# Copyright (c) 2022 Kyle Schouviller (https://github.com/kyle0654)

from datetime import datetime, timezone
from typing import Literal, Union
from pydantic import Field
from .image import ImageField, ImageOutput
from .baseinvocation import BaseInvocation, InvocationContext
from ..services.image_storage import ImageType
from ..services.invocation_services import InvocationServices


class UpscaleInvocation(BaseInvocation):
    """Upscales an image."""
    type: Literal['upscale'] = 'upscale'

    # Inputs
    image: Union[ImageField,None] = Field(description="The input image", default=None)
    strength: float               = Field(default=0.75, gt=0, le=1, description="The strength")
    level: Literal[2,4]           = Field(default=2, description = "The upscale level")

    def invoke(self, context: InvocationContext) -> ImageOutput:
        image = context.services.images.get(self.image.image_type, self.image.image_name)
        results = context.services.generate.upscale_and_reconstruct(
            image_list     = [[image, 0]],
            upscale        = (self.level, self.strength),
            strength       = 0.0, # GFPGAN strength
            save_original  = False,
            image_callback = None,
        )

        # Results are image and seed, unwrap for now
        # TODO: can this return multiple results?
        image_type = ImageType.RESULT
        image_name = context.services.images.create_name(context.graph_execution_state_id, self.id)
        context.services.images.save(image_type, image_name, results[0][0])
        return ImageOutput(
            image = ImageField(image_type = image_type, image_name = image_name)
        )