app.py

import gradio as gr
import numpy as np
import random
from diffusers import DiffusionPipeline
import torch

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

if torch.cuda.is_available():
    torch.cuda.max_memory_allocated(device=device)
    pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", torch_dtype=torch.float16, variant="fp16", use_safetensors=True)
    pipe.enable_xformers_memory_efficient_attention()
    pipe = pipe.to(device)
else:
    pipe = DiffusionPipeline.from_pretrained("stabilityai/sdxl-turbo", use_safetensors=True)
    pipe = pipe.to(device)

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

def infer(prompt, width, height):
    seed = random.randint(0, MAX_SEED)
    generator = torch.Generator().manual_seed(seed)
    
    image = pipe(
        prompt=prompt, 
        guidance_scale=7.5, 
        num_inference_steps=50, 
        width=width, 
        height=height,
        generator=generator
    ).images[0] 
    
    return image

examples = [
    "Sunset over the Atlas Mountains",
    "Flying carpet in space",
    "Unicorn riding a camel in the Sahara Desert",
    "Moroccan souk floating in the sky",
    "Traditional Amazigh jewelry under the moonlight"
]

css="""
#col-container {
    margin: 0 auto;
    max-width: 840px;
    color: #003366;
}
body {
    background-color: white;
}
"""

if torch.cuda.is_available():
    power_device = "GPU"
else:
    power_device = "CPU"

with gr.Blocks(css=css) as demo:
    
    with gr.Column(elem_id="col-container"):
        gr.Markdown(f"""
        # bibou.jpeg
        Generate Moroccan folkloric pictures, inspired by Moroccan and Amazigh arts. 🎨🎶
        Currently running on {power_device}.
        """)
        
        with gr.Row():
            prompt = gr.Textbox(
                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.Row():
            width = gr.Slider(
                label="Width",
                minimum=512,
                maximum=3000,
                step=32,
                value=512,
            )
                
            height = gr.Slider(
                label="Height",
                minimum=512,
                maximum=3000,
                step=32,
                value=512,
            )
        
        gr.Examples(
            examples=examples,
            inputs=[prompt]
        )
        
        gr.Markdown("""
        <div style="text-align: center;">
            Built with ❤️ by <a href="https://www.linkedin.com/in/halimbahae/" target="_blank">Bahae Eddine HALIM</a>
        </div>
        """)

    run_button.click(
        fn=infer,
        inputs=[prompt, width, height],
        outputs=[result]
    )

demo.queue().launch()