import io import os import streamlit as st from dotenv import load_dotenv from PyPDF2 import PdfReader from langchain_community.embeddings import OpenAIEmbeddings from langchain_community.llms import OpenAI from langchain.prompts import PromptTemplate from langchain_community.vectorstores import FAISS import openai # Load environment variables load_dotenv() openai_api_key = os.getenv('OPENAI_API_KEY') # Initialize Streamlit session states if 'vectorDB' not in st.session_state: st.session_state.vectorDB = None # Function to extract text from a PDF file def get_pdf_text(pdf): text = "" pdf_reader = PdfReader(pdf) for page in pdf_reader.pages: text += page.extract_text() return text # Function to create a vector database def get_vectorstore(text_chunks): embeddings = OpenAIEmbeddings(api_key=openai_api_key) vectorstore = FAISS.from_texts(texts=text_chunks, embedding=embeddings) return vectorstore # Function to split text into chunks def get_text_chunks(text): text_chunks = text.split('\n\n') # Modify this based on your text splitting requirements return text_chunks # Function to process PDF and create vector database def processing(pdf): raw_text = get_pdf_text(pdf) text_chunks = get_text_chunks(raw_text) vectorDB = get_vectorstore(text_chunks) return vectorDB # Function to generate quiz questions, options, and correct answers def generate_quiz_content(text, num_questions): messages = [{'role': 'system', 'content': 'You are a helpful assistant.'}] for i in range(num_questions): user_message = {'role': 'user', 'content': f'Generate question {i + 1} from the given text:\n{text}'} messages.append(user_message) response = openai.ChatCompletion.create( model='gpt-3.5-turbo-16k', messages=messages, max_tokens=200, temperature=0.7 ) quiz_data = [] for choice in response.get('choices', []): content = choice.get('content', '').strip() options_start = content.find("Options:") + len("Options:") correct_answer_start = content.find("Correct Answer:") + len("Correct Answer:") question = content[:options_start].strip() options_str = content[options_start:correct_answer_start].strip() correct_answer = content[correct_answer_start:].strip() options = [opt.strip() for opt in options_str.split(',')] quiz_data.append((question, options, correct_answer)) return quiz_data # Function to retrieve quiz data from the vector database def retrieve_quiz_data(vectorDB, num_questions): # Replace this with your actual logic to query the vector database and retrieve quiz data return [(f"Question {i + 1}", [f"Option {j}" for j in range(1, 5)], f"Option {i % 4 + 1}") for i in range(num_questions)] # Function to generate quiz questions def generate_quiz(quiz_name, quiz_topic, num_questions, pdf_content): st.header(f"Quiz Generator: {quiz_name}") st.subheader(f"Topic: {quiz_topic}") # Process PDF and create vector database if st.button('Generate Quiz'): st.session_state['vectorDB'] = processing(pdf_content) st.success('PDF Processed and Vector Database Created') # Generate Quiz Questions if st.session_state.vectorDB: # Retrieve quiz data from the vector database generated_quiz_data = retrieve_quiz_data(st.session_state.vectorDB, num_questions) # Display retrieved questions, options, and correct answers for i, (question, options, correct_answer) in enumerate(generated_quiz_data): st.subheader(f"Question {i + 1}") st.write(f"Retrieved Question: {question}") st.write(f"Options: {', '.join(options)}") st.write(f"Correct Answer: {correct_answer}") # Save button to store vector database if st.session_state.vectorDB: if st.button('Save Vector Database'): st.success('Vector Database Saved') if __name__ =='__main__': st.set_page_config(page_title="CB Quiz Generator", page_icon="📝") st.title('CB Quiz Generator') # User inputs quiz_name = st.text_input('Enter Quiz Name:') quiz_topic = st.text_input('Enter Quiz Topic:') num_questions = st.number_input('Enter Number of Questions:', min_value=1, value=1, step=1) pdf_content = st.file_uploader("Upload PDF Content for Questions:", type='pdf') # Generate quiz if all inputs are provided if quiz_name and quiz_topic and num_questions and pdf_content: generate_quiz(quiz_name, quiz_topic, num_questions, pdf_content)