import torch
from diffusers import StableDiffusionPipeline

# Load model once (important for performance)
model_id = "runwayml/stable-diffusion-v1-5"

pipe = StableDiffusionPipeline.from_pretrained(
    model_id,
    torch_dtype=torch.float16 if torch.cuda.is_available() else torch.float32
)

if torch.cuda.is_available():
    pipe = pipe.to("cuda")

def generate_image(prompt: str):
    if not prompt.strip():
        return None

    image = pipe(
        prompt,
        guidance_scale=7.5,
        num_inference_steps=30
    ).images[0]

    return image