"""Application settings and environment configuration."""

from functools import lru_cache
from pathlib import Path

from pydantic import Field
from pydantic_settings import BaseSettings, SettingsConfigDict


class Settings(BaseSettings):
    """Defines runtime configuration values loaded from environment variables."""

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

    app_name: str = "dcm-dms"
    app_env: str = "development"
    database_url: str = "postgresql+psycopg://dcm:dcm@db:5432/dcm"
    redis_url: str = "redis://redis:6379/0"
    storage_root: Path = Path("/data/storage")
    upload_chunk_size: int = 4 * 1024 * 1024
    max_zip_members: int = 250
    max_zip_depth: int = 2
    max_text_length: int = 500_000
    default_openai_base_url: str = "https://api.openai.com/v1"
    default_openai_model: str = "gpt-4.1-mini"
    default_openai_timeout_seconds: int = 45
    default_openai_handwriting_enabled: bool = True
    default_openai_api_key: str = ""
    default_summary_model: str = "gpt-4.1-mini"
    default_routing_model: str = "gpt-4.1-mini"
    typesense_protocol: str = "http"
    typesense_host: str = "typesense"
    typesense_port: int = 8108
    typesense_api_key: str = "dcm-typesense-key"
    typesense_collection_name: str = "documents"
    typesense_timeout_seconds: int = 120
    typesense_num_retries: int = 0
    public_base_url: str = "http://localhost:8000"
    cors_origins: list[str] = Field(default_factory=lambda: ["http://localhost:5173", "http://localhost:3000"])


@lru_cache(maxsize=1)
def get_settings() -> Settings:
    """Returns a cached settings object for dependency injection and service access."""

    return Settings()