import gradio as gr
import spaces
import numpy as np
import random
import torch
from diffusers import StableDiffusionXLPipeline

device = "cuda" if torch.cuda.is_available() else "cpu"
dtype = torch.float16

repo = "stabilityai/stable-diffusion-xl-base-1.0"
pipe = StableDiffusionXLPipeline.from_pretrained(
    repo,
    torch_dtype=dtype,
    use_safetensors=True
).to(device)

MAX_SEED = np.iinfo(np.int32).max

@spaces.GPU
def infer(prompt, negative_prompt, seed, randomize_seed, guidance_scale, num_inference_steps, progress=gr.Progress(track_tqdm=True)):
    if randomize_seed:
        seed = random.randint(0, MAX_SEED)
    generator = torch.Generator(device=device).manual_seed(seed)

    image = pipe(
        prompt=prompt,
        negative_prompt=negative_prompt,
        guidance_scale=guidance_scale,
        num_inference_steps=num_inference_steps,
        generator=generator
    ).images[0]

    return image, seed

examples = [
    "A cozy Scandinavian living room, soft light, natural wood, white tones",
    "A futuristic cityscape at night with flying cars",
    "A magical forest with glowing mushrooms and fairies"
]

css = """
#col-container {
    margin: 0 auto;
    max-width: 580px;
}
"""

with gr.Blocks(css=css) as demo:
    with gr.Column(elem_id="col-container"):
        gr.Markdown(f"""
        # Generate images [Stable Diffusion XL](https://huggingface.co/stabilityai/stable-diffusion-xl-base-1.0)
        Generate high-quality images with Stability AI's flagship SDXL base model.
        """)

        with gr.Row():
            prompt = gr.Text(
                label="Prompt",
                show_label=False,
                max_lines=1,
                placeholder="Enter your prompt",
                container=False,
            )
            run_button = gr.Button("Run", scale=0)

        result = gr.Image(label="Result", show_label=False)

        with gr.Accordion("Advanced Settings", open=False):
            negative_prompt = gr.Text(
                label="Negative prompt",
                max_lines=1,
                placeholder="Enter a negative prompt",
            )
            seed = gr.Slider(
                label="Seed",
                minimum=0,
                maximum=MAX_SEED,
                step=1,
                value=0,
            )
            randomize_seed = gr.Checkbox(label="Randomize seed", value=True)

            guidance_scale = gr.Slider(
                label="Guidance scale",
                minimum=0.0,
                maximum=20.0,
                step=0.1,
                value=7.5,
            )

            num_inference_steps = gr.Slider(
                label="Number of inference steps",
                minimum=1,
                maximum=50,
                step=1,
                value=30,
            )

        gr.Examples(
            examples=examples,
            inputs=[prompt]
        )

    gr.on(
        triggers=[run_button.click, prompt.submit, negative_prompt.submit],
        fn=infer,
        inputs=[prompt, negative_prompt, seed, randomize_seed, guidance_scale, num_inference_steps],
        outputs=[result, seed]
    )

demo.launch()