Merge branch 'SengokuCola:debug' into debug

bot.py

@@ -1,88 +1,142 @@
 import os
-
+import shutil
 import nonebot
 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}
 
-init()
+def easter_egg():
-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"
+    # 彩蛋
-rainbow_colors = [Fore.RED, Fore.YELLOW, Fore.GREEN, Fore.CYAN, Fore.BLUE, Fore.MAGENTA]
+    from colorama import init, Fore
-rainbow_text = ""
-for i, char in enumerate(text):
-    rainbow_text += rainbow_colors[i % len(rainbow_colors)] + char
-print(rainbow_text)
-'''彩蛋'''
 
-# 初次启动检测
+    init()
-if not os.path.exists("config/bot_config.toml"):
+    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"
-    logger.warning("检测到bot_config.toml不存在，正在从模板复制")
+    rainbow_colors = [Fore.RED, Fore.YELLOW, Fore.GREEN, Fore.CYAN, Fore.BLUE, Fore.MAGENTA]
-    import shutil
+    rainbow_text = ""
-    # 检查config目录是否存在
+    for i, char in enumerate(text):
-    if not os.path.exists("config"):
+        rainbow_text += rainbow_colors[i % len(rainbow_colors)] + char
-        os.makedirs("config")
+    print(rainbow_text)
-        logger.info("创建config目录")
 
-    shutil.copy("template/bot_config_template.toml", "config/bot_config.toml")
+def init_config():
-    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")
+    # 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")
+        
+        # 检查config目录是否存在
+        if not os.path.exists("config"):
+            os.makedirs("config")
+            logger.info("创建config目录")
 
-# 初始化.env 默认ENVIRONMENT=prod
+        shutil.copy("template/bot_config_template.toml", "config/bot_config.toml")
-if not os.path.exists(".env"):
+        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")
-    with open(".env", "w") as f:
-        f.write("ENVIRONMENT=prod")
 
-    # 检测.env.prod文件是否存在
+def init_env():
-    if not os.path.exists(".env.prod"):
+    # 初始化.env 默认ENVIRONMENT=prod
-        logger.error("检测到.env.prod文件不存在")
+    if not os.path.exists(".env"):
-        shutil.copy("template.env", "./.env.prod")
+        with open(".env", "w") as f:
+            f.write("ENVIRONMENT=prod")
 
-# 首先加载基础环境变量.env
+        # 检测.env.prod文件是否存在
-if os.path.exists(".env"):
+        if not os.path.exists(".env.prod"):
-    load_dotenv(".env")
+            logger.error("检测到.env.prod文件不存在")
-    logger.success("成功加载基础环境变量配置")
+            shutil.copy("template.env", "./.env.prod")
 
-# 根据 ENVIRONMENT 加载对应的环境配置
+    # 首先加载基础环境变量.env
-if os.getenv("ENVIRONMENT") == "prod":
+    if os.path.exists(".env"):
-    logger.success("加载生产环境变量配置")
+        load_dotenv(".env")
-    load_dotenv(".env.prod", override=True)  # override=True 允许覆盖已存在的环境变量
+        logger.success("成功加载基础环境变量配置")
-elif os.getenv("ENVIRONMENT") == "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")
-    load_dotenv(f".env.{os.getenv('ENVIRONMENT')}", 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")
-    exit(1)
 
-# 检测Key是否存在
+def load_env():
-if not os.getenv("SILICONFLOW_KEY"):
+    # 使用闭包实现对加载器的横向扩展，避免大量重复判断
-    logger.error("缺失必要的API KEY")
+    def prod():
-    logger.error(f"请至少在.env.{os.getenv('ENVIRONMENT')}文件中填写SILICONFLOW_KEY后重新启动")
+        logger.success("加载生产环境变量配置")
-    exit(1)
+        load_dotenv(".env.prod", override=True)  # override=True 允许覆盖已存在的环境变量
 
-# 获取所有环境变量
+    def dev():
-env_config = {key: os.getenv(key) for key in os.environ}
+        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
 
-# 设置基础配置
+    fn_map = {
-base_config = {
+        "prod": prod,
-    "websocket_port": int(env_config.get("PORT", 8080)),
+        "dev": dev
-    "host": env_config.get("HOST", "127.0.0.1"),
+    }
-    "log_level": "INFO",
-}
 
-# 合并配置
+    env = os.getenv("ENVIRONMENT")
-nonebot.init(**base_config, **env_config)
+    logger.info(f"[load_env] 当前的 ENVIRONMENT 变量值：{env}")
 
-# 注册适配器
+    if env in fn_map:
-driver = nonebot.get_driver()
+        fn_map[env]() # 根据映射执行闭包函数
-driver.register_adapter(Adapter)
 
-# 加载插件
+    elif os.path.exists(f".env.{env}"):
-nonebot.load_plugins("src/plugins")
+        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 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__":
+    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 = {
+        "websocket_port": int(env_config.get("PORT", 8080)),
+        "host": env_config.get("HOST", "127.0.0.1"),
+        "log_level": "INFO",
+    }
+
+    # 合并配置
+    nonebot.init(**base_config, **env_config)
+
+    # 注册适配器
+    driver = nonebot.get_driver()
+    driver.register_adapter(Adapter)
+
+    # 加载插件
+    nonebot.load_plugins("src/plugins")
+
     nonebot.run()

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
     
@@ -87,12 +91,271 @@ class BotConfig:
         if not os.path.exists(config_dir):
             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 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
+            },
+            "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:
@@ -100,136 +363,60 @@ class BotConfig:
                 except(tomli.TOMLDecodeError) as e:
                     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)
+                        # 检查配置文件版本是否在支持范围内
-                config.EMOJI_CHECK = emoji_config.get('enable_check',config.EMOJI_CHECK)
+                        if config.INNER_VERSION in group_specifierset:
-            
+                            # 如果版本在支持范围内，检查是否存在通知
-            if "cq_code" in toml_dict:
+                            if 'notice' in include_configs[key]:
-                cq_code_config = toml_dict["cq_code"]
+                                logger.warning(include_configs[key]["notice"])
-                config.ENABLE_PIC_TRANSLATE = cq_code_config.get("enable_pic_translate", config.ENABLE_PIC_TRANSLATE)
+
-            
+                            include_configs[key]["func"](toml_dict)
-            # 机器人基础配置
+
-            if "bot" in toml_dict:
+                        else:
-                bot_config = toml_dict["bot"]
+                            # 如果版本不在支持范围内，崩溃并提示用户
-                bot_qq = bot_config.get("qq")
+                            logger.error(
-                config.BOT_QQ = int(bot_qq)
+                                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.BOT_NICKNAME = bot_config.get("nickname", config.BOT_NICKNAME)
+                                f"当前程序仅支持以下版本范围: {group_specifierset}"
-                
+                            )
-            if "response" in toml_dict:
+                            raise InvalidVersion(f"当前程序仅支持以下版本范围: {group_specifierset}")
-                response_config = toml_dict["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)
-                
-            # 加载模型配置
-            if "model" in toml_dict:
-                model_config = toml_dict["model"]
-                
-                if "llm_reasoning" in model_config:
-                    config.llm_reasoning = model_config["llm_reasoning"]
-                
-                if "llm_reasoning_minor" in model_config:
-                    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:
+                    # 如果 necessary 项目存在，而且显式声明是 False，进入特殊处理
-                    config.llm_topic_judge = model_config["llm_topic_judge"]
+                    elif "necessary" in include_configs[key] and include_configs[key].get("necessary") == False:
-                
+                        # 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 "llm_summary_by_topic" in model_config:
+                        if key == "keywords_reaction":
-                    config.llm_summary_by_topic = model_config["llm_summary_by_topic"]
+                            pass
-                
-                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:
+                    else:
-                    config.embedding = model_config["embedding"]
+                        # 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 "moderation" in model_config:
+                        raise KeyError(f"配置文件中缺少必需的字段: '{key}'")
-                    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:
+                logger.success(f"成功加载配置文件: {config_path}")
-                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)
-            
-            # print(toml_dict)
-            if "keywords_reaction" in toml_dict:
-                # 读取关键词回复配置
-                keywords_reaction_config = toml_dict["keywords_reaction"]
-                if keywords_reaction_config.get("enable", False):
-                    config.keywords_reaction_rules = keywords_reaction_config.get("rules", config.keywords_reaction_rules)
-
-            # 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/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"]

template/bot_config_template.toml

@@ -1,3 +1,6 @@
+[inner]
+version = "0.0.2"
+
 [bot]
 qq = 123
 nickname = "麦麦"
@@ -93,49 +96,42 @@ 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
 
@@ -143,8 +139,7 @@ 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"
 
 
 
@@ -152,5 +147,4 @@ key = "SILICONFLOW_KEY"
 
 [model.embedding] #嵌入
 name = "BAAI/bge-m3"
-base_url = "SILICONFLOW_BASE_URL"
+provider = "SILICONFLOW"
-key = "SILICONFLOW_KEY"