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"))
    )

    # 意图门控使用选中项自身的概率，阈值需按真实语料校准
    # 新建、修改会改动大屏，阈值较严；问答判错代价低，阈值较宽
    intent_min_probability: float = field(
        default_factory=lambda: float(os.getenv("INTENT_MIN_PROBABILITY", "0.7"))
    )
    intent_qa_min_probability: float = field(
        default_factory=lambda: float(os.getenv("INTENT_QA_MIN_PROBABILITY", "0.5"))
    )
    # 同一问题最多澄清的轮数，用尽后不再追问
    intent_max_clarify_rounds: int = field(
        default_factory=lambda: int(os.getenv("INTENT_MAX_CLARIFY_ROUNDS", "1"))
    )

    # 动作自动修正次数，不含首次生成，0 表示不重试，与用户澄清轮数无关
    max_action_retries: int = field(
        default_factory=lambda: int(os.getenv("MAX_ACTION_RETRIES", "2"))
    )

    # 物料字段 MCP 服务：只给模型查询字段定义，只监听本机，随应用启动
    mcp_material_url: str = field(
        default_factory=lambda: (
            os.getenv("MCP_MATERIAL_URL") or "http://127.0.0.1:8201/mcp"
        )
    )
    # 单次字段查询的超时（秒）
    mcp_tool_timeout: float = field(
        default_factory=lambda: float(os.getenv("MCP_TOOL_TIMEOUT", "5"))
    )
    # 生成动作或修正建议时，最多几轮查询字段，之后必须给出结果
    max_field_tool_rounds: int = field(
        default_factory=lambda: int(os.getenv("MAX_FIELD_TOOL_ROUNDS", "4"))
    )

    # 没有任何对话的空会话保留时长（秒），超时后视为不存在
    conversation_empty_ttl: int = field(
        default_factory=lambda: int(os.getenv("CONVERSATION_EMPTY_TTL", "7200"))
    )
    # 每次请求带入模型的最近对话轮数
    conversation_history_turns: int = field(
        default_factory=lambda: int(os.getenv("CONVERSATION_HISTORY_TURNS", "6"))
    )

    # MongoDB 连接串，未配置时会话记录和检查点回退为进程内存实现
    mongodb_uri: str | None = field(
        default_factory=lambda: os.getenv("MONGODB_URI") or None, repr=False
    )
    mongodb_db: str = field(
        default_factory=lambda: os.getenv("MONGODB_DB") or "screen_agent"
    )
    # 检查点保留时长（秒），超时由 MongoDB TTL 索引清理，0 表示永久保留
    mongodb_checkpoint_ttl: int = field(
        default_factory=lambda: int(os.getenv("MONGODB_CHECKPOINT_TTL", "604800"))
    )

    # 用户中心：请求携带的 token 交给它校验，换回 user_id
    user_center_url: str = field(
        default_factory=lambda: (
            os.getenv("USER_CENTER_URL") or "http://127.0.0.1:8100"
        ).rstrip("/")
    )
    user_center_timeout_seconds: float = field(
        default_factory=lambda: float(os.getenv("USER_CENTER_TIMEOUT_SECONDS", "5"))
    )
    # 关闭后不校验 token，所有请求视为同一个本地调试用户，仅用于开发
    auth_enabled: bool = field(
        default_factory=lambda: (
            os.getenv("AUTH_ENABLED", "true").strip().lower()
            not in ("false", "0", "no", "off")
        )
    )
    # token 校验结果缓存时长（秒），登出或禁用后最多延迟这么久失效，0 表示不缓存
    auth_cache_ttl_seconds: int = field(
        default_factory=lambda: int(os.getenv("AUTH_CACHE_TTL_SECONDS", "30"))
    )

    def __post_init__(self):
        if self.user_center_timeout_seconds <= 0:
            raise ValueError("USER_CENTER_TIMEOUT_SECONDS 必须是正数")
        if self.auth_cache_ttl_seconds < 0:
            raise ValueError("AUTH_CACHE_TTL_SECONDS 必须是非负整数")
        if self.mongodb_checkpoint_ttl < 0:
            raise ValueError("MONGODB_CHECKPOINT_TTL 必须是非负整数")
        if self.conversation_empty_ttl <= 0:
            raise ValueError("CONVERSATION_EMPTY_TTL 必须是正整数")
        if self.conversation_history_turns < 0:
            raise ValueError("CONVERSATION_HISTORY_TURNS 必须是非负整数")
        if type(self.max_action_retries) is not int or self.max_action_retries < 0:
            raise ValueError("MAX_ACTION_RETRIES 必须是非负整数")
        if self.mcp_tool_timeout <= 0:
            raise ValueError("MCP_TOOL_TIMEOUT 必须是正数")
        if self.max_field_tool_rounds < 0:
            raise ValueError("MAX_FIELD_TOOL_ROUNDS 必须是非负整数")
        if not 0 <= self.intent_min_probability <= 1:
            raise ValueError("INTENT_MIN_PROBABILITY 必须在 0 到 1 之间")
        if not 0 <= self.intent_qa_min_probability <= 1:
            raise ValueError("INTENT_QA_MIN_PROBABILITY 必须在 0 到 1 之间")
        if self.intent_max_clarify_rounds < 0:
            raise ValueError("INTENT_MAX_CLARIFY_ROUNDS 必须是非负整数")


settings = Settings()