import gradio as gr
import sys
import os

# Add the dist directory to Python path
sys.path.insert(0, os.path.join(os.path.dirname(__file__), 'dist'))

# Import obfuscated module
try:
    from core_logic import *
except ImportError as e:
    print(f"Error: Obfuscated module not found: {e}")
    print("Current directory:", os.getcwd())
    print("Files in dist:", os.listdir('dist') if os.path.exists('dist') else 'dist not found')
    sys.exit(1)

# Initialize the processor
processor = DocumentProcessor()

def check_id(frame):
    return processor.check_id(frame)

def check_bank(frame):
    return processor.check_bank(frame)

def check_mrz(frame):
    return processor.check_mrz(frame)

def open_whatsapp():
    import webbrowser
    phone_number = "+19162702374"  # Replace with your actual phone number
    message = "Hello! I'm interested in your ID Document Recognition API service."
    whatsapp_url = f"https://wa.me/{phone_number}?text={message}"
    webbrowser.open(whatsapp_url)
    return "WhatsApp opened in your browser!"

# Company information
COMPANY_INFO = """
## About US
### MiniAiLive is a global leader in touchless biometric authentication and identity verification solutions. We deliver robust, cutting-edge technologies including facial recognition, liveness detection, palmprint and palm vein recognition, as well as ID document verification.
### Our solutions are designed for seamless integration with existing client systems, ensuring both enhanced security and operational efficiency.
"""

custom_css = """
.button-gradient {
  background: linear-gradient(45deg, #ff416c, #ff4b2b, #ff9b00, #ff416c);
  background-size: 400% 400%;
  border: none;
  padding: 14px 28px;
  font-size: 16px;
  font-weight: bold;
  color: white;
  border-radius: 10px;
  cursor: pointer;
  transition: 0.3s ease-in-out;
  animation: gradientAnimation 2s infinite linear;
  box-shadow: 0 4px 10px rgba(255, 65, 108, 0.6);
}
@keyframes gradientAnimation {
  0% { background-position: 0% 50%; }
  25% { background-position: 50% 100%; }
  50% { background-position: 100% 50%; }
  75% { background-position: 50% 0%; }
  100% { background-position: 0% 50%; }
}
.button-gradient:hover {
  transform: scale(1.05);
  box-shadow: 0 6px 15px rgba(255, 75, 43, 0.8);
}
"""

# APP Interface
with gr.Blocks(css=custom_css) as MiniAIdemo:
    gr.Markdown(
        """
        <a href="https://miniai.live" style="display: flex; align-items: center;">
            <img src="https://miniai.live/wp-content/uploads/2024/02/logo_name-1-768x426-1.png" style="width: 10%; margin-right: 15px;"/>
            <div>
                <p style="font-size: 50px; font-weight: bold; margin-right: 20px;">ID Document Recognition Playground</p>
            </div>
        </a>
        """
    )
    
    gr.Markdown(COMPANY_INFO)

    # Contact Us section
    with gr.Row():
        with gr.Column(scale=7):
            pass
        with gr.Column(scale=3):
            whatsapp_status = gr.Textbox(label="Status", visible=False)
            whatsapp_btn = gr.Button("� Contact Us on WhatsApp", elem_classes="button-gradient")
            whatsapp_btn.click(open_whatsapp, outputs=whatsapp_status)
    
    with gr.Tabs():
        with gr.Tab("ID Document Recognition"):
            with gr.Row():
                with gr.Column(scale=3):
                    im_id_in = gr.Image(type='filepath', height=300)
                    gr.Examples(
                        [
                            "images/id/demo1.jpg",
                            "images/id/demo2.png",
                            "images/id/demo3.png",
                        ],
                        inputs=im_id_in
                    )
                    btn_f_id = gr.Button("Check Document Details", elem_classes="button-gradient")
                with gr.Column(scale=5):
                    table_id_out = gr.HTML()
                with gr.Column(scale=2):
                    im_id_out = gr.HTML()

            btn_f_id.click(check_id, inputs=im_id_in, outputs=[table_id_out, im_id_out])
        
        with gr.Tab("Bank/Credit Recognition"):
            with gr.Row():
                with gr.Column(scale=3):
                    im_bank_in = gr.Image(type='filepath', height=300)
                    gr.Examples(
                        [
                            "images/bank/demo1.jpg",
                            "images/bank/demo2.png",
                            "images/bank/demo3.png",
                        ],
                        inputs=im_bank_in
                    )
                    btn_f_bank = gr.Button("Check Document Details", elem_classes="button-gradient")
                with gr.Column(scale=5):
                    table_bank_out = gr.HTML()
                with gr.Column(scale=2):
                    im_bank_out = gr.HTML()

            btn_f_bank.click(check_bank, inputs=im_bank_in, outputs=[table_bank_out, im_bank_out])
        
        with gr.Tab("MRZ/Barcode Recognition"):
            with gr.Row():
                with gr.Column(scale=3):
                    im_mrz_in = gr.Image(type='filepath', height=300)
                    gr.Examples(
                        [
                            "images/mrz_barcode/demo1.png",
                            "images/mrz_barcode/demo2.png",
                        ],
                        inputs=im_mrz_in
                    )
                    btn_f_mrz = gr.Button("Check Document Details", elem_classes="button-gradient")
                with gr.Column(scale=5):
                    table_mrz_out = gr.HTML()
                with gr.Column(scale=2):
                    im_mrz_out = gr.HTML()

            btn_f_mrz.click(check_mrz, inputs=im_mrz_in, outputs=[table_mrz_out, im_mrz_out])
    
    gr.HTML('<a href="https://visitorbadge.io/status?path=https%3A%2F%2Fhuggingface.co%2Fspaces%2FMiniAiLive%2FID-Document-Recognition-Demo"><img src="https://api.visitorbadge.io/api/combined?path=https%3A%2F%2Fhuggingface.co%2Fspaces%2FMiniAiLive%2FID-Document-Recognition-Demo&label=VISITORS&labelColor=%2337d67a&countColor=%23ff8a65&style=plastic&labelStyle=none" /></a>')

if __name__ == "__main__":
    MiniAIdemo.launch(
        show_api=False,
        server_name="0.0.0.0",
        server_port=7860
    )