app.py

import gradio as gr
import whisper
import os
import re
import yt_dlp
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline

# Load models
whisper_model = whisper.load_model("base")
multilingual_model = "csebuetnlp/mT5_multilingual_XLSum"
tokenizer = AutoTokenizer.from_pretrained(multilingual_model)
summarizer_model = AutoModelForSeq2SeqLM.from_pretrained(multilingual_model)
translator = pipeline("translation", model="Helsinki-NLP/opus-mt-mul-en")

SUPPORTED_LANGUAGES = {
    "bn": "Bengali", "en": "English", "gu": "Gujarati", "hi": "Hindi",
    "kn": "Kannada", "ml": "Malayalam", "mr": "Marathi", "ta": "Tamil",
    "te": "Telugu", "ur": "Urdu"
}

def download_audio(youtube_url):
    ydl_opts = {
        'format': 'bestaudio/best',
        'outtmpl': 'audio.%(ext)s',
        'postprocessors': [{
            'key': 'FFmpegExtractAudio',
            'preferredcodec': 'mp3',
        }],
        'cookiefile': 'cookies.txt'  # <— Uses your uploaded cookie file
    }

    with yt_dlp.YoutubeDL(ydl_opts) as ydl:
        info_dict = ydl.extract_info(youtube_url, download=True)
        filename = ydl.prepare_filename(info_dict).replace(".webm", ".mp3").replace(".m4a", ".mp3")
    return filename

def extract_thumbnail(youtube_url):
    match = re.search(r"(?:v=|\/)([0-9A-Za-z_-]{11})", youtube_url)
    if match:
        video_id = match.group(1)
        return f"https://img.youtube.com/vi/{video_id}/0.jpg"
    return ""

def summarize_text(text):
    input_text = f"summarize: {text}"
    inputs = tokenizer.encode(input_text, return_tensors="pt", max_length=512, truncation=True)
    summary_ids = summarizer_model.generate(inputs, max_length=150, min_length=30, num_beams=4)
    return tokenizer.decode(summary_ids[0], skip_special_tokens=True)

def transcribe_and_summarize(youtube_url, translate_to_english):
    try:
        audio_file = download_audio(youtube_url)
        result = whisper_model.transcribe(audio_file)
        transcript = result["text"]
        lang_code = result["language"]

        thumbnail_url = extract_thumbnail(youtube_url)

        if lang_code not in SUPPORTED_LANGUAGES:
            return None, f"❌ Language '{lang_code}' not supported.", "", "", None

        summary = summarize_text(transcript)

        if translate_to_english and lang_code != "en":
            translated_summary = translator(summary)[0]["translation_text"]
        else:
            translated_summary = summary

        os.remove(audio_file)

        summary_text = f"Transcript:\n{transcript}\n\nSummary:\n{translated_summary}"

        with open("summary.txt", "w", encoding="utf-8") as f:
            f.write(summary_text)

        return thumbnail_url, f"🗣️ Language: {SUPPORTED_LANGUAGES[lang_code]}", transcript, translated_summary, "summary.txt"

    except Exception as e:
        return None, f"❌ Error: {str(e)}", "", "", None

with gr.Blocks(css="style.css") as demo:
    gr.Markdown("<h1 style='text-align: center;'>🎬 Multilingual YouTube Summarizer</h1>")
    gr.Markdown("Paste any YouTube video link, and get transcript + summary. Works for Hindi, Bengali, Tamil, Urdu, and more!")

    with gr.Row():
        youtube_url = gr.Textbox(label="YouTube Video URL")
        translate_check = gr.Checkbox(label="Translate Summary to English", value=True)

    thumbnail = gr.Image(label="Video Thumbnail", type="filepath")
    lang_out = gr.Text(label="Detected Language")
    transcript_out = gr.Textbox(label="Transcript", lines=8)
    summary_out = gr.Textbox(label="Summary", lines=6)
    download_btn = gr.File(label="Download .txt")

    btn = gr.Button("Generate Summary")

    btn.click(fn=transcribe_and_summarize,
              inputs=[youtube_url, translate_check],
              outputs=[thumbnail, lang_out, transcript_out, summary_out, download_btn])

demo.launch()