app.py

import gradio as gr
from transformers import pipeline

# Initialize the model (example with a text-to-image model)
generator = pipeline("image-generation", model="CompVis/stable-diffusion-v1-4")

# Function to generate an image from a prompt
def generate_image(prompt):
    # The pipeline will return a list with the image as the first element
    return generator(prompt)[0]["image"]

# Set up the Gradio interface
interface = gr.Interface(
    fn=generate_image,   # function to be called
    inputs="text",       # input type: text box for user input (prompt)
    outputs="image",     # output type: image display
    live=True            # allows real-time generation (optional)
)

# Launch the interface
if __name__ == "__main__":
    interface.launch()