app.py

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

repo = "artificialguybr/TshirtDesignRedmond-V2"

# Generate design based on prompts
def infer(color_prompt, phone_type_prompt, design_prompt):
    prompt = (
        f"A single vertical {color_prompt} colored {phone_type_prompt} back cover featuring a bold {design_prompt} design on the front, hanging on the plain wall. 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 = {}
    payload = {
        "inputs": full_prompt,
        "parameters": {
            "negative_prompt": "(worst quality, low quality, lowres, oversaturated, grayscale, bad photo:1.4)",
            "num_inference_steps": 30,
            "scheduler": "DPMSolverMultistepScheduler",
        },
    }

    error_count = 0
    pbar = tqdm(total=None, desc="Loading model")
    while True:
        response = requests.post(api_url, headers=headers, json=payload)
        if response.status_code == 200:
            speech_text = f"Your design is generated with the color '{color_prompt}', mobile type '{phone_type_prompt}', and design '{design_prompt}'."
            return Image.open(BytesIO(response.content)), speech_text
        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:
            raise Exception(f"API Error: {response.status_code}")

# Function to save the design
def save_design(image):
    file_path = "saved_design.png"
    image.save(file_path)
    return f"Design saved as {file_path}!"

# Custom CSS for animations
custom_css = """
body {
    font-family: -apple-system, BlinkMacSystemFont, "Segoe UI", Roboto, Helvetica, Arial, sans-serif;
    margin: 0;
    padding: 0;
    overflow: hidden;
}
body::before {
    content: "";
    position: fixed;
    top: 0;
    left: 0;
    width: 100%;
    height: 100%;
    background: linear-gradient(-45deg, #ff9a9e, #fad0c4, #fbc2eb, #8fd3f4);
    background-size: 400% 400%;
    z-index: -1;
    animation: gradientShift 15s ease infinite;
}
@keyframes gradientShift {
    0% { background-position: 0% 50%; }
    50% { background-position: 100% 50%; }
    100% { background-position: 0% 50%; }
}
.carousel {
    display: flex;
    overflow-x: auto;
    scroll-behavior: smooth;
}
.carousel .image-container {
    display: inline-block;
    text-align: center;
    margin: 0 10px;
}
.carousel img {
    max-height: 200px;
    border-radius: 10px;
    transition: transform 0.3s;
}
.carousel img:hover {
    transform: scale(1.1);
}
.carousel .caption {
    margin-top: 5px;
    font-size: 14px;
    color: #333;
}
"""

# JavaScript for text-to-speech
custom_js = """
<script>
document.addEventListener('DOMContentLoaded', function () {
    function speak(text) {
        const synth = window.speechSynthesis;
        const utterance = new SpeechSynthesisUtterance(text);
        synth.speak(utterance);
    }
    document.addEventListener('gradio_event:output_update', (event) => {
        const outputText = event.detail?.text || '';
        if (outputText) {
            speak(outputText);
        }
    });
});
</script>
"""

# Function to load images dynamically from "New folder (4)"
def load_gallery_images():
    folder_path = "New folder (4)"
    images_with_captions = []
    for filename in os.listdir(folder_path):
        if filename.lower().endswith(('.png', '.jpg', '.jpeg', '.webp')):
            img_path = os.path.join(folder_path, filename)
            caption = filename.rsplit('.', 1)[0]  # Use filename (without extension) as caption
            images_with_captions.append((img_path, caption))
    return images_with_captions

gallery_images = load_gallery_images()

# Gradio interface
with gr.Blocks(css=custom_css) as interface:
    gr.HTML(custom_js)
    gr.Markdown("# **AI Phone Cover Designer**")
    gr.Markdown("Create custom phone covers with AI. Save your designs for future use.")

    # Navigation Tabs
    with gr.Tabs():
        with gr.Tab("Home"):
            gr.Markdown("Welcome to the **AI Phone Cover Designer**! Use the 'Design' tab to start creating custom designs.")
            gr.Markdown("### Gallery")
            gallery_html = "<div class='carousel'>"
            for img_path, caption in gallery_images:
                gallery_html += f"<div class='image-container'><img src='{img_path}' alt='Design'><div class='caption'>{caption}</div></div>"
            gallery_html += "</div>"
            gr.HTML(gallery_html)

        with gr.Tab("Design"):
            with gr.Row():
                with gr.Column(scale=1):
                    color_prompt = gr.Textbox(label="Color", placeholder="E.g., Red")
                    phone_type_prompt = gr.Textbox(label="Mobile type", placeholder="E.g., iPhone, Samsung")
                    design_prompt = gr.Textbox(label="Design Details", placeholder="E.g., Bold stripes with geometric patterns")
                    chatbot = gr.Chatbot()
                    generate_button = gr.Button("Generate Design")
                    save_button = gr.Button("Save Design")
                with gr.Column(scale=1):
                    output_image = gr.Image(label="Generated Design")
                    output_message = gr.Textbox(label="AI Assistant Message", interactive=False)

            # Button Actions
            generate_button.click(
                infer,
                inputs=[color_prompt, phone_type_prompt, design_prompt],
                outputs=[output_image, output_message],
            )
            save_button.click(
                save_design,
                inputs=[output_image],
                outputs=output_message,
            )

        with gr.Tab("About"):
            gr.Markdown("""
            ## About AI Phone Cover Maker
            The **AI Phone Cover Maker** is a cutting-edge tool designed to help users create personalized phone cover designs quickly and easily. 
            Powered by AI, it uses advanced image generation techniques to craft unique, high-quality designs for any mobile device.
            
            ### Features:
            - Create custom designs using simple prompts.
            - Generate designs for various phone models.
            - Save your designs for future use.
            
            Start designing today and bring your creative ideas to life!
            """)

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