import yaml
from typing import Type, TypeVar, Any
from dataclasses import dataclass, asdict

ConfigInst = TypeVar('ConfigInst', bound='Config')
OpenAIConfigInst = TypeVar('OpenAIConfigInst', bound='OpenAIConfig')


@dataclass
class AIConfig:
    """
    The base class of all AI configurations.
    """
    name: str


@dataclass
class OpenAIConfig(AIConfig):
    """
    The OpenAI section of the configuration file.
    """
    api_key: str
    model: str
    temperature: float
    max_tokens: int
    top_p: float
    frequency_penalty: float
    presence_penalty: float

    @classmethod
    def from_dict(cls: Type[OpenAIConfigInst], source: dict[str, Any]) -> OpenAIConfigInst:
        """
        Create OpenAIConfig from a dict.
        """
        return cls(
            name='OpenAI',
            api_key=str(source['api_key']),
            model=str(source['model']),
            max_tokens=int(source['max_tokens']),
            temperature=float(source['temperature']),
            top_p=float(source['top_p']),
            frequency_penalty=float(source['frequency_penalty']),
            presence_penalty=float(source['presence_penalty'])
        )


@dataclass
class Config:
    """
    The configuration file structure.
    """
    system: str
    db: str
    openai: OpenAIConfig

    @classmethod
    def from_dict(cls: Type[ConfigInst], source: dict[str, Any]) -> ConfigInst:
        """
        Create Config from a dict.
        """
        return cls(
            system=str(source['system']),
            db=str(source['db']),
            openai=OpenAIConfig.from_dict(source['openai'])
        )

    @classmethod
    def from_file(cls: Type[ConfigInst], path: str) -> ConfigInst:
        with open(path, 'r') as f:
            source = yaml.load(f, Loader=yaml.FullLoader)
        return cls.from_dict(source)

    def to_file(self, path: str) -> None:
        with open(path, 'w') as f:
            yaml.dump(asdict(self), f, sort_keys=False)

    def as_dict(self) -> dict[str, Any]:
        return asdict(self)