class LlmConfig:
    class openai:
        class models:
            gpt_4o = "gpt-4o"
            gpt_4_1 = "gpt-4.1"

        temperatures = {
            "default": 0.7,
            "drone_bot": 0.3,
            "creative": 0.9
        }

        max_tokens = {
            "default": 2048,
            "summary_bot": 512,
            "explainer": 1024
        }

    class anthropic:
        class models:
            claude_3_opus = "claude-3-opus"
            claude_3_sonnet = "claude-3-sonnet"

        temperatures = {
            "default": 0.5,
            "drone_bot": 0.4,
            "research": 0.2
        }

        max_tokens = {
            "default": 4096,
            "summary_bot": 1024
        }

    @classmethod
    def get_config(cls, provider: str, model_name: str, temp_name: str = "default", token_preset: str = "default") -> dict:
        if not hasattr(cls, provider):
            raise ValueError(f"Provider '{provider}' not found.")

        provider_cls = getattr(cls, provider)

        # Get model value from class (e.g., LlmConfig.openai.models.gpt_4o)
        model_cls = getattr(provider_cls, "models")
        if not hasattr(model_cls, model_name):
            raise ValueError(f"Model '{model_name}' not found under provider '{provider}'.")

        model = getattr(model_cls, model_name)

        if temp_name not in provider_cls.temperatures:
            raise ValueError(f"Temperature preset '{temp_name}' not found under provider '{provider}'.")

        if token_preset not in provider_cls.max_tokens:
            raise ValueError(f"Max token preset '{token_preset}' not found under provider '{provider}'.")

        return {
            "provider": provider,
            "model": model,
            "temperature": provider_cls.temperatures[temp_name],
            "max_tokens": provider_cls.max_tokens[token_preset]
        }