app.py

# Import the necessary libraries
from diffusers import StableDiffusionPipeline
import torch
from PIL import Image
import gradio as gr

# Load the Stable Diffusion model
model_id = "runwayml/stable-diffusion-v1-5"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)

# Use CPU as fallback if CUDA is not available
device = "cuda" if torch.cuda.is_available() else "cpu"
pipe = pipe.to(device)

# Function to generate an image
def generate_image(prompt):
    image = pipe(prompt).images[0]
    return image

# Define the Gradio interface
with gr.Blocks() as demo:
    gr.HTML(
        """
        <div style="text-align: center;">
            <h1>🌄 Generate Stunning Images with Stable Diffusion</h1>
            <h3>Type a prompt to create a beautiful image:</h3>
        </div>
        """
    )
    
    with gr.Row():
        with gr.Column():
            prompt = gr.Textbox(label="Enter your prompt here", placeholder="e.g., beautiful and realistic mountain scenery 🌄", lines=1)
            submit_button = gr.Button("Generate Image 🚀")
        with gr.Column():
            image_output = gr.Image(label="Generated Image", type="pil")
    
    submit_button.click(fn=generate_image, inputs=prompt, outputs=image_output)
    
    gr.HTML(
        """
        <div style="text-align: center;">
            <h4>Developed by Salman Maqbool ✨</h4>
        </div>
        """
    )

# Launch the Gradio app
demo.launch()