app.py

import gradio as gr
import pytube
from youtube_transcript_api import YouTubeTranscriptApi as yt
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM, pipeline
import os
from langchain import PromptTemplate
from langchain import LLMChain
from langchain_together import Together
import re

# Set the API key with double quotes
os.environ['TOGETHER_API_KEY'] = "d88cb7414e4039a84d2ed63f1b47daaaa4230c4c53a422045d8a30a9a3bc87d8"

def Summary_BART(text):
    checkpoint = "sshleifer/distilbart-cnn-12-6"
    tokenizer = AutoTokenizer.from_pretrained(checkpoint)
    model = AutoModelForSeq2SeqLM.from_pretrained(checkpoint)
    inputs = tokenizer(text, max_length=1024, truncation=True, return_tensors="pt")
    summary_ids = model.generate(inputs["input_ids"])
    summary = tokenizer.batch_decode(summary_ids, skip_special_tokens=True, clean_up_tokenization_spaces=False)
    return summary[0]

def translate_text(text, target_language):
    translator = pipeline("translation", model=f"Helsinki-NLP/opus-mt-en-{target_language}")
    translated_text = translator(text, max_length=512)
    return translated_text[0]['translation_text']

def YtToQuizz(link, difficulty_level, language):
    video_id = pytube.extract.video_id(link)
    transcript = yt.get_transcript(video_id)
    data = " ".join([text['text'] for text in transcript])
    
    summary = Summary_BART(data)
    
    if language != "en":
        translated_data = translate_text(data, language)
        translated_summary = Summary_BART(translated_data)
    else:
        translated_summary = summary
    
    mcq_template = """
    Generate 10 different multiple-choice questions (MCQs) related to the following summary: {summary}
    The difficulty level of the questions should be: {difficulty_level}
    Please provide the following for each question:
    1. Question
    2. Correct answer
    3. Three plausible incorrect answer options
    4. Format: "Question: <question text>\\nCorrect answer: <correct answer>\\nIncorrect answers: <option1>, <option2>, <option3>"
    The language of the questions should be: {language}
    """ 
    prompt = PromptTemplate(
        input_variables=['summary', 'difficulty_level', 'language'],
        template=mcq_template
    )
    llama3 = Together(model="meta-llama/Llama-3-70b-chat-hf", max_tokens=2500)
    Generated_mcqs = LLMChain(llm=llama3, prompt=prompt)

    response_en = Generated_mcqs.invoke({
        "summary": summary,
        "difficulty_level": difficulty_level,
        "language": "English"
    })
    
    response_translated = Generated_mcqs.invoke({
        "summary": translated_summary,
        "difficulty_level": difficulty_level,
        "language": language
    })

    response_text_en = response_en['text']
    response_text_translated = response_translated['text']

    # Extract MCQs
    mcq_pattern = r'Question: (.*?)\nCorrect answer: (.*?)\nIncorrect answers: (.*?)(?:\n|$)'
    mcqs_en = re.findall(mcq_pattern, response_text_en, re.DOTALL)
    mcqs_translated = re.findall(mcq_pattern, response_text_translated, re.DOTALL)

    if len(mcqs_en) < 10 or len(mcqs_translated) < 10:
        return ["Failed to generate 10 complete MCQs. Please try again."] * 3, [""] * 3, [""] * 3, [""] * 3, [""] * 3, [""] * 3

    questions_en, correct_answers_en, options_en = [], [], []
    questions_translated, correct_answers_translated, options_translated = [], [], []

    for idx, mcq in enumerate(mcqs_en[:10]):
        question, correct_answer, incorrect_answers = mcq
        incorrect_answers = incorrect_answers.split(', ')
        questions_en.append(f"Q{idx+1}: {question}")
        correct_answers_en.append(f"Q{idx+1}: {correct_answer}")
        options_en.append(f"Q{idx+1}: A) {correct_answer}, B) {incorrect_answers[0]}, C) {incorrect_answers[1]}, D) {incorrect_answers[2]}")

    for idx, mcq in enumerate(mcqs_translated[:10]):
        question, correct_answer, incorrect_answers = mcq
        incorrect_answers = incorrect_answers.split(', ')
        questions_translated.append(f"Q{idx+1}: {question}")
        correct_answers_translated.append(f"Q{idx+1}: {correct_answer}")
        options_translated.append(f"Q{idx+1}: A) {correct_answer}, B) {incorrect_answers[0]}, C) {incorrect_answers[1]}, D) {incorrect_answers[2]}")

    return questions_en, correct_answers_en, options_en, questions_translated, correct_answers_translated, options_translated

def main(link, difficulty_level, language):
    return YtToQuizz(link, difficulty_level, language)

iface = gr.Interface(
    fn=main,
    inputs=[
        gr.components.Textbox(lines=2, placeholder="Enter YouTube video link"),
        gr.components.Dropdown(["Easy", "Medium", "Hard"], label="Select difficulty level:"),
        gr.components.Dropdown(
            ["en", "fr", "es", "de", "it", "pt", "nl", "ru", "zh", "ja", "ko"], 
            label="Select language:"
        )
    ],
    outputs=[
        gr.components.Textbox(label="MCQs Statements (English)", lines=20),
        gr.components.Textbox(label="Correct Answers (English)", lines=10),
        gr.components.Textbox(label="Options (English)", lines=30),
        gr.components.Textbox(label="MCQs Statements (Translated)", lines=20),
        gr.components.Textbox(label="Correct Answers (Translated)", lines=10),
        gr.components.Textbox(label="Options (Translated)", lines=30)
    ],
    title="YouTube Video Subtitle to MCQs Quiz",
    description="Generate MCQs from YouTube video subtitles"
)

if __name__ == '__main__':
    iface.launch()