Stable Cascade App code discussed in a question submitted to StackOverflow

app.py

import gradio as gr
import spaces
from diffusers import StableCascadeCombinedPipeline
import os
import torch
from PIL import Image
import random

# Constants
repo = "stabilityai/stable-cascade"


# Ensure model and scheduler are initialized in GPU-enabled function
if torch.cuda.is_available():
    pipe = StableCascadeCombinedPipeline.from_pretrained(repo, variant="bf16", torch_dtype=torch.bfloat16)
    pipe.to("cuda")

# The generate function
@spaces.GPU(enable_queue=True)
def generate_image(prompt):  
#def generate_image(prompt, images):  
    seed  =  random.randint(-100000,100000)

    results =  pipe(
                prompt=prompt,
                #images=[images],
                height=1024,
                width=1024,
                num_inference_steps=20, 
                generator=torch.Generator(device="cuda").manual_seed(seed)
            )
    return results.images[0]


# ------------- Gradio Interface -----------------------
description = """
This demo utilizes the StableCascade combined pipeline
"""

with gr.Blocks(css="style.css") as demo:
    gr.HTML("<h1><center>Via Stable Cascade ⚡</center></h1>")
    gr.Markdown(description)
    with gr.Group():
        with gr.Row():
            prompt = gr.Textbox(label='Enter your prompt', scale=8, value="holding a puppy")
            submit = gr.Button(scale=1, variant='primary')
    imgin = gr.Image(label='Input Image', type='pil', height=1024, width=1024, interactive=True)
    imgout = gr.Image(label='StableCascade Generated Image', height=1024, width=1024)

    prompt.submit(fn=generate_image,
                 inputs=[prompt],
                 #inputs=[prompt, imgin],
                 outputs=imgout,
                 )
    submit.click(fn=generate_image,
                 inputs=[prompt],
                 #inputs=[prompt, imgin],
                 outputs=imgout,
                 )
    
demo.queue().launch()