app.py

import gradio as gr
import requests
import io
import random
import os
from PIL import 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}"}


    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 = Image.open(io.BytesIO(image_bytes))
    return image

import gradio as gr

css = """
/* General Container Styles */
.gradio-container {
    font-family: 'IBM Plex Sans', sans-serif;
    max-width: 800px !important;
    margin: auto;
    padding-top: 2rem;
}

/* Button Styles */
.gradio-button-primary {
    color: #fff;
    background-color: #2563eb;
    border-color: #1d4ed8;
}

.gradio-button-primary:hover {
    background-color: #1d4ed8;
    border-color: #1d4ed8;
}

/* Input Styles */
.gradio-textbox {
    border-color: #a0aec0;
    padding: 9px 12px;
}

.gradio-textbox:focus {
    border-color: #2563eb;
    box-shadow: 0 0 0 2px rgba(37,99,235,.25);
}

/* Output Image Styles */
.gradio-output img {
    max-width: 100%;
    height: auto;
    border-radius: 6px;
    box-shadow: 0 4px 6px -1px rgba(0, 0, 0, 0.1), 0 2px 4px -1px rgba(0, 0, 0, 0.06);
}
"""

def generate_txt2img(current_model, text_prompt, negative_prompt, image_style):
    # Your generation code here
    pass

favicon = '<img src="" width="48px" style="display: inline">'
title = f"""<h1><center>{favicon} AI Diffusion</center></h1>"""
markdown_title = gr.Markdown(title)

current_model = gr.inputs.Dropdown(label="Current Model", choices=list_models, value=list_models[1])
text_prompt = gr.inputs.Textbox(label="Prompt", placeholder="Enter a prompt", lines=1)
negative_prompt = gr.inputs.Textbox(label="Negative Prompt", value="text, blurry, fuzziness", lines=1)
image_style = gr.inputs.Dropdown(label="Style", choices=["None style", "Cinematic", "Digital Art", "Portrait"], value="None style")

generate_button = gr.outputs.Button(label="Generate", type="button")
image_output = gr.outputs.Image(label="Output Image")

with gr.Blocks(css=css) as demo:
    gr.Grid(col_width="auto", col_gap="10px").push(
        markdown_title,
        current_model,
        text_prompt,
        negative_prompt,
        image_style,
        generate_button,
        image_output
    )

    generate_button.click(generate_txt2img, inputs=[current_model, text_prompt, negative_prompt, image_style], outputs=image_output)

demo.launch(show_api=False)