import gradio as gr
from diffusers import StableDiffusionImg2ImgPipeline
import torch
from PIL import Image

pipe = StableDiffusionImg2ImgPipeline.from_pretrained(
    "hf-internal-testing/tiny-stable-diffusion-pipe",
    torch_dtype=torch.float32
)

def generate(image, prompt):
    if image is None:
        return None

    img = image.convert("RGB").resize((512, 512))

    full_prompt = f"interior design, {prompt}, photorealistic, high quality"
    negative_prompt = "ugly, blurry, bad quality, distorted"

    result = pipe(
        prompt=full_prompt,
        negative_prompt=negative_prompt,
        image=img,
        strength=0.75,
        guidance_scale=7.5,
        num_inference_steps=8,
    ).images[0]

    return result

demo = gr.Interface(
    fn=generate,
    inputs=[
        gr.Image(type="pil", label="Leeg interieur render"),
        gr.Textbox(label="Stijl omschrijving")
    ],
    outputs=gr.Image(type="pil", label="Resultaat"),
    title="Interior AI"
)

if __name__ == "__main__":
    demo.launch()