"""Centralized configuration using Pydantic Settings."""

from functools import lru_cache

from dotenv import load_dotenv
from pydantic import Field, field_validator, model_validator
from pydantic_settings import BaseSettings, SettingsConfigDict

from .nim import NimSettings

load_dotenv()


class Settings(BaseSettings):
    """Application settings loaded from environment variables."""

    # ==================== OpenRouter Config ====================
    open_router_api_key: str = Field(default="", validation_alias="OPENROUTER_API_KEY")

    # ==================== Messaging Platform Selection ====================
    # Valid: "telegram" | "discord"
    messaging_platform: str = Field(
        default="discord", validation_alias="MESSAGING_PLATFORM"
    )

    # ==================== NVIDIA NIM Config ====================
    nvidia_nim_api_key: str = ""

    # ==================== LM Studio Config ====================
    lm_studio_base_url: str = Field(
        default="http://localhost:1234/v1",
        validation_alias="LM_STUDIO_BASE_URL",
    )

    # ==================== Model ====================
    # All Claude model requests are mapped to this single model
    # Format: provider_type/model/name
    model: str = "nvidia_nim/meta/llama3-70b-instruct"

    # ==================== Provider Rate Limiting ====================
    provider_rate_limit: int = Field(default=40, validation_alias="PROVIDER_RATE_LIMIT")
    provider_rate_window: int = Field(
        default=60, validation_alias="PROVIDER_RATE_WINDOW"
    )
    provider_max_concurrency: int = Field(
        default=5, validation_alias="PROVIDER_MAX_CONCURRENCY"
    )

    # ==================== HTTP Client Timeouts ====================
    http_read_timeout: float = Field(
        default=300.0, validation_alias="HTTP_READ_TIMEOUT"
    )
    http_write_timeout: float = Field(
        default=10.0, validation_alias="HTTP_WRITE_TIMEOUT"
    )
    http_connect_timeout: float = Field(
        default=2.0, validation_alias="HTTP_CONNECT_TIMEOUT"
    )

    # ==================== Fast Prefix Detection ====================
    fast_prefix_detection: bool = True

    # ==================== Optimizations ====================
    enable_network_probe_mock: bool = True
    enable_title_generation_skip: bool = True
    enable_suggestion_mode_skip: bool = True
    enable_filepath_extraction_mock: bool = True

    # ==================== NIM Settings ====================
    nim: NimSettings = Field(default_factory=NimSettings)

    # ==================== Voice Note Transcription ====================
    voice_note_enabled: bool = Field(
        default=True, validation_alias="VOICE_NOTE_ENABLED"
    )
    # Device: "cpu" | "cuda" | "nvidia_nim"
    # - "cpu"/"cuda": local Whisper (requires voice_local extra: uv sync --extra voice_local)
    # - "nvidia_nim": NVIDIA NIM Whisper API (requires voice extra: uv sync --extra voice)
    whisper_device: str = Field(default="cpu", validation_alias="WHISPER_DEVICE")
    # Whisper model ID or short name (for local Whisper) or NVIDIA NIM model (for nvidia_nim)
    # Local Whisper: "tiny", "base", "small", "medium", "large-v2", "large-v3", "large-v3-turbo"
    # NVIDIA NIM: "nvidia/parakeet-ctc-1.1b-asr", "openai/whisper-large-v3", etc.
    whisper_model: str = Field(default="base", validation_alias="WHISPER_MODEL")
    # Hugging Face token for faster model downloads (optional, for local Whisper)
    hf_token: str = Field(default="", validation_alias="HF_TOKEN")

    # ==================== Bot Wrapper Config ====================
    telegram_bot_token: str | None = None
    allowed_telegram_user_id: str | None = None
    discord_bot_token: str | None = Field(
        default=None, validation_alias="DISCORD_BOT_TOKEN"
    )
    allowed_discord_channels: str | None = Field(
        default=None, validation_alias="ALLOWED_DISCORD_CHANNELS"
    )
    claude_workspace: str = "./agent_workspace"
    allowed_dir: str = ""

    # ==================== Server ====================
    host: str = "0.0.0.0"
    port: int = 8082
    log_file: str = "server.log"

    # Handle empty strings for optional string fields
    @field_validator(
        "telegram_bot_token",
        "allowed_telegram_user_id",
        "discord_bot_token",
        "allowed_discord_channels",
        mode="before",
    )
    @classmethod
    def parse_optional_str(cls, v):
        if v == "":
            return None
        return v

    @field_validator("whisper_device")
    @classmethod
    def validate_whisper_device(cls, v: str) -> str:
        if v not in ("cpu", "cuda", "nvidia_nim"):
            raise ValueError(
                f"whisper_device must be 'cpu', 'cuda', or 'nvidia_nim', got {v!r}"
            )
        return v

    @field_validator("model")
    @classmethod
    def validate_model_format(cls, v: str) -> str:
        valid_providers = ("nvidia_nim", "open_router", "lmstudio")
        if "/" not in v:
            raise ValueError(
                f"Model must be prefixed with provider type. "
                f"Valid providers: {', '.join(valid_providers)}. "
                f"Format: provider_type/model/name"
            )
        provider = v.split("/", 1)[0]
        if provider not in valid_providers:
            raise ValueError(
                f"Invalid provider: '{provider}'. "
                f"Supported: 'nvidia_nim', 'open_router', 'lmstudio'"
            )
        return v

    @model_validator(mode="after")
    def check_nvidia_nim_api_key(self) -> Settings:
        if (
            self.voice_note_enabled
            and self.whisper_device == "nvidia_nim"
            and not self.nvidia_nim_api_key.strip()
        ):
            raise ValueError(
                "NVIDIA_NIM_API_KEY is required when WHISPER_DEVICE is 'nvidia_nim'. "
                "Set it in your .env file."
            )
        return self

    @property
    def provider_type(self) -> str:
        """Extract provider type from the model string."""
        return self.model.split("/", 1)[0]

    @property
    def model_name(self) -> str:
        """Extract the actual model name from the model string."""
        return self.model.split("/", 1)[1]

    model_config = SettingsConfigDict(
        env_file=".env",
        env_file_encoding="utf-8",
        extra="ignore",
    )


@lru_cache
def get_settings() -> Settings:
    """Get cached settings instance."""
    return Settings()