# generated by datamodel-codegen:
#   filename:  core/forecast_point.json
#   timestamp: 2026-02-12T12:00:44+00:00

from __future__ import annotations

from typing import Annotated

from adcp.types.base import AdCPBaseModel
from pydantic import ConfigDict, Field

from . import forecast_range


class ForecastPoint(AdCPBaseModel):
    model_config = ConfigDict(
        extra='allow',
    )
    budget: Annotated[
        float,
        Field(
            description='Budget amount for this forecast point. For allocation-level forecasts, this is the absolute budget for that allocation (not the percentage). For proposal-level forecasts, this is the total proposal budget.',
            ge=0.0,
        ),
    ]
    metrics: Annotated[
        dict[str, forecast_range.ForecastRange],
        Field(
            description='Forecasted metric values at this budget level. Keys are either forecastable-metric values for delivery/engagement (impressions, reach, spend, etc.) or event-type values for outcomes (purchase, lead, app_install, etc.). Values are ForecastRange objects (low/mid/high). Use { "mid": value } for point estimates. Include spend when the platform predicts it will differ from budget.'
        ),
    ]
