import os
from pathlib import Path

try:
    import tomllib  # Python >= 3.11 (stdlib)
except ModuleNotFoundError:  # pragma: no cover - Fallback fuer aeltere Interpreter
    import tomli as tomllib  # type: ignore

from pydantic.fields import FieldInfo
from pydantic_settings import (
    BaseSettings,
    PydanticBaseSettingsSource,
    SettingsConfigDict,
)

BASE_DIR = Path(__file__).resolve().parent.parent
ENV_FILE = BASE_DIR / ".env"
DEFAULT_CONFIG_FILE = BASE_DIR / "config" / "voice-assistant.toml"


def _setting_lookup(key: str) -> str | None:
    """Liest einen Steuer-Schluessel: echte Umgebung zuerst, dann die .env-Datei.

    Noetig fuer VA_PROFILE/VA_CONFIG_FILE, weil diese gebraucht werden, BEVOR
    pydantic-settings die .env laedt - und .env-Werte sonst nicht in os.environ stehen.
    """
    value = os.getenv(key)
    if value is not None:
        return value
    try:
        from dotenv import dotenv_values
    except ModuleNotFoundError:  # pragma: no cover
        return None
    if ENV_FILE.is_file():
        return dotenv_values(ENV_FILE).get(key)
    return None


def _config_file_path() -> Path:
    return Path(_setting_lookup("VA_CONFIG_FILE") or str(DEFAULT_CONFIG_FILE))


def active_profile() -> str | None:
    """Name des aktiven Profils (VA_PROFILE) aus Umgebung oder .env, falls gesetzt."""
    profile = _setting_lookup("VA_PROFILE")
    return profile.strip() or None if profile else None


def load_profile_config() -> dict:
    """Liest die zentrale TOML-Config und merged [defaults] + [profiles.<VA_PROFILE>].

    - Fehlt die Datei, gilt ein leeres dict (nur ENV/Defaults greifen) - kein Fehler,
      damit reine Cloud-Deployments ohne Datei (nur ENV) funktionieren.
    - Ein gesetztes, aber unbekanntes VA_PROFILE ist ein Konfigurationsfehler.
    """
    path = _config_file_path()
    if not path.is_file():
        return {}

    with path.open("rb") as handle:
        data = tomllib.load(handle)

    merged: dict = dict(data.get("defaults", {}))

    profile = active_profile()
    if profile:
        profiles = data.get("profiles", {})
        if profile not in profiles:
            raise ValueError(
                f"Unbekanntes VA_PROFILE {profile!r}. "
                f"Verfuegbar: {sorted(profiles)}"
            )
        merged.update(profiles[profile])

    return merged


class TomlProfileSource(PydanticBaseSettingsSource):
    """Settings-Quelle aus der zentralen TOML-Config (inkl. aktivem Profil).

    Liegt in der Praezedenz unter ENV/.env, aber ueber den eingebauten Defaults.
    Es werden nur Schluessel durchgereicht, die auch als Settings-Feld existieren.
    """

    def __init__(self, settings_cls):
        super().__init__(settings_cls)
        raw = load_profile_config()
        known = set(settings_cls.model_fields)
        self._values = {
            key.lower(): value
            for key, value in raw.items()
            if key.lower() in known
        }

    def get_field_value(self, field: FieldInfo, field_name: str):
        if field_name in self._values:
            return self._values[field_name], field_name, False
        return None, field_name, False

    def __call__(self) -> dict:
        return dict(self._values)


class Settings(BaseSettings):
    app_env: str = "dev"
    host: str = "0.0.0.0"
    port: int = 8080
    log_level: str = "info"
    openrouter_api_key: str = ""
    openrouter_stt_model: str = "openai/whisper-large-v3"
    openrouter_tts_model: str = "openai/gpt-4o-mini-tts"
    openrouter_tts_voice: str = "alloy"
    openrouter_llm_model: str = "openai/gpt-4.1-mini"
    default_language: str = "de"
    default_input_endpoint: str = "local-default"
    default_output_endpoint: str = "local-default"
    default_stt_provider: str = "openrouter"
    default_llm_provider: str = "local-openai-compatible"
    default_tts_provider: str = "openrouter"
    local_llm_base_url: str = "http://127.0.0.1:11434/v1"
    local_llm_api_key: str = "dummy"
    local_llm_model: str = "llama3.1"
    faster_whisper_model: str = "base"        # tiny|base|small|medium|large-v3
    faster_whisper_device: str = "auto"       # auto|cpu|cuda
    faster_whisper_compute_type: str = "default"  # default|int8|float16|int8_float16
    db_path: str = str(BASE_DIR / "data" / "voice-assistant.db")
    admin_api_key: str = ""
    auth_enabled: bool = True
    history_max_messages: int = 10
    audio_stream_default: bool = True  # satzweises TTS als Default (Admin kann abschalten)
    stt_fallback: str = ""  # kommaseparierte Provider-Namen (Fallback-Kette)
    llm_fallback: str = ""
    tts_fallback: str = ""
    daily_request_limit: int = 0  # 0 = unbegrenzt; Anfragen pro Nutzer pro Tag
    emergency_webhook_url: str = ""  # optionaler Eskalations-Webhook
    model_config = SettingsConfigDict(
        env_file=ENV_FILE, case_sensitive=False, extra="ignore"
    )

    @classmethod
    def settings_customise_sources(
        cls,
        settings_cls,
        init_settings,
        env_settings,
        dotenv_settings,
        file_secret_settings,
    ):
        # Praezedenz (frueher = hoeher): init > ENV > .env > TOML/Profil > Defaults
        return (
            init_settings,
            env_settings,
            dotenv_settings,
            TomlProfileSource(settings_cls),
            file_secret_settings,
        )


settings = Settings()