app.py

import gradio as gr
from gradio_client import Client

def generate_image(prompt, negative_prompt, seed, width, height, prior_inference_steps, prior_guidance_scale, decoder_inference_steps, decoder_guidance_scale, num_images):
    client = Client("multimodalart/stable-cascade")
    result = client.predict(
        prompt,
        negative_prompt,
        seed,
        width,
        height,
        prior_inference_steps,
        prior_guidance_scale,
        decoder_inference_steps,
        decoder_guidance_scale,
        num_images,
        api_name="/run"
    )
    return result

demo = gr.Interface(
    fn=generate_image,
    inputs=[
        gr.Textbox(label="Prompt"),
        gr.Textbox(label="Negative prompt"),
        gr.Slider(label="Seed", minimum=0, maximum=2147483647, step=1),
        gr.Slider(label="Width", minimum=1024, maximum=1536, step=1),
        gr.Slider(label="Height", minimum=1024, maximum=1536, step=1),
        gr.Slider(label="Prior Inference Steps", minimum=10, maximum=30, step=1),
        gr.Slider(label="Prior Guidance Scale", minimum=0, maximum=20, step=1),
        gr.Slider(label="Decoder Inference Steps", minimum=4, maximum=12, step=1),
        gr.Slider(label="Decoder Guidance Scale", minimum=0, maximum=0, step=1),
        gr.Slider(label="Number of Images", minimum=1, maximum=2, step=1),
    ],
    outputs=["image"],
    theme = "soft"
)

demo.launch()