import os
from pathlib import Path

import numpy as np
from PIL import Image

from mflux import Flux1, Config, ModelConfig


class ImageGeneratorTestHelper:
    @staticmethod
    def assert_matches_reference_image(
        reference_image_path: str,
        output_image_path: str,
        model_config: ModelConfig,
        prompt: str,
        steps: int,
        seed: int,
        lora_paths: list[str] | None = None,
        lora_scales: list[float] | None = None,
    ):
        # resolve paths
        reference_image_path = ImageGeneratorTestHelper.resolve_path(reference_image_path)
        output_image_path = ImageGeneratorTestHelper.resolve_path(output_image_path)
        lora_paths = [str(ImageGeneratorTestHelper.resolve_path(p)) for p in lora_paths] if lora_paths else None

        try:
            # given
            flux = Flux1(
                model_config=model_config,
                quantize=8,
                lora_paths=lora_paths,
                lora_scales=lora_scales
            )  # fmt: off

            # when
            image = flux.generate_image(
                seed=seed,
                prompt=prompt,
                config=Config(
                    num_inference_steps=steps,
                    height=341,
                    width=768,
                ),
            )
            image.save(path=output_image_path)

            # then
            np.testing.assert_array_equal(
                np.array(Image.open(output_image_path)),
                np.array(Image.open(reference_image_path)),
                err_msg="Generated image doesn't match reference image",
            )

        finally:
            # cleanup
            if os.path.exists(output_image_path):
                os.remove(output_image_path)

    @staticmethod
    def resolve_path(path) -> Path:
        return Path(__file__).parent.parent / "resources" / path