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 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( """

Stable Diffusion v1.5

Stable Diffusion v1-5 is the latest version of the state of the art text-to-image model.

""" ) with gr.Group(): with gr.Box(): with gr.Row(elem_id="prompt-container").style(mobile_collapse=False, equal_height=True): text = gr.Textbox( label="Enter your prompt", show_label=False, max_lines=1, placeholder="Enter your prompt", elem_id="prompt-text-input", ).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), full_width=False, ) gallery = gr.Gallery( label="Generated images", show_label=False, elem_id="gallery" ).style(grid=[2], height="auto") with gr.Group(elem_id="container-advanced-btns"): advanced_button = gr.Button("Advanced options", elem_id="advanced-btn") with gr.Group(elem_id="share-btn-container"): community_icon = gr.HTML(community_icon_html) loading_icon = gr.HTML(loading_icon_html) share_button = gr.Button("Share to community", elem_id="share-btn") with gr.Row(elem_id="advanced-options"): gr.Markdown("Advanced settings are temporarily unavailable") samples = gr.Slider(label="Images", minimum=1, maximum=4, value=4, step=1) steps = gr.Slider(label="Steps", minimum=1, maximum=50, value=45, step=1) scale = gr.Slider( label="Guidance Scale", minimum=0, maximum=50, value=7.5, step=0.1 ) seed = gr.Slider( label="Seed", minimum=0, maximum=2147483647, step=1, randomize=True, ) ex = gr.Examples(examples=examples, fn=infer, inputs=text, outputs=[gallery], cache_examples=True, postprocess=False) ex.dataset.headers = [""] text.submit(infer, inputs=text, outputs=[gallery], postprocess=False) btn.click(infer, inputs=text, outputs=[gallery], postprocess=False) advanced_button.click( None, [], text, _js=""" () => { const options = document.querySelector("body > gradio-app").querySelector("#advanced-options"); options.style.display = ["none", ""].includes(options.style.display) ? "flex" : "none"; }""", ) share_button.click( None, [], [], _js=share_js, ) gr.HTML( """
""" ) block.queue(concurrency_count=40, max_size=20).launch(max_threads=150)