262 lines
11 KiB
Python
262 lines
11 KiB
Python
from functools import lru_cache
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from pathlib import Path
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from typing import Optional
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from pydantic import AliasChoices, AnyUrl, Field, HttpUrl, validator
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from pydantic_settings import BaseSettings, SettingsConfigDict
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from sqlalchemy.engine import URL, make_url
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class Settings(BaseSettings):
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"""应用全局配置，所有可调参数集中于此，统一加载自环境变量。"""
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# -------------------- 基础应用配置 --------------------
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app_name: str = Field(default="AI Novel Generator API", description="FastAPI 文档标题")
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environment: str = Field(default="development", description="当前环境标识")
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debug: bool = Field(default=True, description="是否开启调试模式")
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allow_registration: bool = Field(
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default=True,
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env="ALLOW_USER_REGISTRATION",
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description="是否允许用户自助注册",
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)
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logging_level: str = Field(
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default="INFO",
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env="LOGGING_LEVEL",
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description="应用日志级别",
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)
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enable_linuxdo_login: bool = Field(
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default=False,
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env="ENABLE_LINUXDO_LOGIN",
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description="是否启用 Linux.do OAuth 登录",
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)
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# -------------------- 安全相关配置 --------------------
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secret_key: str = Field(..., env="SECRET_KEY", description="JWT 加密密钥")
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jwt_algorithm: str = Field(default="HS256", env="JWT_ALGORITHM", description="JWT 加密算法")
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access_token_expire_minutes: int = Field(
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default=60 * 24 * 7,
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env="ACCESS_TOKEN_EXPIRE_MINUTES",
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description="访问令牌过期时间，单位分钟"
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)
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# -------------------- 数据库配置 --------------------
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database_url: Optional[str] = Field(
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default=None,
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env="DATABASE_URL",
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description="完整的数据库连接串，填入后覆盖下方数据库配置"
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)
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db_provider: str = Field(
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default="mysql",
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env="DB_PROVIDER",
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description="数据库类型，仅支持 mysql 或 sqlite"
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)
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mysql_host: str = Field(default="localhost", env="MYSQL_HOST", description="MySQL 主机名")
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mysql_port: int = Field(default=3306, env="MYSQL_PORT", description="MySQL 端口")
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mysql_user: str = Field(default="root", env="MYSQL_USER", description="MySQL 用户名")
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mysql_password: str = Field(default="", env="MYSQL_PASSWORD", description="MySQL 密码")
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mysql_database: str = Field(default="arboris", env="MYSQL_DATABASE", description="MySQL 数据库名称")
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# -------------------- 管理员初始化配置 --------------------
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admin_default_username: str = Field(default="admin", env="ADMIN_DEFAULT_USERNAME", description="默认管理员用户名")
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admin_default_password: str = Field(default="ChangeMe123!", env="ADMIN_DEFAULT_PASSWORD", description="默认管理员密码")
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admin_default_email: Optional[str] = Field(default=None, env="ADMIN_DEFAULT_EMAIL", description="默认管理员邮箱")
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# -------------------- LLM 相关配置 --------------------
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openai_api_key: Optional[str] = Field(default=None, env="OPENAI_API_KEY", description="默认的 LLM API Key")
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openai_base_url: Optional[HttpUrl] = Field(
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default=None,
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env="OPENAI_API_BASE_URL",
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validation_alias=AliasChoices("OPENAI_API_BASE_URL", "OPENAI_BASE_URL"),
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description="LLM API Base URL",
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)
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openai_model_name: str = Field(default="gpt-4o-mini", env="OPENAI_MODEL_NAME", description="默认 LLM 模型名称")
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writer_chapter_versions: int = Field(
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default=2,
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ge=1,
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env="WRITER_CHAPTER_VERSION_COUNT",
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validation_alias=AliasChoices("WRITER_CHAPTER_VERSION_COUNT", "WRITER_CHAPTER_VERSIONS"),
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description="每次生成章节的候选版本数量",
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)
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embedding_provider: str = Field(
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default="openai",
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env="EMBEDDING_PROVIDER",
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description="嵌入模型提供方，支持 openai 或 ollama",
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)
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embedding_base_url: Optional[AnyUrl] = Field(
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default=None,
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env="EMBEDDING_BASE_URL",
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description="嵌入模型使用的 Base URL",
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)
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embedding_api_key: Optional[str] = Field(
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default=None,
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env="EMBEDDING_API_KEY",
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description="嵌入模型专用 API Key",
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)
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embedding_model: str = Field(
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default="text-embedding-3-large",
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env="EMBEDDING_MODEL",
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validation_alias=AliasChoices("EMBEDDING_MODEL", "VECTOR_EMBEDDING_MODEL"),
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description="默认的嵌入模型名称",
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)
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embedding_model_vector_size: Optional[int] = Field(
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default=None,
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env="EMBEDDING_MODEL_VECTOR_SIZE",
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description="嵌入向量维度，未配置时将自动检测",
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)
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ollama_embedding_base_url: Optional[AnyUrl] = Field(
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default=None,
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env="OLLAMA_EMBEDDING_BASE_URL",
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description="Ollama 嵌入模型服务地址",
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)
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ollama_embedding_model: str = Field(
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default="nomic-embed-text:latest",
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env="OLLAMA_EMBEDDING_MODEL",
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description="Ollama 嵌入模型名称",
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)
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vector_db_url: Optional[str] = Field(
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default=None,
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env="VECTOR_DB_URL",
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description="libsql 向量库连接地址",
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)
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vector_db_auth_token: Optional[str] = Field(
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default=None,
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env="VECTOR_DB_AUTH_TOKEN",
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description="libsql 访问令牌",
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)
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vector_top_k_chunks: int = Field(
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default=5,
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ge=0,
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env="VECTOR_TOP_K_CHUNKS",
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description="剧情 chunk 检索条数",
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)
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vector_top_k_summaries: int = Field(
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default=3,
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ge=0,
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env="VECTOR_TOP_K_SUMMARIES",
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description="章节摘要检索条数",
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)
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vector_chunk_size: int = Field(
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default=480,
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ge=128,
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env="VECTOR_CHUNK_SIZE",
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description="章节分块的目标字数",
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)
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vector_chunk_overlap: int = Field(
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default=120,
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ge=0,
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env="VECTOR_CHUNK_OVERLAP",
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description="章节分块重叠字数",
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)
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# -------------------- Linux.do OAuth 配置 --------------------
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linuxdo_client_id: Optional[str] = Field(default=None, env="LINUXDO_CLIENT_ID", description="Linux.do OAuth Client ID")
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linuxdo_client_secret: Optional[str] = Field(
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default=None, env="LINUXDO_CLIENT_SECRET", description="Linux.do OAuth Client Secret"
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)
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linuxdo_redirect_uri: Optional[HttpUrl] = Field(
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default=None, env="LINUXDO_REDIRECT_URI", description="Linux.do OAuth 回调地址"
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)
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linuxdo_auth_url: Optional[HttpUrl] = Field(
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default=None, env="LINUXDO_AUTH_URL", description="Linux.do OAuth 授权地址"
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)
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linuxdo_token_url: Optional[HttpUrl] = Field(
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default=None, env="LINUXDO_TOKEN_URL", description="Linux.do OAuth Token 获取地址"
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)
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linuxdo_user_info_url: Optional[HttpUrl] = Field(
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default=None, env="LINUXDO_USER_INFO_URL", description="Linux.do 用户信息接口地址"
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)
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# -------------------- 邮件配置 --------------------
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smtp_server: Optional[str] = Field(default=None, env="SMTP_SERVER", description="SMTP 服务地址")
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smtp_port: int = Field(default=587, env="SMTP_PORT", description="SMTP 服务端口")
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smtp_username: Optional[str] = Field(default=None, env="SMTP_USERNAME", description="SMTP 登录用户名")
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smtp_password: Optional[str] = Field(default=None, env="SMTP_PASSWORD", description="SMTP 登录密码")
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email_from: Optional[str] = Field(default=None, env="EMAIL_FROM", description="邮件发送方显示名或邮箱")
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model_config = SettingsConfigDict(
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env_file=("new-backend/.env", ".env", "backend/.env"),
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env_file_encoding="utf-8",
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extra="ignore"
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)
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@validator("database_url", pre=True, always=True)
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def _normalize_database_url(cls, value: Optional[str]) -> Optional[str]:
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"""当环境变量中提供 DATABASE_URL 时，原样返回，便于自定义。"""
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return value.strip() if isinstance(value, str) and value.strip() else value
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@validator("db_provider", pre=True)
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def _normalize_db_provider(cls, value: Optional[str]) -> str:
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"""统一数据库类型大小写，并限制为受支持的驱动。"""
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candidate = (value or "mysql").strip().lower()
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if candidate not in {"mysql", "sqlite"}:
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raise ValueError("DB_PROVIDER 仅支持 mysql 或 sqlite")
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return candidate
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@validator("embedding_provider", pre=True)
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def _normalize_embedding_provider(cls, value: Optional[str]) -> str:
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"""限制嵌入模型提供方的取值范围。"""
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candidate = (value or "openai").strip().lower()
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if candidate not in {"openai", "ollama"}:
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raise ValueError("EMBEDDING_PROVIDER 仅支持 openai 或 ollama")
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return candidate
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@validator("logging_level", pre=True)
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def _normalize_logging_level(cls, value: Optional[str]) -> str:
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"""规范日志级别配置。"""
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candidate = (value or "INFO").strip().upper()
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valid_levels = {"CRITICAL", "ERROR", "WARNING", "INFO", "DEBUG", "NOTSET"}
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if candidate not in valid_levels:
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raise ValueError("LOGGING_LEVEL 仅支持 CRITICAL/ERROR/WARNING/INFO/DEBUG/NOTSET")
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return candidate
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@property
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def sqlalchemy_database_uri(self) -> str:
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"""生成 SQLAlchemy 兼容的异步连接串，数据库类型由 DB_PROVIDER 控制。"""
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if self.database_url:
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url = make_url(self.database_url)
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database = (url.database or "").strip("/")
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normalized = URL.create(
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drivername=url.drivername,
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username=url.username,
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password=url.password,
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host=url.host,
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port=url.port,
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database=database or None,
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query=url.query,
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)
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return normalized.render_as_string(hide_password=False)
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if self.db_provider == "sqlite":
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# SQLite 固定使用 storage/arboris.db，并转换为绝对路径以避免运行目录差异
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project_root = Path(__file__).resolve().parents[2]
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db_path = (project_root / "storage" / "arboris.db").resolve()
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return f"sqlite+aiosqlite:///{db_path}"
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# MySQL 分支：统一对密码进行 URL 编码，避免特殊字符破坏连接串
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from urllib.parse import quote_plus
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encoded_password = quote_plus(self.mysql_password)
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database = (self.mysql_database or "").strip("/")
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return (
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f"mysql+asyncmy://{self.mysql_user}:{encoded_password}"
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f"@{self.mysql_host}:{self.mysql_port}/{database}"
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)
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@property
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def is_sqlite_backend(self) -> bool:
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"""辅助属性：判断当前连接串是否指向 SQLite，用于差异化初始化流程。"""
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return make_url(self.sqlalchemy_database_uri).get_backend_name() == "sqlite"
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@property
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def vector_store_enabled(self) -> bool:
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"""是否已经配置向量库，用于在业务逻辑中快速判断。"""
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return bool(self.vector_db_url)
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@lru_cache
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def get_settings() -> Settings:
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"""使用 LRU 缓存确保配置只初始化一次，减少 IO 与解析开销。"""
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return Settings()
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settings = get_settings()
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