_emoji_cq_base64(seg.data)
-        elif seg.type == 'at':
+        elif seg.type == "at":
             return f"[CQ:at,qq={seg.data}]"
-        elif seg.type == 'reply':
+        elif seg.type == "reply":
             return cq_code_tool.create_reply_cq(int(seg.data))
         else:
             return f"[{seg.data}]"
-

src/plugins/chat/prompt_builder.py

@@ -3,7 +3,7 @@ import time
 from typing import Optional
 from loguru import logger
 
-from ...common.database import Database
+from ...common.database import db
 from ..memory_system.memory import hippocampus, memory_graph
 from ..moods.moods import MoodManager
 from ..schedule.schedule_generator import bot_schedule
@@ -16,7 +16,6 @@ class PromptBuilder:
     def __init__(self):
         self.prompt_built = ''
         self.activate_messages = ''
-        self.db = Database.get_instance()
 
 
 
@@ -76,7 +75,7 @@ class PromptBuilder:
         chat_in_group=True
         chat_talking_prompt = ''
         if stream_id:
-            chat_talking_prompt = get_recent_group_detailed_plain_text(self.db, stream_id, limit=global_config.MAX_CONTEXT_SIZE,combine = True)   
+            chat_talking_prompt = get_recent_group_detailed_plain_text(stream_id, limit=global_config.MAX_CONTEXT_SIZE,combine = True)   
             chat_stream=chat_manager.get_stream(stream_id)
             if chat_stream.group_info:
                 chat_talking_prompt = f"以下是群里正在聊天的内容：\n{chat_talking_prompt}"
@@ -199,7 +198,7 @@ class PromptBuilder:
 
         chat_talking_prompt = ''
         if group_id:
-            chat_talking_prompt = get_recent_group_detailed_plain_text(self.db, group_id,
+            chat_talking_prompt = get_recent_group_detailed_plain_text(group_id,
                                                                        limit=global_config.MAX_CONTEXT_SIZE,
                                                                        combine=True)
 
@@ -311,7 +310,7 @@ class PromptBuilder:
             {"$project": {"content": 1, "similarity": 1}}
         ]
 
-        results = list(self.db.knowledges.aggregate(pipeline))
+        results = list(db.knowledges.aggregate(pipeline))
         # print(f"\033[1;34m[调试]\033[0m获取知识库内容结果: {results}")
 
         if not results:

src/plugins/chat/relationship_manager.py

@@ -2,7 +2,7 @@ import asyncio
 from typing import Optional
 from loguru import logger
 
-from ...common.database import Database
+from ...common.database import db
 from .message_base import UserInfo
 from .chat_stream import ChatStream
 
@@ -167,14 +167,12 @@ class RelationshipManager:
 
     async def load_all_relationships(self):
         """加载所有关系对象"""
-        db = Database.get_instance()
         all_relationships = db.relationships.find({})
         for data in all_relationships:
             await self.load_relationship(data)
 
     async def _start_relationship_manager(self):
         """每5分钟自动保存一次关系数据"""
-        db = Database.get_instance()
         # 获取所有关系记录
         all_relationships = db.relationships.find({})
         # 依次加载每条记录
@@ -205,7 +203,6 @@ class RelationshipManager:
         age = relationship.age
         saved = relationship.saved
 
-        db = Database.get_instance()
         db.relationships.update_one(
             {'user_id': user_id, 'platform': platform},
             {'$set': {

src/plugins/chat/storage.py

@@ -1,15 +1,12 @@
 from typing import Optional, Union
 
-from ...common.database import Database
+from ...common.database import db
 from .message import MessageSending, MessageRecv
 from .chat_stream import ChatStream
 from loguru import logger
 
 
 class MessageStorage:
-    def __init__(self):
-        self.db = Database.get_instance()
-        
     async def store_message(self, message: Union[MessageSending, MessageRecv],chat_stream:ChatStream, topic: Optional[str] = None) -> None:
         """存储消息到数据库"""
         try:
@@ -23,7 +20,7 @@ class MessageStorage:
                     "detailed_plain_text": message.detailed_plain_text,
                     "topic": topic,
                 }
-            self.db.messages.insert_one(message_data)
+            db.messages.insert_one(message_data)
         except Exception:
             logger.exception("存储消息失败")
 

src/plugins/chat/utils.py

@@ -16,6 +16,7 @@ from .message import MessageRecv,Message
 from .message_base import UserInfo
 from .chat_stream import ChatStream
 from ..moods.moods import MoodManager
+from ...common.database import db
 
 driver = get_driver()
 config = driver.config
@@ -76,11 +77,10 @@ def calculate_information_content(text):
     return entropy
 
 
-def get_cloest_chat_from_db(db, length: int, timestamp: str):
+def get_closest_chat_from_db(length: int, timestamp: str):
     """从数据库中获取最接近指定时间戳的聊天记录
     
     Args:
-        db: 数据库实例
         length: 要获取的消息数量
         timestamp: 时间戳
         
@@ -115,11 +115,10 @@ def get_cloest_chat_from_db(db, length: int, timestamp: str):
     return []
 
 
-async def get_recent_group_messages(db, chat_id:str, limit: int = 12) -> list:
+async def get_recent_group_messages(chat_id:str, limit: int = 12) -> list:
     """从数据库获取群组最近的消息记录
     
     Args:
-        db: Database实例
         group_id: 群组ID
         limit: 获取消息数量，默认12条
         
@@ -161,7 +160,7 @@ async def get_recent_group_messages(db, chat_id:str, limit: int = 12) -> list:
     return message_objects
 
 
-def get_recent_group_detailed_plain_text(db, chat_stream_id: int, limit: int = 12, combine=False):
+def get_recent_group_detailed_plain_text(chat_stream_id: int, limit: int = 12, combine=False):
     recent_messages = list(db.messages.find(
         {"chat_id": chat_stream_id},
         {

src/plugins/chat/utils_image.py

@@ -10,231 +10,95 @@ import io
 from loguru import logger
 from nonebot import get_driver
 
-from ...common.database import Database
+from ...common.database import db
 from ..chat.config import global_config
 from ..models.utils_model import LLM_request
+
 driver = get_driver()
 config = driver.config
 
+
 class ImageManager:
     _instance = None
     IMAGE_DIR = "data"  # 图像存储根目录
-    
+
     def __new__(cls):
         if cls._instance is None:
             cls._instance = super().__new__(cls)
-            cls._instance.db = None
             cls._instance._initialized = False
         return cls._instance
-    
+
     def __init__(self):
         if not self._initialized:
-            self.db = Database.get_instance()
             self._ensure_image_collection()
             self._ensure_description_collection()
             self._ensure_image_dir()
             self._initialized = True
             self._llm = LLM_request(model=global_config.vlm, temperature=0.4, max_tokens=300)
-            
+
     def _ensure_image_dir(self):
         """确保图像存储目录存在"""
         os.makedirs(self.IMAGE_DIR, exist_ok=True)
-        
+
     def _ensure_image_collection(self):
         """确保images集合存在并创建索引"""
-        if 'images' not in self.db.list_collection_names():
+        if "images" not in db.list_collection_names():
-            self.db.create_collection('images')
+            db.create_collection("images")
-            # 创建索引
+
-            self.db.images.create_index([('hash', 1)], unique=True)
+        # 删除旧索引
-            self.db.images.create_index([('url', 1)])
+        db.images.drop_indexes()
-            self.db.images.create_index([('path', 1)])
+        # 创建新的复合索引
+        db.images.create_index([("hash", 1), ("type", 1)], unique=True)
+        db.images.create_index([("url", 1)])
+        db.images.create_index([("path", 1)])
 
     def _ensure_description_collection(self):
         """确保image_descriptions集合存在并创建索引"""
-        if 'image_descriptions' not in self.db.list_collection_names():
+        if "image_descriptions" not in db.list_collection_names():
-            self.db.create_collection('image_descriptions')
+            db.create_collection("image_descriptions")
-            # 创建索引
+
-            self.db.image_descriptions.create_index([('hash', 1)], unique=True)
+        # 删除旧索引
-            self.db.image_descriptions.create_index([('type', 1)])
+        db.image_descriptions.drop_indexes()
+        # 创建新的复合索引
+        db.image_descriptions.create_index([("hash", 1), ("type", 1)], unique=True)
 
     def _get_description_from_db(self, image_hash: str, description_type: str) -> Optional[str]:
         """从数据库获取图片描述
-        
+
         Args:
             image_hash: 图片哈希值
             description_type: 描述类型 ('emoji' 或 'image')
-            
+
         Returns:
             Optional[str]: 描述文本，如果不存在则返回None
         """
-        result= self.db.image_descriptions.find_one({
+        result = db.image_descriptions.find_one({"hash": image_hash, "type": description_type})
-            'hash': image_hash,
+        return result["description"] if result else None
-            'type': description_type
-        })
-        return result['description'] if result else None
 
     def _save_description_to_db(self, image_hash: str, description: str, description_type: str) -> None:
         """保存图片描述到数据库
-        
+
         Args:
             image_hash: 图片哈希值
             description: 描述文本
             description_type: 描述类型 ('emoji' 或 'image')
         """
-        self.db.image_descriptions.update_one(
+        try:
-            {'hash': image_hash, 'type': description_type},
+            db.image_descriptions.update_one(
-            {
+                {"hash": image_hash, "type": description_type},
-                '$set': {
+                {
-                    'description': description,
+                    "$set": {
-                    'timestamp': int(time.time())
+                        "description": description,
-                }
+                        "timestamp": int(time.time()),
-            },
+                        "hash": image_hash,  # 确保hash字段存在
-            upsert=True
+                        "type": description_type,  # 确保type字段存在
-        )
+                    }
+                },
+                upsert=True,
+            )
+        except Exception as e:
+            logger.error(f"保存描述到数据库失败: {str(e)}")
 
-    async def save_image(self, 
-                        image_data: Union[str, bytes], 
-                        url: str = None, 
-                        description: str = None, 
-                        is_base64: bool = False) -> Optional[str]:
-        """保存图像
-        Args:
-            image_data: 图像数据(base64字符串或字节)
-            url: 图像URL
-            description: 图像描述
-            is_base64: image_data是否为base64格式
-        Returns:
-            str: 保存后的文件路径,失败返回None
-        """
-        try:
-            # 转换为字节格式
-            if is_base64:
-                if isinstance(image_data, str):
-                    image_bytes = base64.b64decode(image_data)
-                else:
-                    return None
-            else:
-                if isinstance(image_data, bytes):
-                    image_bytes = image_data
-                else:
-                    return None
-                    
-            # 计算哈希值
-            image_hash = hashlib.md5(image_bytes).hexdigest()
-            image_format = Image.open(io.BytesIO(image_bytes)).format.lower()
-            
-            # 查重
-            existing = self.db.images.find_one({'hash': image_hash})
-            if existing:
-                return existing['path']
-                
-            # 生成文件名和路径
-            timestamp = int(time.time())
-            filename = f"{timestamp}_{image_hash[:8]}.{image_format}"
-            file_path = os.path.join(self.IMAGE_DIR, filename)
-            
-            # 保存文件
-            with open(file_path, "wb") as f:
-                f.write(image_bytes)
-                
-            # 保存到数据库
-            image_doc = {
-                'hash': image_hash,
-                'path': file_path,
-                'url': url,
-                'description': description,
-                'timestamp': timestamp
-            }
-            self.db.images.insert_one(image_doc)
-            
-            return file_path
-            
-        except Exception as e:
-            logger.error(f"保存图像失败: {str(e)}")
-            return None
-            
-    async def get_image_by_url(self, url: str) -> Optional[str]:
-        """根据URL获取图像路径(带查重)
-        Args:
-            url: 图像URL
-        Returns:
-            str: 本地文件路径,不存在返回None
-        """
-        try:
-            # 先查找是否已存在
-            existing = self.db.images.find_one({'url': url})
-            if existing:
-                return existing['path']
-                
-            # 下载图像
-            async with aiohttp.ClientSession() as session:
-                async with session.get(url) as resp:
-                    if resp.status == 200:
-                        image_bytes = await resp.read()
-                        return await self.save_image(image_bytes, url=url)
-            return None
-            
-        except Exception as e:
-            logger.error(f"获取图像失败: {str(e)}")
-            return None
-            
-    async def get_base64_by_url(self, url: str) -> Optional[str]:
-        """根据URL获取base64(带查重)
-        Args:
-            url: 图像URL
-        Returns:
-            str: base64字符串,失败返回None
-        """
-        try:
-            image_path = await self.get_image_by_url(url)
-            if not image_path:
-                return None
-                
-            with open(image_path, 'rb') as f:
-                image_bytes = f.read()
-                return base64.b64encode(image_bytes).decode('utf-8')
-                
-        except Exception as e:
-            logger.error(f"获取base64失败: {str(e)}")
-            return None
-            
-        
-    def check_url_exists(self, url: str) -> bool:
-        """检查URL是否已存在
-        Args:
-            url: 图像URL
-        Returns:
-            bool: 是否存在
-        """
-        return self.db.images.find_one({'url': url}) is not None
-        
-    def check_hash_exists(self, image_data: Union[str, bytes], is_base64: bool = False) -> bool:
-        """检查图像是否已存在
-        Args:
-            image_data: 图像数据(base64或字节)
-            is_base64: 是否为base64格式
-        Returns:
-            bool: 是否存在
-        """
-        try:
-            if is_base64:
-                if isinstance(image_data, str):
-                    image_bytes = base64.b64decode(image_data)
-                else:
-                    return False
-            else:
-                if isinstance(image_data, bytes):
-                    image_bytes = image_data
-                else:
-                    return False
-                    
-            image_hash = hashlib.md5(image_bytes).hexdigest()
-            return self.db.images.find_one({'hash': image_hash}) is not None
-            
-        except Exception as e:
-            logger.error(f"检查哈希失败: {str(e)}")
-            return False
-        
     async def get_emoji_description(self, image_base64: str) -> str:
         """获取表情包描述，带查重和保存功能"""
         try:
@@ -244,7 +108,7 @@ class ImageManager:
             image_format = Image.open(io.BytesIO(image_bytes)).format.lower()
 
             # 查询缓存的描述
-            cached_description = self._get_description_from_db(image_hash, 'emoji')
+            cached_description = self._get_description_from_db(image_hash, "emoji")
             if cached_description:
                 logger.info(f"缓存表情包描述: {cached_description}")
                 return f"[表情包：{cached_description}]"
@@ -252,39 +116,42 @@ class ImageManager:
             # 调用AI获取描述
             prompt = "这是一个表情包，使用中文简洁的描述一下表情包的内容和表情包所表达的情感"
             description, _ = await self._llm.generate_response_for_image(prompt, image_base64, image_format)
-            
+
+            cached_description = self._get_description_from_db(image_hash, "emoji")
+            if cached_description:
+                logger.warning(f"虽然生成了描述，但是找到缓存表情包描述: {cached_description}")
+                return f"[表情包：{cached_description}]"
+
             # 根据配置决定是否保存图片
             if global_config.EMOJI_SAVE:
                 # 生成文件名和路径
                 timestamp = int(time.time())
                 filename = f"{timestamp}_{image_hash[:8]}.{image_format}"
-                file_path = os.path.join(self.IMAGE_DIR, 'emoji',filename)
+                if not os.path.exists(os.path.join(self.IMAGE_DIR, "emoji")):
-                
+                    os.makedirs(os.path.join(self.IMAGE_DIR, "emoji"))
+                file_path = os.path.join(self.IMAGE_DIR, "emoji", filename)
+
                 try:
                     # 保存文件
                     with open(file_path, "wb") as f:
                         f.write(image_bytes)
-                    
+
                     # 保存到数据库
                     image_doc = {
-                        'hash': image_hash,
+                        "hash": image_hash,
-                        'path': file_path,
+                        "path": file_path,
-                        'type': 'emoji',
+                        "type": "emoji",
-                        'description': description,
+                        "description": description,
-                        'timestamp': timestamp
+                        "timestamp": timestamp,
                     }
-                    self.db.images.update_one(
+                    db.images.update_one({"hash": image_hash}, {"$set": image_doc}, upsert=True)
-                        {'hash': image_hash},
-                        {'$set': image_doc},
-                        upsert=True
-                    )
                     logger.success(f"保存表情包: {file_path}")
                 except Exception as e:
                     logger.error(f"保存表情包文件失败: {str(e)}")
-            
+
             # 保存描述到数据库
-            self._save_description_to_db(image_hash, description, 'emoji')
+            self._save_description_to_db(image_hash, description, "emoji")
-            
+
             return f"[表情包：{description}]"
         except Exception as e:
             logger.error(f"获取表情包描述失败: {str(e)}")
@@ -293,67 +160,70 @@ class ImageManager:
     async def get_image_description(self, image_base64: str) -> str:
         """获取普通图片描述，带查重和保存功能"""
         try:
-            print("处理图片中")
             # 计算图片哈希
             image_bytes = base64.b64decode(image_base64)
             image_hash = hashlib.md5(image_bytes).hexdigest()
             image_format = Image.open(io.BytesIO(image_bytes)).format.lower()
 
             # 查询缓存的描述
-            cached_description = self._get_description_from_db(image_hash, 'image')
+            cached_description = self._get_description_from_db(image_hash, "image")
             if cached_description:
-                print("图片描述缓存中")
+                logger.info(f"图片描述缓存中 {cached_description}")
                 return f"[图片：{cached_description}]"
 
             # 调用AI获取描述
-            prompt = "请用中文描述这张图片的内容。如果有文字，请把文字都描述出来。并尝试猜测这个图片的含义。最多200个字。"
+            prompt = (
+                "请用中文描述这张图片的内容。如果有文字，请把文字都描述出来。并尝试猜测这个图片的含义。最多200个字。"
+            )
             description, _ = await self._llm.generate_response_for_image(prompt, image_base64, image_format)
-            
+
-            print(f"描述是{description}")
+            cached_description = self._get_description_from_db(image_hash, "image")
-            
+            if cached_description:
+                logger.warning(f"虽然生成了描述，但是找到缓存图片描述 {cached_description}")
+                return f"[图片：{cached_description}]"
+
+            logger.info(f"描述是{description}")
+
             if description is None:
                 logger.warning("AI未能生成图片描述")
                 return "[图片]"
-            
+
             # 根据配置决定是否保存图片
             if global_config.EMOJI_SAVE:
                 # 生成文件名和路径
                 timestamp = int(time.time())
                 filename = f"{timestamp}_{image_hash[:8]}.{image_format}"
-                file_path = os.path.join(self.IMAGE_DIR,'image', filename)
+                if not os.path.exists(os.path.join(self.IMAGE_DIR, "image")):
-                
+                    os.makedirs(os.path.join(self.IMAGE_DIR, "image"))
+                file_path = os.path.join(self.IMAGE_DIR, "image", filename)
+
                 try:
                     # 保存文件
                     with open(file_path, "wb") as f:
                         f.write(image_bytes)
-                    
+
                     # 保存到数据库
                     image_doc = {
-                        'hash': image_hash,
+                        "hash": image_hash,
-                        'path': file_path,
+                        "path": file_path,
-                        'type': 'image',
+                        "type": "image",
-                        'description': description,
+                        "description": description,
-                        'timestamp': timestamp
+                        "timestamp": timestamp,
                     }
-                    self.db.images.update_one(
+                    db.images.update_one({"hash": image_hash}, {"$set": image_doc}, upsert=True)
-                        {'hash': image_hash},
-                        {'$set': image_doc},
-                        upsert=True
-                    )
                     logger.success(f"保存图片: {file_path}")
                 except Exception as e:
                     logger.error(f"保存图片文件失败: {str(e)}")
-            
+
             # 保存描述到数据库
-            self._save_description_to_db(image_hash, description, 'image')
+            self._save_description_to_db(image_hash, description, "image")
-            
+
             return f"[图片：{description}]"
         except Exception as e:
             logger.error(f"获取图片描述失败: {str(e)}")
             return "[图片]"
 
 
-
 # 创建全局单例
 image_manager = ImageManager()
 
@@ -366,9 +236,9 @@ def image_path_to_base64(image_path: str) -> str:
         str: base64编码的图片数据
     """
     try:
-        with open(image_path, 'rb') as f:
+        with open(image_path, "rb") as f:
             image_data = f.read()
-            return base64.b64encode(image_data).decode('utf-8')
+            return base64.b64encode(image_data).decode("utf-8")
     except Exception as e:
         logger.error(f"读取图片失败: {image_path}, 错误: {str(e)}")
-        return None 
+        return None

src/plugins/chat/utils_user.py

@@ -5,14 +5,16 @@ from .relationship_manager import relationship_manager
 def get_user_nickname(user_id: int) -> str:
     if int(user_id) == int(global_config.BOT_QQ):
         return global_config.BOT_NICKNAME
-#     print(user_id)
+    #     print(user_id)
     return relationship_manager.get_name(user_id)
 
+
 def get_user_cardname(user_id: int) -> str:
     if int(user_id) == int(global_config.BOT_QQ):
         return global_config.BOT_NICKNAME
-#     print(user_id)
+    #     print(user_id)
-    return ''
+    return ""
+
 
 def get_groupname(group_id: int) -> str:
-    return f"群{group_id}"
+    return f"群{group_id}"

src/plugins/chat/willing_manager.py

@@ -55,14 +55,14 @@ class WillingManager:
             for chat_id in list(self.chat_high_willing_mode.keys()):
                 last_change_time = self.chat_last_mode_change.get(chat_id, 0)
                 is_high_mode = self.chat_high_willing_mode.get(chat_id, False)
-                
+
                 # 获取当前模式的持续时间
                 duration = 0
                 if is_high_mode:
                     duration = self.chat_high_willing_duration.get(chat_id, 180)  # 使用已存储的持续时间或默认3分钟
                 else:
                     duration = self.chat_low_willing_duration.get(chat_id, 300)  # 使用已存储的持续时间或默认5分钟
-                
+
                 # 检查是否需要切换模式
                 if current_time - last_change_time > duration:
                     self._switch_willing_mode(chat_id)
@@ -111,7 +111,7 @@ class WillingManager:
     def _ensure_chat_initialized(self, chat_id: str):
         """确保聊天流的所有数据已初始化"""
         current_time = time.time()
-        
+
         if chat_id not in self.chat_reply_willing:
             self.chat_reply_willing[chat_id] = 0.1
         
@@ -263,7 +263,7 @@ class WillingManager:
                 # 冷群中提高回复概率为三倍
                 reply_probability = min(reply_probability * 3.0)
                 logger.debug(f"检测到冷群 {group_id}，提高回复概率到: {reply_probability:.2f}")
-        
+
         # 检查群组权限（如果是群聊）
         if chat_stream.group_info and config:               
             if chat_stream.group_info.group_id in config.talk_frequency_down_groups:

src/plugins/memory_system/draw_memory.py

@@ -13,7 +13,7 @@ from loguru import logger
 root_path = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../.."))
 sys.path.append(root_path)
 
-from src.common.database import Database  # 使用正确的导入语法
+from src.common.database import db  # 使用正确的导入语法
 
 # 加载.env.dev文件
 env_path = os.path.join(os.path.dirname(os.path.dirname(os.path.dirname(os.path.dirname(__file__)))), '.env.dev')
@@ -23,7 +23,6 @@ load_dotenv(env_path)
 class Memory_graph:
     def __init__(self):
         self.G = nx.Graph()  # 使用 networkx 的图结构
-        self.db = Database.get_instance()
 
     def connect_dot(self, concept1, concept2):
         self.G.add_edge(concept1, concept2)
@@ -96,7 +95,7 @@ class Memory_graph:
             dot_data = {
                 "concept": node
             }
-            self.db.store_memory_dots.insert_one(dot_data)
+            db.store_memory_dots.insert_one(dot_data)
 
     @property
     def dots(self):
@@ -106,7 +105,7 @@ class Memory_graph:
     def get_random_chat_from_db(self, length: int, timestamp: str):
         # 从数据库中根据时间戳获取离其最近的聊天记录
         chat_text = ''
-        closest_record = self.db.messages.find_one({"time": {"$lte": timestamp}}, sort=[('time', -1)])  # 调试输出
+        closest_record = db.messages.find_one({"time": {"$lte": timestamp}}, sort=[('time', -1)])  # 调试输出
         logger.info(
             f"距离time最近的消息时间: {time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(int(closest_record['time'])))}")
 
@@ -115,7 +114,7 @@ class Memory_graph:
             group_id = closest_record['group_id']  # 获取groupid
             # 获取该时间戳之后的length条消息，且groupid相同
             chat_record = list(
-                self.db.messages.find({"time": {"$gt": closest_time}, "group_id": group_id}).sort('time', 1).limit(
+                db.messages.find({"time": {"$gt": closest_time}, "group_id": group_id}).sort('time', 1).limit(
                     length))
             for record in chat_record:
                 time_str = time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(int(record['time'])))
@@ -130,50 +129,39 @@ class Memory_graph:
 
     def save_graph_to_db(self):
         # 清空现有的图数据
-        self.db.graph_data.delete_many({})
+        db.graph_data.delete_many({})
         # 保存节点
         for node in self.G.nodes(data=True):
             node_data = {
                 'concept': node[0],
                 'memory_items': node[1].get('memory_items', [])  # 默认为空列表
             }
-            self.db.graph_data.nodes.insert_one(node_data)
+            db.graph_data.nodes.insert_one(node_data)
         # 保存边
         for edge in self.G.edges():
             edge_data = {
                 'source': edge[0],
                 'target': edge[1]
             }
-            self.db.graph_data.edges.insert_one(edge_data)
+            db.graph_data.edges.insert_one(edge_data)
 
     def load_graph_from_db(self):
         # 清空当前图
         self.G.clear()
         # 加载节点
-        nodes = self.db.graph_data.nodes.find()
+        nodes = db.graph_data.nodes.find()
         for node in nodes:
             memory_items = node.get('memory_items', [])
             if not isinstance(memory_items, list):
                 memory_items = [memory_items] if memory_items else []
             self.G.add_node(node['concept'], memory_items=memory_items)
         # 加载边
-        edges = self.db.graph_data.edges.find()
+        edges = db.graph_data.edges.find()
         for edge in edges:
             self.G.add_edge(edge['source'], edge['target'])
 
 
 def main():
-    # 初始化数据库
-    Database.initialize(
-        uri=os.getenv("MONGODB_URI"),
-        host=os.getenv("MONGODB_HOST", "127.0.0.1"),
-        port=int(os.getenv("MONGODB_PORT", "27017")),
-        db_name=os.getenv("DATABASE_NAME", "MegBot"),
-        username=os.getenv("MONGODB_USERNAME"),
-        password=os.getenv("MONGODB_PASSWORD"),
-        auth_source=os.getenv("MONGODB_AUTH_SOURCE"),
-    )
-
     memory_graph = Memory_graph()
     memory_graph.load_graph_from_db()
 

src/plugins/memory_system/memory.py

@@ -10,12 +10,12 @@ import networkx as nx
 
 from loguru import logger
 from nonebot import get_driver
-from ...common.database import Database  # 使用正确的导入语法
+from ...common.database import db  # 使用正确的导入语法
 from ..chat.config import global_config
 from ..chat.utils import (
     calculate_information_content,
     cosine_similarity,
-    get_cloest_chat_from_db,
+    get_closest_chat_from_db,
     text_to_vector,
 )
 from ..models.utils_model import LLM_request
@@ -23,7 +23,6 @@ from ..models.utils_model import LLM_request
 class Memory_graph:
     def __init__(self):
         self.G = nx.Graph()  # 使用 networkx 的图结构
-        self.db = Database.get_instance()
 
     def connect_dot(self, concept1, concept2):
         # 避免自连接
@@ -191,19 +190,19 @@ class Hippocampus:
         # 短期：1h   中期：4h   长期：24h
         for _ in range(time_frequency.get('near')):
             random_time = current_timestamp - random.randint(1, 3600)
-            messages = get_cloest_chat_from_db(db=self.memory_graph.db, length=chat_size, timestamp=random_time)
+            messages = get_closest_chat_from_db(length=chat_size, timestamp=random_time)
             if messages:
                 chat_samples.append(messages)
 
         for _ in range(time_frequency.get('mid')):
             random_time = current_timestamp - random.randint(3600, 3600 * 4)
-            messages = get_cloest_chat_from_db(db=self.memory_graph.db, length=chat_size, timestamp=random_time)
+            messages = get_closest_chat_from_db(length=chat_size, timestamp=random_time)
             if messages:
                 chat_samples.append(messages)
 
         for _ in range(time_frequency.get('far')):
             random_time = current_timestamp - random.randint(3600 * 4, 3600 * 24)
-            messages = get_cloest_chat_from_db(db=self.memory_graph.db, length=chat_size, timestamp=random_time)
+            messages = get_closest_chat_from_db(length=chat_size, timestamp=random_time)
             if messages:
                 chat_samples.append(messages)
 
@@ -349,7 +348,7 @@ class Hippocampus:
     def sync_memory_to_db(self):
         """检查并同步内存中的图结构与数据库"""
         # 获取数据库中所有节点和内存中所有节点
-        db_nodes = list(self.memory_graph.db.graph_data.nodes.find())
+        db_nodes = list(db.graph_data.nodes.find())
         memory_nodes = list(self.memory_graph.G.nodes(data=True))
 
         # 转换数据库节点为字典格式,方便查找
@@ -377,7 +376,7 @@ class Hippocampus:
                     'created_time': created_time,
                     'last_modified': last_modified
                 }
-                self.memory_graph.db.graph_data.nodes.insert_one(node_data)
+                db.graph_data.nodes.insert_one(node_data)
             else:
                 # 获取数据库中节点的特征值
                 db_node = db_nodes_dict[concept]
@@ -385,7 +384,7 @@ class Hippocampus:
 
                 # 如果特征值不同,则更新节点
                 if db_hash != memory_hash:
-                    self.memory_graph.db.graph_data.nodes.update_one(
+                    db.graph_data.nodes.update_one(
                         {'concept': concept},
                         {'$set': {
                             'memory_items': memory_items,
@@ -396,7 +395,7 @@ class Hippocampus:
                     )
 
         # 处理边的信息
-        db_edges = list(self.memory_graph.db.graph_data.edges.find())
+        db_edges = list(db.graph_data.edges.find())
         memory_edges = list(self.memory_graph.G.edges(data=True))
 
         # 创建边的哈希值字典
@@ -428,11 +427,11 @@ class Hippocampus:
                     'created_time': created_time,
                     'last_modified': last_modified
                 }
-                self.memory_graph.db.graph_data.edges.insert_one(edge_data)
+                db.graph_data.edges.insert_one(edge_data)
             else:
                 # 检查边的特征值是否变化
                 if db_edge_dict[edge_key]['hash'] != edge_hash:
-                    self.memory_graph.db.graph_data.edges.update_one(
+                    db.graph_data.edges.update_one(
                         {'source': source, 'target': target},
                         {'$set': {
                             'hash': edge_hash,
@@ -451,7 +450,7 @@ class Hippocampus:
         self.memory_graph.G.clear()
 
         # 从数据库加载所有节点
-        nodes = list(self.memory_graph.db.graph_data.nodes.find())
+        nodes = list(db.graph_data.nodes.find())
         for node in nodes:
             concept = node['concept']
             memory_items = node.get('memory_items', [])
@@ -468,7 +467,7 @@ class Hippocampus:
                 if 'last_modified' not in node:
                     update_data['last_modified'] = current_time
                 
-                self.memory_graph.db.graph_data.nodes.update_one(
+                db.graph_data.nodes.update_one(
                     {'concept': concept},
                     {'$set': update_data}
                 )
@@ -485,7 +484,7 @@ class Hippocampus:
                                        last_modified=last_modified)
 
         # 从数据库加载所有边
-        edges = list(self.memory_graph.db.graph_data.edges.find())
+        edges = list(db.graph_data.edges.find())
         for edge in edges:
             source = edge['source']
             target = edge['target']
@@ -501,7 +500,7 @@ class Hippocampus:
                 if 'last_modified' not in edge:
                     update_data['last_modified'] = current_time
                 
-                self.memory_graph.db.graph_data.edges.update_one(
+                db.graph_data.edges.update_one(
                     {'source': source, 'target': target},
                     {'$set': update_data}
                 )

src/plugins/memory_system/memory_manual_build.py

@@ -19,7 +19,7 @@ import jieba
 root_path = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../.."))
 sys.path.append(root_path)
 
-from src.common.database import Database
+from src.common.database import db
 from src.plugins.memory_system.offline_llm import LLMModel
 
 # 获取当前文件的目录
@@ -49,7 +49,7 @@ def calculate_information_content(text):
     
     return entropy
 
-def get_cloest_chat_from_db(db, length: int, timestamp: str):
+def get_closest_chat_from_db(length: int, timestamp: str):
     """从数据库中获取最接近指定时间戳的聊天记录，并记录读取次数
     
     Returns:
@@ -91,7 +91,6 @@ def get_cloest_chat_from_db(db, length: int, timestamp: str):
 class Memory_graph:
     def __init__(self):
         self.G = nx.Graph()  # 使用 networkx 的图结构
-        self.db = Database.get_instance()
         
     def connect_dot(self, concept1, concept2):
         # 如果边已存在，增加 strength
@@ -186,19 +185,19 @@ class Hippocampus:
         # 短期：1h   中期：4h   长期：24h
         for _ in range(time_frequency.get('near')):
             random_time = current_timestamp - random.randint(1, 3600*4)
-            messages = get_cloest_chat_from_db(db=self.memory_graph.db, length=chat_size, timestamp=random_time)
+            messages = get_closest_chat_from_db(length=chat_size, timestamp=random_time)
             if messages:
                 chat_samples.append(messages)
                 
         for _ in range(time_frequency.get('mid')):
             random_time = current_timestamp - random.randint(3600*4, 3600*24)
-            messages = get_cloest_chat_from_db(db=self.memory_graph.db, length=chat_size, timestamp=random_time)
+            messages = get_closest_chat_from_db(length=chat_size, timestamp=random_time)
             if messages:
                 chat_samples.append(messages)
                 
         for _ in range(time_frequency.get('far')):
             random_time = current_timestamp - random.randint(3600*24, 3600*24*7)
-            messages = get_cloest_chat_from_db(db=self.memory_graph.db, length=chat_size, timestamp=random_time)
+            messages = get_closest_chat_from_db(length=chat_size, timestamp=random_time)
             if messages:
                 chat_samples.append(messages)
                 
@@ -323,7 +322,7 @@ class Hippocampus:
         self.memory_graph.G.clear()
         
         # 从数据库加载所有节点
-        nodes = self.memory_graph.db.graph_data.nodes.find()
+        nodes = db.graph_data.nodes.find()
         for node in nodes:
             concept = node['concept']
             memory_items = node.get('memory_items', [])
@@ -334,7 +333,7 @@ class Hippocampus:
             self.memory_graph.G.add_node(concept, memory_items=memory_items)
             
         # 从数据库加载所有边
-        edges = self.memory_graph.db.graph_data.edges.find()
+        edges = db.graph_data.edges.find()
         for edge in edges:
             source = edge['source']
             target = edge['target']
@@ -371,7 +370,7 @@ class Hippocampus:
         使用特征值(哈希值)快速判断是否需要更新
         """
         # 获取数据库中所有节点和内存中所有节点
-        db_nodes = list(self.memory_graph.db.graph_data.nodes.find())
+        db_nodes = list(db.graph_data.nodes.find())
         memory_nodes = list(self.memory_graph.G.nodes(data=True))
         
         # 转换数据库节点为字典格式，方便查找
@@ -394,7 +393,7 @@ class Hippocampus:
                     'memory_items': memory_items,
                     'hash': memory_hash
                 }
-                self.memory_graph.db.graph_data.nodes.insert_one(node_data)
+                db.graph_data.nodes.insert_one(node_data)
             else:
                 # 获取数据库中节点的特征值
                 db_node = db_nodes_dict[concept]
@@ -403,7 +402,7 @@ class Hippocampus:
                 # 如果特征值不同，则更新节点
                 if db_hash != memory_hash:
                     # logger.info(f"更新节点内容: {concept}")
-                    self.memory_graph.db.graph_data.nodes.update_one(
+                    db.graph_data.nodes.update_one(
                         {'concept': concept},
                         {'$set': {
                             'memory_items': memory_items,
@@ -416,10 +415,10 @@ class Hippocampus:
         for db_node in db_nodes:
             if db_node['concept'] not in memory_concepts:
                 # logger.info(f"删除多余节点: {db_node['concept']}")
-                self.memory_graph.db.graph_data.nodes.delete_one({'concept': db_node['concept']})
+                db.graph_data.nodes.delete_one({'concept': db_node['concept']})
                 
         # 处理边的信息
-        db_edges = list(self.memory_graph.db.graph_data.edges.find())
+        db_edges = list(db.graph_data.edges.find())
         memory_edges = list(self.memory_graph.G.edges())
         
         # 创建边的哈希值字典
@@ -445,12 +444,12 @@ class Hippocampus:
                     'num': 1,
                     'hash': edge_hash
                 }
-                self.memory_graph.db.graph_data.edges.insert_one(edge_data)
+                db.graph_data.edges.insert_one(edge_data)
             else:
                 # 检查边的特征值是否变化
                 if db_edge_dict[edge_key]['hash'] != edge_hash:
                     logger.info(f"更新边: {source} - {target}")
-                    self.memory_graph.db.graph_data.edges.update_one(
+                    db.graph_data.edges.update_one(
                         {'source': source, 'target': target},
                         {'$set': {'hash': edge_hash}}
                     )
@@ -461,7 +460,7 @@ class Hippocampus:
             if edge_key not in memory_edge_set:
                 source, target = edge_key
                 logger.info(f"删除多余边: {source} - {target}")
-                self.memory_graph.db.graph_data.edges.delete_one({
+                db.graph_data.edges.delete_one({
                     'source': source,
                     'target': target
                 })
@@ -487,9 +486,9 @@ class Hippocampus:
             topic: 要删除的节点概念
         """
         # 删除节点
-        self.memory_graph.db.graph_data.nodes.delete_one({'concept': topic})
+        db.graph_data.nodes.delete_one({'concept': topic})
         # 删除所有涉及该节点的边
-        self.memory_graph.db.graph_data.edges.delete_many({
+        db.graph_data.edges.delete_many({
             '$or': [
                 {'source': topic},
                 {'target': topic}
@@ -902,17 +901,6 @@ def visualize_graph_lite(memory_graph: Memory_graph, color_by_memory: bool = Fal
     plt.show()
 
 async def main():
-    # 初始化数据库
-    logger.info("正在初始化数据库连接...")
-    Database.initialize(
-        uri=os.getenv("MONGODB_URI"),
-        host=os.getenv("MONGODB_HOST", "127.0.0.1"),
-        port=int(os.getenv("MONGODB_PORT", "27017")),
-        db_name=os.getenv("DATABASE_NAME", "MegBot"),
-        username=os.getenv("MONGODB_USERNAME"),
-        password=os.getenv("MONGODB_PASSWORD"),
-        auth_source=os.getenv("MONGODB_AUTH_SOURCE"),
-    )
     start_time = time.time()
 
     test_pare = {'do_build_memory':False,'do_forget_topic':False,'do_visualize_graph':True,'do_query':False,'do_merge_memory':False}

src/plugins/memory_system/memory_test1.py

@@ -38,7 +38,7 @@ import jieba
 
 # from chat.config import global_config
 sys.path.append("C:/GitHub/MaiMBot")  # 添加项目根目录到 Python 路径
-from src.common.database import Database
+from src.common.database import db
 from src.plugins.memory_system.offline_llm import LLMModel
 
 # 获取当前文件的目录
@@ -56,45 +56,6 @@ else:
     logger.warning(f"未找到环境变量文件: {env_path}")
     logger.info("将使用默认配置")
 
-class Database:
-    _instance = None
-    db = None
-    
-    @classmethod
-    def get_instance(cls):
-        if cls._instance is None:
-            cls._instance = cls()
-        return cls._instance
-    
-    def __init__(self):
-        if not Database.db:
-            Database.initialize(
-                    uri=os.getenv("MONGODB_URI"),
-                    host=os.getenv("MONGODB_HOST", "127.0.0.1"),
-                    port=int(os.getenv("MONGODB_PORT", "27017")),
-                    db_name=os.getenv("DATABASE_NAME", "MegBot"),
-                    username=os.getenv("MONGODB_USERNAME"),
-                    password=os.getenv("MONGODB_PASSWORD"),
-                    auth_source=os.getenv("MONGODB_AUTH_SOURCE"),
-                )
-            
-    @classmethod
-    def initialize(cls, host, port, db_name, username=None, password=None, auth_source="admin"):
-        try:
-            if username and password:
-                uri = f"mongodb://{username}:{password}@{host}:{port}/{db_name}?authSource={auth_source}"
-            else:
-                uri = f"mongodb://{host}:{port}"
-                
-            client = pymongo.MongoClient(uri)
-            cls.db = client[db_name]
-            # 测试连接
-            client.server_info()
-            logger.success("MongoDB连接成功!")
-            
-        except Exception as e:
-            logger.error(f"初始化MongoDB失败: {str(e)}")
-            raise
 
 def calculate_information_content(text):
     """计算文本的信息量（熵）"""
@@ -108,7 +69,7 @@ def calculate_information_content(text):
     
     return entropy
 
-def get_cloest_chat_from_db(db, length: int, timestamp: str):
+def get_closest_chat_from_db(length: int, timestamp: str):
     """从数据库中获取最接近指定时间戳的聊天记录，并记录读取次数
     
     Returns:
@@ -163,7 +124,7 @@ class Memory_cortex:
         default_time = datetime.datetime.now().timestamp()
         
         # 从数据库加载所有节点
-        nodes = self.memory_graph.db.graph_data.nodes.find()
+        nodes = db.graph_data.nodes.find()
         for node in nodes:
             concept = node['concept']
             memory_items = node.get('memory_items', [])
@@ -180,7 +141,7 @@ class Memory_cortex:
                 created_time = default_time
                 last_modified = default_time
                 # 更新数据库中的节点
-                self.memory_graph.db.graph_data.nodes.update_one(
+                db.graph_data.nodes.update_one(
                     {'concept': concept},
                     {'$set': {
                         'created_time': created_time,
@@ -196,7 +157,7 @@ class Memory_cortex:
                                        last_modified=last_modified)
             
         # 从数据库加载所有边
-        edges = self.memory_graph.db.graph_data.edges.find()
+        edges = db.graph_data.edges.find()
         for edge in edges:
             source = edge['source']
             target = edge['target']
@@ -212,7 +173,7 @@ class Memory_cortex:
                     created_time = default_time
                     last_modified = default_time
                     # 更新数据库中的边
-                    self.memory_graph.db.graph_data.edges.update_one(
+                    db.graph_data.edges.update_one(
                         {'source': source, 'target': target},
                         {'$set': {
                             'created_time': created_time,
@@ -256,7 +217,7 @@ class Memory_cortex:
         current_time = datetime.datetime.now().timestamp()
         
         # 获取数据库中所有节点和内存中所有节点
-        db_nodes = list(self.memory_graph.db.graph_data.nodes.find())
+        db_nodes = list(db.graph_data.nodes.find())
         memory_nodes = list(self.memory_graph.G.nodes(data=True))
         
         # 转换数据库节点为字典格式，方便查找
@@ -280,7 +241,7 @@ class Memory_cortex:
                     'created_time': data.get('created_time', current_time),
                     'last_modified': data.get('last_modified', current_time)
                 }
-                self.memory_graph.db.graph_data.nodes.insert_one(node_data)
+                db.graph_data.nodes.insert_one(node_data)
             else:
                 # 获取数据库中节点的特征值
                 db_node = db_nodes_dict[concept]
@@ -288,7 +249,7 @@ class Memory_cortex:
                 
                 # 如果特征值不同，则更新节点
                 if db_hash != memory_hash:
-                    self.memory_graph.db.graph_data.nodes.update_one(
+                    db.graph_data.nodes.update_one(
                         {'concept': concept},
                         {'$set': {
                             'memory_items': memory_items,
@@ -301,10 +262,10 @@ class Memory_cortex:
         memory_concepts = set(node[0] for node in memory_nodes)
         for db_node in db_nodes:
             if db_node['concept'] not in memory_concepts:
-                self.memory_graph.db.graph_data.nodes.delete_one({'concept': db_node['concept']})
+                db.graph_data.nodes.delete_one({'concept': db_node['concept']})
                 
         # 处理边的信息
-        db_edges = list(self.memory_graph.db.graph_data.edges.find())
+        db_edges = list(db.graph_data.edges.find())
         memory_edges = list(self.memory_graph.G.edges(data=True))
         
         # 创建边的哈希值字典
@@ -332,11 +293,11 @@ class Memory_cortex:
                     'created_time': data.get('created_time', current_time),
                     'last_modified': data.get('last_modified', current_time)
                 }
-                self.memory_graph.db.graph_data.edges.insert_one(edge_data)
+                db.graph_data.edges.insert_one(edge_data)
             else:
                 # 检查边的特征值是否变化
                 if db_edge_dict[edge_key]['hash'] != edge_hash:
-                    self.memory_graph.db.graph_data.edges.update_one(
+                    db.graph_data.edges.update_one(
                         {'source': source, 'target': target},
                         {'$set': {
                             'hash': edge_hash,
@@ -350,7 +311,7 @@ class Memory_cortex:
         for edge_key in db_edge_dict:
             if edge_key not in memory_edge_set:
                 source, target = edge_key
-                self.memory_graph.db.graph_data.edges.delete_one({
+                db.graph_data.edges.delete_one({
                     'source': source,
                     'target': target
                 })
@@ -365,9 +326,9 @@ class Memory_cortex:
             topic: 要删除的节点概念
         """
         # 删除节点
-        self.memory_graph.db.graph_data.nodes.delete_one({'concept': topic})
+        db.graph_data.nodes.delete_one({'concept': topic})
         # 删除所有涉及该节点的边
-        self.memory_graph.db.graph_data.edges.delete_many({
+        db.graph_data.edges.delete_many({
             '$or': [
                 {'source': topic},
                 {'target': topic}
@@ -377,7 +338,6 @@ class Memory_cortex:
 class Memory_graph:
     def __init__(self):
         self.G = nx.Graph()  # 使用 networkx 的图结构
-        self.db = Database.get_instance()
         
     def connect_dot(self, concept1, concept2):
         # 避免自连接
@@ -492,19 +452,19 @@ class Hippocampus:
         # 短期：1h   中期：4h   长期：24h
         for _ in range(time_frequency.get('near')):
             random_time = current_timestamp - random.randint(1, 3600*4)
-            messages = get_cloest_chat_from_db(db=self.memory_graph.db, length=chat_size, timestamp=random_time)
+            messages = get_closest_chat_from_db(length=chat_size, timestamp=random_time)
             if messages:
                 chat_samples.append(messages)
                 
         for _ in range(time_frequency.get('mid')):
             random_time = current_timestamp - random.randint(3600*4, 3600*24)
-            messages = get_cloest_chat_from_db(db=self.memory_graph.db, length=chat_size, timestamp=random_time)
+            messages = get_closest_chat_from_db(length=chat_size, timestamp=random_time)
             if messages:
                 chat_samples.append(messages)
                 
         for _ in range(time_frequency.get('far')):
             random_time = current_timestamp - random.randint(3600*24, 3600*24*7)
-            messages = get_cloest_chat_from_db(db=self.memory_graph.db, length=chat_size, timestamp=random_time)
+            messages = get_closest_chat_from_db(length=chat_size, timestamp=random_time)
             if messages:
                 chat_samples.append(messages)
                 
@@ -1134,7 +1094,6 @@ def visualize_graph_lite(memory_graph: Memory_graph, color_by_memory: bool = Fal
 async def main():
     # 初始化数据库
     logger.info("正在初始化数据库连接...")
-    db = Database.get_instance()
     start_time = time.time()
     
     test_pare = {'do_build_memory':True,'do_forget_topic':False,'do_visualize_graph':True,'do_query':False,'do_merge_memory':False}

src/plugins/models/utils_model.py

@@ -10,7 +10,7 @@ from nonebot import get_driver
 import base64
 from PIL import Image
 import io
-from ...common.database import Database
+from ...common.database import db
 from ..chat.config import global_config
 
 driver = get_driver()
@@ -34,17 +34,16 @@ class LLM_request:
         self.pri_out = model.get("pri_out", 0)
 
         # 获取数据库实例
-        self.db = Database.get_instance()
         self._init_database()
 
     def _init_database(self):
         """初始化数据库集合"""
         try:
             # 创建llm_usage集合的索引
-            self.db.llm_usage.create_index([("timestamp", 1)])
+            db.llm_usage.create_index([("timestamp", 1)])
-            self.db.llm_usage.create_index([("model_name", 1)])
+            db.llm_usage.create_index([("model_name", 1)])
-            self.db.llm_usage.create_index([("user_id", 1)])
+            db.llm_usage.create_index([("user_id", 1)])
-            self.db.llm_usage.create_index([("request_type", 1)])
+            db.llm_usage.create_index([("request_type", 1)])
         except Exception:
             logger.error("创建数据库索引失败")
 
@@ -73,7 +72,7 @@ class LLM_request:
                 "status": "success",
                 "timestamp": datetime.now()
             }
-            self.db.llm_usage.insert_one(usage_data)
+            db.llm_usage.insert_one(usage_data)
             logger.info(
                 f"Token使用情况 - 模型: {self.model_name}, "
                 f"用户: {user_id}, 类型: {request_type}, "
@@ -133,7 +132,7 @@ class LLM_request:
         # 常见Error Code Mapping
         error_code_mapping = {
             400: "参数不正确",
-            401: "API key 错误，认证失败",
+            401: "API key 错误，认证失败，请检查/config/bot_config.toml和.env.prod中的配置是否正确哦~",
             402: "账号余额不足",
             403: "需要实名,或余额不足",
             404: "Not Found",

src/plugins/schedule/schedule_generator.py

@@ -8,18 +8,20 @@ from nonebot import get_driver
 
 from src.plugins.chat.config import global_config
 
-from ...common.database import Database  # 使用正确的导入语法
+from ...common.database import db  # 使用正确的导入语法
 from ..models.utils_model import LLM_request
 
 driver = get_driver()
 config = driver.config
 
+
 class ScheduleGenerator:
+    enable_output: bool = True
+
     def __init__(self):
         # 根据global_config.llm_normal这一字典配置指定模型
         # self.llm_scheduler = LLMModel(model = global_config.llm_normal,temperature=0.9)
         self.llm_scheduler = LLM_request(model=global_config.llm_normal, temperature=0.9)
-        self.db = Database.get_instance()
         self.today_schedule_text = ""
         self.today_schedule = {}
         self.tomorrow_schedule_text = ""
@@ -33,43 +35,50 @@ class ScheduleGenerator:
         yesterday = datetime.datetime.now() - datetime.timedelta(days=1)
 
         self.today_schedule_text, self.today_schedule = await self.generate_daily_schedule(target_date=today)
-        self.tomorrow_schedule_text, self.tomorrow_schedule = await self.generate_daily_schedule(target_date=tomorrow,
+        self.tomorrow_schedule_text, self.tomorrow_schedule = await self.generate_daily_schedule(
-                                                                                                 read_only=True)
+            target_date=tomorrow, read_only=True
+        )
         self.yesterday_schedule_text, self.yesterday_schedule = await self.generate_daily_schedule(
-            target_date=yesterday, read_only=True)
+            target_date=yesterday, read_only=True
-
+        )
-    async def generate_daily_schedule(self, target_date: datetime.datetime = None, read_only: bool = False) -> Dict[
-        str, str]:
 
+    async def generate_daily_schedule(
+        self, target_date: datetime.datetime = None, read_only: bool = False
+    ) -> Dict[str, str]:
         date_str = target_date.strftime("%Y-%m-%d")
         weekday = target_date.strftime("%A")
 
         schedule_text = str
 
-        existing_schedule = self.db.schedule.find_one({"date": date_str})
+        existing_schedule = db.schedule.find_one({"date": date_str})
         if existing_schedule:
-            logger.debug(f"{date_str}的日程已存在:")
+            if self.enable_output:
+                logger.debug(f"{date_str}的日程已存在:")
             schedule_text = existing_schedule["schedule"]
             # print(self.schedule_text)
 
         elif not read_only:
             logger.debug(f"{date_str}的日程不存在，准备生成新的日程。")
-            prompt = f"""我是{global_config.BOT_NICKNAME}，{global_config.PROMPT_SCHEDULE_GEN}，请为我生成{date_str}（{weekday}）的日程安排，包括：""" + \
+            prompt = (
-                     """
+                f"""我是{global_config.BOT_NICKNAME}，{global_config.PROMPT_SCHEDULE_GEN}，请为我生成{date_str}（{weekday}）的日程安排，包括："""
+                + """
             1. 早上的学习和工作安排
             2. 下午的活动和任务
             3. 晚上的计划和休息时间
             请按照时间顺序列出具体时间点和对应的活动，用一个时间点而不是时间段来表示时间，用JSON格式返回日程表，仅返回内容，不要返回注释，不要添加任何markdown或代码块样式，时间采用24小时制，格式为{"时间": "活动","时间": "活动",...}。"""
+            )
 
             try:
                 schedule_text, _ = await self.llm_scheduler.generate_response(prompt)
-                self.db.schedule.insert_one({"date": date_str, "schedule": schedule_text})
+                db.schedule.insert_one({"date": date_str, "schedule": schedule_text})
+                self.enable_output = True
             except Exception as e:
                 logger.error(f"生成日程失败: {str(e)}")
                 schedule_text = "生成日程时出错了"
             # print(self.schedule_text)
         else:
-            logger.debug(f"{date_str}的日程不存在。")
+            if self.enable_output:
+                logger.debug(f"{date_str}的日程不存在。")
             schedule_text = "忘了"
 
             return schedule_text, None
@@ -96,7 +105,7 @@ class ScheduleGenerator:
 
         # 找到最接近当前时间的任务
         closest_time = None
-        min_diff = float('inf')
+        min_diff = float("inf")
 
         # 检查今天的日程
         if not self.today_schedule:
@@ -143,12 +152,13 @@ class ScheduleGenerator:
         """打印完整的日程安排"""
         if not self._parse_schedule(self.today_schedule_text):
             logger.warning("今日日程有误，将在下次运行时重新生成")
-            self.db.schedule.delete_one({"date": datetime.datetime.now().strftime("%Y-%m-%d")})
+            db.schedule.delete_one({"date": datetime.datetime.now().strftime("%Y-%m-%d")})
         else:
             logger.info("=== 今日日程安排 ===")
             for time_str, activity in self.today_schedule.items():
                 logger.info(f"时间[{time_str}]: 活动[{activity}]")
             logger.info("==================")
+            self.enable_output = False
 
 
 # def main():

src/plugins/utils/statistic.py

@@ -5,7 +5,7 @@ from datetime import datetime, timedelta
 from typing import Any, Dict
 from loguru import logger
 
-from ...common.database import Database
+from ...common.database import db
 
 
 class LLMStatistics:
@@ -15,7 +15,6 @@ class LLMStatistics:
         Args:
             output_file: 统计结果输出文件路径
         """
-        self.db = Database.get_instance()
         self.output_file = output_file
         self.running = False
         self.stats_thread = None
@@ -53,7 +52,7 @@ class LLMStatistics:
             "costs_by_model": defaultdict(float)
         }
         
-        cursor = self.db.llm_usage.find({
+        cursor = db.llm_usage.find({
             "timestamp": {"$gte": start_time}
         })
         

src/plugins/zhishi/knowledge_library.py

@@ -14,7 +14,7 @@ root_path = os.path.abspath(os.path.join(os.path.dirname(__file__), "../../.."))
 sys.path.append(root_path)
 
 # 现在可以导入src模块
-from src.common.database import Database
+from src.common.database import db
 
 # 加载根目录下的env.edv文件
 env_path = os.path.join(root_path, ".env.prod")
@@ -24,18 +24,6 @@ load_dotenv(env_path)
 
 class KnowledgeLibrary:
     def __init__(self):
-        # 初始化数据库连接
-        if Database._instance is None:
-            Database.initialize(
-                uri=os.getenv("MONGODB_URI"),
-                host=os.getenv("MONGODB_HOST", "127.0.0.1"),
-                port=int(os.getenv("MONGODB_PORT", "27017")),
-                db_name=os.getenv("DATABASE_NAME", "MegBot"),
-                username=os.getenv("MONGODB_USERNAME"),
-                password=os.getenv("MONGODB_PASSWORD"),
-                auth_source=os.getenv("MONGODB_AUTH_SOURCE"),
-            )
-        self.db = Database.get_instance()
         self.raw_info_dir = "data/raw_info"
         self._ensure_dirs()
         self.api_key = os.getenv("SILICONFLOW_KEY")
@@ -176,7 +164,7 @@ class KnowledgeLibrary:
         
         try:
             current_hash = self.calculate_file_hash(file_path)
-            processed_record = self.db.processed_files.find_one({"file_path": file_path})
+            processed_record = db.processed_files.find_one({"file_path": file_path})
             
             if processed_record:
                 if processed_record.get("hash") == current_hash:
@@ -197,14 +185,14 @@ class KnowledgeLibrary:
                         "split_length": knowledge_length,
                         "created_at": datetime.now()
                     }
-                    self.db.knowledges.insert_one(knowledge)
+                    db.knowledges.insert_one(knowledge)
                     result["chunks_processed"] += 1
             
             split_by = processed_record.get("split_by", []) if processed_record else []
             if knowledge_length not in split_by:
                 split_by.append(knowledge_length)
             
-            self.db.knowledges.processed_files.update_one(
+            db.knowledges.processed_files.update_one(
                 {"file_path": file_path},
                 {
                     "$set": {
@@ -322,7 +310,7 @@ class KnowledgeLibrary:
             {"$project": {"content": 1, "similarity": 1, "file_path": 1}}
         ]
         
-        results = list(self.db.knowledges.aggregate(pipeline))
+        results = list(db.knowledges.aggregate(pipeline))
         return results
 
 # 创建单例实例
@@ -346,7 +334,7 @@ if __name__ == "__main__":
         elif choice == '2':
             confirm = input("确定要删除所有知识吗？这个操作不可撤销！(y/n): ").strip().lower()
             if confirm == 'y':
-                knowledge_library.db.knowledges.delete_many({})
+                db.knowledges.delete_many({})
                 console.print("[green]已清空所有知识！[/green]")
             continue
         elif choice == '1':

template.env

@@ -23,7 +23,7 @@ CHAT_ANY_WHERE_BASE_URL=https://api.chatanywhere.tech/v1
 SILICONFLOW_BASE_URL=https://api.siliconflow.cn/v1/
 DEEP_SEEK_BASE_URL=https://api.deepseek.com/v1
 
-#定义你要用的api的base_url
+#定义你要用的api的key(需要去对应网站申请哦)
 DEEP_SEEK_KEY=
 CHAT_ANY_WHERE_KEY=
 SILICONFLOW_KEY=