import gradio as gr
from diffusers import DiffusionPipeline

model_repo_id = "runwayml/stable-diffusion-v1-5"  # Replace to the model you would like to use

pipe = DiffusionPipeline.from_pretrained(model_repo_id)
pipe.load_lora_weights("OVAWARE/plixel-minecraft")


# @spaces.GPU #[uncomment to use ZeroGPU]
def infer(
    prompt
):
    image = pipe(
        prompt=prompt
    ).images[0]

    return image


css = """
#col-container {
    margin: 0 auto;
    max-width: 640px;
}
"""

with gr.Blocks(css=css) as demo:
    with gr.Column(elem_id="col-container"):
        gr.Markdown(" # Text-to-Image Gradio Template")

        with gr.Row():
            prompt = gr.Text(
                label="Prompt",
                show_label=False,
                max_lines=1,
                placeholder="Enter your prompt",
                container=False,
            )

            run_button = gr.Button("Run", scale=0, variant="primary")

        result = gr.Image(label="Result", show_label=False)

    gr.on(
        triggers=[run_button.click, prompt.submit],
        fn=infer,
        inputs=[
            prompt
        ],
        outputs=[result],
    )

if __name__ == "__main__":
    demo.launch()