app.py

import gradio as gr
from diffusers import StableDiffusionPipeline
import torch

pipe = None

def load_model():
    global pipe
    if pipe is None:
        pipe = StableDiffusionPipeline.from_pretrained(
            "runwayml/stable-diffusion-v1-5",
            torch_dtype=torch.float32
        )
        pipe.unet.load_attn_procs("YOUR_USERNAME/sd-lora-nigerian-adire")
        pipe = pipe.to("cpu")
    return pipe

def generate(prompt, steps, guidance):
    pipe = load_model()
    image = pipe(
        prompt,
        num_inference_steps=steps,
        guidance_scale=guidance
    ).images[0]
    return image

demo = gr.Interface(
    fn=generate,
    inputs=[
        gr.Textbox(
            label="Prompt",
            placeholder="a nigerian_adire_style painting of...",
            value="a nigerian_adire_style sunset over Lagos"
        ),
        gr.Slider(20, 50, value=30, step=5, label="Steps"),
        gr.Slider(5, 15, value=7.5, step=0.5, label="Guidance Scale"),
    ],
    outputs=gr.Image(label="Generated Image"),
    title="Nigerian Adire Style Generator",
    description="Fine-tuned Stable Diffusion with LoRA",
)

demo.launch()