Class LLMModelConfig

config.py:82–115

Configuration for a single LLM model within an ensemble.

@dataclass
class LLMModelConfig:
    """Configuration for a single LLM model within an ensemble."""

    # API configuration
    api_base: str = None
    api_key: Optional[str] = None
    name: str = None

    # Custom LLM client initialization function (optional)
    init_client: Optional[Callable] = None

    # Weight for this model in the ensemble (used for sampling)
    weight: float = 1.0

    # Generation parameters
    system_message: Optional[str] = None
    temperature: float = None
    top_p: float = None
    max_tokens: int = None

    # Request parameters
    timeout: int = None
    retries: int = None
    retry_delay: int = None

    # Reproducibility
    random_seed: Optional[int] = None

    # Reasoning parameters (for specific models)
    reasoning_effort: Optional[str] = None

    def __post_init__(self):
        """Post-initialization to resolve ${VAR} env var references in api_key."""
        self.api_key = _resolve_env_var(self.api_key)


@dataclass