app.py

import streamlit as st
from transformers import pipeline
import openai

from transformers import pipeline

messages = [
    {"role": "user", "content": "Who are you?"},
]
generator = pipeline("text-generation", model="meta-llama/Meta-Llama-3-8B-Instruct")


# Function to generate MCQs using open-source LLM
def generate_mcq(text, num_questions):
    questions = []
    for _ in range(num_questions):
        # Use max_new_tokens to avoid length issues
        question = generator(text, max_new_tokens=50, num_return_sequences=1)[0]['generated_text']
        questions.append(question)
    return questions

# Function to generate MCQs using OpenAI API with gpt-3.5-turbo
def generate_mcq_openai(text, num_questions):
    openai.api_key = "sk-proj-uHasdgbriPPlFMm99ZtJT3BlbkFJOl231YfdxCSNmQjVEpMX"
    messages = [
        {"role": "system", "content": "You are a helpful assistant that generates multiple-choice questions."},
        {"role": "user", "content": f"Generate {num_questions} multiple choice questions based on the following text:\n\n{text}"}
    ]
    response = openai.ChatCompletion.create(
        model="gpt-3.5-turbo",
        messages=messages,
        max_tokens=450,  # Adjust to a reasonable value
        n=1,
        stop=None,
        temperature=0.7,
    )
    questions = response.choices[0].message["content"].strip().split("\n\n")
    return questions

# Streamlit app
st.title("MCQ Question Generator")
text = st.text_area("Enter the text for generating MCQs:", "")
num_questions = st.selectbox("Select number of questions:", [5, 10, 15])
model_type = st.radio("Select the model to generate questions:", ("Open-Source LLM", "OpenAI API"))

if st.button("Generate MCQs"):
    if text:
        if model_type == "Open-Source LLM":
            mcq_questions = generate_mcq(text, num_questions)
        else:
            mcq_questions = generate_mcq_openai(text, num_questions)

        for i, question in enumerate(mcq_questions):
            st.markdown(f"**Q{i+1}:** {question.split('?')[0]}?")
            options = question.split('?')[1].strip().split('\n')
            for option in options:
                st.write(option)