app.py

import gradio as gr

import torch
from torch import autocast
from diffusers import StableDiffusionPipeline
from datasets import load_dataset
from PIL import Image  
import re
import streamlit as st

model_id = "CompVis/stable-diffusion-v1-4"
device = "cpu"

#If you are running this code locally, you need to either do a 'huggingface-cli login` or paste your User Access Token from here https://huggingface.co/settings/tokens into the use_auth_token field below. 
pipe = StableDiffusionPipeline.from_pretrained(model_id, use_auth_token=st.secrets["AUTH_KEY"], torch_dtype=torch.float32)
def dummy(images, **kwargs): return images, False 
pipe.safety_checker = dummy

def infer(prompt, width, height, steps, scale, seed):      
    if seed == -1:	
        images_list = pipe(
            [prompt],
            height=height, 
            width=width,
            num_inference_steps=steps,
            guidance_scale=scale,
            generator=torch.Generator(device=device).manual_seed(seed))
    else:
        images_list = pipe(
            [prompt],
            height=height, 
            width=width,
            num_inference_steps=steps,
            guidance_scale=scale)

    return images_list["sample"]
    
css = """
        .gradio-container {
            font-family: 'IBM Plex Sans', sans-serif;
        }
        .gr-button {
            color: white;
            border-color: black;
            background: black;
        }
        input[type='range'] {
            accent-color: black;
        }
        .dark input[type='range'] {
            accent-color: #dfdfdf;
        }
        .container {
            max-width: 730px;
            margin: auto;
            padding-top: 1.5rem;
        }
        #gallery {
            min-height: 22rem;
            margin-bottom: 15px;
            margin-left: auto;
            margin-right: auto;
            border-bottom-right-radius: .5rem !important;
            border-bottom-left-radius: .5rem !important;
        }
        #gallery>div>.h-full {
            min-height: 20rem;
        }
        .details:hover {
            text-decoration: underline;
        }
        .gr-button {
            white-space: nowrap;
        }
        .gr-button:focus {
            border-color: rgb(147 197 253 / var(--tw-border-opacity));
            outline: none;
            box-shadow: var(--tw-ring-offset-shadow), var(--tw-ring-shadow), var(--tw-shadow, 0 0 #0000);
            --tw-border-opacity: 1;
            --tw-ring-offset-shadow: var(--tw-ring-inset) 0 0 0 var(--tw-ring-offset-width) var(--tw-ring-offset-color);
            --tw-ring-shadow: var(--tw-ring-inset) 0 0 0 calc(3px var(--tw-ring-offset-width)) var(--tw-ring-color);
            --tw-ring-color: rgb(191 219 254 / var(--tw-ring-opacity));
            --tw-ring-opacity: .5;
        }
        .footer {
            margin-bottom: 45px;
            margin-top: 35px;
            text-align: center;
            border-bottom: 1px solid #e5e5e5;
        }
        .footer>p {
            font-size: .8rem;
            display: inline-block;
            padding: 0 10px;
            transform: translateY(10px);
            background: white;
        }
        .dark .footer {
            border-color: #303030;
        }
        .dark .footer>p {
            background: #0b0f19;
        }
        .acknowledgments h4{
            margin: 1.25em 0 .25em 0;
            font-weight: bold;
            font-size: 115%;
        }
"""

block = gr.Blocks(css=css)

with block:
    gr.HTML(
        """
            <div style="text-align: center; max-width: 650px; margin: 0 auto;">
              <div
                style="
                  display: inline-flex;
                  align-items: center;
                  gap: 0.8rem;
                  font-size: 1.75rem;
                "
              >
                <h1 style="font-weight: 900; margin-bottom: 7px;">
                  Stable Diffusion CPU
                </h1>
              </div>
            </div>
        """
    )
    with gr.Group():
        with gr.Box():
            with gr.Row().style(mobile_collapse=False, equal_height=True):
                text = gr.Textbox(
                    label="Enter your prompt",
                    show_label=False,
                    max_lines=1,
                    placeholder="Enter your prompt",
                ).style(
                    border=(True, False, True, True),
                    rounded=(True, False, False, True),
                    container=False,
                )
                btn = gr.Button("Generate image").style(
                    margin=False,
                    rounded=(False, True, True, False),
                )

        gallery = gr.Gallery(
            label="Generated images", show_label=False, elem_id="gallery"
        ).style(grid=[2], height="auto")

        with gr.Row().style(mobile_collapse=False, equal_height=True):
            width = gr.Slider(label="Width", minimum=32, maximum=1024, value=512, step=8)
            height = gr.Slider(label="Height", minimum=32, maximum=1024, value=512, step=8)

        with gr.Row():
            steps = gr.Slider(label="Steps", minimum=1, maximum=50, value=30, step=1)
            scale = gr.Slider(
                label="Guidance Scale", minimum=0, maximum=50, value=7.5, step=0.1
            )
            seed = gr.Slider(
                label="Seed",
                minimum=-1,
                maximum=2147483647,
                step=1,
                value=-1,
            )
        
        text.submit(infer, inputs=[text, width, height, steps, scale, seed], outputs=gallery)
        btn.click(infer, inputs=[text, width, height, steps, scale, seed], outputs=gallery)

block.queue(max_size=10).launch()