app.py

import gradio as gr
import requests
import os
from PIL import Image
from io import BytesIO
from tqdm import tqdm
import time

repo = "artificialguybr/TshirtDesignRedmond-V2"

def infer(color_prompt, Phone_type_prompt, design_prompt):
    prompt = (
        f"A single {color_prompt} colored {Phone_type_prompt} back cover featuring a bold {design_prompt} design on the front. The soft light and shadows, creating a striking contrast against the minimal background, evoking modern sophistication.")
    full_prompt = f"{prompt}"

    print("Generating image with prompt:", full_prompt)
    api_url = f"https://api-inference.huggingface.co/models/{repo}"
    headers = {
        # "Authorization": f"Bearer {token}"  # Uncomment and use your Hugging Face API token
    }
    payload = {
        "inputs": full_prompt,
        "parameters": {
            "negative_prompt": "(worst quality, low quality, normal quality, lowres, low details, oversaturated, undersaturated, overexposed, underexposed, grayscale, bw, bad photo, bad photography, bad art:1.4), (watermark, signature, text font, username, error, logo, words, letters, digits, autograph, trademark, name:1.2), (blur, blurry, grainy), morbid, ugly, asymmetrical, mutated malformed, mutilated, poorly lit, bad shadow, draft, cropped, out of frame, cut off, censored, jpeg artifacts, out of focus, glitch, duplicate, (airbrushed, cartoon, anime, semi-realistic, cgi, render, blender, digital art, manga, amateur:1.3), (3D ,3D Game, 3D Game Scene, 3D Character:1.1), (bad hands, bad anatomy, bad body, bad face, bad teeth, bad arms, bad legs, deformities:1.3)",
            "num_inference_steps": 30,
            "scheduler": "DPMSolverMultistepScheduler"
        },
    }

    error_count = 0
    pbar = tqdm(total=None, desc="Loading model")
    while True:
        print("Sending request to API...")
        response = requests.post(api_url, headers=headers, json=payload)
        print("API response status code:", response.status_code)
        if response.status_code == 200:
            print("Image generation successful!")
            return Image.open(BytesIO(response.content))
        elif response.status_code == 503:
            time.sleep(1)
            pbar.update(1)
        elif response.status_code == 500 and error_count < 5:
            time.sleep(1)
            error_count += 1
        else:
            print("API Error:", response.status_code)
            raise Exception(f"API Error: {response.status_code}")

# Customized CSS and JS for Enhanced UI
custom_css = """
body {
    font-family: 'Poppins', sans-serif;
    background-color: #f8f9fa;
    margin: 0;
    padding: 0;
}

#component-1, #component-2, #component-3 {
    margin-bottom: 20px;
}

.gradio-container {
    width: 90%;
    max-width: 1200px;
    margin: auto;
    padding: 20px;
    box-shadow: 0 4px 6px rgba(0, 0, 0, 0.1);
    border-radius: 12px;
    background: white;
    position: relative;
}

button {
    font-size: 1.2rem;
    padding: 10px 20px;
    background-color: #007bff;
    border: none;
    color: white;
    border-radius: 5px;
    cursor: pointer;
    transition: 0.3s all;
    box-shadow: 0px 8px 15px rgba(0, 123, 255, 0.2);
}

button:hover {
    background-color: #0056b3;
    box-shadow: 0px 15px 20px rgba(0, 123, 255, 0.4);
    transform: translateY(-2px);
}

textarea {
    border: 2px solid #ccc;
    border-radius: 8px;
    padding: 10px;
    font-size: 1rem;
}

textarea:focus {
    border-color: #007bff;
}

.gr-input {
    padding: 10px;
    border: 2px solid #ccc;
    border-radius: 8px;
    transition: 0.3s;
}

.gr-input:focus {
    border-color: #007bff;
    outline: none;
}

.output-image {
    max-width: 100%;
    border-radius: 12px;
    border: 2px solid #007bff;
}

.flashy-btn {
    animation: flash 1.5s infinite;
}

@keyframes flash {
    0%, 100% {
        box-shadow: 0 0 10px #007bff, 0 0 40px #007bff, 0 0 80px #007bff;
    }
    50% {
        box-shadow: 0 0 20px #0056b3, 0 0 50px #0056b3, 0 0 100px #0056b3;
    }
}
"""

custom_js = """
<script>
document.addEventListener('DOMContentLoaded', function () {
    const button = document.querySelector('button');
    button.addEventListener('mouseenter', () => {
        button.classList.add('flashy-btn');
    });
    button.addEventListener('mouseleave', () => {
        button.classList.remove('flashy-btn');
    });
});
</script>
"""

# Create the Gradio interface
with gr.Blocks(css=custom_css) as interface:
    gr.HTML(custom_js)
    gr.Markdown(
        """
        # **AI Phone Cover Designer**
        Create custom designs for your brand with AI. Specify color, style, and design details.
        """
    )
    with gr.Row():
        with gr.Column():
            color_prompt = gr.Textbox(label="Color", placeholder="E.g., Red", elem_id="component-1")
            Back_cover_prompt = gr.Textbox(label="Mobile type", placeholder="E.g., iPhone, Samsung", elem_id="component-2")
            design_prompt = gr.Textbox(label="Design Details", placeholder="E.g., Bold stripes with geometric patterns", elem_id="component-3")
            generate_button = gr.Button("Generate Design")
        with gr.Column():
            output = gr.Image(label="Generated Design", elem_id="output-image")

    generate_button.click(infer, inputs=[color_prompt, Back_cover_prompt, design_prompt], outputs=output)

# Launch the app
interface.launch(debug=True)