app.py

from gradio_client import Client
import gradio as gr

# Create a client for the other space
client = Client("radames/Enhance-This-HiDiffusion-SDXL")

# Define your interface function

def my_interface(input_image, prompt="This is a beautiful scenery", negative_prompt="blurry, ugly, duplicate, poorly drawn, deformed, mosaic", seed=1415926535897932, guidance_scale=8.5, scale=2, controlnet_conditioning_scale=0.5, strength=1.0, controlnet_start=0.0, controlnet_end=1.0, guassian_sigma=2.0, intensity_threshold=3):
    # Call the other space's predict function
    result = client.predict(
        input_image=input_image, 
        prompt=prompt, 
        negative_prompt=negative_prompt, 
        seed=seed, 
        guidance_scale=guidance_scale, 
        scale=scale, 
        controlnet_conditioning_scale=controlnet_conditioning_scale, 
        strength=strength, 
        controlnet_start=controlnet_start, 
        controlnet_end=controlnet_end, 
        guassian_sigma=guassian_sigma, 
        intensity_threshold=intensity_threshold, 
        api_name="/predict"
    )
    # Return only the first image from the result
    return result[0][0]

# Define your Gradio interface
iface = gr.Interface(fn=my_interface, 
                     inputs=gr.Image(), 
                     outputs=gr.Image())

# Launch your Gradio interface
iface.launch()