import torch
from diffusers import StableDiffusionPipeline
import gradio as gr

model_id = "runwayml/stable-diffusion-v1-5"

# Detect if GPU is available, else fall back to CPU and float32
device = "cuda" if torch.cuda.is_available() else "cpu"
dtype = torch.float16 if device == "cuda" else torch.float32

pipe = StableDiffusionPipeline.from_pretrained(model_id, torch_dtype=dtype)
pipe.to(device)

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

iface = gr.Interface(fn=generate, inputs="text", outputs="image", title="Stable Diffusion Image Generator")
iface.launch()