""" 应用配置模块 使用 Pydantic BaseModel 实现配置管理，支持： - 从 TOML 文件加载用户配置 - 仅保存用户修改过的配置项 - 默认配置定义在代码中 """ import os from pathlib import Path from typing import Any import tomli import tomli_w from pydantic import BaseModel, Field from src.config.static.models import ( DEFAULT_CHAT_MODEL_PROVIDERS, DEFAULT_EMBED_MODELS, DEFAULT_RERANKERS, ChatModelProvider, EmbedModelInfo, RerankerInfo, ) from src.utils.logging_config import logger class Config(BaseModel): """应用配置类""" # ============================================================ # 基础配置 # ============================================================ save_dir: str = Field(default="saves", description="保存目录") model_dir: str = Field(default="", description="本地模型目录") # ============================================================ # 功能开关 # ============================================================ enable_reranker: bool = Field(default=False, description="是否开启重排序") enable_content_guard: bool = Field(default=False, description="是否启用内容审查") enable_content_guard_llm: bool = Field(default=False, description="是否启用LLM内容审查") enable_web_search: bool = Field(default=False, description="是否启用网络搜索") # ============================================================ # 模型配置 # ============================================================ default_model: str = Field( default="siliconflow/deepseek-ai/DeepSeek-V3.2-Exp", description="默认对话模型", ) fast_model: str = Field( default="siliconflow/THUDM/GLM-4-9B-0414", description="快速响应模型", ) embed_model: str = Field( default="siliconflow/BAAI/bge-m3", description="Embedding 模型", ) reranker: str = Field( default="siliconflow/BAAI/bge-reranker-v2-m3", description="Re-Ranker 模型", ) content_guard_llm_model: str = Field( default="siliconflow/Qwen/Qwen3-235B-A22B-Instruct-2507", description="内容审查LLM模型", ) # ============================================================ # 智能体配置 # ============================================================ default_agent_id: str = Field(default="", description="默认智能体ID") # ============================================================ # 模型信息（只读，不持久化） # ============================================================ model_names: dict[str, ChatModelProvider] = Field( default_factory=lambda: DEFAULT_CHAT_MODEL_PROVIDERS.copy(), description="聊天模型提供商配置", exclude=True, ) embed_model_names: dict[str, EmbedModelInfo] = Field( default_factory=lambda: DEFAULT_EMBED_MODELS.copy(), description="嵌入模型配置", exclude=True, ) reranker_names: dict[str, RerankerInfo] = Field( default_factory=lambda: DEFAULT_RERANKERS.copy(), description="重排序模型配置", exclude=True, ) # ============================================================ # 运行时状态（不持久化） # ============================================================ model_provider_status: dict[str, bool] = Field( default_factory=dict, description="模型提供商可用状态", exclude=True, ) valuable_model_provider: list[str] = Field( default_factory=list, description="可用的模型提供商列表", exclude=True, ) # 内部状态 _config_file: Path | None = None _user_modified_fields: set[str] = set() _modified_providers: set[str] = set() # 记录具体修改的模型提供商 model_config = {"arbitrary_types_allowed": True, "extra": "allow"} def __init__(self, **data): super().__init__(**data) self._setup_paths() self._load_user_config() self._handle_environment() def _setup_paths(self): """设置配置文件路径""" self.save_dir = os.getenv("SAVE_DIR", self.save_dir) self._config_file = Path(self.save_dir) / "config" / "base.toml" self._config_file.parent.mkdir(parents=True, exist_ok=True) def _load_user_config(self): """从 TOML 文件加载用户配置""" if not self._config_file or not self._config_file.exists(): logger.info(f"Config file not found, using defaults: {self._config_file}") return logger.info(f"Loading config from {self._config_file}") try: with open(self._config_file, "rb") as f: user_config = tomli.load(f) # 记录用户修改的字段 self._user_modified_fields = set(user_config.keys()) # 更新配置 for key, value in user_config.items(): if key == "model_names": # 特殊处理模型配置 self._load_model_names(value) elif hasattr(self, key): setattr(self, key, value) else: logger.warning(f"Unknown config key: {key}") except Exception as e: logger.error(f"Failed to load config from {self._config_file}: {e}") def _load_model_names(self, model_names_data): """加载用户自定义的模型配置""" try: for provider, provider_data in model_names_data.items(): if provider in self.model_names: # 更新现有提供商的模型列表 if "models" in provider_data: self.model_names[provider].models = provider_data["models"] else: # 添加新的提供商 self.model_names[provider] = ChatModelProvider(**provider_data) logger.info(f"Loaded custom model configurations for {len(model_names_data)} providers") except Exception as e: logger.error(f"Failed to load model names: {e}") def _handle_environment(self): """处理环境变量和运行时状态""" # 处理模型目录 self.model_dir = os.environ.get("MODEL_DIR", self.model_dir) if self.model_dir: if os.path.exists(self.model_dir): logger.debug(f"Model directory ({self.model_dir}) contains: {os.listdir(self.model_dir)}") else: logger.warning( f"Model directory ({self.model_dir}) does not exist. If not configured, please ignore it." ) # 检查模型提供商的环境变量 self.model_provider_status = {} for provider, info in self.model_names.items(): env_var = info.env if env_var == "NO_API_KEY": self.model_provider_status[provider] = True else: self.model_provider_status[provider] = bool(os.getenv(env_var)) # 检查网络搜索 if os.getenv("TAVILY_API_KEY"): self.enable_web_search = True # 获取可用的模型提供商 self.valuable_model_provider = [k for k, v in self.model_provider_status.items() if v] if not self.valuable_model_provider: raise ValueError("No model provider available, please check your `.env` file.") def save(self): """保存配置到 TOML 文件（仅保存用户修改的字段）""" if not self._config_file: logger.warning("Config file path not set") return logger.info(f"Saving config to {self._config_file}") # 获取默认配置 default_config = Config.model_construct() # 对比当前配置和默认配置，找出用户修改的字段 user_modified = {} for field_name in self.model_fields.keys(): # 跳过 exclude=True 的字段 field_info = self.model_fields[field_name] if field_info.exclude: continue current_value = getattr(self, field_name) default_value = getattr(default_config, field_name) # 如果值不同，说明用户修改了 if current_value != default_value: user_modified[field_name] = current_value # 写入 TOML 文件 try: with open(self._config_file, "wb") as f: tomli_w.dump(user_modified, f) logger.info(f"Config saved to {self._config_file}") except Exception as e: logger.error(f"Failed to save config to {self._config_file}: {e}") def dump_config(self) -> dict[str, Any]: """导出配置为字典（用于 API 返回）""" config_dict = self.model_dump( exclude={ "model_names", "embed_model_names", "reranker_names", "model_provider_status", "valuable_model_provider", } ) # 添加模型信息（转换为字典格式供前端使用） config_dict["model_names"] = {provider: info.model_dump() for provider, info in self.model_names.items()} config_dict["embed_model_names"] = { model_id: info.model_dump() for model_id, info in self.embed_model_names.items() } config_dict["reranker_names"] = {model_id: info.model_dump() for model_id, info in self.reranker_names.items()} # 添加运行时状态信息 config_dict["model_provider_status"] = self.model_provider_status config_dict["valuable_model_provider"] = self.valuable_model_provider fields_info = {} for field_name, field_info in Config.model_fields.items(): if not field_info.exclude: # 排除内部字段 fields_info[field_name] = { "des": field_info.description, "default": field_info.default, "type": field_info.annotation.__name__ if hasattr(field_info.annotation, "__name__") else str(field_info.annotation), "exclude": field_info.exclude if hasattr(field_info, "exclude") else False, } config_dict["_config_items"] = fields_info return config_dict def get_model_choices(self) -> list[str]: """获取所有可用的聊天模型列表""" choices = [] for provider, info in self.model_names.items(): if self.model_provider_status.get(provider, False): for model in info.models: choices.append(f"{provider}/{model}") return choices def get_embed_model_choices(self) -> list[str]: """获取所有可用的嵌入模型列表""" return list(self.embed_model_names.keys()) def get_reranker_choices(self) -> list[str]: """获取所有可用的重排序模型列表""" return list(self.reranker_names.keys()) # ============================================================ # 兼容旧代码的方法 # ============================================================ def __getitem__(self, key: str) -> Any: """支持字典式访问 config[key]""" logger.warning("Using deprecated dict-style access for Config. Please use attribute access instead.") return getattr(self, key, None) def __setitem__(self, key: str, value: Any): """支持字典式赋值 config[key] = value""" logger.warning("Using deprecated dict-style assignment for Config. Please use attribute access instead.") setattr(self, key, value) def update(self, other: dict): """批量更新配置（兼容旧代码）""" for key, value in other.items(): if hasattr(self, key): setattr(self, key, value) else: logger.warning(f"Unknown config key: {key}") def _save_models_to_file(self, provider_name: str = None): """保存模型配置到主配置文件 Args: provider_name: 如果提供，只保存特定provider的修改；否则保存所有model_names """ if not self._config_file: logger.warning("Config file path not set") return logger.info(f"Saving models config to {self._config_file}") try: # 读取现有配置 user_config = {} if self._config_file.exists(): with open(self._config_file, "rb") as f: user_config = tomli.load(f) # 初始化 model_names 配置（如果不存在） if "model_names" not in user_config: user_config["model_names"] = {} if provider_name: # 只保存特定 provider 的修改 if provider_name in self.model_names: user_config["model_names"][provider_name] = self.model_names[provider_name].model_dump() # 记录具体修改的 provider self._modified_providers.add(provider_name) logger.info(f"Saved models config for provider: {provider_name}") else: # 保存所有 model_names user_config["model_names"] = { provider: info.model_dump() for provider, info in self.model_names.items() } # 记录整个 model_names 字段的修改 self._user_modified_fields.add("model_names") logger.info("Saved all models config") # 写入配置文件 with open(self._config_file, "wb") as f: tomli_w.dump(user_config, f) logger.info(f"Models config saved to {self._config_file}") except Exception as e: logger.error(f"Failed to save models config to {self._config_file}: {e}") # 全局配置实例 config = Config()