# This file was auto-generated by Fern from our API Definition.

import enum
import typing

T_Result = typing.TypeVar("T_Result")


class SingleSeriesInsampleForecastModel(str, enum.Enum):
    """
    Model to use as a string. Options are: `timegpt-1`, and `timegpt-1-long-horizon.` We recommend using `timegpt-1-long-horizon` for forecasting if you want to predict more than one seasonal period given the frequency of your data.
    """

    TIMEGPT_1 = "timegpt-1"
    TIMEGPT_1_LONG_HORIZON = "timegpt-1-long-horizon"
    SHORT_HORIZON = "short-horizon"
    LONG_HORIZON = "long-horizon"
    AZUREAI = "azureai"

    def visit(
        self,
        timegpt_1: typing.Callable[[], T_Result],
        timegpt_1_long_horizon: typing.Callable[[], T_Result],
        short_horizon: typing.Callable[[], T_Result],
        long_horizon: typing.Callable[[], T_Result],
        azureai: typing.Callable[[], T_Result],
    ) -> T_Result:
        if self is SingleSeriesInsampleForecastModel.TIMEGPT_1:
            return timegpt_1()
        if self is SingleSeriesInsampleForecastModel.TIMEGPT_1_LONG_HORIZON:
            return timegpt_1_long_horizon()
        if self is SingleSeriesInsampleForecastModel.SHORT_HORIZON:
            return short_horizon()
        if self is SingleSeriesInsampleForecastModel.LONG_HORIZON:
            return long_horizon()
        if self is SingleSeriesInsampleForecastModel.AZUREAI:
            return azureai()
