app.py

import gradio as gr
from diffusers import StableDiffusionPipeline
import torch

# Model load
model_id = "runwayml/stable-diffusion-v1-5"
pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=torch.float16)
pipe = pipe.to("cuda" if torch.cuda.is_available() else "cpu")

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

# Gradio UI
demo = gr.Interface(
    fn=generate,
    inputs=gr.Textbox(label="Enter your prompt"),
    outputs=gr.Image(type="pil", label="Generated Image")
)

demo.launch()