app.py

import gradio as gr
import google.generativeai as genai

genai.configure(api_key="AIzaSyBPQF0g5EfEPzEiGRzA3iNzJZK4jDukMvE")

model = genai.GenerativeModel('gemini-pro')

def generate_summary_and_quiz(transcript, num_questions):
    """Generate a summary and quiz questions based on the video transcript."""
    prompt = f"""
    Based on the following video lecture transcript, please provide:
    1. A concise summary of the main points (about 100 words)
    2. {num_questions} multiple-choice quiz questions to test understanding of key concepts

    Transcript:
    {transcript}

    Format your response as follows:
    Summary:
    [Your summary here]

    Quiz Questions:
    1. [Question]
    a) [Option A]
    b) [Option B]
    c) [Option C]
    d) [Option D]
    Correct Answer: [Correct option letter]

    2. [Next question and options...]

    Ensure the questions cover different aspects of the lecture and vary in difficulty.
    """

    try:
        response = model.generate_content(prompt)
        return response.text
    except Exception as e:
        return f"Error generating summary and quiz: {str(e)}"

def process_lecture(transcript, num_questions):
    with gr.Row():
        gr.Markdown("Generating summary and quiz...")
    result = generate_summary_and_quiz(transcript, num_questions)
    return result

with gr.Blocks() as demo:
    gr.Markdown("# Video Lecture Summarizer and Quiz Generator")
    
    transcript_input = gr.Textbox(label="Video Lecture Transcript", lines=10, placeholder="Paste the video transcript or a detailed description of the lecture content here...")
    num_questions = gr.Slider(minimum=1, maximum=10, value=3, step=1, label="Number of Quiz Questions")
    
    generate_btn = gr.Button("Generate Summary and Quiz")
    output = gr.Textbox(label="Summary and Quiz", lines=20)
    
    generate_btn.click(process_lecture, inputs=[transcript_input, num_questions], outputs=output)

if __name__ == "__main__":
    demo.launch()