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sd3-with-LLM
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# Thanks: https://huggingface.co/spaces/markmagic/Stable-Diffusion-3/blob/main/app.py

import os
import random
import uuid

import gradio as gr
import numpy as np
from PIL import Image
import spaces
import torch
from diffusers import StableDiffusion3Pipeline, DPMSolverMultistepScheduler, AutoencoderKL

DESCRIPTION = """# 日本語で入力できるStable Diffusion 3"""

pipe = StableDiffusion3Pipeline.from_pretrained(
    "stabilityai/stable-diffusion-3-medium-diffusers",
    torch_dtype=torch.float16,
    token=os.getenv("TOKEN")
)

@spaces.GPU()
def generate(
    prompt: str,
    negative_prompt: str = "",
    seed: int = 0,
    width: int = 1024,
    height: int = 1024,
    guidance_scale: float = 7,
    num_inference_steps=30,
    progress=gr.Progress(track_tqdm=True),
):
    pipe = pipe.to("cuda")
    generator = torch.Generator().manual_seed(seed)
    
    output = pipe(
        prompt=prompt,
        negative_prompt=negative_prompt,
        width=width,
        height=height,
        guidance_scale=guidance_scale,
        num_inference_steps=num_inference_steps,
        generator=generator,
        output_type="pil",
    ).images

    return output


examples = [
    "A red sofa on top of a white building.",
]

css = '''
.gradio-container{max-width: 1000px !important}
h1{text-align:center}
'''
with gr.Blocks(css=css) as demo:
    with gr.Row():
        with gr.Column():
            gr.HTML(
            """
            <h1 style='text-align: center'>
            日本語で入力できるStable Diffusion 3 Medium
            </h1>
            """
        )
            gr.HTML(
                """
               
                """
        )
    with gr.Group():
        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.Gallery(label="Result", elem_id="gallery", show_label=False)
    with gr.Accordion("Advanced options", open=False):
        with gr.Row():
            negative_prompt = gr.Text(
                label="Negative prompt",
                max_lines=1,
                value = "deformed, distorted, disfigured, poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, mutated hands and fingers, disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation, NSFW",
                visible=True,
            )
        seed = gr.Slider(
            label="Seed",
            minimum=0,
            maximum=MAX_SEED,
            step=1,
            value=0,
        )

        steps = gr.Slider(
            label="Steps",
            minimum=0,
            maximum=60,
            step=1,
            value=30,
        )
        
        with gr.Row():
            guidance_scale = gr.Slider(
                label="Guidance Scale",
                minimum=0.1,
                maximum=10,
                step=0.1,
                value=7.0,
            )

    gr.Examples(
        examples=examples,
        inputs=prompt,
        outputs=[result],
        fn=generate,
        cache_examples=CACHE_EXAMPLES,
    )

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

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