import gradio as gr import requests import io import random import os from PIL import Image API_URL = os.getenv("HF_MODEL_API_URL") API_TOKEN = os.getenv("HF_READ_TOKEN") headers = {"Authorization": f"Bearer {API_TOKEN}"} def query(prompt, is_negative=False, image_style="None style", steps=50, cfg_scale=7, seed=None): if image_style == "None style": payload = { "inputs": prompt + ", 8k", "is_negative": is_negative, "steps": steps, "cfg_scale": cfg_scale, "seed": seed if seed is not None else random.randint(-1, 2147483647) } elif image_style == "Cinematic": payload = { "inputs": prompt+", realistic, detailed, textured, skin, hair, eyes, by Alex Huguet, Mike Hill, Ian Spriggs, JaeCheol Park, Marek Denko", "is_negative": is_negative+", abstract, cartoon, stylized", "steps": steps, "cfg_scale": cfg_scale, "seed": seed if seed is not None else random.randint(-1, 2147483647) } elif image_style == "Digital Art": payload = { "inputs": prompt + ", faded , vintage , nostalgic , by Jose Villa , Elizabeth Messina , Ryan Brenizer , Jonas Peterson , Jasmine Star", "is_negative": is_negative + ", sharp , modern , bright", "steps": steps, "cfg_scale": cfg_scale, "seed": seed if seed is not None else random.randint(-1, 2147483647) } elif image_style == "Portrait": payload = { "inputs": prompt + ", soft light, sharp, exposure blend, medium shot, bokeh, (hdr:1.4), high contrast, (cinematic, teal and orange:0.85), (muted colors, dim colors, soothing tones:1.3), low saturation, (hyperdetailed:1.2), (noir:0.4), (natural skin texture, hyperrealism, soft light, sharp:1.2)", "is_negative": is_negative, "steps": steps, "cfg_scale": cfg_scale, "seed": seed if seed is not None else random.randint(-1, 2147483647) } # Вставьте ваш код для запроса к модели и получения изображения image_bytes = requests.post(API_URL, headers=headers, json=payload).content image = Image.open(io.BytesIO(image_bytes)) return image 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; } .gradio-container { max-width: 730px !important; 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%; } .animate-spin { animation: spin 1s linear infinite; } @keyframes spin { from { transform: rotate(0deg); } to { transform: rotate(360deg); } } #share-btn-container {padding-left: 0.5rem !important; padding-right: 0.5rem !important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px !important; max-width: 13rem; margin-left: auto;} div#share-btn-container > div {flex-direction: row;background: black;align-items: center} #share-btn-container:hover {background-color: #060606} #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: 0.5rem !important; padding-bottom: 0.5rem !important;right:0;} #share-btn * {all: unset} #share-btn-container div:nth-child(-n+2){width: auto !important;min-height: 0px !important;} #share-btn-container .wrap {display: none !important} #share-btn-container.hidden {display: none!important} .gr-form{ flex: 1 1 50%; border-top-right-radius: 0; border-bottom-right-radius: 0; } #prompt-container{ gap: 0; } #prompt-container .form{ border-top-right-radius: 0; border-bottom-right-radius: 0; } #gen-button{ border-top-left-radius:0; border-bottom-left-radius:0; } #prompt-text-input, #negative-prompt-text-input{padding: .45rem 0.625rem} #component-16{border-top-width: 1px!important;margin-top: 1em} .image_duplication{position: absolute; width: 100px; left: 50px} .tabitem{border: 0 !important} """ with gr.Blocks(css=css) as sdxl: gr.HTML( """

🎨 New Super-Fast SDXL

SDXL is a high quality text-to-image model from Stability AI. This demo is running on HuggingFace Inference API ⚡, to achieve efficient and cost-effective inference of 1024×1024 images. What model?

""" ) with gr.Row(elem_id="prompt-container"): text_prompt = gr.Textbox(label="Prompt", placeholder="a cute cat", lines=1, elem_id="prompt-text-input") text_button = gr.Button("Generate", variant='primary', elem_id="gen-button") with gr.Row(): image_output = gr.Image(type="pil", label="Output Image", elem_id="gallery") with gr.Accordion("Advanced settings", open=False): negative_prompt = gr.Textbox(label="Negative Prompt", value="text, blurry, fuzziness", lines=1, elem_id="negative-prompt-text-input") image_style = gr.Dropdown(label="Style", choices=["None style", "Cinematic", "Digital Art", "Portrait"], value="None style", allow_custom_value=False) text_button.click(query, inputs=[text_prompt, negative_prompt, image_style], outputs=image_output) sdxl.launch(show_api=False)