app.py

import gradio as gr
from processing import process_input
from visualization import update_visibility_and_charts

def create_interface():
    with gr.Blocks() as iface:
        gr.Markdown("# Personality Analysis Classification")
        gr.Markdown("Upload a Video, TXT, or PDF file.")
        
        with gr.Row():
            input_file = gr.File(label="Upload File (TXT, PDF, or Video)")
        
        with gr.Column():
            progress = gr.Progress()
            status_text = gr.Textbox(label="Status")
            execution_time = gr.Textbox(label="Execution Time", visible=False)
            detected_language = gr.Textbox(label="Detected Language", visible=False)
            
            # Create placeholders for charts and explanations
            charts_and_explanations = []
            for _ in range(6):  # 3 analysis types * 2 speakers
                with gr.Row():
                    charts_and_explanations.append(gr.Plot(visible=False))
                    charts_and_explanations.append(gr.Textbox(visible=False))

        def process_and_update(input_file):
            # Process the input
            results = process_input(input_file, progress=gr.Progress())
            
            # Create and update charts and explanations
            return update_visibility_and_charts(*results)

        input_file.upload(
            fn=process_and_update,
            inputs=[input_file],
            outputs=[status_text, execution_time, detected_language] + charts_and_explanations
        )

    return iface

iface = create_interface()

# Launch the app
if __name__ == "__main__":
    iface.launch()