app.py

import gradio as gr
import moviepy.editor as mp
import librosa
from transformers import pipeline
from concurrent.futures import ThreadPoolExecutor
import tempfile
import docx  # To create Word documents
from moviepy.video.tools.subtitles import SubtitlesClip
from moviepy.editor import TextClip
import os

# Load Whisper model for speech-to-text (using smaller 'tiny' model for faster performance)
asr = pipeline("automatic-speech-recognition", model="openai/whisper-tiny")  # Use 'whisper-tiny' for faster transcription

# MarianMT or M2M100 for translation (multi-language)
translator = pipeline("translation", model="facebook/m2m100_418M")

# Store generated subtitles and translations
subtitle_storage = {}

# Supported languages with their codes
languages = {
    "Persian": "fa",
    "French": "fr",
    "Spanish": "es",
    "German": "de",
    "Chinese": "zh",
    "Arabic": "ar",
    "Hindi": "hi",
    "Russian": "ru"
}

def transcribe_audio(chunk):
    """Transcribe a single audio chunk."""
    return asr(chunk)["text"]

def add_subtitle(video):
    try:
        # The video is passed as a file path string, so we use it directly
        video_path = video if isinstance(video, str) else None
        if not video_path:
            return "No video provided!"
        
        video = mp.VideoFileClip(video_path)
        audio = video.audio

        # Use a temporary file for audio extraction
        with tempfile.NamedTemporaryFile(delete=True, suffix='.wav') as tmp_audio_file:
            audio.write_audiofile(tmp_audio_file.name, codec='pcm_s16le')
            waveform, sr = librosa.load(tmp_audio_file.name, sr=16000)

            # Transcribe in chunks (parallel)
            chunk_duration = 15  # seconds
            chunk_size = sr * chunk_duration
            chunks = [waveform[i:i + chunk_size] for i in range(0, len(waveform), chunk_size) if len(waveform[i:i + chunk_size]) > 0]

            with ThreadPoolExecutor() as executor:
                transcriptions = list(executor.map(transcribe_audio, chunks))

            full_transcription = " ".join(transcriptions)
            subtitle_storage["original"] = full_transcription  # Store the original subtitle
            subtitle_storage["video_path"] = video_path  # Store the video path
            
        return f"Subtitle added: {full_transcription[:100]}..."  # Display first 100 characters

    except Exception as e:
        return f"Error in adding subtitle: {e}"

def translate_subtitle(video, language):
    try:
        # Translate the stored subtitle
        original_subtitle = subtitle_storage.get("original")
        if not original_subtitle:
            return "No subtitle to translate!"
        
        # Translate using the selected language
        translated_subtitle = translator(
            original_subtitle, 
            src_lang="en",  # Source language (assuming the subtitle is in English)
            tgt_lang=languages[language]  # Get the language code from the dropdown selection
        )[0]["translation_text"]

        subtitle_storage["translated"] = translated_subtitle  # Store the translated subtitle
        
        return f"Subtitle translated to {language} successfully!"
    
    except Exception as e:
        return f"Error in translating subtitle: {e}"

def download_word():
    try:
        # Save translated subtitles to a Word document
        translated_subtitle = subtitle_storage.get("translated")
        if not translated_subtitle:
            return "No translated subtitle to save!"
        
        doc = docx.Document()
        doc.add_heading('Translated Subtitles', 0)
        doc.add_paragraph(translated_subtitle)
        
        file_path = "translated_subtitles.docx"
        doc.save(file_path)

        return f"Translated subtitles saved as Word document: {file_path}"
    
    except Exception as e:
        return f"Error in saving subtitles as Word: {e}"

def download_video():
    try:
        # Add subtitles to the video
        original_subtitle = subtitle_storage.get("original")
        translated_subtitle = subtitle_storage.get("translated")

        if not original_subtitle or not translated_subtitle:
            return "No subtitles to overlay on video!"

        video_path = subtitle_storage.get("video_path")
        video = mp.VideoFileClip(video_path)

        # Function to generate subtitle text
        generator = lambda txt: TextClip(txt, font='Arial', fontsize=24, color='white')

        # Simulated subtitle time intervals for simplicity (assumes 5 seconds per subtitle)
        subs = [(i * 5, translated_subtitle[i:i+50]) for i in range(0, len(translated_subtitle), 50)]

        # Create subtitle clips
        subtitles = SubtitlesClip(subs, generator)

        # Overlay subtitles on video
        subtitled_video = mp.CompositeVideoClip([video, subtitles.set_position(('center', 'bottom'))])

        output_video_path = "subtitled_video.mp4"
        subtitled_video.write_videofile(output_video_path)

        return f"Subtitled video is ready for download: {output_video_path}"
    
    except Exception as e:
        return f"Error in generating subtitled video: {e}"

# Gradio UI Interface
with gr.Blocks() as demo:
    # Title
    gr.Markdown("<h1 style='text-align: center;'>Video Subtitle Translator</h1>")
    
    # Video Upload
    with gr.Row():
        video_input = gr.Video(label="Upload Video")
        upload_button = gr.Button("Upload Video")
        upload_status = gr.Textbox(label="Upload Status")
    
    upload_button.click(add_subtitle, inputs=video_input, outputs=upload_status)
    
    # Add Subtitle
    with gr.Row():
        add_subtitle_button = gr.Button("Add Subtitle")
        subtitle_status = gr.Textbox(label="Subtitle Status")
    
    add_subtitle_button.click(add_subtitle, inputs=video_input, outputs=subtitle_status)
    
    # Translate Subtitle
    with gr.Row():
        language_dropdown = gr.Dropdown(choices=list(languages.keys()), label="Choose Target Language", value="Persian")
        translate_button = gr.Button("Translate Subtitle")
        translate_status = gr.Textbox(label="Translation Status")
    
    translate_button.click(translate_subtitle, inputs=[video_input, language_dropdown], outputs=translate_status)
    
    # Download as Word
    with gr.Row():
        download_button = gr.Button("Download as Word")
        download_status = gr.Textbox(label="Download Status")
    
    download_button.click(download_word, inputs=None, outputs=download_status)
    
    # Download Subtitled Video
    with gr.Row():
        download_video_button = gr.Button("Download Subtitled Video")
        download_video_status = gr.Textbox(label="Download Video Status")
    
    download_video_button.click(download_video, inputs=None, outputs=download_video_status)

# Launch the Gradio app
demo.launch()