import gradio as gr import requests import io import random import os from PIL import Image from huggingface_hub import InferenceApi, InferenceClient def get_params(request: gr.Request): params = request.query_params ip = request.client.host req = {"params": params, "ip": ip} client = InferenceClient() models = client.list_deployed_models() list_models = models["text-to-image"] return list_models client = InferenceClient() models = client.list_deployed_models() list_models = models["text-to-image"] ''' list_models = [ "SDXL-1.0", "SD-1.5", "OpenJourney-V4", "Anything-V4", "Disney-Pixar-Cartoon", "Pixel-Art-XL", "Dalle-3-XL", "Midjourney-V4-XL", ] ''' def generate_txt2img(current_model, prompt, is_negative=False, image_style="None style", steps=50, cfg_scale=7, seed=None): ''' if current_model == "SD-1.5": API_URL = "https://api-inference.huggingface.co/models/runwayml/stable-diffusion-v1-5" elif current_model == "SDXL-1.0": API_URL = "https://api-inference.huggingface.co/models/stabilityai/stable-diffusion-xl-base-1.0" elif current_model == "OpenJourney-V4": API_URL = "https://api-inference.huggingface.co/models/prompthero/openjourney" elif current_model == "Anything-V4": API_URL = "https://api-inference.huggingface.co/models/xyn-ai/anything-v4.0" elif current_model == "Disney-Pixar-Cartoon": API_URL = "https://api-inference.huggingface.co/models/stablediffusionapi/disney-pixar-cartoon" elif current_model == "Pixel-Art-XL": API_URL = "https://api-inference.huggingface.co/models/nerijs/pixel-art-xl" elif current_model == "Dalle-3-XL": API_URL = "https://api-inference.huggingface.co/models/openskyml/dalle-3-xl" elif current_model == "Midjourney-V4-XL": API_URL = "https://api-inference.huggingface.co/models/openskyml/midjourney-v4-xl" ''' API_TOKEN = os.environ.get("HF_READ_TOKEN") headers = {"Authorization": f"Bearer {API_TOKEN}"} api = InferenceApi(current_model) api.headers = headers 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) } #image_bytes = requests.post(API_URL, headers=headers, json=payload).content image = api(data = payload) return image ''' image = Image.open(io.BytesIO(image_bytes)) return image ''' css = """ /* General Container Styles */ .gradio-container { font-family: 'IBM Plex Sans', sans-serif; max-width: 730px !important; margin: auto; padding-top: 1.5rem; } /* Button Styles */ .gr-button { color: white; border-color: black; background: black; 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 Styles */ .footer, .dark .footer { margin-bottom: 45px; margin-top: 35px; text-align: center; border-bottom: 1px solid #e5e5e5; } .footer > p, .dark .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; } /* Share Button Styles */ #share-btn-container { padding: 0 0.5rem !important; background-color: #000000; justify-content: center; align-items: center; border-radius: 9999px !important; max-width: 13rem; margin-left: auto; } #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: 0.5rem !important; right: 0; } /* Animation Styles */ .animate-spin { animation: spin 1s linear infinite; } @keyframes spin { from { transform: rotate(0deg); } to { transform: rotate(360deg); } } /* Other Styles */ #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; } """ with gr.Blocks(css=css) as demo: favicon = '' gr.Markdown( f"""

🐦 {favicon} AII Diffusion

""" ) with gr.Row(elem_id="prompt-container"): btn_refresh = gr.Button(value="Refresh to get deployed models") btn_refresh.click(None, js="window.location.reload()") current_model = gr.Dropdown(label="Current Model", choices=list_models, value=list_models[0]) with gr.Row(elem_id="prompt-container"): text_prompt = gr.Textbox(label="Prompt", placeholder="a cute dog", value = "a lovely 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(generate_txt2img, inputs=[current_model, text_prompt, negative_prompt, image_style], outputs=image_output) demo.load(get_params, None, current_model) demo.launch(show_api=False)