import gradio as gr
from diffusers import DiffusionPipeline
import torch

pipe = DiffusionPipeline.from_pretrained("stabilityai/stable-diffusion-xl-base-1.0", torch_dtype=torch.float16, use_safetensors=True, variant="fp16")
pipe.enable_model_cpu_offload()

def infer(prompt):

    prompt = "A cinematic shot of a baby racoon wearing an intricate italian priest robe."
    image = pipe(prompt=prompt, num_inference_steps=1, guidance_scale=0.0).images[0]

    return image

with gr.Blocks() as demo:
    
    with gr.Column():
        
        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)
        
        result = gr.Image(label="Result", show_label=False)

    run_button.click(
        fn = infer,
        inputs = [prompt],
        outputs = [result]
    )

demo.queue().launch()