import gradio as gr
#from diffusers import StableDiffusionPipeline
from diffuser import AutoPipelineForText2Image
import torch

#model_id = "runwayml/stable-diffusion-v1-5"
model_id = "stabilityai/sdxl-turbo"
pipe = AutoPipelineForText2Image.from_pretrained(model_id, torch_dtype=torch.float32, safety_checker=None)


def infer(prompt):

    prompt = "a photo of an astronaut riding a horse on mars"
    image = pipe(prompt=prompt, guidance_scale=10.0, num_inference_steps=2, width=256, height=256).images[0]  

    return image

css="""
#col-container {
    margin: 0 auto;
    max-width: 720px;
}
"""

with gr.Blocks(css=css) as demo:
    
    with gr.Column(elem_id="col-container"):
        
        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()