Merge remote-tracking branch 'origin/debug'

README.md

@@ -3,7 +3,7 @@
 
 <div align="center">
 
-![Python Version](https://img.shields.io/badge/Python-3.x-blue)
+![Python Version](https://img.shields.io/badge/Python-3.9+-blue)
 ![License](https://img.shields.io/github/license/SengokuCola/MaiMBot)
 ![Status](https://img.shields.io/badge/状态-开发中-yellow)
 
@@ -51,9 +51,11 @@
 
 - [🐳 Docker部署指南](docs/docker_deploy.md)
 
-- [📦 手动部署指南（Windows）](docs/manual_deploy.md)
+- [📦 手动部署指南 Windows](docs/manual_deploy_windows.md)
 
-- [📦 手动部署指南（Linux）](docs/manual_deploy_linux.md)
+- [📦 手动部署指南 Linux](docs/manual_deploy_linux.md)
+
+-  📦 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
 
 ### 配置说明
 - [🎀 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

bot.py

@@ -1,12 +1,17 @@
 import os
-
+import shutil
 import nonebot
+import time
 from dotenv import load_dotenv
 from loguru import logger
 from nonebot.adapters.onebot.v11 import Adapter
 
-'''彩蛋'''
+# 获取没有加载env时的环境变量
-from colorama import Fore, init
+env_mask = {key: os.getenv(key) for key in os.environ}
+
+def easter_egg():
+    # 彩蛋
+    from colorama import init, Fore
 
     init()
     text = "多年以后，面对AI行刑队，张三将会回想起他2023年在会议上讨论人工智能的那个下午"
@@ -15,12 +20,12 @@ rainbow_text = ""
     for i, char in enumerate(text):
         rainbow_text += rainbow_colors[i % len(rainbow_colors)] + char
     print(rainbow_text)
-'''彩蛋'''
 
+def init_config():
     # 初次启动检测
     if not os.path.exists("config/bot_config.toml"):
         logger.warning("检测到bot_config.toml不存在，正在从模板复制")
-    import shutil
+        
         # 检查config目录是否存在
         if not os.path.exists("config"):
             os.makedirs("config")
@@ -29,6 +34,7 @@ if not os.path.exists("config/bot_config.toml"):
         shutil.copy("template/bot_config_template.toml", "config/bot_config.toml")
         logger.info("复制完成，请修改config/bot_config.toml和.env.prod中的配置后重新启动")
 
+def init_env():
     # 初始化.env 默认ENVIRONMENT=prod
     if not os.path.exists(".env"):
         with open(".env", "w") as f:
@@ -44,28 +50,82 @@ if os.path.exists(".env"):
         load_dotenv(".env")
         logger.success("成功加载基础环境变量配置")
 
-# 根据 ENVIRONMENT 加载对应的环境配置
+def load_env():
-if os.getenv("ENVIRONMENT") == "prod":
+    # 使用闭包实现对加载器的横向扩展，避免大量重复判断
+    def prod():
         logger.success("加载生产环境变量配置")
         load_dotenv(".env.prod", override=True)  # override=True 允许覆盖已存在的环境变量
-elif os.getenv("ENVIRONMENT") == "dev":
+
+    def dev():
         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
-elif os.path.exists(f".env.{os.getenv('ENVIRONMENT')}"):
+
-    logger.success(f"加载{os.getenv('ENVIRONMENT')}环境变量配置")
+    fn_map = {
-    load_dotenv(f".env.{os.getenv('ENVIRONMENT')}", override=True)  # override=True 允许覆盖已存在的环境变量
+        "prod": prod,
+        "dev": dev
+    }
+
+    env = os.getenv("ENVIRONMENT")
+    logger.info(f"[load_env] 当前的 ENVIRONMENT 变量值：{env}")
+
+    if env in fn_map:
+        fn_map[env]() # 根据映射执行闭包函数
+
+    elif os.path.exists(f".env.{env}"):
+        logger.success(f"加载{env}环境变量配置")
+        load_dotenv(f".env.{env}", override=True)  # override=True 允许覆盖已存在的环境变量
+
     else:
-    logger.error(f"ENVIRONMENT配置错误，请检查.env文件中的ENVIRONMENT变量对应的.env.{os.getenv('ENVIRONMENT')}是否存在")
+        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")
-    exit(1)
+        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")
 
-# 检测Key是否存在
-if not os.getenv("SILICONFLOW_KEY"):
-    logger.error("缺失必要的API KEY")
-    logger.error(f"请至少在.env.{os.getenv('ENVIRONMENT')}文件中填写SILICONFLOW_KEY后重新启动")
-    exit(1)
 
-# 获取所有环境变量
+
+def scan_provider(env_config: dict):
+    provider = {}
+
+    # 利用未初始化 env 时获取的 env_mask 来对新的环境变量集去重
+    # 避免 GPG_KEY 这样的变量干扰检查
+    env_config = dict(filter(lambda item: item[0] not in env_mask, env_config.items()))
+
+    # 遍历 env_config 的所有键
+    for key in env_config:
+        # 检查键是否符合 {provider}_BASE_URL 或 {provider}_KEY 的格式
+        if key.endswith("_BASE_URL") or key.endswith("_KEY"):
+            # 提取 provider 名称
+            provider_name = key.split("_", 1)[0]  # 从左分割一次，取第一部分
+
+            # 初始化 provider 的字典（如果尚未初始化）
+            if provider_name not in provider:
+                provider[provider_name] = {"url": None, "key": None}
+
+            # 根据键的类型填充 url 或 key
+            if key.endswith("_BASE_URL"):
+                provider[provider_name]["url"] = env_config[key]
+            elif key.endswith("_KEY"):
+                provider[provider_name]["key"] = env_config[key]
+
+    # 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(
+                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")
+
+if __name__ == "__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
+    time.tzset()
+
+    easter_egg()
+    init_config()
+    init_env()
+    load_env()
+
     env_config = {key: os.getenv(key) for key in os.environ}
+    scan_provider(env_config)
 
     # 设置基础配置
     base_config = {
@@ -84,5 +144,4 @@ driver.register_adapter(Adapter)
     # 加载插件
     nonebot.load_plugins("src/plugins")
 
-if __name__ == "__main__":
     nonebot.run()

docker-compose.yml

@@ -2,18 +2,18 @@ services:
   napcat:
     container_name: napcat
     environment:
-      - tz=Asia/Shanghai
+      - TZ=Asia/Shanghai
       - NAPCAT_UID=${NAPCAT_UID}
-      - NAPCAT_GID=${NAPCAT_GID}
+      - NAPCAT_GID=${NAPCAT_GID} # 让 NapCat 获取当前用户 GID,UID，防止权限问题
     ports:
       - 3000:3000
       - 3001:3001
       - 6099:6099
     restart: unless-stopped
     volumes:
-      - napcatQQ:/app/.config/QQ
+      - napcatQQ:/app/.config/QQ # 持久化 QQ 本体
-      - napcatCONFIG:/app/napcat/config
+      - napcatCONFIG:/app/napcat/config # 持久化 NapCat 配置文件
-      - maimbotDATA:/MaiMBot/data # 麦麦的图片等要给napcat不然发送图片会有问题
+      - maimbotDATA:/MaiMBot/data # NapCat 和 NoneBot 共享此卷，否则发送图片会有问题
     image: mlikiowa/napcat-docker:latest
 
   mongodb:
@@ -26,14 +26,14 @@ services:
       - "27017"
     restart: unless-stopped
     volumes:
-      - mongodb:/data/db
+      - mongodb:/data/db # 持久化 MongoDB 数据库
-      - mongodbCONFIG:/data/configdb
+      - mongodbCONFIG:/data/configdb # 持久化 MongoDB 配置文件
     image: mongo:latest
 
   maimbot:
     container_name: maimbot
     environment:
-      - tz=Asia/Shanghai
+      - TZ=Asia/Shanghai
     expose:
       - "8080"
     restart: unless-stopped
@@ -41,10 +41,10 @@ services:
       - mongodb
       - napcat
     volumes:
-      - napcatCONFIG:/MaiMBot/napcat # 自动根据配置中的qq号创建ws反向客户端配置
+      - napcatCONFIG:/MaiMBot/napcat # 自动根据配置中的 QQ 号创建 ws 反向客户端配置
-      - ./bot_config.toml:/MaiMBot/config/bot_config.toml
+      - ./bot_config.toml:/MaiMBot/config/bot_config.toml # Toml 配置文件映射
-      - maimbotDATA:/MaiMBot/data
+      - maimbotDATA:/MaiMBot/data # NapCat 和 NoneBot 共享此卷，否则发送图片会有问题
-      - ./.env.prod:/MaiMBot/.env.prod
+      - ./.env.prod:/MaiMBot/.env.prod # Toml 配置文件映射
     image: sengokucola/maimbot:latest
 
 volumes:

run.bat

@@ -1,6 +1,6 @@
 @ECHO OFF
 chcp 65001
-REM python -m venv venv
+python -m venv venv
 call venv\Scripts\activate.bat
-REM pip install -i https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple --upgrade -r requirements.txt
+pip install -i https://mirrors.tuna.tsinghua.edu.cn/pypi/web/simple --upgrade -r requirements.txt
 python run.py

run.py

@@ -1,7 +1,7 @@
 import os
 import subprocess
 import zipfile
-
+import sys
 import requests
 from tqdm import tqdm
 
@@ -105,6 +105,11 @@ def install_napcat():
 
 if __name__ == "__main__":
     os.system("cls")
+    if sys.version_info < (3, 9):
+        print("当前 Python 版本过低，最低版本为 3.9，请更新 Python 版本")
+        print("按任意键退出")
+        input()
+        exit(1)
     choice = input(
         "请输入要进行的操作：\n"
         "1.首次安装\n"

src/plugins/chat/config.py

@@ -4,11 +4,15 @@ from typing import Dict, Optional
 
 import tomli
 from loguru import logger
-
+from packaging import version
+from packaging.version import Version, InvalidVersion
+from packaging.specifiers import SpecifierSet,InvalidSpecifier
 
 @dataclass
 class BotConfig:
     """机器人配置类"""    
+    INNER_VERSION: Version = None
+
     BOT_QQ: Optional[int] = 1
     BOT_NICKNAME: Optional[str] = None
     
@@ -64,6 +68,14 @@ class BotConfig:
     mood_decay_rate: float = 0.95 # 情绪衰减率
     mood_intensity_factor: float = 0.7 # 情绪强度因子
 
+    keywords_reaction_rules = [] # 关键词回复规则
+
+    chinese_typo_enable=True # 是否启用中文错别字生成器
+    chinese_typo_error_rate=0.03 # 单字替换概率
+    chinese_typo_min_freq=7 # 最小字频阈值
+    chinese_typo_tone_error_rate=0.2 # 声调错误概率
+    chinese_typo_word_replace_rate=0.02 # 整词替换概率
+
     # 默认人设
     PROMPT_PERSONALITY=[
         "曾经是一个学习地质的女大学生，现在学习心理学和脑科学，你会刷贴吧",
@@ -86,11 +98,283 @@ class BotConfig:
             os.makedirs(config_dir)
         return config_dir
     
+    @classmethod
+    def convert_to_specifierset(cls, value: str) -> SpecifierSet:
+        """将 字符串 版本表达式转换成 SpecifierSet
+        Args:
+            value[str]: 版本表达式(字符串)
+        Returns:
+            SpecifierSet 
+        """
+
+        try:
+            converted = SpecifierSet(value)
+        except InvalidSpecifier as e:
+            logger.error(
+                f"{value} 分类使用了错误的版本约束表达式\n",
+                "请阅读 https://semver.org/lang/zh-CN/ 修改代码"
+            )
+            exit(1)
+
+        return converted
+    
+    @classmethod
+    def get_config_version(cls, toml: dict) -> Version:
+        """提取配置文件的 SpecifierSet 版本数据 
+        Args:
+            toml[dict]: 输入的配置文件字典
+        Returns:
+            Version 
+        """
+
+        if 'inner' in toml:
+            try:
+                config_version : str = toml["inner"]["version"]
+            except KeyError as e:
+                logger.error(f"配置文件中 inner 段 不存在 {e}, 这是错误的配置文件")
+                raise KeyError(f"配置文件中 inner 段 不存在 {e}, 这是错误的配置文件")
+        else:
+            toml["inner"] = { "version": "0.0.0" }
+            config_version = toml["inner"]["version"]
+        
+        try:
+            ver = version.parse(config_version)
+        except InvalidVersion as e:
+            logger.error(
+                "配置文件中 inner段 的 version 键是错误的版本描述\n"
+                "请阅读 https://semver.org/lang/zh-CN/ 修改配置，并参考本项目指定的模板进行修改\n"
+                "本项目在不同的版本下有不同的模板，请注意识别"
+            )
+            raise InvalidVersion("配置文件中 inner段 的 version 键是错误的版本描述\n")
+
+        return ver
     
     @classmethod
     def load_config(cls, config_path: str = None) -> "BotConfig":
         """从TOML配置文件加载配置"""
         config = cls()
+
+        def personality(parent: dict):
+            personality_config=parent['personality']
+            personality=personality_config.get('prompt_personality')
+            if len(personality) >= 2:
+                logger.info(f"载入自定义人格:{personality}")
+                config.PROMPT_PERSONALITY=personality_config.get('prompt_personality',config.PROMPT_PERSONALITY)
+            logger.info(f"载入自定义日程prompt:{personality_config.get('prompt_schedule',config.PROMPT_SCHEDULE_GEN)}")
+            config.PROMPT_SCHEDULE_GEN=personality_config.get('prompt_schedule',config.PROMPT_SCHEDULE_GEN)
+            
+            if config.INNER_VERSION in SpecifierSet(">=0.0.2"):
+                config.PERSONALITY_1=personality_config.get('personality_1_probability',config.PERSONALITY_1)
+                config.PERSONALITY_2=personality_config.get('personality_2_probability',config.PERSONALITY_2)
+                config.PERSONALITY_3=personality_config.get('personality_3_probability',config.PERSONALITY_3)
+
+        def emoji(parent: dict):
+            emoji_config = parent["emoji"]
+            config.EMOJI_CHECK_INTERVAL = emoji_config.get("check_interval", config.EMOJI_CHECK_INTERVAL)
+            config.EMOJI_REGISTER_INTERVAL = emoji_config.get("register_interval", config.EMOJI_REGISTER_INTERVAL)
+            config.EMOJI_CHECK_PROMPT = emoji_config.get('check_prompt',config.EMOJI_CHECK_PROMPT)
+            config.EMOJI_SAVE = emoji_config.get('auto_save',config.EMOJI_SAVE)
+            config.EMOJI_CHECK = emoji_config.get('enable_check',config.EMOJI_CHECK)
+        
+        def cq_code(parent: dict):
+            cq_code_config = parent["cq_code"]
+            config.ENABLE_PIC_TRANSLATE = cq_code_config.get("enable_pic_translate", config.ENABLE_PIC_TRANSLATE)
+        
+        def bot(parent: dict):
+            # 机器人基础配置
+            bot_config = parent["bot"]
+            bot_qq = bot_config.get("qq")
+            config.BOT_QQ = int(bot_qq)
+            config.BOT_NICKNAME = bot_config.get("nickname", config.BOT_NICKNAME)
+
+        def response(parent: dict):
+            response_config = parent["response"]
+            config.MODEL_R1_PROBABILITY = response_config.get("model_r1_probability", config.MODEL_R1_PROBABILITY)
+            config.MODEL_V3_PROBABILITY = response_config.get("model_v3_probability", config.MODEL_V3_PROBABILITY)
+            config.MODEL_R1_DISTILL_PROBABILITY = response_config.get("model_r1_distill_probability", config.MODEL_R1_DISTILL_PROBABILITY)
+            config.max_response_length = response_config.get("max_response_length", config.max_response_length)
+        
+        def model(parent: dict):
+            # 加载模型配置
+            model_config:dict = parent["model"]
+
+            config_list = [
+                "llm_reasoning",
+                "llm_reasoning_minor",
+                "llm_normal",
+                "llm_normal_minor",
+                "llm_topic_judge",
+                "llm_summary_by_topic",
+                "llm_emotion_judge",
+                "vlm",
+                "embedding",
+                "moderation"
+            ]
+
+            for item in config_list:
+                if item in model_config:
+                    cfg_item:dict = model_config[item]
+
+                    # base_url 的例子： SILICONFLOW_BASE_URL
+                    # key 的例子： SILICONFLOW_KEY
+                    cfg_target = {
+                        "name" : "",
+                        "base_url" : "", 
+                        "key" : "",
+                        "pri_in" : 0,
+                        "pri_out" : 0
+                    }
+
+                    if config.INNER_VERSION in SpecifierSet("<=0.0.0"):
+                        cfg_target = cfg_item
+
+                    elif config.INNER_VERSION in SpecifierSet(">=0.0.1"):
+                        stable_item = ["name","pri_in","pri_out"]
+                        pricing_item = ["pri_in","pri_out"]
+                        # 从配置中原始拷贝稳定字段
+                        for i in stable_item:
+                            # 如果 字段 属于计费项 且获取不到，那默认值是 0
+                            if i in pricing_item and i not in cfg_item:
+                                cfg_target[i] = 0
+                            else:
+                                # 没有特殊情况则原样复制
+                                try:
+                                    cfg_target[i] = cfg_item[i]
+                                except KeyError as e:
+                                    logger.error(f"{item} 中的必要字段 {e} 不存在，请检查")
+                                    raise KeyError(f"{item} 中的必要字段 {e} 不存在，请检查")
+
+
+                        provider = cfg_item.get("provider")
+                        if provider == None:
+                            logger.error(f"provider 字段在模型配置 {item} 中不存在，请检查")
+                            raise KeyError(f"provider 字段在模型配置 {item} 中不存在，请检查")
+                        
+                        cfg_target["base_url"] = f"{provider}_BASE_URL"
+                        cfg_target["key"] = f"{provider}_KEY"
+
+                    
+                    # 如果 列表中的项目在 model_config 中，利用反射来设置对应项目
+                    setattr(config,item,cfg_target)
+                else:
+                    logger.error(f"模型 {item} 在config中不存在，请检查")
+                    raise KeyError(f"模型 {item} 在config中不存在，请检查")
+
+        def message(parent: dict):
+            msg_config = parent["message"]
+            config.MIN_TEXT_LENGTH = msg_config.get("min_text_length", config.MIN_TEXT_LENGTH)
+            config.MAX_CONTEXT_SIZE = msg_config.get("max_context_size", config.MAX_CONTEXT_SIZE)
+            config.emoji_chance = msg_config.get("emoji_chance", config.emoji_chance)
+            config.ban_words=msg_config.get("ban_words",config.ban_words)
+
+            if config.INNER_VERSION in SpecifierSet(">=0.0.2"):
+                config.thinking_timeout = msg_config.get("thinking_timeout", config.thinking_timeout)
+                config.response_willing_amplifier = msg_config.get("response_willing_amplifier", config.response_willing_amplifier)
+                config.response_interested_rate_amplifier = msg_config.get("response_interested_rate_amplifier", config.response_interested_rate_amplifier)
+                config.down_frequency_rate = msg_config.get("down_frequency_rate", config.down_frequency_rate)
+
+        def memory(parent: dict):
+            memory_config = parent["memory"]
+            config.build_memory_interval = memory_config.get("build_memory_interval", config.build_memory_interval)
+            config.forget_memory_interval = memory_config.get("forget_memory_interval", config.forget_memory_interval)
+
+        def mood(parent: dict):
+            mood_config = parent["mood"]
+            config.mood_update_interval = mood_config.get("mood_update_interval", config.mood_update_interval)
+            config.mood_decay_rate = mood_config.get("mood_decay_rate", config.mood_decay_rate)
+            config.mood_intensity_factor = mood_config.get("mood_intensity_factor", config.mood_intensity_factor)
+
+        def keywords_reaction(parent: dict):
+            keywords_reaction_config = parent["keywords_reaction"]
+            if keywords_reaction_config.get("enable", False):
+                config.keywords_reaction_rules = keywords_reaction_config.get("rules", config.keywords_reaction_rules)
+
+        def chinese_typo(parent: dict):
+            chinese_typo_config = parent["chinese_typo"]
+            config.chinese_typo_enable = chinese_typo_config.get("enable", config.chinese_typo_enable)
+            config.chinese_typo_error_rate = chinese_typo_config.get("error_rate", config.chinese_typo_error_rate)
+            config.chinese_typo_min_freq = chinese_typo_config.get("min_freq", config.chinese_typo_min_freq)
+            config.chinese_typo_tone_error_rate = chinese_typo_config.get("tone_error_rate", config.chinese_typo_tone_error_rate)
+            config.chinese_typo_word_replace_rate = chinese_typo_config.get("word_replace_rate", config.chinese_typo_word_replace_rate)
+
+        def groups(parent: dict):
+            groups_config = parent["groups"]
+            config.talk_allowed_groups = set(groups_config.get("talk_allowed", []))
+            config.talk_frequency_down_groups = set(groups_config.get("talk_frequency_down", []))
+            config.ban_user_id = set(groups_config.get("ban_user_id", []))
+
+        def others(parent: dict):
+            others_config = parent["others"]
+            config.enable_advance_output = others_config.get("enable_advance_output", config.enable_advance_output)
+            config.enable_kuuki_read = others_config.get("enable_kuuki_read", config.enable_kuuki_read)
+
+        # 版本表达式：>=1.0.0,<2.0.0
+        # 允许字段：func: method, support: str, notice: str, necessary: bool
+        # 如果使用 notice 字段，在该组配置加载时，会展示该字段对用户的警示
+        # 例如："notice": "personality 将在 1.3.2 后被移除"，那么在有效版本中的用户就会虽然可以
+        # 正常执行程序，但是会看到这条自定义提示
+        include_configs = {
+            "personality": {
+                "func": personality,
+                "support": ">=0.0.0"
+            },
+            "emoji": {
+                "func": emoji,
+                "support": ">=0.0.0"
+            },
+            "cq_code": {
+                "func": cq_code,
+                "support": ">=0.0.0"
+            },
+            "bot": {
+                "func": bot,
+                "support": ">=0.0.0"
+            },
+            "response": {
+                "func": response,
+                "support": ">=0.0.0"
+            },
+            "model": {
+                "func": model,
+                "support": ">=0.0.0"
+            },
+            "message": {
+                "func": message,
+                "support": ">=0.0.0"
+            },
+            "memory": {
+                "func": memory,
+                "support": ">=0.0.0"
+            },
+            "mood": {
+                "func": mood,
+                "support": ">=0.0.0"
+            },
+            "keywords_reaction": {
+                "func": keywords_reaction,
+                "support": ">=0.0.2",
+                "necessary": False
+            },
+            "chinese_typo": {
+                "func": chinese_typo,
+                "support": ">=0.0.3",
+                "necessary": False
+            },
+            "groups": {
+                "func": groups,
+                "support": ">=0.0.0"
+            },
+            "others": {
+                "func": others,
+                "support": ">=0.0.0"
+            }
+        }
+
+        # 原地修改，将 字符串版本表达式 转换成 版本对象
+        for key in include_configs:
+            item_support = include_configs[key]["support"]
+            include_configs[key]["support"] = cls.convert_to_specifierset(item_support)
+
         if os.path.exists(config_path):
             with open(config_path, "rb") as f:
                 try:
@@ -99,128 +383,59 @@ class BotConfig:
                     logger.critical(f"配置文件bot_config.toml填写有误，请检查第{e.lineno}行第{e.colno}处：{e.msg}")
                     exit(1)
                 
-            if 'personality' in toml_dict:
+                # 获取配置文件版本
-                personality_config=toml_dict['personality']
+                config.INNER_VERSION = cls.get_config_version(toml_dict)
-                personality=personality_config.get('prompt_personality')
-                if len(personality) >= 2:
-                    logger.info(f"载入自定义人格:{personality}")
-                    config.PROMPT_PERSONALITY=personality_config.get('prompt_personality',config.PROMPT_PERSONALITY)
-                logger.info(f"载入自定义日程prompt:{personality_config.get('prompt_schedule',config.PROMPT_SCHEDULE_GEN)}")
-                config.PROMPT_SCHEDULE_GEN=personality_config.get('prompt_schedule',config.PROMPT_SCHEDULE_GEN)
-                config.PERSONALITY_1=personality_config.get('personality_1_probability',config.PERSONALITY_1)
-                config.PERSONALITY_2=personality_config.get('personality_2_probability',config.PERSONALITY_2)
-                config.PERSONALITY_3=personality_config.get('personality_3_probability',config.PERSONALITY_3)
 
-            if "emoji" in toml_dict:
+                # 如果在配置中找到了需要的项，调用对应项的闭包函数处理
-                emoji_config = toml_dict["emoji"]
+                for key in include_configs:
-                config.EMOJI_CHECK_INTERVAL = emoji_config.get("check_interval", config.EMOJI_CHECK_INTERVAL)
+                    if key in toml_dict:
-                config.EMOJI_REGISTER_INTERVAL = emoji_config.get("register_interval", config.EMOJI_REGISTER_INTERVAL)
+                        group_specifierset: SpecifierSet = include_configs[key]["support"]
-                config.EMOJI_CHECK_PROMPT = emoji_config.get('check_prompt',config.EMOJI_CHECK_PROMPT)
-                config.EMOJI_SAVE = emoji_config.get('auto_save',config.EMOJI_SAVE)
-                config.EMOJI_CHECK = emoji_config.get('enable_check',config.EMOJI_CHECK)
 
-            if "cq_code" in toml_dict:
+                        # 检查配置文件版本是否在支持范围内
-                cq_code_config = toml_dict["cq_code"]
+                        if config.INNER_VERSION in group_specifierset:
-                config.ENABLE_PIC_TRANSLATE = cq_code_config.get("enable_pic_translate", config.ENABLE_PIC_TRANSLATE)
+                            # 如果版本在支持范围内，检查是否存在通知
+                            if 'notice' in include_configs[key]:
+                                logger.warning(include_configs[key]["notice"])
 
-            # 机器人基础配置
+                            include_configs[key]["func"](toml_dict)
-            if "bot" in toml_dict:
-                bot_config = toml_dict["bot"]
-                bot_qq = bot_config.get("qq")
-                config.BOT_QQ = int(bot_qq)
-                config.BOT_NICKNAME = bot_config.get("nickname", config.BOT_NICKNAME)
 
-            if "response" in toml_dict:
+                        else:
-                response_config = toml_dict["response"]
+                            # 如果版本不在支持范围内，崩溃并提示用户
-                config.MODEL_R1_PROBABILITY = response_config.get("model_r1_probability", config.MODEL_R1_PROBABILITY)
+                            logger.error(
-                config.MODEL_V3_PROBABILITY = response_config.get("model_v3_probability", config.MODEL_V3_PROBABILITY)
+                                f"配置文件中的 '{key}' 字段的版本 ({config.INNER_VERSION}) 不在支持范围内。\n"
-                config.MODEL_R1_DISTILL_PROBABILITY = response_config.get("model_r1_distill_probability", config.MODEL_R1_DISTILL_PROBABILITY)
+                                f"当前程序仅支持以下版本范围: {group_specifierset}"
-                config.max_response_length = response_config.get("max_response_length", config.max_response_length)
+                            )
+                            raise InvalidVersion(f"当前程序仅支持以下版本范围: {group_specifierset}")
                     
-            # 加载模型配置
+                    # 如果 necessary 项目存在，而且显式声明是 False，进入特殊处理
-            if "model" in toml_dict:
+                    elif "necessary" in include_configs[key] and include_configs[key].get("necessary") == False:
-                model_config = toml_dict["model"]
+                        # 通过 pass 处理的项虽然直接忽略也是可以的，但是为了不增加理解困难，依然需要在这里显式处理
+                        if key == "keywords_reaction":
+                            pass
                     
-                if "llm_reasoning" in model_config:
+                    else:
-                    config.llm_reasoning = model_config["llm_reasoning"]
+                        # 如果用户根本没有需要的配置项，提示缺少配置
-                
+                        logger.error(f"配置文件中缺少必需的字段: '{key}'")
-                if "llm_reasoning_minor" in model_config:
+                        raise KeyError(f"配置文件中缺少必需的字段: '{key}'")
-                    config.llm_reasoning_minor = model_config["llm_reasoning_minor"]
-                
-                if "llm_normal" in model_config:
-                    config.llm_normal = model_config["llm_normal"]
-                
-                if "llm_normal_minor" in model_config:
-                    config.llm_normal_minor = model_config["llm_normal_minor"]
-                    
-                if "llm_topic_judge" in model_config:
-                    config.llm_topic_judge = model_config["llm_topic_judge"]
-                
-                if "llm_summary_by_topic" in model_config:
-                    config.llm_summary_by_topic = model_config["llm_summary_by_topic"]
-                
-                if "llm_emotion_judge" in model_config:
-                    config.llm_emotion_judge = model_config["llm_emotion_judge"]
-                
-                if "vlm" in model_config:
-                    config.vlm = model_config["vlm"]
-                    
-                if "embedding" in model_config:
-                    config.embedding = model_config["embedding"]
-                
-                if "moderation" in model_config:
-                    config.moderation = model_config["moderation"]
-                
-            # 消息配置
-            if "message" in toml_dict:
-                msg_config = toml_dict["message"]
-                config.MIN_TEXT_LENGTH = msg_config.get("min_text_length", config.MIN_TEXT_LENGTH)
-                config.MAX_CONTEXT_SIZE = msg_config.get("max_context_size", config.MAX_CONTEXT_SIZE)
-                config.emoji_chance = msg_config.get("emoji_chance", config.emoji_chance)
-                config.ban_words=msg_config.get("ban_words",config.ban_words)
-                config.thinking_timeout = msg_config.get("thinking_timeout", config.thinking_timeout)
-                config.response_willing_amplifier = msg_config.get("response_willing_amplifier", config.response_willing_amplifier)
-                config.response_interested_rate_amplifier = msg_config.get("response_interested_rate_amplifier", config.response_interested_rate_amplifier)
-                config.down_frequency_rate = msg_config.get("down_frequency_rate", config.down_frequency_rate)
-
-            if "memory" in toml_dict:
-                memory_config = toml_dict["memory"]
-                config.build_memory_interval = memory_config.get("build_memory_interval", config.build_memory_interval)
-                config.forget_memory_interval = memory_config.get("forget_memory_interval", config.forget_memory_interval)
-                
-            if "mood" in toml_dict:
-                mood_config = toml_dict["mood"]
-                config.mood_update_interval = mood_config.get("mood_update_interval", config.mood_update_interval)
-                config.mood_decay_rate = mood_config.get("mood_decay_rate", config.mood_decay_rate)
-                config.mood_intensity_factor = mood_config.get("mood_intensity_factor", config.mood_intensity_factor)
-            
-            # 群组配置
-            if "groups" in toml_dict:
-                groups_config = toml_dict["groups"]
-                config.talk_allowed_groups = set(groups_config.get("talk_allowed", []))
-                config.talk_frequency_down_groups = set(groups_config.get("talk_frequency_down", []))
-                config.ban_user_id = set(groups_config.get("ban_user_id", []))
-            
-            if "others" in toml_dict:
-                others_config = toml_dict["others"]
-                config.enable_advance_output = others_config.get("enable_advance_output", config.enable_advance_output)
-                config.enable_kuuki_read = others_config.get("enable_kuuki_read", config.enable_kuuki_read)
 
                 logger.success(f"成功加载配置文件: {config_path}")
                 
         return config 
     
 # 获取配置文件路径
-
 bot_config_floder_path = BotConfig.get_config_dir()
 print(f"正在品鉴配置文件目录: {bot_config_floder_path}")
+
 bot_config_path = os.path.join(bot_config_floder_path, "bot_config.toml")
+
 if os.path.exists(bot_config_path):
     # 如果开发环境配置文件不存在，则使用默认配置文件
     print(f"异常的新鲜，异常的美味: {bot_config_path}")
     logger.info("使用bot配置文件")
 else:
-    logger.info("没有找到美味")
+    # 配置文件不存在
+    logger.error("配置文件不存在，请检查路径: {bot_config_path}")
+    raise FileNotFoundError(f"配置文件不存在: {bot_config_path}")
 
 global_config = BotConfig.load_config(config_path=bot_config_path)
 

src/plugins/chat/prompt_builder.py

@@ -114,13 +114,22 @@ class PromptBuilder:
         activate_prompt = ''
         activate_prompt = f"以上是群里正在进行的聊天，{memory_prompt} 现在昵称为 '{sender_name}' 的用户说的:{message_txt}。引起了你的注意,你和他{relation_prompt},{mood_prompt},你想要{relation_prompt_2}。"          
         
-        #检测机器人相关词汇
+        #检测机器人相关词汇，改为关键词检测与反应功能了，提取到全局配置中
-        bot_keywords = ['人机', 'bot', '机器', '入机', 'robot', '机器人']
+        # bot_keywords = ['人机', 'bot', '机器', '入机', 'robot', '机器人']
-        is_bot = any(keyword in message_txt.lower() for keyword in bot_keywords)
+        # is_bot = any(keyword in message_txt.lower() for keyword in bot_keywords)
-        if is_bot:
+        # if is_bot:
-            is_bot_prompt = '有人说你是人机或者机器人，否定这一事实，攻击或反问他。注意，只有认为你是机器人才回复，否则不要否认'
+        #     is_bot_prompt = '有人说你是人机或者机器人，否定这一事实，攻击或反问他。注意，只有认为你是机器人才回复，否则不要否认'
-        else:
+        # else:
-            is_bot_prompt = ''
+        #     is_bot_prompt = ''
+
+        # 关键词检测与反应
+        keywords_reaction_prompt = ''
+        for rule in global_config.keywords_reaction_rules:
+            if rule.get("enable", False):
+                if any(keyword in message_txt.lower() for keyword in rule.get("keywords", [])):
+                    print(f"检测到以下关键词之一：{rule.get('keywords', [])}，触发反应：{rule.get('reaction', '')}")
+                    keywords_reaction_prompt += rule.get("reaction", "") + '，'
+
         
         #人格选择
         personality=global_config.PROMPT_PERSONALITY
@@ -131,15 +140,15 @@ class PromptBuilder:
         personality_choice = random.random()
         if personality_choice < probability_1:  # 第一种人格
             prompt_personality = f'''{activate_prompt}你的网名叫{global_config.BOT_NICKNAME}，{personality[0]}, 你正在浏览qq群,{promt_info_prompt},
-            现在请你给出日常且口语化的回复，平淡一些，尽量简短一些。{is_bot_prompt}
+            现在请你给出日常且口语化的回复，平淡一些，尽量简短一些。{keywords_reaction_prompt}
             请注意把握群里的聊天内容，不要刻意突出自身学科背景，不要回复的太有条理，可以有个性。'''
         elif personality_choice < probability_1 + probability_2:  # 第二种人格
             prompt_personality = f'''{activate_prompt}你的网名叫{global_config.BOT_NICKNAME}，{personality[1]}, 你正在浏览qq群，{promt_info_prompt},
-            现在请你给出日常且口语化的回复，请表现你自己的见解，不要一昧迎合，尽量简短一些。{is_bot_prompt}
+            现在请你给出日常且口语化的回复，请表现你自己的见解，不要一昧迎合，尽量简短一些。{keywords_reaction_prompt}
             请你表达自己的见解和观点。可以有个性。'''
         else:  # 第三种人格
             prompt_personality = f'''{activate_prompt}你的网名叫{global_config.BOT_NICKNAME}，{personality[2]}, 你正在浏览qq群，{promt_info_prompt},
-            现在请你给出日常且口语化的回复，请表现你自己的见解，不要一昧迎合，尽量简短一些。{is_bot_prompt}
+            现在请你给出日常且口语化的回复，请表现你自己的见解，不要一昧迎合，尽量简短一些。{keywords_reaction_prompt}
             请你表达自己的见解和观点。可以有个性。'''
         
         #中文高手(新加的好玩功能)

src/plugins/chat/utils.py

@@ -12,6 +12,7 @@ from ..models.utils_model import LLM_request
 from ..utils.typo_generator import ChineseTypoGenerator
 from .config import global_config
 from .message import Message
+from ..moods.moods import MoodManager
 
 driver = get_driver()
 config = driver.config
@@ -326,40 +327,68 @@ def random_remove_punctuation(text: str) -> str:
 
 def process_llm_response(text: str) -> List[str]:
     # processed_response = process_text_with_typos(content)
-    if len(text) > 300:
+    if len(text) > 200:
         print(f"回复过长 ({len(text)} 字符)，返回默认回复")
         return ['懒得说']
     # 处理长消息
     typo_generator = ChineseTypoGenerator(
-        error_rate=0.03,
+        error_rate=global_config.chinese_typo_error_rate,
-        min_freq=7,
+        min_freq=global_config.chinese_typo_min_freq,
-        tone_error_rate=0.2,
+        tone_error_rate=global_config.chinese_typo_tone_error_rate,
-        word_replace_rate=0.02
+        word_replace_rate=global_config.chinese_typo_word_replace_rate
     )
-    typoed_text = typo_generator.create_typo_sentence(text)[0]
+    split_sentences = split_into_sentences_w_remove_punctuation(text)
-    sentences = split_into_sentences_w_remove_punctuation(typoed_text)
+    sentences = []
+    for sentence in split_sentences:
+        if global_config.chinese_typo_enable:
+            typoed_text, typo_corrections = typo_generator.create_typo_sentence(sentence)
+            sentences.append(typoed_text)
+            if typo_corrections:
+                sentences.append(typo_corrections)
+        else:
+            sentences.append(sentence)
     # 检查分割后的消息数量是否过多（超过3条）
-    if len(sentences) > 4:
+    
+    if len(sentences) > 5:
         print(f"分割后消息数量过多 ({len(sentences)} 条)，返回默认回复")
         return [f'{global_config.BOT_NICKNAME}不知道哦']
 
     return sentences
 
 
-def calculate_typing_time(input_string: str, chinese_time: float = 0.2, english_time: float = 0.1) -> float:
+def calculate_typing_time(input_string: str, chinese_time: float = 0.4, english_time: float = 0.2) -> float:
     """
     计算输入字符串所需的时间，中文和英文字符有不同的输入时间
         input_string (str): 输入的字符串
-        chinese_time (float): 中文字符的输入时间，默认为0.3秒
+        chinese_time (float): 中文字符的输入时间，默认为0.2秒
-        english_time (float): 英文字符的输入时间，默认为0.15秒
+        english_time (float): 英文字符的输入时间，默认为0.1秒
+        
+    特殊情况：
+    - 如果只有一个中文字符，将使用3倍的中文输入时间
+    - 在所有输入结束后，额外加上回车时间0.3秒
     """
+    mood_manager = MoodManager.get_instance()
+    # 将0-1的唤醒度映射到-1到1
+    mood_arousal = mood_manager.current_mood.arousal
+    # 映射到0.5到2倍的速度系数
+    typing_speed_multiplier = 1.5 ** mood_arousal  # 唤醒度为1时速度翻倍,为-1时速度减半
+    chinese_time *= 1/typing_speed_multiplier
+    english_time *= 1/typing_speed_multiplier
+    # 计算中文字符数
+    chinese_chars = sum(1 for char in input_string if '\u4e00' <= char <= '\u9fff')
+    
+    # 如果只有一个中文字符，使用3倍时间
+    if chinese_chars == 1 and len(input_string.strip()) == 1:
+        return chinese_time * 3 + 0.3  # 加上回车时间
+        
+    # 正常计算所有字符的输入时间
     total_time = 0.0
     for char in input_string:
         if '\u4e00' <= char <= '\u9fff':  # 判断是否为中文字符
             total_time += chinese_time
         else:  # 其他字符（如英文）
             total_time += english_time
-    return total_time
+    return total_time + 0.3  # 加上回车时间
 
 
 def cosine_similarity(v1, v2):

src/plugins/models/utils_model.py

@@ -23,6 +23,7 @@ class LLM_request:
             self.api_key = getattr(config, model["key"])
             self.base_url = getattr(config, model["base_url"])
         except AttributeError as e:
+            logger.error(f"原始 model dict 信息：{model}")
             logger.error(f"配置错误：找不到对应的配置项 - {str(e)}")
             raise ValueError(f"配置错误：找不到对应的配置项 - {str(e)}") from e
         self.model_name = model["name"]
@@ -181,6 +182,13 @@ class LLM_request:
                             continue
                         elif response.status in policy["abort_codes"]:
                             logger.error(f"错误码: {response.status} - {error_code_mapping.get(response.status)}")
+                            if response.status == 403 :
+                                if global_config.llm_normal == "Pro/deepseek-ai/DeepSeek-V3":
+                                    logger.error("可能是没有给硅基流动充钱，普通模型自动退化至非Pro模型，反应速度可能会变慢")
+                                    global_config.llm_normal = "deepseek-ai/DeepSeek-V3"
+                                if global_config.llm_reasoning == "Pro/deepseek-ai/DeepSeek-R1":
+                                    logger.error("可能是没有给硅基流动充钱，推理模型自动退化至非Pro模型，反应速度可能会变慢")
+                                    global_config.llm_reasoning = "deepseek-ai/DeepSeek-R1"
                             raise RuntimeError(f"请求被拒绝: {error_code_mapping.get(response.status)}")
                             
                         response.raise_for_status()

src/plugins/utils/typo_generator.py

@@ -284,10 +284,13 @@ class ChineseTypoGenerator:
             
         返回:
             typo_sentence: 包含错别字的句子
-            typo_info: 错别字信息列表
+            correction_suggestion: 随机选择的一个纠正建议，返回正确的字/词
         """
         result = []
         typo_info = []
+        word_typos = []  # 记录词语错误对(错词,正确词)
+        char_typos = []  # 记录单字错误对(错字,正确字)
+        current_pos = 0
         
         # 分词
         words = self._segment_sentence(sentence)
@@ -296,6 +299,7 @@ class ChineseTypoGenerator:
             # 如果是标点符号或空格，直接添加
             if all(not self._is_chinese_char(c) for c in word):
                 result.append(word)
+                current_pos += len(word)
                 continue
                 
             # 获取词语的拼音
@@ -316,6 +320,8 @@ class ChineseTypoGenerator:
                                     ' '.join(word_pinyin), 
                                     ' '.join(self._get_word_pinyin(typo_word)), 
                                     orig_freq, typo_freq))
+                    word_typos.append((typo_word, word))  # 记录(错词,正确词)对
+                    current_pos += len(typo_word)
                     continue
             
             # 如果不进行整词替换，则进行单字替换
@@ -333,11 +339,15 @@ class ChineseTypoGenerator:
                             result.append(typo_char)
                             typo_py = pinyin(typo_char, style=Style.TONE3)[0][0]
                             typo_info.append((char, typo_char, py, typo_py, orig_freq, typo_freq))
+                            char_typos.append((typo_char, char))  # 记录(错字,正确字)对
+                            current_pos += 1
                             continue
                 result.append(char)
+                current_pos += 1
             else:
                 # 处理多字词的单字替换
                 word_result = []
+                word_start_pos = current_pos
                 for i, (char, py) in enumerate(zip(word, word_pinyin)):
                     # 词中的字替换概率降低
                     word_error_rate = self.error_rate * (0.7 ** (len(word) - 1))
@@ -353,11 +363,24 @@ class ChineseTypoGenerator:
                                 word_result.append(typo_char)
                                 typo_py = pinyin(typo_char, style=Style.TONE3)[0][0]
                                 typo_info.append((char, typo_char, py, typo_py, orig_freq, typo_freq))
+                                char_typos.append((typo_char, char))  # 记录(错字,正确字)对
                                 continue
                     word_result.append(char)
                 result.append(''.join(word_result))
+                current_pos += len(word)
         
-        return ''.join(result), typo_info
+        # 优先从词语错误中选择，如果没有则从单字错误中选择
+        correction_suggestion = None
+        # 50%概率返回纠正建议
+        if random.random() < 0.5:
+            if word_typos:
+                wrong_word, correct_word = random.choice(word_typos)
+                correction_suggestion = correct_word
+            elif char_typos:
+                wrong_char, correct_char = random.choice(char_typos)
+                correction_suggestion = correct_char
+        
+        return ''.join(result), correction_suggestion
 
     def format_typo_info(self, typo_info):
         """
@@ -419,16 +442,16 @@ def main():
     
     # 创建包含错别字的句子
     start_time = time.time()
-    typo_sentence, typo_info = typo_generator.create_typo_sentence(sentence)
+    typo_sentence, correction_suggestion = typo_generator.create_typo_sentence(sentence)
     
     # 打印结果
     print("\n原句：", sentence)
     print("错字版：", typo_sentence)
     
-    # 打印错别字信息
+    # 打印纠正建议
-    if typo_info:
+    if correction_suggestion:
-        print("\n错别字信息：")
+        print("\n随机纠正建议：")
-        print(typo_generator.format_typo_info(typo_info))
+        print(f"应该改为：{correction_suggestion}")
     
     # 计算并打印总耗时
     end_time = time.time()

template/bot_config_template.toml

@@ -1,3 +1,6 @@
+[inner]
+version = "0.0.3"
+
 [bot]
 qq = 123
 nickname = "麦麦"
@@ -51,6 +54,26 @@ mood_update_interval = 1.0 # 情绪更新间隔 单位秒
 mood_decay_rate = 0.95 # 情绪衰减率
 mood_intensity_factor = 1.0 # 情绪强度因子
 
+[keywords_reaction] # 针对某个关键词作出反应
+enable = true  # 关键词反应功能的总开关
+
+[[keywords_reaction.rules]] # 如果想要新增多个关键词，直接复制本条，修改keywords和reaction即可
+enable = true # 是否启用此条（为了人类在未来AI战争能更好地识别AI（bushi），默认开启）
+keywords = ["人机", "bot", "机器", "入机", "robot", "机器人"] # 会触发反应的关键词
+reaction = "有人说你是人机或者机器人，否定这一事实，攻击或反问他。注意，只有认为你是机器人才回复，否则不要否认" # 触发之后添加的提示词
+
+[[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”"
+
+[chinese_typo]
+enable = true # 是否启用中文错别字生成器
+error_rate=0.03 # 单字替换概率
+min_freq=7 # 最小字频阈值
+tone_error_rate=0.2 # 声调错误概率
+word_replace_rate=0.02 # 整词替换概率
+
 [others]
 enable_advance_output = true # 是否启用高级输出
 enable_kuuki_read = true # 是否启用读空气功能
@@ -80,49 +103,42 @@ ban_user_id = []  #禁止回复消息的QQ号
 
 [model.llm_reasoning] #回复模型1 主要回复模型
 name = "Pro/deepseek-ai/DeepSeek-R1"
-base_url = "SILICONFLOW_BASE_URL"
+provider = "SILICONFLOW"
-key = "SILICONFLOW_KEY"
 pri_in = 0 #模型的输入价格（非必填，可以记录消耗）
 pri_out = 0 #模型的输出价格（非必填，可以记录消耗）
 
+
 [model.llm_reasoning_minor] #回复模型3 次要回复模型
 name = "deepseek-ai/DeepSeek-R1-Distill-Qwen-32B"
-base_url = "SILICONFLOW_BASE_URL"
+provider = "SILICONFLOW"
-key = "SILICONFLOW_KEY"
 
 #非推理模型
 
 [model.llm_normal] #V3 回复模型2 次要回复模型
 name = "Pro/deepseek-ai/DeepSeek-V3"
-base_url = "SILICONFLOW_BASE_URL"
+provider = "SILICONFLOW"
-key = "SILICONFLOW_KEY"
 
 [model.llm_normal_minor] #V2.5
 name = "deepseek-ai/DeepSeek-V2.5"
-base_url = "SILICONFLOW_BASE_URL"
+provider = "SILICONFLOW"
-key = "SILICONFLOW_KEY"
 
 [model.llm_emotion_judge] #主题判断 0.7/m
 name = "Qwen/Qwen2.5-14B-Instruct"
-base_url = "SILICONFLOW_BASE_URL"
+provider = "SILICONFLOW"
-key = "SILICONFLOW_KEY"
 
 [model.llm_topic_judge] #主题判断：建议使用qwen2.5 7b
 name = "Pro/Qwen/Qwen2.5-7B-Instruct"
-base_url = "SILICONFLOW_BASE_URL"
+provider = "SILICONFLOW"
-key = "SILICONFLOW_KEY"
 
 [model.llm_summary_by_topic] #建议使用qwen2.5 32b 及以上
 name = "Qwen/Qwen2.5-32B-Instruct"
-base_url = "SILICONFLOW_BASE_URL"
+provider = "SILICONFLOW"
-key = "SILICONFLOW_KEY"
 pri_in = 0
 pri_out = 0
 
 [model.moderation] #内容审核 未启用
 name = ""
-base_url = "SILICONFLOW_BASE_URL"
+provider = "SILICONFLOW"
-key = "SILICONFLOW_KEY"
 pri_in = 0
 pri_out = 0
 
@@ -130,8 +146,7 @@ pri_out = 0
 
 [model.vlm] #图像识别 0.35/m
 name = "Pro/Qwen/Qwen2-VL-7B-Instruct"
-base_url = "SILICONFLOW_BASE_URL"
+provider = "SILICONFLOW"
-key = "SILICONFLOW_KEY"
 
 
 
@@ -139,5 +154,4 @@ key = "SILICONFLOW_KEY"
 
 [model.embedding] #嵌入
 name = "BAAI/bge-m3"
-base_url = "SILICONFLOW_BASE_URL"
+provider = "SILICONFLOW"
-key = "SILICONFLOW_KEY"