app.py

import gradio as gr
from utils.file_utils import validate_and_process_file, convert_mp4_to_mp3
from utils.transcription_utils import transcribe_audio
import tempfile
from tqdm import tqdm

# Application header
title = "ScribbleBot by Heuristica.pl"
description = "Audio transcription application - convert speech to text. Enter your API key and upload your audio file (.mp3, .wav, .mp4). Bot will transcribe your audio content into text format!"

def process_input(api_key, file_path, progress=gr.Progress(track_tqdm=True)):
    logs = []
    
    if not file_path:
        return "Please select a file for transcription.", None, False, ""

    logs.append("Processing file...")
    progress(0, desc="Starting file processing...")

    try:
        # Check if file is MP4
        if isinstance(file_path, str) and file_path.lower().endswith(".mp4"):
            logs.append("Converting MP4 to MP3...")
            progress(0.2, desc="Converting MP4 to MP3...")
            try:
                file_path = convert_mp4_to_mp3(file_path)
                logs.append(f"File converted to: {file_path}")
            except Exception as e:
                logs.append(f"Conversion error: {str(e)}")
                return "\n".join(logs), None, False, ""

        processed_files = validate_and_process_file(file_path)
        transcriptions = []
        
        # Calculate total steps for progress bar
        total_steps = len(processed_files)
        progress(0.3, desc="Starting transcription...")
        
        for i, file in enumerate(processed_files):
            # Calculate progress from 30% to 90%
            current_progress = 0.3 + (0.6 * (i / total_steps))
            progress(current_progress, desc=f"Transcribing part {i + 1}/{total_steps}...")
            
            logs.append(f"Transcribing part {i + 1}/{total_steps}...")
            transcription = transcribe_audio(api_key, file)
            transcriptions.append(transcription)
            logs.append(f"Part {i + 1} transcription completed.")

        progress(0.9, desc="Finalizing...")
        
        # Połącz wszystkie transkrypcje
        full_transcription = "\n\n".join(transcriptions)
        
        # Save transcription to temporary file
        with tempfile.NamedTemporaryFile(delete=False, mode="w", suffix=".txt", encoding="utf-8") as f:
            f.write(full_transcription)
            temp_file_path = f.name

        progress(1.0, desc="Completed!")
        logs.append("Transcription completed. Ready for download.")
        return "\n".join(logs), temp_file_path, True, full_transcription
            
    except Exception as e:
        error_msg = str(e)
        logs.append(f"An error occurred: {error_msg}")
        return "\n".join(logs), None, False, ""

# User interface
with gr.Blocks() as demo:
    gr.Markdown(f"# {title}")
    gr.Markdown(description)

    with gr.Row():
        api_key = gr.Textbox(label="Enter OpenAI API Key", placeholder="sk-...")

    with gr.Row():
        file_input = gr.File(
            label="Upload audio file", 
            file_types=[".mp3", ".wav", ".mp4"]
        )
        upload_progress = gr.Textbox(
            label="Upload Status",
            value="No file selected",
            interactive=False
        )

    with gr.Row():
        submit_button = gr.Button("Start Transcription")
        stop_button = gr.Button("Stop", variant="stop")

    with gr.Row():
        logs = gr.Textbox(label="Process", interactive=False, lines=10)

    with gr.Row():
        download_link = gr.File(label="Download Transcription", visible=False)
        
    with gr.Row():
        transcription_preview = gr.Textbox(
            label="Transcription Preview", 
            interactive=False, 
            lines=15,
            placeholder="Transcription will appear here..."
        )

    # Add visibility management component
    download_visibility = gr.Checkbox(value=False, visible=False)

    # Update upload status when file is selected
    def update_upload_status(file):
        if file is None:
            return "No file selected"
        else:
            return f"File uploaded: {file.name}"
            
    file_input.change(
        fn=update_upload_status,
        inputs=[file_input],
        outputs=[upload_progress]
    )

    submit_button.click(
        process_input,
        inputs=[api_key, file_input],
        outputs=[logs, download_link, download_visibility, transcription_preview]
    )

    # Set download_link visibility based on download_visibility value
    download_visibility.change(
        lambda visible: gr.File(visible=visible),
        inputs=download_visibility,
        outputs=download_link
    )

# Launch application
if __name__ == "__main__":
    demo.launch(share=True)