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import PyPDF2
import nltk
from nltk.tokenize import sent_tokenize
import random
import requests
import streamlit as st
from langchain_openai import OpenAI, OpenAIEmbeddings
from langchain.prompts import PromptTemplate
from langchain.chains import LLMChain
# Download NLTK data (if not already downloaded)
nltk.download('punkt')
nltk.download('averaged_perceptron_tagger')
# ChatGPT API endpoint
CHATGPT_API_ENDPOINT = "https://api.openai.com/v1/chat/completions"
OPENAI_API_KEY = "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"
def extract_text_from_pdf(pdf_file):
pdf_reader = PyPDF2.PdfReader(pdf_file)
text = ""
for page_num in range(len(pdf_reader.pages)):
text += pdf_reader.pages[page_num].extract_text()
return text
def generate_mcqs_on_topic(text, topic, num_mcqs=5):
# Tokenize the text into sentences
sentences = nltk.sent_tokenize(text)
# Randomly select sentences to create Questions
selected_sentences = random.sample(sentences, min(num_mcqs, len(sentences)))
mcqs = []
for sentence in selected_sentences:
# Use ChatGPT for interactive question generation
chatgpt_question = generate_question_with_chatgpt(sentence)
mcqs.append(chatgpt_question)
return mcqs
def generate_question_with_chatgpt(context):
llm = OpenAI(temperature=0.4)
headers = {
"Content-Type": "application/json",
"Authorization": f"Bearer {OPENAI_API_KEY}",
}
# Initializing the default value
generated_question = {
'content': "Unable to generate a question..",
'options': [], # assuming options is a list
'correct_answer': "Unknown"
}
data = {
"model": "gpt-3.5-turbo",
"messages": [
{"role": "system", "content": "You are a helpful assistant."},
{"role": "user", "content": f"What is the question for the following? {context}"},
],
}
response = requests.post(CHATGPT_API_ENDPOINT, json=data, headers=headers)
result = response.json()
print("API Response:", result) # Add this line for debugging
if 'choices' in result:
# Extract the generated question, options, and correct answer from the response
generated_question = {
'content': result["choices"][0]["message"]["content"],
'options': result["choices"][0]["message"].get("options", []),
'correct_answer': result["choices"][0]["message"].get("correct_answer", "Unknown")
}
else:
print("Unexpected API response format.")
return generated_question
def main():
# Title of the Application
st.header("🤖CB Quiz Generator🧠", divider='rainbow')
st.subheader("☕CoffeeBeans☕")
# User input
pdf_file = st.file_uploader("Upload PDF Document:", type=["pdf"])
num_mcqs = st.number_input("Enter Number of MCQs to Generate:", min_value=1, step=1, value=5)
topic = st.text_input("Enter the Topic in which the quiz has to be generated")
# Button to trigger QUIZ generation
if st.button("Generate Quiz"):
if pdf_file:
text = extract_text_from_pdf(pdf_file)
mcqs = generate_mcqs_on_topic(text, topic, num_mcqs)
# Display the generated Questions
st.success(f"Generated {num_mcqs} Questions:")
for i, generated_question in enumerate(mcqs, start=1):
st.write(f"\nQuestion {i}: {generated_question['content']}")
st.write(f"Options: {', '.join(generated_question['options'])}")
st.write(f"Correct Answer: {generated_question['correct_answer']}")
else:
st.error("Please upload a PDF document.")
if __name__ == "__main__":
main()
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