app.py

import gradio as gr
from diffusers import StableDiffusionPipeline
import torch

# Load the model from Hugging Face
model_id = "CompVis/stable-diffusion-v1-4"
pipe = StableDiffusionPipeline.from_pretrained(model_id)

# Move model to CPU to use free tier
pipe.to("cpu")

# Define function to generate image from text prompt
def generate_image(prompt):
    image = pipe(prompt).images[0]
    return image

# Create Gradio interface
with gr.Blocks() as demo:
    gr.Markdown("## Simple Text-to-Image Generator using Stable Diffusion")
    
    prompt = gr.Textbox(label="Enter a text prompt")
    image_output = gr.Image()
    
    # Create a button to trigger image generation
    generate_button = gr.Button("Generate Image")
    
    # On clicking the button, call the generate_image function
    generate_button.click(fn=generate_image, inputs=prompt, outputs=image_output)

# Launch the demo
demo.launch()