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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()
import gradio as gr
import google.generativeai as genai
import re
# Initialize Gemini API (replace with your actual API key)
# genai.configure(api_key="YOUR_API_KEY_HERE")
# Initialize the model
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)
# Extracting summary and questions
summary_match = re.search(r'Summary:(.*?)Quiz Questions:', result, re.DOTALL)
summary = summary_match.group(1).strip() if summary_match else "Summary not found."
questions_match = re.findall(r'(\d+\.\s.*?)(?=\d+\.|$)', result.split('Quiz Questions:')[1], re.DOTALL)
questions = [q.strip() for q in questions_match]
return summary, questions
def create_quiz_interface(questions):
quiz_elements = []
for i, question in enumerate(questions):
q_parts = question.split('\n')
q_text = q_parts[0].split('.', 1)[1].strip()
options = [opt.strip() for opt in q_parts[1:5]]
quiz_elements.extend([
gr.Markdown(f"**Question {i+1}:** {q_text}"),
gr.Radio(options, label=f"Options for Question {i+1}")
])
return quiz_elements
def check_answers(questions, *user_answers):
correct_answers = []
user_results = []
for question, user_answer in zip(questions, user_answers):
correct_answer = re.search(r'Correct Answer: (\w)', question).group(1)
correct_answers.append(correct_answer)
options = [opt.strip() for opt in question.split('\n')[1:5]]
user_choice = chr(ord('a') + options.index(user_answer)) if user_answer in options else 'No answer'
is_correct = user_choice == correct_answer
user_results.append(f"Your answer: {user_choice}, Correct answer: {correct_answer}, {'Correct!' if is_correct else 'Incorrect'}")
return "\n".join(user_results)
# Create the Gradio interface
with gr.Blocks() as demo:
gr.Markdown("# Interactive Video Lecture Assistant")
with gr.Tab("Generate Summary and Quiz"):
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")
summary_output = gr.Textbox(label="Summary", lines=5)
quiz_output = gr.Textbox(label="Quiz Questions", lines=15, visible=False)
with gr.Tab("Take Quiz"):
quiz_interface = gr.Column()
submit_quiz_btn = gr.Button("Submit Quiz")
quiz_results = gr.Textbox(label="Quiz Results", lines=5)
def update_quiz_interface(questions):
quiz_interface.clear()
elements = create_quiz_interface(questions)
for element in elements:
quiz_interface.append(element)
return {quiz_interface: gr.update(visible=True)}
generate_btn.click(
process_lecture,
inputs=[transcript_input, num_questions],
outputs=[summary_output, quiz_output]
).then(
update_quiz_interface,
inputs=[quiz_output],
outputs=[quiz_interface]
)
submit_quiz_btn.click(
check_answers,
inputs=[quiz_output] + [child for child in quiz_interface.children if isinstance(child, gr.components.Radio)],
outputs=[quiz_results]
)
if __name__ == "__main__":
demo.launch() |