app.py

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

def create_interface():
    example_video_path = "examples/Scenes.From.A.Marriage.US.mp4"
    
    with gr.Blocks() as iface:
        gr.Markdown("# Personality Analysis Classification")
        gr.Markdown("Upload a Video, TXT, or PDF file or use the example video.")
    
        with gr.Row():
            with gr.Column(scale=3):
                input_file = gr.File(label="Upload File (TXT, PDF, or Video)")
            
            with gr.Column(scale=1):
                example_video = gr.Video(value=example_video_path, label="Example Video Preview")
                example_button = gr.Button("Use Example 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)
            
            # Add a Textbox for the SRT transcription
            transcription_text = gr.Textbox(label="Transcription", visible=False, lines=10)
            
            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.Plot(visible=False))
                    charts_and_explanations.append(gr.Textbox(visible=False))

        def process_and_update(input_file):
            if input_file is None:
                return [gr.update(value="No file selected")] + [gr.update(visible=False)] * 21  # +1 for transcription
            
            results = process_input(input_file, progress=gr.Progress())
            
            if len(results) != 10:
                return [gr.update(value="Error: Unexpected number of results")] + [gr.update(visible=False)] * 21
            
            # Extract transcription from results (assuming it's the last item)
            transcription = results[-1]
            
            # Remove token information and transcription from results
            results = results[:3] + results[3:6] + [transcription]
            
            visibility_updates = update_visibility_and_charts(*results[:6])
            
            # Add update for transcription text
            transcription_update = gr.update(value=transcription, visible=True)
            
            return visibility_updates + [transcription_update]

        def use_example_video():
            return example_video_path

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

        example_button.click(
            fn=use_example_video,
            inputs=[],
            outputs=input_file
        ).then(
            fn=process_and_update,
            inputs=[input_file],
            outputs=[status_text, execution_time, detected_language] + charts_and_explanations + [transcription_text]
        )

    return iface

iface = create_interface()

if __name__ == "__main__":
    iface.launch(share=True)