app.py

import gradio as gr
from datasets import load_dataset
from PIL import Image
import re
import os
import requests

from share_btn import community_icon_html, loading_icon_html, share_js

model_id = "runwayml/stable-diffusion-v1-5"
device = "cuda"

word_list_dataset = load_dataset("stabilityai/word-list", data_files="list.txt", use_auth_token=True)
word_list = word_list_dataset["train"]['text']

is_gpu_busy = False

def infer(prompt):
    global is_gpu_busy
    samples = 4
    steps = 50
    scale = 7.5
    for filter in word_list:
        if re.search(rf"\b{filter}\b", prompt):
            raise gr.Error("Unsafe content found. Please try again with different prompts.")
        
    images = []
    url = os.getenv('JAX_BACKEND_URL')
    payload = {'prompt': prompt}
    images_request = requests.post(url, json=payload)
    for image in images_request.json()["images"]:
        image_b64 = (f"data:image/jpeg;base64,{image}")
        images.append(image_b64)
    
    return images

API_URL = "https://edmx2y4mrvq3tal8.us-east-1.aws.endpoints.huggingface.cloud"  # Replace with your actual API URL
headers = {"Content-Type": "application/json"}

def query(payload):
    response = requests.post(API_URL, headers=headers, json=payload)
    return response.content

def generate(prompt):   
    payload = {
        "inputs": prompt,
        "parameters": {
            "height": 1024,
            "width": 1024,
            "num_inference_steps": 25,
                "negative_prompt": "deformed, distorted, disfigured:1.3), poorly drawn, bad anatomy, wrong anatomy, extra limb, missing limb, floating limbs, (mutated hands and fingers:1.4), disconnected limbs, mutation, mutated, ugly, disgusting, blurry, amputation, (NSFW:1.25)",
                "num_images_per_prompt": 4           
        }
    }
    output = query(payload)
    images = []
    for i in range(4):
        image = Image.open(io.BytesIO(output))
        images.append(image)
    return images
    

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;
        }
        #advanced-btn {
            font-size:.7rem!important;
            line-height: 19px;
            margin-top: 12px;
            margin-bottom: 12px;
            padding: 2px 8px;
            border-radius: 14px!important;
        }
        #advanced-options {
            display: none;
            margin-bottom: 20px;
        }
       .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%;
        }
        #container-advanced-btns{
            display: flex;
            flex-wrap: wrap;
            justify-content: space-between;
            align-items: center;
        }
       .animate-spin {
            animation: spin 1s linear infinite;
        }
        @keyframes spin {
            from {
                transform: rotate(0deg);
            }
            to {
                transform: rotate(360deg);
            }
        }
        #share-btn-container {
            display: flex; padding-left: 0.5rem!important; padding-right: 0.5rem!important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px!important; width: 13rem;
        }
        #share-btn {
            all: initial; color: #ffffff;font-weight: 600; cursor:pointer; font-family: 'IBM Plex Sans', sans-serif; margin-left: 0.5rem!important; padding-top: 0.25rem!important; padding-bottom: 0.25rem!important;
        }
        #share-btn * {
            all: unset;
        }
       .gr-form{
            flex: 1 1 50%; border-top-right-radius: 0; border-bottom-right-radius: 0;
        }
        #prompt-container{
            gap: 0;
        }
        #share-btn-container div:nth-child(-n+2){
        width: auto!important;
        min-height: 0px!important;
        } 
"""

block = gr.Blocks(css=css)

examples = [
    [
        'The spirit of a tamagotchi wandering in the city of Paris',
#        4,
#        45,
#        7.5,
#        1024,
    ],
    [
        'A delicious ceviche cheesecake slice',
#        4,
#        45,
#        7,
#        1024,
    ],
    [
        'A pao de queijo foodcart in front of a japanese castle',
#        4,
#        45,
#        7,
#        1024,
    ],
    [
        'alone in the amusement park by Edward Hopper',
#        4,
#        45,
#        7,
#        1024,
    ],
    [
        "A large cabin on top of a sunny mountain in the style of Dreamworks, artstation",
#        4,
#        45,
#        7,
#        1024,
    ],
]


with block:
    gr.HTML(
        """
            <div style="text-align: center; max-width: 650px; margin: 0 auto; padding-top: 7px;">
              <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 v1-5 Demo
                </h1>
              </div>
              <p style="margin-bottom: 10px; font-size: 94%">
                Stable Diffusion v1-5 is the latest version of the state of the art text-to-image model.<br>For faster generation you can try
      <a href="https://app.runwayml.com/ai-tools/text-to-image"
        style="text-decoration: underline;" target="_blank">text to image tool at Runway.</a>
              </p>
            </div>
        """
    )
    with gr.Group():
        with gr.Box():
            with gr.Row(elem_id="prompt-container").style(mobile_collapse=False, equal_height=True):
                text = gr.Textbox(