app.py

import os
import json
import pandas as pd
import traceback
import streamlit as st
from utils import get_table_data
from mcqgen import generate_evaluate_chain
from transformers import GPT2LMHeadModel, GPT2Tokenizer

# Load the JSON file
with open('response.json', 'r', encoding="utf-8") as file:
    RESPONSE_JSON = json.load(file)

# Create a title
st.title("MCQ Creator Application with OpenAI's GPT-2")

# Create a form using st.form
with st.form("user_inputs"):
    uploaded_file = st.file_uploader("Upload a PDF file", type="pdf")
    mcq_count = st.number_input("No. of MCQ", min_value=3, max_value=50, value=5)
    tone = st.text_input("Complexity level of Questions", max_chars=20, value="simple")
    button = st.form_submit_button("Create MCQs")

    if button and uploaded_file is not None and mcq_count and tone:
        with st.spinner("Loading..."):
            try:
                text = uploaded_file.read().decode("utf-8")
                response = generate_evaluate_chain({
                    "text": text,
                    "number": mcq_count,
                    "tone": tone,
                    "response_json": json.dumps(RESPONSE_JSON)
                })
            except Exception as e:
                traceback.print_exception(type(e), e, e.__traceback__)
                st.error("Error")

            if isinstance(response, dict):
                # Extract quiz data from the response
                quiz = response.get("quiz", None)
                if quiz is not None:
                    table_data = get_table_data(quiz)
                    if table_data is not None:
                        df = pd.DataFrame(table_data)
                        df.index = df.index + 1
                        st.table(df)
                        # Display the review in a textbox as well
                        st.text_area(label="Review", value=response["review"])
                    else:
                        st.error("Error in the table data")
            else:
                st.write(response)