mirror of https://github.com/Mai-with-u/MaiBot.git
Cindy-Master
GitHub
commit
a2c782cb7f
|
|
@ -77,10 +77,6 @@
|
|||
- [🎀 新手配置指南](docs/installation_cute.md) - 通俗易懂的配置教程，适合初次使用的猫娘
|
||||
- [⚙️ 标准配置指南](docs/installation_standard.md) - 简明专业的配置说明，适合有经验的用户
|
||||
|
||||
### 常见问题
|
||||
|
||||
- [❓ 快速 Q & A ](docs/fast_q_a.md) - 针对新手的疑难解答，适合完全没接触过编程的新手
|
||||
|
||||
<div align="left">
|
||||
<h3>了解麦麦 </h3>
|
||||
</div>
|
||||
|
|
|
|||
15
bot.py
15
bot.py
|
|
@ -12,8 +12,6 @@ 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}
|
||||
|
||||
|
|
@ -111,17 +109,6 @@ 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
|
||||
|
|
@ -223,7 +210,6 @@ def raw_main():
|
|||
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}
|
||||
|
|
@ -249,6 +235,7 @@ def raw_main():
|
|||
|
||||
|
||||
if __name__ == "__main__":
|
||||
|
||||
try:
|
||||
raw_main()
|
||||
|
||||
|
|
|
|||
|
|
@ -0,0 +1,141 @@
|
|||
cbb569e - Create 如果你更新了版本，点我.txt
|
||||
a91ef7b - 自动升级配置文件脚本
|
||||
ed18f2e - 新增了知识库一键启动漂亮脚本
|
||||
80ed568 - fix: 删除print调试代码
|
||||
c681a82 - 修复小名无效问题
|
||||
e54038f - fix: 从 nixpkgs 增加 numpy 依赖，以避免出现 libc++.so 找不到的问题
|
||||
26782c9 - fix: 修复 ENVIRONMENT 变量在同一终端下不能被覆盖的问题
|
||||
8c34637 - 提高健壮性
|
||||
2688a96 - close SengokuCola/MaiMBot#225 让麦麦可以正确读取分享卡片
|
||||
cd16e68 - 修复表情包发送时的缺失参数
|
||||
b362c35 - feat: 更新 flake.nix ，采用 venv 的方式生成环境，nixos用户也可以本机运行项目了
|
||||
3c8c897 - 屏蔽一个臃肿的debug信息
|
||||
9d0152a - 修复了合并过程中造成的代码重复
|
||||
956135c - 添加一些注释
|
||||
a412741 - 将print变为logger.debug
|
||||
3180426 - 修复了没有改掉的typo字段
|
||||
aea3bff - 添加私聊过滤开关,更新config,增加约束
|
||||
cda6281 - chore: update emoji_manager.py
|
||||
baed856 - 修正了私聊屏蔽词输出
|
||||
66a0f18 - 修复了私聊时产生reply消息的bug
|
||||
3bf5cd6 - feat: 新增运行时重载配置文件；新增根据不同环境(dev;prod)显示不同级别的log
|
||||
33cd83b - 添加私聊功能
|
||||
aa41f0d - fix: 放反了
|
||||
ef8691c - fix: 修改message继承逻辑，修复回复消息无法识别
|
||||
7d017be - fix:模型降级
|
||||
e1019ad - fix: 修复变量拼写错误并优化代码可读性
|
||||
c24bb70 - fix: 流式输出模式增加结束判断与token用量记录
|
||||
60a9376 - 添加logger的debug输出开关,默认为不开启
|
||||
bfa9a3c - fix: 添加群信息获取的错误处理 (#173)
|
||||
4cc5c8e - 修正.env.prod和.env.dev的生成
|
||||
dea14c1 - fix: 模型降级目前只对硅基流动的V3和R1生效
|
||||
b6edbea - fix: 图片保存路径不正确
|
||||
01a6fa8 - fix: 删除神秘test
|
||||
20f009d - 修复systemctl强制停止maimbot的问题
|
||||
af962c2 - 修复了情绪管理器没有正确导入导致发布出消息
|
||||
0586700 - 按照Sourcery提供的建议修改systemctl管理指南
|
||||
e48b32a - 在手动部署教程中增加使用systemctl管理
|
||||
5760412 - fix: 小修
|
||||
1c9b0cc - fix: 修复部分cq码解析错误，merge
|
||||
b6867b9 - fix: 统一使用os.getenv获取数据库连接信息，避免从config对象获取不存在的值时出现KeyError
|
||||
5e069f7 - 修复记忆保存时无时间信息的bug
|
||||
73a3e41 - 修复记忆更新bug
|
||||
52c93ba - refactor: use Base64 for emoji CQ codes
|
||||
67f6d7c - fix: 保证能运行的小修改
|
||||
c32c4fb - refactor: 修改配置文件的版本号
|
||||
a54ca8c - Merge remote-tracking branch 'upstream/debug' into feat_regix
|
||||
8cbf9bb - feat: 史上最好的消息流重构和图片管理
|
||||
9e41c4f - feat: 修改 bot_config 0.0.5 版本的变更日志
|
||||
eede406 - fix: 修复nonebot无法加载项目的问题
|
||||
00e02ed - fix: 0.0.5 版本的增加分层控制项
|
||||
0f99d6a - Update docs/docker_deploy.md
|
||||
c789074 - feat: 增加ruff依赖
|
||||
ff65ab8 - feat: 修改默认的ruff配置文件，同时消除config的所有不符合规范的地方
|
||||
bf97013 - feat: 精简日志，禁用Uvicorn/NoneBot默认日志；启动方式改为显示加载uvicorn，以便优雅shutdown
|
||||
d9a2863 - 优化Docker部署文档更新容器部分
|
||||
efcf00f - Docker部署文档追加更新部分
|
||||
a63ce96 - fix: 更新情感判断模型配置（使配置文件里的 llm_emotion_judge 生效）
|
||||
1294c88 - feat: 增加标准化格式化设置
|
||||
2e8cd47 - fix: 避免可能出现的日程解析错误
|
||||
043a724 - 修一下文档跳转，小美化（
|
||||
e4b8865 - 支持别名，可以用不同名称召唤机器人
|
||||
7b35ddd - ruff 哥又有新点子
|
||||
7899e67 - feat: 重构完成开始测试debug
|
||||
354d6d0 - 记忆系统优化
|
||||
6cef8fd - 修复时区，删去napcat用不到的端口
|
||||
cd96644 - 添加使用说明
|
||||
84495f8 - fix
|
||||
204744c - 修改配置名与修改过滤对象为raw_message
|
||||
a03b490 - Update README.md
|
||||
2b2b342 - feat: 增加 ruff 依赖
|
||||
72a6749 - fix: 修复docker部署时区指定问题
|
||||
ee579bc - Update README.md
|
||||
1b611ec - resolve SengokuCola/MaiMBot#167 根据正则表达式过滤消息
|
||||
6e2ea82 - refractor: 几乎写完了，进入测试阶段
|
||||
2ffdfef - More
|
||||
e680405 - fix: typo 'discription'
|
||||
68b3f57 - Minor Doc Update
|
||||
312f065 - Create linux_deploy_guide_for_beginners.md
|
||||
ed505a4 - fix: 使用动态路径替换硬编码的项目路径
|
||||
8ff7bb6 - docs: 更新文档，修正格式并添加必要的换行符
|
||||
6e36a56 - feat: 增加 MONGODB_URI 的配置项，并将所有env文件的注释单独放在一行（python的dotenv有时无法正确处理行内注释）
|
||||
4baa6c6 - feat: 实现MongoDB URI方式连接，并统一数据库连接代码。
|
||||
8a32d18 - feat: 优化willing_manager逻辑，增加回复保底概率
|
||||
c9f1244 - docs: 改进README.md文档格式和排版
|
||||
e1b484a - docs: 添加CLAUDE.md开发指南文件（用于Claude Code）
|
||||
a43f949 - fix: remove duplicate message(CR comments)
|
||||
fddb641 - fix: 修复错误的空值检测逻辑
|
||||
8b7876c - fix: 修复没有上传tag的问题
|
||||
6b4130e - feat: 增加stable-dev分支的打包
|
||||
052e67b - refactor: 日志打印优化（终于改完了，爽了
|
||||
a7f9d05 - 修复记忆整理传入格式问题
|
||||
536bb1d - fix: 更新情感判断模型配置
|
||||
8d99592 - fix: logger初始化顺序
|
||||
052802c - refactor: logger promotion
|
||||
8661d94 - doc: README.md - telegram version information
|
||||
5746afa - refactor: logger in src\plugins\chat\bot.py
|
||||
288dbb6 - refactor: logger in src\plugins\chat\__init__.py
|
||||
8428a06 - fix: memory logger optimization (CR comment)
|
||||
665c459 - 改进了可视化脚本
|
||||
6c35704 - fix: 调用了错误的函数
|
||||
3223153 - feat: 一键脚本新增记忆可视化
|
||||
3149dd3 - fix: mongodb.zip 无法解压 fix:更换执行命令的方法 fix:当 db 不存在时自动创建 feat: 一键安装完成后启动麦麦
|
||||
089d6a6 - feat: 针对硅基流动的Pro模型添加了自动降级功能
|
||||
c4b0917 - 一个记忆可视化小脚本
|
||||
6a71ea4 - 修复了记忆时间bug,config添加了记忆屏蔽关键词
|
||||
1b5344f - fix: 优化bot初始化的日志&格式
|
||||
41aa974 - fix: 优化chat/config.py的日志&格式
|
||||
980cde7 - fix: 优化scheduler_generator日志&格式
|
||||
31a5514 - fix: 调整全局logger加载顺序
|
||||
8baef07 - feat: 添加全局logger初始化设置
|
||||
5566f17 - refractor: 几乎写完了，进入测试阶段
|
||||
6a66933 - feat: 添加开发环境.env.dev初始化
|
||||
411ff1a - feat: 安装 MongoDB Compass
|
||||
0de9eba - feat: 增加实时更新贡献者列表的功能
|
||||
f327f45 - fix: 优化src/plugins/chat/__init__.py的import
|
||||
826daa5 - fix: 当虚拟环境存在时跳过创建
|
||||
f54de42 - fix: time.tzset 仅在类 Unix 系统可用
|
||||
47c4990 - fix: 修复docker部署场景下时间错误的问题
|
||||
e23a371 - docs: 添加 compose 注释
|
||||
1002822 - docs: 标注 Python 最低版本
|
||||
564350d - feat: 校验 Python 版本
|
||||
4cc4482 - docs: 添加傻瓜式脚本
|
||||
757173a - 带麦麦看了心理医生，让她没那么容易陷入负面情绪
|
||||
39bb99c - 将错别字生成提取到配置，一句一个错别字太烦了！
|
||||
fe36847 - feat: 超大型重构
|
||||
e304dd7 - Update README.md
|
||||
b7cfe6d - feat: 发布第 0.0.2 版本配置模板
|
||||
ca929d5 - 补充Docker部署文档
|
||||
1e97120 - 补充Docker部署文档
|
||||
25f7052 - fix: 修复兼容性选项和目前第一个版本之间的版本间隙 0.0.0 版，并将所有的直接退出修改为抛出异常
|
||||
c5bdc4f - 防ipv6炸，虽然小概率事件
|
||||
d86610d - fix: 修复不能加载环境变量的问题
|
||||
2306ebf - feat: 因为判断临界版本范围比较麻烦，增加 notice 字段，删除原本的判断逻辑（存在故障）
|
||||
dd09576 - fix: 修复 TypeError: BotConfig.convert_to_specifierset() takes 1 positional argument but 2 were given
|
||||
18f839b - fix: 修复 missing 1 required positional argument: 'INNER_VERSION'
|
||||
6adb5ed - 调整一些细节，docker部署时可选数据库账密
|
||||
07f48e9 - fix: 利用filter来过滤环境变量，避免直接删除key造成的 RuntimeError: dictionary changed size during iteration
|
||||
5856074 - fix: 修复无法进行基础设置的问题
|
||||
32aa032 - feat: 发布 0.0.1 版本的配置文件
|
||||
edc07ac - feat: 重构配置加载器，增加配置文件版本控制和程序兼容能力
|
||||
0f492ed - fix: 修复 BASE_URL/KEY 组合检查中被 GPG_KEY 干扰的问题
|
||||
18
run.bat
18
run.bat
|
|
@ -1,10 +1,10 @@
|
|||
@ECHO OFF
|
||||
chcp 65001
|
||||
if not exist "venv" (
|
||||
python -m venv venv
|
||||
call venv\Scripts\activate.bat
|
||||
pip install -i https://mirrors.aliyun.com/pypi/simple --upgrade -r requirements.txt
|
||||
) else (
|
||||
call venv\Scripts\activate.bat
|
||||
)
|
||||
@ECHO OFF
|
||||
chcp 65001
|
||||
if not exist "venv" (
|
||||
python -m venv venv
|
||||
call venv\Scripts\activate.bat
|
||||
pip install -i https://mirrors.aliyun.com/pypi/simple --upgrade -r requirements.txt
|
||||
) else (
|
||||
call venv\Scripts\activate.bat
|
||||
)
|
||||
python run.py
|
||||
|
|
@ -1,29 +1,29 @@
|
|||
@echo on
|
||||
chcp 65001 > nul
|
||||
set /p CONDA_ENV="请输入要激活的 conda 环境名称: "
|
||||
call conda activate %CONDA_ENV%
|
||||
if errorlevel 1 (
|
||||
echo 激活 conda 环境失败
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
echo Conda 环境 "%CONDA_ENV%" 激活成功
|
||||
|
||||
set /p OPTION="请选择运行选项 (1: 运行全部绘制, 2: 运行简单绘制): "
|
||||
if "%OPTION%"=="1" (
|
||||
python src/plugins/memory_system/memory_manual_build.py
|
||||
) else if "%OPTION%"=="2" (
|
||||
python src/plugins/memory_system/draw_memory.py
|
||||
) else (
|
||||
echo 无效的选项
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
if errorlevel 1 (
|
||||
echo 命令执行失败，错误代码 %errorlevel%
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
echo 脚本成功完成
|
||||
@echo on
|
||||
chcp 65001 > nul
|
||||
set /p CONDA_ENV="请输入要激活的 conda 环境名称: "
|
||||
call conda activate %CONDA_ENV%
|
||||
if errorlevel 1 (
|
||||
echo 激活 conda 环境失败
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
echo Conda 环境 "%CONDA_ENV%" 激活成功
|
||||
|
||||
set /p OPTION="请选择运行选项 (1: 运行全部绘制, 2: 运行简单绘制): "
|
||||
if "%OPTION%"=="1" (
|
||||
python src/plugins/memory_system/memory_manual_build.py
|
||||
) else if "%OPTION%"=="2" (
|
||||
python src/plugins/memory_system/draw_memory.py
|
||||
) else (
|
||||
echo 无效的选项
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
if errorlevel 1 (
|
||||
echo 命令执行失败，错误代码 %errorlevel%
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
echo 脚本成功完成
|
||||
pause
|
||||
|
|
@ -1,7 +1,7 @@
|
|||
chcp 65001
|
||||
call conda activate maimbot
|
||||
cd .
|
||||
|
||||
REM 执行nb run命令
|
||||
nb run
|
||||
chcp 65001
|
||||
call conda activate maimbot
|
||||
cd .
|
||||
|
||||
REM 执行nb run命令
|
||||
nb run
|
||||
pause
|
||||
|
|
@ -1,5 +1,5 @@
|
|||
call conda activate niuniu
|
||||
cd src\gui
|
||||
start /b python reasoning_gui.py
|
||||
exit
|
||||
|
||||
call conda activate niuniu
|
||||
cd src\gui
|
||||
start /b python reasoning_gui.py
|
||||
exit
|
||||
|
||||
|
|
|
|||
|
|
@ -1,68 +1,68 @@
|
|||
@echo off
|
||||
setlocal enabledelayedexpansion
|
||||
chcp 65001
|
||||
|
||||
REM 修正路径获取逻辑
|
||||
cd /d "%~dp0" || (
|
||||
echo 错误：切换目录失败
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
if not exist "venv\" (
|
||||
echo 正在初始化虚拟环境...
|
||||
|
||||
where python >nul 2>&1
|
||||
if %errorlevel% neq 0 (
|
||||
echo 未找到Python解释器
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
for /f "tokens=2" %%a in ('python --version 2^>^&1') do set version=%%a
|
||||
for /f "tokens=1,2 delims=." %%b in ("!version!") do (
|
||||
set major=%%b
|
||||
set minor=%%c
|
||||
)
|
||||
|
||||
if !major! lss 3 (
|
||||
echo 需要Python大于等于3.0，当前版本 !version!
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
if !major! equ 3 if !minor! lss 9 (
|
||||
echo 需要Python大于等于3.9，当前版本 !version!
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
echo 正在安装virtualenv...
|
||||
python -m pip install virtualenv || (
|
||||
echo virtualenv安装失败
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
echo 正在创建虚拟环境...
|
||||
python -m virtualenv venv || (
|
||||
echo 虚拟环境创建失败
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
call venv\Scripts\activate.bat
|
||||
|
||||
) else (
|
||||
call venv\Scripts\activate.bat
|
||||
)
|
||||
|
||||
echo 正在更新依赖...
|
||||
pip install -r requirements.txt
|
||||
|
||||
echo 当前代理设置：
|
||||
echo HTTP_PROXY=%HTTP_PROXY%
|
||||
echo HTTPS_PROXY=%HTTPS_PROXY%
|
||||
|
||||
set HTTP_PROXY=
|
||||
set HTTPS_PROXY=
|
||||
echo 代理已取消。
|
||||
|
||||
set no_proxy=0.0.0.0/32
|
||||
|
||||
call nb run
|
||||
@echo off
|
||||
setlocal enabledelayedexpansion
|
||||
chcp 65001
|
||||
|
||||
REM 修正路径获取逻辑
|
||||
cd /d "%~dp0" || (
|
||||
echo 错误：切换目录失败
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
if not exist "venv\" (
|
||||
echo 正在初始化虚拟环境...
|
||||
|
||||
where python >nul 2>&1
|
||||
if %errorlevel% neq 0 (
|
||||
echo 未找到Python解释器
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
for /f "tokens=2" %%a in ('python --version 2^>^&1') do set version=%%a
|
||||
for /f "tokens=1,2 delims=." %%b in ("!version!") do (
|
||||
set major=%%b
|
||||
set minor=%%c
|
||||
)
|
||||
|
||||
if !major! lss 3 (
|
||||
echo 需要Python大于等于3.0，当前版本 !version!
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
if !major! equ 3 if !minor! lss 9 (
|
||||
echo 需要Python大于等于3.9，当前版本 !version!
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
echo 正在安装virtualenv...
|
||||
python -m pip install virtualenv || (
|
||||
echo virtualenv安装失败
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
echo 正在创建虚拟环境...
|
||||
python -m virtualenv venv || (
|
||||
echo 虚拟环境创建失败
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
call venv\Scripts\activate.bat
|
||||
|
||||
) else (
|
||||
call venv\Scripts\activate.bat
|
||||
)
|
||||
|
||||
echo 正在更新依赖...
|
||||
pip install -r requirements.txt
|
||||
|
||||
echo 当前代理设置：
|
||||
echo HTTP_PROXY=%HTTP_PROXY%
|
||||
echo HTTPS_PROXY=%HTTPS_PROXY%
|
||||
|
||||
set HTTP_PROXY=
|
||||
set HTTPS_PROXY=
|
||||
echo 代理已取消。
|
||||
|
||||
set no_proxy=0.0.0.0/32
|
||||
|
||||
call nb run
|
||||
pause
|
||||
|
|
@ -1,6 +1,5 @@
|
|||
from typing import Optional
|
||||
from pymongo import MongoClient
|
||||
from pymongo.database import Database as MongoDatabase
|
||||
|
||||
class Database:
|
||||
_instance: Optional["Database"] = None
|
||||
|
|
@ -26,7 +25,7 @@ class Database:
|
|||
else:
|
||||
# 否则使用无认证连接
|
||||
self.client = MongoClient(host, port)
|
||||
self.db: MongoDatabase = self.client[db_name]
|
||||
self.db = self.client[db_name]
|
||||
|
||||
@classmethod
|
||||
def initialize(
|
||||
|
|
@ -38,36 +37,15 @@ class Database:
|
|||
password: Optional[str] = None,
|
||||
auth_source: Optional[str] = None,
|
||||
uri: Optional[str] = None,
|
||||
) -> MongoDatabase:
|
||||
) -> "Database":
|
||||
if cls._instance is None:
|
||||
cls._instance = cls(
|
||||
host, port, db_name, username, password, auth_source, uri
|
||||
)
|
||||
return cls._instance.db
|
||||
return cls._instance
|
||||
|
||||
@classmethod
|
||||
def get_instance(cls) -> MongoDatabase:
|
||||
def get_instance(cls) -> "Database":
|
||||
if cls._instance is None:
|
||||
raise RuntimeError("Database not initialized")
|
||||
return cls._instance.db
|
||||
|
||||
|
||||
#测试用
|
||||
|
||||
def get_random_group_messages(self, group_id: str, limit: int = 5):
|
||||
# 先随机获取一条消息
|
||||
random_message = list(self.db.messages.aggregate([
|
||||
{"$match": {"group_id": group_id}},
|
||||
{"$sample": {"size": 1}}
|
||||
]))[0]
|
||||
|
||||
# 获取该消息之后的消息
|
||||
subsequent_messages = list(self.db.messages.find({
|
||||
"group_id": group_id,
|
||||
"time": {"$gt": random_message["time"]}
|
||||
}).sort("time", 1).limit(limit))
|
||||
|
||||
# 将随机消息和后续消息合并
|
||||
messages = [random_message] + subsequent_messages
|
||||
|
||||
return messages
|
||||
return cls._instance
|
||||
|
|
@ -46,7 +46,7 @@ class ReasoningGUI:
|
|||
|
||||
# 初始化数据库连接
|
||||
try:
|
||||
self.db = Database.get_instance()
|
||||
self.db = Database.get_instance().db
|
||||
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...")
|
||||
|
|
@ -60,7 +60,7 @@ class ReasoningGUI:
|
|||
password=os.getenv("MONGODB_PASSWORD"),
|
||||
auth_source=os.getenv("MONGODB_AUTH_SOURCE"),
|
||||
)
|
||||
self.db = Database.get_instance()
|
||||
self.db = Database.get_instance().db
|
||||
logger.success("数据库初始化成功")
|
||||
except Exception:
|
||||
logger.exception("数据库初始化失败")
|
||||
|
|
|
|||
|
|
@ -32,6 +32,18 @@ _message_manager_started = False
|
|||
driver = get_driver()
|
||||
config = driver.config
|
||||
|
||||
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"),
|
||||
)
|
||||
logger.success("初始化数据库成功")
|
||||
|
||||
|
||||
# 初始化表情管理器
|
||||
emoji_manager.initialize()
|
||||
|
||||
|
|
|
|||
|
|
@ -235,10 +235,10 @@ class ChatBot:
|
|||
is_head=not mark_head,
|
||||
is_emoji=False,
|
||||
)
|
||||
logger.debug(f"bot_message: {bot_message}")
|
||||
print(f"bot_message: {bot_message}")
|
||||
if not mark_head:
|
||||
mark_head = True
|
||||
logger.debug(f"添加消息到message_set: {bot_message}")
|
||||
print(f"添加消息到message_set: {bot_message}")
|
||||
message_set.add_message(bot_message)
|
||||
|
||||
# message_set 可以直接加入 message_manager
|
||||
|
|
|
|||
|
|
@ -111,11 +111,11 @@ 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():
|
||||
self.db.create_collection("chat_streams")
|
||||
if "chat_streams" not in self.db.db.list_collection_names():
|
||||
self.db.db.create_collection("chat_streams")
|
||||
# 创建索引
|
||||
self.db.chat_streams.create_index([("stream_id", 1)], unique=True)
|
||||
self.db.chat_streams.create_index(
|
||||
self.db.db.chat_streams.create_index([("stream_id", 1)], unique=True)
|
||||
self.db.db.chat_streams.create_index(
|
||||
[("platform", 1), ("user_info.user_id", 1), ("group_info.group_id", 1)]
|
||||
)
|
||||
|
||||
|
|
@ -168,7 +168,7 @@ 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 = self.db.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 +204,7 @@ 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(
|
||||
self.db.db.chat_streams.update_one(
|
||||
{"stream_id": stream.stream_id}, {"$set": stream.to_dict()}, upsert=True
|
||||
)
|
||||
stream.saved = True
|
||||
|
|
@ -216,7 +216,7 @@ 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 = self.db.db.chat_streams.find({})
|
||||
for data in all_streams:
|
||||
stream = ChatStream.from_dict(data)
|
||||
self.streams[stream.stream_id] = stream
|
||||
|
|
|
|||
|
|
@ -105,6 +105,11 @@ class BotConfig:
|
|||
default_factory=lambda: ["表情包", "图片", "回复", "聊天记录"]
|
||||
) # 添加新的配置项默认值
|
||||
|
||||
# 记忆群组配置，用于定义私有记忆群组
|
||||
# 格式：{"group1": ["123456", "234567"], "group2": ["345678", "456789"]}
|
||||
# 每个群组内的群聊ID共享记忆，但不与其他群组共享
|
||||
memory_private_groups: Dict[str, List[str]] = field(default_factory=dict)
|
||||
|
||||
@staticmethod
|
||||
def get_config_dir() -> str:
|
||||
"""获取配置文件目录"""
|
||||
|
|
@ -304,6 +309,11 @@ class BotConfig:
|
|||
config.memory_forget_time = memory_config.get("memory_forget_time", config.memory_forget_time)
|
||||
config.memory_forget_percentage = memory_config.get("memory_forget_percentage", config.memory_forget_percentage)
|
||||
config.memory_compress_rate = memory_config.get("memory_compress_rate", config.memory_compress_rate)
|
||||
|
||||
# 加载群组私有记忆配置
|
||||
if "memory_private_groups" in memory_config:
|
||||
config.memory_private_groups = memory_config.get("memory_private_groups", config.memory_private_groups)
|
||||
logger.info(f"已加载群组私有记忆配置: {len(config.memory_private_groups)}个群组")
|
||||
|
||||
def mood(parent: dict):
|
||||
mood_config = parent["mood"]
|
||||
|
|
|
|||
|
|
@ -4,8 +4,6 @@ import time
|
|||
from dataclasses import dataclass
|
||||
from typing import Dict, List, Optional, Union
|
||||
|
||||
import os
|
||||
|
||||
import requests
|
||||
|
||||
# 解析各种CQ码
|
||||
|
|
|
|||
|
|
@ -76,16 +76,16 @@ class EmojiManager:
|
|||
|
||||
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():
|
||||
self.db.create_collection('emoji')
|
||||
self.db.emoji.create_index([('embedding', '2dsphere')])
|
||||
self.db.emoji.create_index([('filename', 1)], unique=True)
|
||||
if 'emoji' not in self.db.db.list_collection_names():
|
||||
self.db.db.create_collection('emoji')
|
||||
self.db.db.emoji.create_index([('embedding', '2dsphere')])
|
||||
self.db.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(
|
||||
self.db.db.emoji.update_one(
|
||||
{'_id': emoji_id},
|
||||
{'$inc': {'usage_count': 1}}
|
||||
)
|
||||
|
|
@ -119,7 +119,7 @@ class EmojiManager:
|
|||
|
||||
try:
|
||||
# 获取所有表情包
|
||||
all_emojis = list(self.db.emoji.find({}, {'_id': 1, 'path': 1, 'embedding': 1, 'description': 1}))
|
||||
all_emojis = list(self.db.db.emoji.find({}, {'_id': 1, 'path': 1, 'embedding': 1, 'description': 1}))
|
||||
|
||||
if not all_emojis:
|
||||
logger.warning("数据库中没有任何表情包")
|
||||
|
|
@ -157,7 +157,7 @@ class EmojiManager:
|
|||
|
||||
if selected_emoji and 'path' in selected_emoji:
|
||||
# 更新使用次数
|
||||
self.db.emoji.update_one(
|
||||
self.db.db.emoji.update_one(
|
||||
{'_id': selected_emoji['_id']},
|
||||
{'$inc': {'usage_count': 1}}
|
||||
)
|
||||
|
|
@ -239,7 +239,7 @@ class EmojiManager:
|
|||
image_hash = hashlib.md5(image_bytes).hexdigest()
|
||||
|
||||
# 检查是否已经注册过
|
||||
existing_emoji = self.db['emoji'].find_one({'filename': filename})
|
||||
existing_emoji = self.db.db['emoji'].find_one({'filename': filename})
|
||||
description = None
|
||||
|
||||
if existing_emoji:
|
||||
|
|
@ -305,7 +305,7 @@ class EmojiManager:
|
|||
}
|
||||
|
||||
# 保存到emoji数据库
|
||||
self.db['emoji'].insert_one(emoji_record)
|
||||
self.db.db['emoji'].insert_one(emoji_record)
|
||||
logger.success(f"注册新表情包: {filename}")
|
||||
logger.info(f"描述: {description}")
|
||||
|
||||
|
|
@ -346,7 +346,7 @@ 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(self.db.db.emoji.find())
|
||||
removed_count = 0
|
||||
total_count = len(all_emojis)
|
||||
|
||||
|
|
@ -354,13 +354,13 @@ class EmojiManager:
|
|||
try:
|
||||
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']})
|
||||
self.db.db.emoji.delete_one({'_id': emoji['_id']})
|
||||
removed_count += 1
|
||||
continue
|
||||
|
||||
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']})
|
||||
self.db.db.emoji.delete_one({'_id': emoji['_id']})
|
||||
removed_count += 1
|
||||
continue
|
||||
|
||||
|
|
@ -368,7 +368,7 @@ class EmojiManager:
|
|||
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 = self.db.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
|
||||
|
|
@ -379,7 +379,7 @@ class EmojiManager:
|
|||
continue
|
||||
|
||||
# 验证清理结果
|
||||
remaining_count = self.db.emoji.count_documents({})
|
||||
remaining_count = self.db.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}")
|
||||
|
|
|
|||
|
|
@ -154,7 +154,7 @@ class ResponseGenerator:
|
|||
reasoning_content: str,
|
||||
):
|
||||
"""保存对话记录到数据库"""
|
||||
self.db.reasoning_logs.insert_one(
|
||||
self.db.db.reasoning_logs.insert_one(
|
||||
{
|
||||
"time": time.time(),
|
||||
"chat_id": message.chat_stream.stream_id,
|
||||
|
|
|
|||
|
|
@ -10,7 +10,6 @@ from .message import MessageSending, MessageThinking, MessageRecv, MessageSet
|
|||
|
||||
from .storage import MessageStorage
|
||||
from .config import global_config
|
||||
from .utils import truncate_message
|
||||
|
||||
|
||||
class Message_Sender:
|
||||
|
|
@ -35,7 +34,6 @@ class Message_Sender:
|
|||
message_json = message.to_dict()
|
||||
message_send = MessageSendCQ(data=message_json)
|
||||
# logger.debug(message_send.message_info,message_send.raw_message)
|
||||
message_preview = truncate_message(message.processed_plain_text)
|
||||
if (
|
||||
message_send.message_info.group_info
|
||||
and message_send.message_info.group_info.group_id
|
||||
|
|
@ -46,10 +44,10 @@ class Message_Sender:
|
|||
message=message_send.raw_message,
|
||||
auto_escape=False,
|
||||
)
|
||||
logger.success(f"[调试] 发送消息“{message_preview}”成功")
|
||||
logger.success(f"[调试] 发送消息{message.processed_plain_text}成功")
|
||||
except Exception as e:
|
||||
logger.error(f"[调试] 发生错误 {e}")
|
||||
logger.error(f"[调试] 发送消息“{message_preview}”失败")
|
||||
logger.error(f"[调试] 发送消息{message.processed_plain_text}失败")
|
||||
else:
|
||||
try:
|
||||
logger.debug(message.message_info.user_info)
|
||||
|
|
@ -58,10 +56,10 @@ class Message_Sender:
|
|||
message=message_send.raw_message,
|
||||
auto_escape=False,
|
||||
)
|
||||
logger.success(f"[调试] 发送消息“{message_preview}”成功")
|
||||
logger.success(f"[调试] 发送消息{message.processed_plain_text}成功")
|
||||
except Exception as e:
|
||||
logger.error(f"[调试] 发生错误 {e}")
|
||||
logger.error(f"[调试] 发送消息“{message_preview}”失败")
|
||||
logger.error(f"发生错误 {e}")
|
||||
logger.error(f"[调试] 发送消息{message.processed_plain_text}失败")
|
||||
|
||||
|
||||
class MessageContainer:
|
||||
|
|
@ -186,7 +184,7 @@ class MessageManager:
|
|||
await message_earliest.process()
|
||||
|
||||
print(
|
||||
f"\033[1;34m[调试]\033[0m 消息“{truncate_message(message_earliest.processed_plain_text)}”正在发送中"
|
||||
f"\033[1;34m[调试]\033[0m 消息'{message_earliest.processed_plain_text}'正在发送中"
|
||||
)
|
||||
|
||||
await self.storage.store_message(
|
||||
|
|
|
|||
|
|
@ -91,12 +91,20 @@ class PromptBuilder:
|
|||
memory_prompt = ''
|
||||
start_time = time.time()
|
||||
|
||||
# 调用 hippocampus 的 get_relevant_memories 方法
|
||||
# 获取群聊ID
|
||||
stream_group_id = None
|
||||
if stream_id:
|
||||
chat_stream = chat_manager.get_stream(stream_id)
|
||||
if chat_stream and chat_stream.group_info:
|
||||
stream_group_id = str(chat_stream.group_info.group_id)
|
||||
|
||||
# 调用 hippocampus 的 get_relevant_memories 方法，添加群聊ID参数
|
||||
relevant_memories = await hippocampus.get_relevant_memories(
|
||||
text=message_txt,
|
||||
max_topics=5,
|
||||
similarity_threshold=0.4,
|
||||
max_memory_num=5
|
||||
max_memory_num=5,
|
||||
group_id=stream_group_id
|
||||
)
|
||||
|
||||
if relevant_memories:
|
||||
|
|
@ -311,7 +319,7 @@ class PromptBuilder:
|
|||
{"$project": {"content": 1, "similarity": 1}}
|
||||
]
|
||||
|
||||
results = list(self.db.knowledges.aggregate(pipeline))
|
||||
results = list(self.db.db.knowledges.aggregate(pipeline))
|
||||
# print(f"\033[1;34m[调试]\033[0m获取知识库内容结果: {results}")
|
||||
|
||||
if not results:
|
||||
|
|
|
|||
|
|
@ -168,7 +168,7 @@ class RelationshipManager:
|
|||
async def load_all_relationships(self):
|
||||
"""加载所有关系对象"""
|
||||
db = Database.get_instance()
|
||||
all_relationships = db.relationships.find({})
|
||||
all_relationships = db.db.relationships.find({})
|
||||
for data in all_relationships:
|
||||
await self.load_relationship(data)
|
||||
|
||||
|
|
@ -176,7 +176,7 @@ class RelationshipManager:
|
|||
"""每5分钟自动保存一次关系数据"""
|
||||
db = Database.get_instance()
|
||||
# 获取所有关系记录
|
||||
all_relationships = db.relationships.find({})
|
||||
all_relationships = db.db.relationships.find({})
|
||||
# 依次加载每条记录
|
||||
for data in all_relationships:
|
||||
await self.load_relationship(data)
|
||||
|
|
@ -206,7 +206,7 @@ class RelationshipManager:
|
|||
saved = relationship.saved
|
||||
|
||||
db = Database.get_instance()
|
||||
db.relationships.update_one(
|
||||
db.db.relationships.update_one(
|
||||
{'user_id': user_id, 'platform': platform},
|
||||
{'$set': {
|
||||
'platform': platform,
|
||||
|
|
|
|||
|
|
@ -13,17 +13,23 @@ class MessageStorage:
|
|||
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:
|
||||
# 提取群组ID信息，如果存在的话
|
||||
group_id = None
|
||||
if chat_stream.group_info:
|
||||
group_id = str(chat_stream.group_info.group_id)
|
||||
|
||||
message_data = {
|
||||
"message_id": message.message_info.message_id,
|
||||
"time": message.message_info.time,
|
||||
"chat_id":chat_stream.stream_id,
|
||||
"chat_id": chat_stream.stream_id,
|
||||
"chat_info": chat_stream.to_dict(),
|
||||
"user_info": message.message_info.user_info.to_dict(),
|
||||
"processed_plain_text": message.processed_plain_text,
|
||||
"detailed_plain_text": message.detailed_plain_text,
|
||||
"topic": topic,
|
||||
"group_id": group_id, # 显式添加group_id字段
|
||||
}
|
||||
self.db.messages.insert_one(message_data)
|
||||
self.db.db.messages.insert_one(message_data)
|
||||
except Exception:
|
||||
logger.exception("存储消息失败")
|
||||
|
||||
|
|
|
|||
|
|
@ -104,11 +104,20 @@ def get_cloest_chat_from_db(db, length: int, timestamp: str):
|
|||
# 转换记录格式
|
||||
formatted_records = []
|
||||
for record in chat_records:
|
||||
formatted_records.append({
|
||||
formatted_record = {
|
||||
'time': record["time"],
|
||||
'chat_id': record["chat_id"],
|
||||
'detailed_plain_text': record.get("detailed_plain_text", "") # 添加文本内容
|
||||
})
|
||||
}
|
||||
|
||||
# 添加group_id信息，如果存在
|
||||
if 'group_id' in record:
|
||||
formatted_record['group_id'] = record['group_id']
|
||||
elif 'chat_info' in record and 'group_info' in record['chat_info'] and record['chat_info']['group_info']:
|
||||
# 从chat_info中提取group_id
|
||||
formatted_record['group_id'] = record['chat_info']['group_info'].get('group_id')
|
||||
|
||||
formatted_records.append(formatted_record)
|
||||
|
||||
return formatted_records
|
||||
|
||||
|
|
@ -406,10 +415,3 @@ def find_similar_topics_simple(text: str, topics: list, top_k: int = 5) -> list:
|
|||
|
||||
# 按相似度降序排序并返回前k个
|
||||
return sorted(similarities, key=lambda x: x[1], reverse=True)[:top_k]
|
||||
|
||||
|
||||
def truncate_message(message: str, max_length=20) -> str:
|
||||
"""截断消息，使其不超过指定长度"""
|
||||
if len(message) > max_length:
|
||||
return message[:max_length] + "..."
|
||||
return message
|
||||
|
|
|
|||
|
|
@ -40,20 +40,20 @@ class ImageManager:
|
|||
|
||||
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():
|
||||
self.db.create_collection('images')
|
||||
if 'images' not in self.db.db.list_collection_names():
|
||||
self.db.db.create_collection('images')
|
||||
# 创建索引
|
||||
self.db.images.create_index([('hash', 1)], unique=True)
|
||||
self.db.images.create_index([('url', 1)])
|
||||
self.db.images.create_index([('path', 1)])
|
||||
self.db.db.images.create_index([('hash', 1)], unique=True)
|
||||
self.db.db.images.create_index([('url', 1)])
|
||||
self.db.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():
|
||||
self.db.create_collection('image_descriptions')
|
||||
if 'image_descriptions' not in self.db.db.list_collection_names():
|
||||
self.db.db.create_collection('image_descriptions')
|
||||
# 创建索引
|
||||
self.db.image_descriptions.create_index([('hash', 1)], unique=True)
|
||||
self.db.image_descriptions.create_index([('type', 1)])
|
||||
self.db.db.image_descriptions.create_index([('hash', 1)], unique=True)
|
||||
self.db.db.image_descriptions.create_index([('type', 1)])
|
||||
|
||||
def _get_description_from_db(self, image_hash: str, description_type: str) -> Optional[str]:
|
||||
"""从数据库获取图片描述
|
||||
|
|
@ -65,7 +65,7 @@ class ImageManager:
|
|||
Returns:
|
||||
Optional[str]: 描述文本，如果不存在则返回None
|
||||
"""
|
||||
result= self.db.image_descriptions.find_one({
|
||||
result= self.db.db.image_descriptions.find_one({
|
||||
'hash': image_hash,
|
||||
'type': description_type
|
||||
})
|
||||
|
|
@ -79,7 +79,7 @@ class ImageManager:
|
|||
description: 描述文本
|
||||
description_type: 描述类型 ('emoji' 或 'image')
|
||||
"""
|
||||
self.db.image_descriptions.update_one(
|
||||
self.db.db.image_descriptions.update_one(
|
||||
{'hash': image_hash, 'type': description_type},
|
||||
{
|
||||
'$set': {
|
||||
|
|
@ -121,7 +121,7 @@ class ImageManager:
|
|||
image_hash = hashlib.md5(image_bytes).hexdigest()
|
||||
|
||||
# 查重
|
||||
existing = self.db.images.find_one({'hash': image_hash})
|
||||
existing = self.db.db.images.find_one({'hash': image_hash})
|
||||
if existing:
|
||||
return existing['path']
|
||||
|
||||
|
|
@ -142,7 +142,7 @@ class ImageManager:
|
|||
'description': description,
|
||||
'timestamp': timestamp
|
||||
}
|
||||
self.db.images.insert_one(image_doc)
|
||||
self.db.db.images.insert_one(image_doc)
|
||||
|
||||
return file_path
|
||||
|
||||
|
|
@ -159,7 +159,7 @@ class ImageManager:
|
|||
"""
|
||||
try:
|
||||
# 先查找是否已存在
|
||||
existing = self.db.images.find_one({'url': url})
|
||||
existing = self.db.db.images.find_one({'url': url})
|
||||
if existing:
|
||||
return existing['path']
|
||||
|
||||
|
|
@ -203,7 +203,7 @@ class ImageManager:
|
|||
Returns:
|
||||
bool: 是否存在
|
||||
"""
|
||||
return self.db.images.find_one({'url': url}) is not None
|
||||
return self.db.db.images.find_one({'url': url}) is not None
|
||||
|
||||
def check_hash_exists(self, image_data: Union[str, bytes], is_base64: bool = False) -> bool:
|
||||
"""检查图像是否已存在
|
||||
|
|
@ -226,7 +226,7 @@ class ImageManager:
|
|||
return False
|
||||
|
||||
image_hash = hashlib.md5(image_bytes).hexdigest()
|
||||
return self.db.images.find_one({'hash': image_hash}) is not None
|
||||
return self.db.db.images.find_one({'hash': image_hash}) is not None
|
||||
|
||||
except Exception as e:
|
||||
logger.error(f"检查哈希失败: {str(e)}")
|
||||
|
|
@ -269,7 +269,7 @@ class ImageManager:
|
|||
'description': description,
|
||||
'timestamp': timestamp
|
||||
}
|
||||
self.db.images.update_one(
|
||||
self.db.db.images.update_one(
|
||||
{'hash': image_hash},
|
||||
{'$set': image_doc},
|
||||
upsert=True
|
||||
|
|
@ -326,7 +326,7 @@ class ImageManager:
|
|||
'description': description,
|
||||
'timestamp': timestamp
|
||||
}
|
||||
self.db.images.update_one(
|
||||
self.db.db.images.update_one(
|
||||
{'hash': image_hash},
|
||||
{'$set': image_doc},
|
||||
upsert=True
|
||||
|
|
|
|||
|
|
@ -5,98 +5,101 @@ from typing import Dict
|
|||
from .config import global_config
|
||||
from .chat_stream import ChatStream
|
||||
|
||||
from loguru import logger
|
||||
|
||||
|
||||
class WillingManager:
|
||||
def __init__(self):
|
||||
self.chat_reply_willing: Dict[str, float] = {} # 存储每个聊天流的回复意愿
|
||||
self.chat_reply_willing: Dict[str, float] = {} # 存储每个聊天流的回复意愿
|
||||
self._decay_task = None
|
||||
self._started = False
|
||||
|
||||
|
||||
async def _decay_reply_willing(self):
|
||||
"""定期衰减回复意愿"""
|
||||
while True:
|
||||
await asyncio.sleep(5)
|
||||
for chat_id in self.chat_reply_willing:
|
||||
self.chat_reply_willing[chat_id] = max(0, self.chat_reply_willing[chat_id] * 0.6)
|
||||
|
||||
def get_willing(self, chat_stream: ChatStream) -> float:
|
||||
for chat_id in self.chat_reply_willing:
|
||||
self.chat_reply_willing[chat_id] = max(0, self.chat_reply_willing[chat_id] * 0.6)
|
||||
|
||||
def get_willing(self,chat_stream:ChatStream) -> float:
|
||||
"""获取指定聊天流的回复意愿"""
|
||||
stream = chat_stream
|
||||
if stream:
|
||||
return self.chat_reply_willing.get(stream.stream_id, 0)
|
||||
return 0
|
||||
|
||||
|
||||
def set_willing(self, chat_id: str, willing: float):
|
||||
"""设置指定聊天流的回复意愿"""
|
||||
self.chat_reply_willing[chat_id] = willing
|
||||
|
||||
async def change_reply_willing_received(
|
||||
self,
|
||||
chat_stream: ChatStream,
|
||||
topic: str = None,
|
||||
is_mentioned_bot: bool = False,
|
||||
config=None,
|
||||
is_emoji: bool = False,
|
||||
interested_rate: float = 0,
|
||||
) -> float:
|
||||
def set_willing(self, chat_id: str, willing: float):
|
||||
"""设置指定聊天流的回复意愿"""
|
||||
self.chat_reply_willing[chat_id] = willing
|
||||
|
||||
async def change_reply_willing_received(self,
|
||||
chat_stream:ChatStream,
|
||||
topic: str = None,
|
||||
is_mentioned_bot: bool = False,
|
||||
config = None,
|
||||
is_emoji: bool = False,
|
||||
interested_rate: float = 0) -> float:
|
||||
"""改变指定聊天流的回复意愿并返回回复概率"""
|
||||
# 获取或创建聊天流
|
||||
stream = chat_stream
|
||||
chat_id = stream.stream_id
|
||||
|
||||
|
||||
current_willing = self.chat_reply_willing.get(chat_id, 0)
|
||||
|
||||
|
||||
# print(f"初始意愿: {current_willing}")
|
||||
if is_mentioned_bot and current_willing < 1.0:
|
||||
current_willing += 0.9
|
||||
logger.debug(f"被提及, 当前意愿: {current_willing}")
|
||||
print(f"被提及, 当前意愿: {current_willing}")
|
||||
elif is_mentioned_bot:
|
||||
current_willing += 0.05
|
||||
logger.debug(f"被重复提及, 当前意愿: {current_willing}")
|
||||
|
||||
print(f"被重复提及, 当前意愿: {current_willing}")
|
||||
|
||||
if is_emoji:
|
||||
current_willing *= 0.1
|
||||
logger.debug(f"表情包, 当前意愿: {current_willing}")
|
||||
|
||||
logger.debug(f"放大系数_interested_rate: {global_config.response_interested_rate_amplifier}")
|
||||
interested_rate *= global_config.response_interested_rate_amplifier # 放大回复兴趣度
|
||||
print(f"表情包, 当前意愿: {current_willing}")
|
||||
|
||||
print(f"放大系数_interested_rate: {global_config.response_interested_rate_amplifier}")
|
||||
interested_rate *= global_config.response_interested_rate_amplifier #放大回复兴趣度
|
||||
if interested_rate > 0.4:
|
||||
# print(f"兴趣度: {interested_rate}, 当前意愿: {current_willing}")
|
||||
current_willing += interested_rate - 0.4
|
||||
|
||||
current_willing *= global_config.response_willing_amplifier # 放大回复意愿
|
||||
current_willing += interested_rate-0.4
|
||||
|
||||
current_willing *= global_config.response_willing_amplifier #放大回复意愿
|
||||
# print(f"放大系数_willing: {global_config.response_willing_amplifier}, 当前意愿: {current_willing}")
|
||||
|
||||
|
||||
reply_probability = max((current_willing - 0.45) * 2, 0)
|
||||
|
||||
|
||||
# 检查群组权限（如果是群聊）
|
||||
if chat_stream.group_info:
|
||||
if chat_stream.group_info:
|
||||
if chat_stream.group_info.group_id in config.talk_frequency_down_groups:
|
||||
reply_probability = reply_probability / global_config.down_frequency_rate
|
||||
|
||||
reply_probability = min(reply_probability, 1)
|
||||
if reply_probability < 0:
|
||||
reply_probability = 0
|
||||
|
||||
|
||||
self.chat_reply_willing[chat_id] = min(current_willing, 3.0)
|
||||
return reply_probability
|
||||
|
||||
def change_reply_willing_sent(self, chat_stream: ChatStream):
|
||||
|
||||
def change_reply_willing_sent(self, chat_stream:ChatStream):
|
||||
"""开始思考后降低聊天流的回复意愿"""
|
||||
stream = chat_stream
|
||||
if stream:
|
||||
current_willing = self.chat_reply_willing.get(stream.stream_id, 0)
|
||||
self.chat_reply_willing[stream.stream_id] = max(0, current_willing - 2)
|
||||
|
||||
def change_reply_willing_after_sent(self, chat_stream: ChatStream):
|
||||
|
||||
def change_reply_willing_after_sent(self,chat_stream:ChatStream):
|
||||
"""发送消息后提高聊天流的回复意愿"""
|
||||
stream = chat_stream
|
||||
if stream:
|
||||
current_willing = self.chat_reply_willing.get(stream.stream_id, 0)
|
||||
if current_willing < 1:
|
||||
self.chat_reply_willing[stream.stream_id] = min(1, current_willing + 0.2)
|
||||
|
||||
|
||||
async def ensure_started(self):
|
||||
"""确保衰减任务已启动"""
|
||||
if not self._started:
|
||||
|
|
@ -104,6 +107,5 @@ class WillingManager:
|
|||
self._decay_task = asyncio.create_task(self._decay_reply_willing())
|
||||
self._started = True
|
||||
|
||||
|
||||
# 创建全局实例
|
||||
willing_manager = WillingManager()
|
||||
willing_manager = WillingManager()
|
||||
|
|
@ -96,7 +96,7 @@ class Memory_graph:
|
|||
dot_data = {
|
||||
"concept": node
|
||||
}
|
||||
self.db.store_memory_dots.insert_one(dot_data)
|
||||
self.db.db.store_memory_dots.insert_one(dot_data)
|
||||
|
||||
@property
|
||||
def dots(self):
|
||||
|
|
@ -106,7 +106,7 @@ 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 = self.db.db.messages.find_one({"time": {"$lte": timestamp}}, sort=[('time', -1)]) # 调试输出
|
||||
logger.info(
|
||||
f"距离time最近的消息时间: {time.strftime('%Y-%m-%d %H:%M:%S', time.localtime(int(closest_record['time'])))}")
|
||||
|
||||
|
|
@ -115,7 +115,7 @@ class Memory_graph:
|
|||
group_id = closest_record['group_id'] # 获取groupid
|
||||
# 获取该时间戳之后的length条消息，且groupid相同
|
||||
chat_record = list(
|
||||
self.db.messages.find({"time": {"$gt": closest_time}, "group_id": group_id}).sort('time', 1).limit(
|
||||
self.db.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'])))
|
||||
|
|
@ -130,34 +130,34 @@ class Memory_graph:
|
|||
|
||||
def save_graph_to_db(self):
|
||||
# 清空现有的图数据
|
||||
self.db.graph_data.delete_many({})
|
||||
self.db.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)
|
||||
self.db.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)
|
||||
self.db.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 = self.db.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 = self.db.db.graph_data.edges.find()
|
||||
for edge in edges:
|
||||
self.G.add_edge(edge['source'], edge['target'])
|
||||
|
||||
|
|
|
|||
|
|
@ -44,9 +44,19 @@ class Memory_graph:
|
|||
created_time=current_time, # 添加创建时间
|
||||
last_modified=current_time) # 添加最后修改时间
|
||||
|
||||
def add_dot(self, concept, memory):
|
||||
def add_dot(self, concept, memory, group_id=None):
|
||||
current_time = datetime.datetime.now().timestamp()
|
||||
|
||||
# 如果memory不是字典格式，将其转换为字典
|
||||
if not isinstance(memory, dict):
|
||||
memory = {
|
||||
'content': memory,
|
||||
'group_id': group_id
|
||||
}
|
||||
# 如果memory是字典但没有group_id，添加group_id
|
||||
elif 'group_id' not in memory and group_id is not None:
|
||||
memory['group_id'] = group_id
|
||||
|
||||
if concept in self.G:
|
||||
if 'memory_items' in self.G.nodes[concept]:
|
||||
if not isinstance(self.G.nodes[concept]['memory_items'], list):
|
||||
|
|
@ -218,6 +228,16 @@ class Hippocampus:
|
|||
if not messages:
|
||||
return set(), {}
|
||||
|
||||
# 提取群聊ID信息
|
||||
group_id = None
|
||||
for msg in messages:
|
||||
if 'group_id' in msg and msg['group_id']:
|
||||
group_id = msg['group_id']
|
||||
break
|
||||
|
||||
# 获取群组类型
|
||||
group_type = self.get_group_type(group_id) if group_id else None
|
||||
|
||||
# 合并消息文本，同时保留时间信息
|
||||
input_text = ""
|
||||
time_info = ""
|
||||
|
|
@ -264,17 +284,50 @@ class Hippocampus:
|
|||
# 等待所有任务完成
|
||||
compressed_memory = set()
|
||||
similar_topics_dict = {} # 存储每个话题的相似主题列表
|
||||
|
||||
for topic, task in tasks:
|
||||
response = await task
|
||||
if response:
|
||||
compressed_memory.add((topic, response[0]))
|
||||
# 为每个话题查找相似的已存在主题
|
||||
# 为每个主题创建特定群聊/群组的主题节点名称
|
||||
topic_node_name = topic
|
||||
|
||||
# 如果是私有群组的群聊，使用群组前缀
|
||||
if group_type:
|
||||
topic_node_name = f"{topic}_GT{group_type}"
|
||||
# 否则使用群聊ID前缀（如果有）
|
||||
elif group_id:
|
||||
topic_node_name = f"{topic}_g{group_id}"
|
||||
|
||||
# 记录主题内容
|
||||
memory_content = response[0]
|
||||
compressed_memory.add((topic_node_name, memory_content))
|
||||
|
||||
# 为每个话题查找相似的已存在主题（不考虑群聊/群组前缀）
|
||||
existing_topics = list(self.memory_graph.G.nodes())
|
||||
similar_topics = []
|
||||
|
||||
for existing_topic in existing_topics:
|
||||
# 提取基础主题名和群组/群聊信息
|
||||
base_existing_topic = existing_topic
|
||||
existing_group_type = None
|
||||
existing_group_id = None
|
||||
|
||||
# 检查是否有群组前缀
|
||||
if "_GT" in existing_topic:
|
||||
parts = existing_topic.split("_GT")
|
||||
base_existing_topic = parts[0]
|
||||
if len(parts) > 1:
|
||||
existing_group_type = parts[1]
|
||||
# 检查是否有群聊前缀
|
||||
elif "_g" in existing_topic:
|
||||
parts = existing_topic.split("_g")
|
||||
base_existing_topic = parts[0]
|
||||
if len(parts) > 1:
|
||||
existing_group_id = parts[1]
|
||||
|
||||
# 计算基础主题的相似度
|
||||
topic_words = set(jieba.cut(topic))
|
||||
existing_words = set(jieba.cut(existing_topic))
|
||||
existing_words = set(jieba.cut(base_existing_topic))
|
||||
|
||||
all_words = topic_words | existing_words
|
||||
v1 = [1 if word in topic_words else 0 for word in all_words]
|
||||
|
|
@ -282,12 +335,27 @@ class Hippocampus:
|
|||
|
||||
similarity = cosine_similarity(v1, v2)
|
||||
|
||||
if similarity >= 0.6:
|
||||
similar_topics.append((existing_topic, similarity))
|
||||
# 如果相似度高且不是完全相同的主题
|
||||
if similarity >= 0.6 and existing_topic != topic_node_name:
|
||||
# 如果当前主题属于群组，只连接该群组内的主题或公共主题
|
||||
if group_type:
|
||||
# 只连接同群组主题或没有群组/群聊标识的通用主题
|
||||
if (existing_group_type == group_type) or (not existing_group_type and not existing_group_id):
|
||||
similar_topics.append((existing_topic, similarity))
|
||||
# 如果当前主题不属于群组但有群聊ID
|
||||
elif group_id:
|
||||
# 只连接同群聊主题或没有群组/群聊标识的通用主题
|
||||
if (existing_group_id == group_id) or (not existing_group_type and not existing_group_id):
|
||||
similar_topics.append((existing_topic, similarity))
|
||||
# 如果当前主题既不属于群组也没有群聊ID（通用主题）
|
||||
else:
|
||||
# 只连接没有群组标识的主题
|
||||
if not existing_group_type:
|
||||
similar_topics.append((existing_topic, similarity))
|
||||
|
||||
similar_topics.sort(key=lambda x: x[1], reverse=True)
|
||||
similar_topics = similar_topics[:5]
|
||||
similar_topics_dict[topic] = similar_topics
|
||||
similar_topics_dict[topic_node_name] = similar_topics
|
||||
|
||||
return compressed_memory, similar_topics_dict
|
||||
|
||||
|
|
@ -315,6 +383,11 @@ class Hippocampus:
|
|||
bar = '█' * filled_length + '-' * (bar_length - filled_length)
|
||||
logger.debug(f"进度: [{bar}] {progress:.1f}% ({i}/{len(memory_samples)})")
|
||||
|
||||
# 获取该批次消息的group_id
|
||||
group_id = None
|
||||
if messages and len(messages) > 0 and 'group_id' in messages[0]:
|
||||
group_id = messages[0]['group_id']
|
||||
|
||||
compress_rate = global_config.memory_compress_rate
|
||||
compressed_memory, similar_topics_dict = await self.memory_compress(messages, compress_rate)
|
||||
logger.info(f"压缩后记忆数量: {len(compressed_memory)}，似曾相识的话题: {len(similar_topics_dict)}")
|
||||
|
|
@ -323,15 +396,25 @@ class Hippocampus:
|
|||
|
||||
for topic, memory in compressed_memory:
|
||||
logger.info(f"添加节点: {topic}")
|
||||
self.memory_graph.add_dot(topic, memory)
|
||||
self.memory_graph.add_dot(topic, memory) # 不再需要传递group_id，因为已经包含在topic名称中
|
||||
all_topics.append(topic)
|
||||
|
||||
# 连接相似的已存在主题
|
||||
# 连接相似的已存在主题，但使用较弱的连接强度
|
||||
if topic in similar_topics_dict:
|
||||
similar_topics = similar_topics_dict[topic]
|
||||
for similar_topic, similarity in similar_topics:
|
||||
if topic != similar_topic:
|
||||
# 如果是跨群聊的相似主题，使用较弱的连接强度
|
||||
is_cross_group = False
|
||||
if ("_g" in topic and "_g" in similar_topic and
|
||||
topic.split("_g")[1] != similar_topic.split("_g")[1]):
|
||||
is_cross_group = True
|
||||
|
||||
# 跨群聊的相似主题使用较弱的连接强度
|
||||
strength = int(similarity * 10)
|
||||
if is_cross_group:
|
||||
strength = int(similarity * 5) # 降低跨群聊连接的强度
|
||||
|
||||
logger.info(f"连接相似节点: {topic} 和 {similar_topic} (强度: {strength})")
|
||||
self.memory_graph.G.add_edge(topic, similar_topic,
|
||||
strength=strength,
|
||||
|
|
@ -682,11 +765,12 @@ class Hippocampus:
|
|||
prompt = f'这是一段文字，{time_info}：{text}。我想让你基于这段文字来概括"{topic}"这个概念，帮我总结成一句自然的话，可以包含时间和人物，以及具体的观点。只输出这句话就好'
|
||||
return prompt
|
||||
|
||||
async def _identify_topics(self, text: str) -> list:
|
||||
async def _identify_topics(self, text: str, group_id: str = None) -> list:
|
||||
"""从文本中识别可能的主题
|
||||
|
||||
Args:
|
||||
text: 输入文本
|
||||
group_id: 群聊ID，用于生成群聊特定的主题名
|
||||
|
||||
Returns:
|
||||
list: 识别出的主题列表
|
||||
|
|
@ -697,6 +781,15 @@ class Hippocampus:
|
|||
topics_response[0].replace("，", ",").replace("、", ",").replace(" ", ",").split(",") if topic.strip()]
|
||||
# print(f"话题: {topics}")
|
||||
|
||||
# 如果提供了群聊ID，添加群聊/群组标识
|
||||
if group_id:
|
||||
# 检查群聊是否属于特定群组
|
||||
group_type = self.get_group_type(group_id)
|
||||
if group_type:
|
||||
topics = [f"{topic}_GT{group_type}" for topic in topics]
|
||||
else:
|
||||
topics = [f"{topic}_g{group_id}" for topic in topics]
|
||||
|
||||
return topics
|
||||
|
||||
def _find_similar_topics(self, topics: list, similarity_threshold: float = 0.4, debug_info: str = "") -> list:
|
||||
|
|
@ -719,11 +812,47 @@ class Hippocampus:
|
|||
# print(f"\033[1;32m[{debug_info}]\033[0m 正在思考有没有见过: {topic}")
|
||||
pass
|
||||
|
||||
topic_vector = text_to_vector(topic)
|
||||
# 提取基础主题（去除群聊/群组标识）
|
||||
base_topic = topic
|
||||
topic_group_type = None
|
||||
topic_group_id = None
|
||||
|
||||
# 检查是否有群组前缀
|
||||
if "_GT" in topic:
|
||||
parts = topic.split("_GT")
|
||||
base_topic = parts[0]
|
||||
if len(parts) > 1:
|
||||
topic_group_type = parts[1]
|
||||
# 检查是否有群聊前缀
|
||||
elif "_g" in topic:
|
||||
parts = topic.split("_g")
|
||||
base_topic = parts[0]
|
||||
if len(parts) > 1:
|
||||
topic_group_id = parts[1]
|
||||
|
||||
topic_vector = text_to_vector(base_topic)
|
||||
has_similar_topic = False
|
||||
|
||||
for memory_topic in all_memory_topics:
|
||||
memory_vector = text_to_vector(memory_topic)
|
||||
# 提取记忆主题的基础主题和群聊/群组ID
|
||||
base_memory_topic = memory_topic
|
||||
memory_group_type = None
|
||||
memory_group_id = None
|
||||
|
||||
# 检查是否有群组前缀
|
||||
if "_GT" in memory_topic:
|
||||
parts = memory_topic.split("_GT")
|
||||
base_memory_topic = parts[0]
|
||||
if len(parts) > 1:
|
||||
memory_group_type = parts[1]
|
||||
# 检查是否有群聊前缀
|
||||
elif "_g" in memory_topic:
|
||||
parts = memory_topic.split("_g")
|
||||
base_memory_topic = parts[0]
|
||||
if len(parts) > 1:
|
||||
memory_group_id = parts[1]
|
||||
|
||||
memory_vector = text_to_vector(base_memory_topic)
|
||||
# 获取所有唯一词
|
||||
all_words = set(topic_vector.keys()) | set(memory_vector.keys())
|
||||
# 构建向量
|
||||
|
|
@ -732,7 +861,32 @@ class Hippocampus:
|
|||
# 计算相似度
|
||||
similarity = cosine_similarity(v1, v2)
|
||||
|
||||
if similarity >= similarity_threshold:
|
||||
# 检查是否应该考虑这个主题
|
||||
should_consider = False
|
||||
|
||||
# 如果当前主题属于群组
|
||||
if topic_group_type:
|
||||
# 只考虑同群组主题或公共主题
|
||||
if (memory_group_type == topic_group_type) or (not memory_group_type and not memory_group_id):
|
||||
should_consider = True
|
||||
# 如果当前主题属于特定群聊但不属于群组
|
||||
elif topic_group_id:
|
||||
# 只考虑同群聊主题或公共主题
|
||||
if (memory_group_id == topic_group_id) or (not memory_group_type and not memory_group_id):
|
||||
should_consider = True
|
||||
# 如果当前主题是公共主题
|
||||
else:
|
||||
# 只考虑公共主题
|
||||
if not memory_group_type and not memory_group_id:
|
||||
should_consider = True
|
||||
|
||||
# 如果基础主题相似且应该考虑该主题
|
||||
if similarity >= similarity_threshold and should_consider:
|
||||
# 如果两个主题属于同一群组/群聊，提高相似度
|
||||
if (topic_group_type and memory_group_type and topic_group_type == memory_group_type) or \
|
||||
(topic_group_id and memory_group_id and topic_group_id == memory_group_id):
|
||||
similarity *= 1.2 # 提高20%的相似度
|
||||
|
||||
has_similar_topic = True
|
||||
if debug_info:
|
||||
# print(f"\033[1;32m[{debug_info}]\033[0m 找到相似主题: {topic} -> {memory_topic} (相似度: {similarity:.2f})")
|
||||
|
|
@ -841,10 +995,21 @@ class Hippocampus:
|
|||
return activation
|
||||
|
||||
async def get_relevant_memories(self, text: str, max_topics: int = 5, similarity_threshold: float = 0.4,
|
||||
max_memory_num: int = 5) -> list:
|
||||
"""根据输入文本获取相关的记忆内容"""
|
||||
# 识别主题
|
||||
identified_topics = await self._identify_topics(text)
|
||||
max_memory_num: int = 5, group_id: str = None) -> list:
|
||||
"""根据输入文本获取相关的记忆内容
|
||||
|
||||
Args:
|
||||
text: 输入文本
|
||||
max_topics: 最大主题数量
|
||||
similarity_threshold: 相似度阈值
|
||||
max_memory_num: 最大记忆数量
|
||||
group_id: 群聊ID，用于优先获取指定群聊的记忆
|
||||
"""
|
||||
# 获取群组类型
|
||||
group_type = self.get_group_type(group_id) if group_id else None
|
||||
|
||||
# 识别主题，传入群聊ID
|
||||
identified_topics = await self._identify_topics(text, group_id)
|
||||
|
||||
# 查找相似主题
|
||||
all_similar_topics = self._find_similar_topics(
|
||||
|
|
@ -857,30 +1022,140 @@ class Hippocampus:
|
|||
relevant_topics = self._get_top_topics(all_similar_topics, max_topics)
|
||||
|
||||
# 获取相关记忆内容
|
||||
relevant_memories = []
|
||||
current_group_memories = [] # 当前群组/群聊的记忆
|
||||
other_memories = [] # 其他群聊/公共的记忆
|
||||
|
||||
for topic, score in relevant_topics:
|
||||
# 检查主题是否属于当前群组/群聊
|
||||
topic_group_type = None
|
||||
topic_group_id = None
|
||||
|
||||
# 检查是否有群组前缀
|
||||
if "_GT" in topic:
|
||||
parts = topic.split("_GT")
|
||||
if len(parts) > 1:
|
||||
topic_group_type = parts[1]
|
||||
# 检查是否有群聊前缀
|
||||
elif "_g" in topic:
|
||||
parts = topic.split("_g")
|
||||
if len(parts) > 1:
|
||||
topic_group_id = parts[1]
|
||||
|
||||
# 获取该主题的记忆内容
|
||||
first_layer, _ = self.memory_graph.get_related_item(topic, depth=1)
|
||||
if first_layer:
|
||||
# 如果记忆条数超过限制，随机选择指定数量的记忆
|
||||
if len(first_layer) > max_memory_num / 2:
|
||||
first_layer = random.sample(first_layer, max_memory_num // 2)
|
||||
# 为每条记忆添加来源主题和相似度信息
|
||||
# 构建记忆项
|
||||
for memory in first_layer:
|
||||
relevant_memories.append({
|
||||
memory_item = {
|
||||
'topic': topic,
|
||||
'similarity': score,
|
||||
'content': memory
|
||||
})
|
||||
|
||||
# 如果记忆数量超过5个,随机选择5个
|
||||
'content': memory if not isinstance(memory, dict) else memory.get('content', memory),
|
||||
'group_id': topic_group_id,
|
||||
'group_type': topic_group_type
|
||||
}
|
||||
|
||||
# 分类记忆
|
||||
# 如果主题属于当前群组
|
||||
if group_type and topic_group_type == group_type:
|
||||
current_group_memories.append(memory_item)
|
||||
# 如果主题属于当前群聊（且群聊不属于任何群组）
|
||||
elif not group_type and topic_group_id == group_id:
|
||||
current_group_memories.append(memory_item)
|
||||
# 如果主题是公共主题（没有群组/群聊标识）
|
||||
elif not topic_group_type and not topic_group_id:
|
||||
other_memories.append(memory_item)
|
||||
# 如果是其他群聊/群组的主题且不是私有群组，也可以添加
|
||||
elif (topic_group_type and not topic_group_type in global_config.memory_private_groups) or \
|
||||
(not topic_group_type and topic_group_id):
|
||||
other_memories.append(memory_item)
|
||||
|
||||
# 按相似度排序
|
||||
relevant_memories.sort(key=lambda x: x['similarity'], reverse=True)
|
||||
current_group_memories.sort(key=lambda x: x['similarity'], reverse=True)
|
||||
other_memories.sort(key=lambda x: x['similarity'], reverse=True)
|
||||
|
||||
# 记录日志
|
||||
logger.debug(f"[记忆检索] 当前群聊/群组找到 {len(current_group_memories)} 条记忆，其他群聊/公共找到 {len(other_memories)} 条记忆")
|
||||
|
||||
# 控制返回的记忆数量
|
||||
# 优先添加当前群组/群聊的记忆，如果不足，再添加其他群聊/公共的记忆
|
||||
final_memories = current_group_memories
|
||||
remaining_slots = max_memory_num - len(final_memories)
|
||||
|
||||
if remaining_slots > 0 and other_memories:
|
||||
# 添加其他记忆，但最多添加remaining_slots个
|
||||
final_memories.extend(other_memories[:remaining_slots])
|
||||
|
||||
# 如果记忆总数仍然超过限制，随机采样
|
||||
if len(final_memories) > max_memory_num:
|
||||
final_memories = random.sample(final_memories, max_memory_num)
|
||||
|
||||
# 记录日志，显示最终返回多少条记忆
|
||||
logger.debug(f"[记忆检索] 最终返回 {len(final_memories)} 条记忆")
|
||||
|
||||
return final_memories
|
||||
|
||||
if len(relevant_memories) > max_memory_num:
|
||||
relevant_memories = random.sample(relevant_memories, max_memory_num)
|
||||
def get_group_memories(self, group_id: str) -> list:
|
||||
"""获取特定群聊的所有记忆
|
||||
|
||||
Args:
|
||||
group_id: 群聊ID
|
||||
|
||||
Returns:
|
||||
list: 该群聊的记忆列表，每个记忆包含主题和内容
|
||||
"""
|
||||
all_memories = []
|
||||
all_nodes = list(self.memory_graph.G.nodes(data=True))
|
||||
|
||||
# 获取群组类型
|
||||
group_type = self.get_group_type(group_id)
|
||||
|
||||
for concept, data in all_nodes:
|
||||
# 检查是否应该包含该主题的记忆
|
||||
should_include = False
|
||||
|
||||
# 如果群聊属于群组
|
||||
if group_type and f"_GT{group_type}" in concept:
|
||||
should_include = True
|
||||
# 如果是特定群聊的记忆
|
||||
elif f"_g{group_id}" in concept:
|
||||
should_include = True
|
||||
# 如果是公共记忆（没有群组/群聊标识）
|
||||
elif not "_GT" in concept and not "_g" in concept:
|
||||
should_include = True
|
||||
|
||||
if should_include:
|
||||
memory_items = data.get('memory_items', [])
|
||||
if not isinstance(memory_items, list):
|
||||
memory_items = [memory_items] if memory_items else []
|
||||
|
||||
# 添加所有记忆项
|
||||
for memory in memory_items:
|
||||
all_memories.append({
|
||||
'topic': concept,
|
||||
'content': memory if not isinstance(memory, dict) else memory.get('content', str(memory))
|
||||
})
|
||||
|
||||
return all_memories
|
||||
|
||||
return relevant_memories
|
||||
def get_group_type(self, group_id: str) -> str:
|
||||
"""获取群聊所属的群组类型
|
||||
|
||||
Args:
|
||||
group_id: 群聊ID
|
||||
|
||||
Returns:
|
||||
str: 群组类型名称，如果不属于任何群组则返回None
|
||||
"""
|
||||
if not group_id:
|
||||
return None
|
||||
|
||||
# 检查该群聊ID是否属于任何群组
|
||||
for group_name, group_ids in global_config.memory_private_groups.items():
|
||||
if group_id in group_ids:
|
||||
return group_name
|
||||
|
||||
# 如果不属于任何群组，返回None
|
||||
return None
|
||||
|
||||
|
||||
def segment_text(text):
|
||||
|
|
@ -892,6 +1167,15 @@ config = driver.config
|
|||
|
||||
start_time = time.time()
|
||||
|
||||
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"),
|
||||
)
|
||||
# 创建记忆图
|
||||
memory_graph = Memory_graph()
|
||||
# 创建海马体
|
||||
|
|
|
|||
|
|
@ -41,10 +41,10 @@ class LLM_request:
|
|||
"""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)])
|
||||
self.db.llm_usage.create_index([("model_name", 1)])
|
||||
self.db.llm_usage.create_index([("user_id", 1)])
|
||||
self.db.llm_usage.create_index([("request_type", 1)])
|
||||
self.db.db.llm_usage.create_index([("timestamp", 1)])
|
||||
self.db.db.llm_usage.create_index([("model_name", 1)])
|
||||
self.db.db.llm_usage.create_index([("user_id", 1)])
|
||||
self.db.db.llm_usage.create_index([("request_type", 1)])
|
||||
except Exception:
|
||||
logger.error("创建数据库索引失败")
|
||||
|
||||
|
|
@ -73,7 +73,7 @@ class LLM_request:
|
|||
"status": "success",
|
||||
"timestamp": datetime.now()
|
||||
}
|
||||
self.db.llm_usage.insert_one(usage_data)
|
||||
self.db.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}, "
|
||||
|
|
@ -235,7 +235,7 @@ class LLM_request:
|
|||
delta_content = ""
|
||||
accumulated_content += delta_content
|
||||
# 检测流式输出文本是否结束
|
||||
finish_reason = chunk["choices"][0].get("finish_reason")
|
||||
finish_reason = chunk["choices"][0]["finish_reason"]
|
||||
if finish_reason == "stop":
|
||||
usage = chunk.get("usage", None)
|
||||
if usage:
|
||||
|
|
|
|||
|
|
@ -14,6 +14,16 @@ from ..models.utils_model import LLM_request
|
|||
driver = get_driver()
|
||||
config = driver.config
|
||||
|
||||
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"),
|
||||
)
|
||||
|
||||
class ScheduleGenerator:
|
||||
def __init__(self):
|
||||
# 根据global_config.llm_normal这一字典配置指定模型
|
||||
|
|
@ -46,7 +56,7 @@ class ScheduleGenerator:
|
|||
|
||||
schedule_text = str
|
||||
|
||||
existing_schedule = self.db.schedule.find_one({"date": date_str})
|
||||
existing_schedule = self.db.db.schedule.find_one({"date": date_str})
|
||||
if existing_schedule:
|
||||
logger.debug(f"{date_str}的日程已存在:")
|
||||
schedule_text = existing_schedule["schedule"]
|
||||
|
|
@ -63,7 +73,7 @@ class ScheduleGenerator:
|
|||
|
||||
try:
|
||||
schedule_text, _ = await self.llm_scheduler.generate_response(prompt)
|
||||
self.db.schedule.insert_one({"date": date_str, "schedule": schedule_text})
|
||||
self.db.db.schedule.insert_one({"date": date_str, "schedule": schedule_text})
|
||||
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"
|
||||
|
|
@ -143,7 +153,7 @@ 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")})
|
||||
self.db.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():
|
||||
|
|
|
|||
|
|
@ -53,7 +53,7 @@ class LLMStatistics:
|
|||
"costs_by_model": defaultdict(float)
|
||||
}
|
||||
|
||||
cursor = self.db.llm_usage.find({
|
||||
cursor = self.db.db.llm_usage.find({
|
||||
"timestamp": {"$gte": start_time}
|
||||
})
|
||||
|
||||
|
|
|
|||
|
|
@ -13,8 +13,6 @@ from pathlib import Path
|
|||
import jieba
|
||||
from pypinyin import Style, pinyin
|
||||
|
||||
from loguru import logger
|
||||
|
||||
|
||||
class ChineseTypoGenerator:
|
||||
def __init__(self,
|
||||
|
|
@ -40,9 +38,7 @@ class ChineseTypoGenerator:
|
|||
self.max_freq_diff = max_freq_diff
|
||||
|
||||
# 加载数据
|
||||
# print("正在加载汉字数据库，请稍候...")
|
||||
logger.info("正在加载汉字数据库，请稍候...")
|
||||
|
||||
print("正在加载汉字数据库，请稍候...")
|
||||
self.pinyin_dict = self._create_pinyin_dict()
|
||||
self.char_frequency = self._load_or_create_char_frequency()
|
||||
|
||||
|
|
|
|||
|
|
@ -77,6 +77,16 @@ memory_ban_words = [ #不希望记忆的词
|
|||
# "403","张三"
|
||||
]
|
||||
|
||||
# 群组私有记忆配置 - 同一群组内的群聊共享记忆，但不与其他群组共享
|
||||
# 格式为 { 群组名称 = [群聊ID列表] }
|
||||
# 未配置在任何群组中的群聊记忆可以与所有群聊共享(群组内群数量过少 聊天记录过少的情况下 建议修改其他记忆参数 加强回复概率等)
|
||||
# 例如：
|
||||
# memory_private_groups = {
|
||||
# "游戏群组" = ["123456", "234567"],
|
||||
# "工作群组" = ["345678", "456789"]
|
||||
# }
|
||||
memory_private_groups = { }
|
||||
|
||||
[mood]
|
||||
mood_update_interval = 1.0 # 情绪更新间隔 单位秒
|
||||
mood_decay_rate = 0.95 # 情绪衰减率
|
||||
|
|
@ -93,7 +103,7 @@ reaction = "有人说你是人机或者机器人，否定这一事实，攻击
|
|||
[[keywords_reaction.rules]] # 就像这样复制
|
||||
enable = false # 仅作示例，不会触发
|
||||
keywords = ["测试关键词回复","test",""]
|
||||
reaction = "回答“测试成功”"
|
||||
reaction = "回答"测试成功""
|
||||
|
||||
[chinese_typo]
|
||||
enable = true # 是否启用中文错别字生成器
|
||||
|
|
|
|||
|
|
@ -1,45 +1,45 @@
|
|||
@echo off
|
||||
setlocal enabledelayedexpansion
|
||||
chcp 65001
|
||||
cd /d %~dp0
|
||||
|
||||
echo =====================================
|
||||
echo 选择Python环境:
|
||||
echo 1 - venv (推荐)
|
||||
echo 2 - conda
|
||||
echo =====================================
|
||||
choice /c 12 /n /m "输入数字(1或2): "
|
||||
|
||||
if errorlevel 2 (
|
||||
echo =====================================
|
||||
set "CONDA_ENV="
|
||||
set /p CONDA_ENV="请输入要激活的 conda 环境名称: "
|
||||
|
||||
:: 检查输入是否为空
|
||||
if "!CONDA_ENV!"=="" (
|
||||
echo 错误：环境名称不能为空
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
call conda activate !CONDA_ENV!
|
||||
if errorlevel 1 (
|
||||
echo 激活 conda 环境失败
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
echo Conda 环境 "!CONDA_ENV!" 激活成功
|
||||
python config/auto_update.py
|
||||
) else (
|
||||
if exist "venv\Scripts\python.exe" (
|
||||
venv\Scripts\python config/auto_update.py
|
||||
) else (
|
||||
echo =====================================
|
||||
echo 错误: venv环境不存在，请先创建虚拟环境
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
)
|
||||
endlocal
|
||||
pause
|
||||
@echo off
|
||||
setlocal enabledelayedexpansion
|
||||
chcp 65001
|
||||
cd /d %~dp0
|
||||
|
||||
echo =====================================
|
||||
echo 选择Python环境:
|
||||
echo 1 - venv (推荐)
|
||||
echo 2 - conda
|
||||
echo =====================================
|
||||
choice /c 12 /n /m "输入数字(1或2): "
|
||||
|
||||
if errorlevel 2 (
|
||||
echo =====================================
|
||||
set "CONDA_ENV="
|
||||
set /p CONDA_ENV="请输入要激活的 conda 环境名称: "
|
||||
|
||||
:: 检查输入是否为空
|
||||
if "!CONDA_ENV!"=="" (
|
||||
echo 错误：环境名称不能为空
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
call conda activate !CONDA_ENV!
|
||||
if errorlevel 1 (
|
||||
echo 激活 conda 环境失败
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
echo Conda 环境 "!CONDA_ENV!" 激活成功
|
||||
python config/auto_update.py
|
||||
) else (
|
||||
if exist "venv\Scripts\python.exe" (
|
||||
venv\Scripts\python config/auto_update.py
|
||||
) else (
|
||||
echo =====================================
|
||||
echo 错误: venv环境不存在，请先创建虚拟环境
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
)
|
||||
endlocal
|
||||
pause
|
||||
|
|
|
|||
90
麦麦开始学习.bat
90
麦麦开始学习.bat
|
|
@ -1,45 +1,45 @@
|
|||
@echo off
|
||||
setlocal enabledelayedexpansion
|
||||
chcp 65001
|
||||
cd /d %~dp0
|
||||
|
||||
echo =====================================
|
||||
echo 选择Python环境:
|
||||
echo 1 - venv (推荐)
|
||||
echo 2 - conda
|
||||
echo =====================================
|
||||
choice /c 12 /n /m "输入数字(1或2): "
|
||||
|
||||
if errorlevel 2 (
|
||||
echo =====================================
|
||||
set "CONDA_ENV="
|
||||
set /p CONDA_ENV="请输入要激活的 conda 环境名称: "
|
||||
|
||||
:: 检查输入是否为空
|
||||
if "!CONDA_ENV!"=="" (
|
||||
echo 错误：环境名称不能为空
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
call conda activate !CONDA_ENV!
|
||||
if errorlevel 1 (
|
||||
echo 激活 conda 环境失败
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
echo Conda 环境 "!CONDA_ENV!" 激活成功
|
||||
python src/plugins/zhishi/knowledge_library.py
|
||||
) else (
|
||||
if exist "venv\Scripts\python.exe" (
|
||||
venv\Scripts\python src/plugins/zhishi/knowledge_library.py
|
||||
) else (
|
||||
echo =====================================
|
||||
echo 错误: venv环境不存在，请先创建虚拟环境
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
)
|
||||
endlocal
|
||||
pause
|
||||
@echo off
|
||||
setlocal enabledelayedexpansion
|
||||
chcp 65001
|
||||
cd /d %~dp0
|
||||
|
||||
echo =====================================
|
||||
echo 选择Python环境:
|
||||
echo 1 - venv (推荐)
|
||||
echo 2 - conda
|
||||
echo =====================================
|
||||
choice /c 12 /n /m "输入数字(1或2): "
|
||||
|
||||
if errorlevel 2 (
|
||||
echo =====================================
|
||||
set "CONDA_ENV="
|
||||
set /p CONDA_ENV="请输入要激活的 conda 环境名称: "
|
||||
|
||||
:: 检查输入是否为空
|
||||
if "!CONDA_ENV!"=="" (
|
||||
echo 错误：环境名称不能为空
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
call conda activate !CONDA_ENV!
|
||||
if errorlevel 1 (
|
||||
echo 激活 conda 环境失败
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
|
||||
echo Conda 环境 "!CONDA_ENV!" 激活成功
|
||||
python src/plugins/zhishi/knowledge_library.py
|
||||
) else (
|
||||
if exist "venv\Scripts\python.exe" (
|
||||
venv\Scripts\python src/plugins/zhishi/knowledge_library.py
|
||||
) else (
|
||||
echo =====================================
|
||||
echo 错误: venv环境不存在，请先创建虚拟环境
|
||||
pause
|
||||
exit /b 1
|
||||
)
|
||||
)
|
||||
endlocal
|
||||
pause
|
||||
|
|
|
|||
Loading…
Reference in New Issue