"""Application configuration — multi-model pool by domain."""

from pathlib import Path
from pydantic_settings import BaseSettings


class Settings(BaseSettings):
    # --- Model Pool ---
    # Global analysis (English-native): strongest global reasoning
    llm_global: str = "openai/Claude-3.5-Sonnet"
    # China domestic (Chinese-native): deepest Chinese market knowledge
    llm_china: str = "openai/DeepSeek-R1"
    # Synthesis & review: strongest reasoning for cross-domain work
    llm_reasoning: str = "openai/Claude-3.5-Sonnet"
    # Data & fast tasks: cost-effective structured output
    llm_fast: str = "openai/Gemini-2.0-Flash"
    # Translation: high-quality bidirectional EN↔ZH
    llm_translation: str = "openai/Claude-3.5-Sonnet"

    # Fallback default (if domain not specified)
    llm_model: str = "openai/Claude-3.5-Sonnet"

    # API config (Poe as unified gateway)
    llm_api_key: str = ""
    llm_api_base: str = "https://api.poe.com/bot/"

    # Server
    host: str = "0.0.0.0"
    port: int = 4200

    # Paths
    base_dir: Path = Path(__file__).resolve().parent.parent
    templates_dir: Path = base_dir / "templates"
    output_dir: Path = base_dir / "output"

    model_config = {"env_file": ".env", "env_file_encoding": "utf-8"}

    def model_for_domain(self, domain: str) -> str:
        """Get the best model for a content domain.

        Domains:
            global   — international markets, global competition, tech trends
            china    — Chinese market, domestic policy, local competition
            reasoning — synthesis, review, strategic recommendations
            fast     — data processing, chart generation, structured output
            translation — high-quality EN↔ZH translation
        """
        return {
            "global": self.llm_global,
            "china": self.llm_china,
            "reasoning": self.llm_reasoning,
            "fast": self.llm_fast,
            "translation": self.llm_translation,
        }.get(domain, self.llm_model)


settings = Settings()