"""Configuration from environment / .env."""
from __future__ import annotations

import os
from pathlib import Path
from dotenv import load_dotenv

# Load .env from backend/ (project root for this app)
_BACKEND_DIR = Path(__file__).resolve().parent.parent
load_dotenv(_BACKEND_DIR / ".env", override=True)


def _get_bool(name: str, default: bool = False) -> bool:
    raw = os.environ.get(name)
    if raw is None:
        return default
    return raw.strip().lower() in {"1", "true", "yes", "on"}


def resolve_llm() -> tuple[str, str, str, str | None]:
    """Return (base_url, model, api_key, provider_name)."""
    provider = os.environ.get("LLM_PROVIDER", "").strip()
    explicit_base = os.environ.get("LLM_BASE_URL", "").strip()
    explicit_model = os.environ.get("LLM_MODEL_NAME", "").strip()
    api_key = os.environ.get("LLM_API_KEY", "").strip() or None

    presets = {
        "deepseek": ("https://api.deepseek.com/v1", "deepseek-chat"),
        "openai": ("https://api.openai.com/v1", "gpt-4o-mini"),
        "custom": ("", ""),
    }
    if provider and provider in presets:
        base_url, model = presets[provider]
        if explicit_base:
            base_url = explicit_base
        if explicit_model:
            model = explicit_model
        return base_url, model, api_key or "", provider
    # No/unknown provider: fall back to explicit config
    return (
        explicit_base or "https://api.openai.com/v1",
        explicit_model or "gpt-4o-mini",
        api_key or "",
        provider or None,
    )


class Config:
    APP_NAME = "Sales Trainer"
    SECRET_KEY = os.environ.get("JWT_SECRET", "dev-secret-change-me")
    JWT_ALGO = "HS256"
    JWT_EXPIRES_HOURS = int(os.environ.get("JWT_EXPIRES_HOURS", "24"))

    DATA_DIR = Path(
        os.environ.get("DATA_DIR", str(_BACKEND_DIR / "data"))
    ).resolve()

    FLASK_HOST = os.environ.get("FLASK_HOST", "0.0.0.0")
    FLASK_PORT = int(os.environ.get("FLASK_PORT", "5001"))
    FLASK_DEBUG = _get_bool("FLASK_DEBUG", True)

    UPLOAD_MAX_MB = int(os.environ.get("UPLOAD_MAX_MB", "15"))
    ALLOWED_UPLOAD_EXTS = {"pdf", "md", "txt"}

    # LLM
    LLM_BASE_URL, LLM_MODEL, LLM_API_KEY, LLM_PROVIDER = resolve_llm()

    ROLES = ("super_admin", "admin", "user")

    @classmethod
    def ensure_dirs(cls) -> None:
        for name in ("users", "orgs", "groups", "sessions"):
            (cls.DATA_DIR / name).mkdir(parents=True, exist_ok=True)