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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()
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