app.py

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 = '<img src="" width="48px" style="display: inline">'
    gr.Markdown(
        f"""<h1><center>🐦 {favicon} AII Diffusion</center></h1>
            """
    )
    
    with gr.Row(elem_id="prompt-container"):
        with gr.Column():
            btn_refresh = gr.Button(value="Click Refresh to get current 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)

    with gr.Row():
        gr.Examples(
            [
            "Chinese ink painting",
            "silk road",
            "masterpiece, best quality, 1girl, solo, crop top, denim shorts, choker, (graffiti:1.5), paint splatter, arms behind back, against wall, looking at viewer, armband, thigh strap, paint on body, head tilt, bored, multicolored hair, aqua eyes, headset,",
            "beautiful home",
            "interior design of living room",
            "1girl, aqua eyes, baseball cap, blonde hair, closed mouth, earrings, green background, hat, hoop earrings, jewelry, looking at viewer, shirt, short hair, simple background, solo, upper body, yellow shirt",
            ],
            inputs = text_prompt,
            label = "Prompt Examples"
        )
    
    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)