import os
from dataclasses import dataclass, field
from pathlib import Path

from dotenv import load_dotenv

load_dotenv(Path(__file__).resolve().parent.parent / ".env")


@dataclass(frozen=True)
class Settings:
    # LLM 配置
    llm_api_key: str = field(
        default_factory=lambda: os.getenv("LLM_API_KEY", ""),
        repr=False,
    )
    llm_model: str = field(default_factory=lambda: os.getenv("LLM_MODEL", ""))
    llm_base_url: str | None = field(
        default_factory=lambda: os.getenv("LLM_BASE_URL") or None
    )
    llm_timeout: float = 60.0
    llm_max_retries: int = 2

    # Jev
    typesafe_api_key: str = field(
        default_factory=lambda: os.getenv("TYPESAFE_API_KEY", ""), repr=False
    )
    typesafe_model: str = field(
        default_factory=lambda: os.getenv("TYPESAFE_DEFAULT_MODEL") or "jev-latest"
    )
    typesafe_base_url: str = field(
        default_factory=lambda: (
            os.getenv("TYPESAFE_BASE_URL") or "https://api.typesafe.ai"
        )
    )
    typesafe_timeout: float = field(
        default_factory=lambda: float(os.getenv("TYPESAFE_TIMEOUT", "30"))
    )
    typesafe_max_retries: int = field(
        default_factory=lambda: int(os.getenv("TYPESAFE_MAX_RETRIES", "2"))
    )

    # 意图门控使用 Jev confidence，阈值需按真实语料校准
    intent_min_confidence: float = field(
        default_factory=lambda: float(os.getenv("INTENT_MIN_CONFIDENCE", "0.7"))
    )

    def __post_init__(self):
        if not 0 <= self.intent_min_confidence <= 1:
            raise ValueError("INTENT_MIN_CONFIDENCE 必须在 0 到 1 之间")


settings = Settings()