app.py

import os
import streamlit as st
from dotenv import load_dotenv
from docx import Document
import fitz  # PyMuPDF
import google.generativeai as genai


def extract_text_from_pdf(file):
    """Extract text from PDF."""
    text = ""
    doc = fitz.open(stream=file.read(), filetype="pdf")
    for page in doc:
        text += page.get_text()
    return text

def create_multiple_choice_prompt(num_questions, quiz_context, expertise):
    """Create the prompt template for multiple-choice quiz."""
    template = f"""
You are an expert in {expertise}. Generate a quiz with {num_questions} multiple-choice questions that are relevant to {expertise} based on the following content: {quiz_context}.
The questions should be at the level of {expertise} and should challenge the knowledge of someone proficient in this field.
also add a blooms taxonomy skills with each question that is which question is generated on which blooms taxonomy.
The format of the quiz is as follows:
- Multiple-choice:
- Questions:
    1. <Question1>:
        a. Answer 1
        b. Answer 2
        c. Answer 3
        d. Answer 4
    2. <Question2>:
        a. Answer 1
        b. Answer 2
        c. Answer 3
        d. Answer 4
    ....
- Answers:
    1. <a|b|c|d>
    2. <a|b|c|d>
    ....
Example:
- Questions:
    1. What is the time complexity of a binary search tree?
        a. O(n)
        b. O(log n)
        c. O(n^2)
        d. O(1)
- Answers:
    1. b
"""
    return template

def create_true_false_prompt(num_questions, quiz_context, expertise):
    """Create the prompt template for true-false quiz."""
    template = f"""
You are an expert in {expertise}. Generate a quiz with {num_questions} true-false questions that are relevant to {expertise} based on the following content: {quiz_context}.
The questions should be at the level of {expertise} and should challenge the knowledge of someone proficient in this field.
also add a blooms taxonomy skills with each question that is which question is generated on which blooms taxonomy.
The format of the quiz is as follows:
- True-false:
- Questions:
    1. <Question1>: <True|False>
    2. <Question2>: <True|False>
    .....
- Answers:
    1. <True|False>
    2. <True|False>
    .....
Example:
- Questions:
    1. A binary search tree is a type of data structure.
    2. Binary search trees are typically used for sorting and searching operations.
- Answers:
    1. True
    2. True
"""
    return template

def create_open_ended_prompt(num_questions, quiz_context, expertise):
    """Create the prompt template for open-ended quiz."""
    template = f"""
You are an expert in {expertise}. Generate a quiz with {num_questions} open-ended questions that are relevant to {expertise} based on the following content: {quiz_context}.
The questions should be at the level of {expertise} and should challenge the knowledge of someone proficient in this field.
For each question, also specify the Bloom's Taxonomy level it corresponds to, choosing from the following levels:
1. Remember
2. Understand
3. Apply
4. Analyze
5. Evaluate
6. Create

The format of the quiz is as follows:
- Open-ended:
- Questions:
    1. <Question1>
    2. <Question2>
    ....
Example:
- Questions:
    1. What is a binary search tree?
    2. How are binary search trees implemented?
"""
    return template

def create_fill_in_the_blank_prompt(num_questions, quiz_context, expertise):
    """Create the prompt template for fill-in-the-blank quiz."""
    template = f"""
You are an expert in {expertise}. Generate a quiz with {num_questions} fill-in-the-blank questions that are relevant to {expertise} based on the following content: {quiz_context}.
The questions should be at the level of {expertise} and should challenge the knowledge of someone proficient in this field.
also add a blooms taxonomy skills with each question that is which question is generated on which blooms taxonomy.
The format of the quiz is as follows:
- Fill-in-the-blank:
- Questions:
    1. <Question1>: <Fill-in-the-blank>
    2. <Question2>: <Fill-in-the-blank>
    ....
Example:
- Questions:
    1. A binary search tree is a ________ data structure.
    2. Binary search trees are implemented using ________.
- Answers:
    1. hierarchical
    2. linked lists
"""
    return template

def create_mixed_questions_prompt(num_questions, quiz_context, expertise):
    """Create the prompt template for a mix of all question types."""
    template = f"""
You are an expert in {expertise}. Generate a quiz with exactly {num_questions} questions that include a random mix of multiple-choice, true-false, open-ended, and fill-in-the-blank questions relevant to {expertise} based on the following content: {quiz_context}.
The questions should be at the level of {expertise} and should challenge the knowledge of someone proficient in this field. Ensure that the questions are randomly mixed among the different types.
also add a blooms taxonomy skills with each question that is which question is generated on which blooms taxonomy.
The format of the quiz is as follows:
- Mixed Questions:
- Questions:
    1. <Question1> (Question type):
        <Answers if applicable>
    2. <Question2> (Question type):
        <Answers if applicable>
    3. <Question3> (Question type):
        <Answers if applicable>
    ...
    {num_questions}. <Question{num_questions}> (Question type):
        <Answers if applicable>
Example:
- Questions:
    1. What is the time complexity of a binary search tree? (Multiple-choice)
        a. O(n)
        b. O(log n)
        c. O(n^2)
        d. O(1)
    2. A binary search tree is a type of data structure. (True/False)
    3. What is a binary search tree? (Open-ended)
    4. A binary search tree is a ________ data structure. (Fill-in-the-blank)
    5. Another sample question. (Multiple-choice)
        a. Sample 1
        b. Sample 2
        c. Sample 3
        d. Sample 4
- Answers:
    1. b
    2. True
    3. A binary search tree is a data structure used to store data in a sorted manner.
    4. hierarchical
    5. b
Note:Ensure there are exactly {num_questions} questions in total with a random mix of question types.Here only template is given if there are more than mentioned example questions generate questions by your own.
"""
    return template


def get_gemini_response(question, prompt):
    """Function to load Google Gemini model and provide queries as response."""
    model = genai.GenerativeModel('gemini-1.5-flash')
    response = model.generate_content([prompt, question])
    return response.text

def split_questions_answers(quiz_response):
    """Function that splits the questions and answers from the quiz response."""
    if "Answers:" in quiz_response:
        questions = quiz_response.split("Answers:")[0]
        answers = quiz_response.split("Answers:")[1]
    else:
        questions = quiz_response
        answers = "Answers section not found in the response."
    return questions, answers

def main():
    st.title("Question Generation Application")
    st.write("This app generates questions based on the uploaded document.")
    load_dotenv()
    genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))
    
    uploaded_file = st.file_uploader("Upload a PDF document", type=["pdf"])
    if uploaded_file is not None:
        text = extract_text_from_pdf(uploaded_file)
        num_questions = st.number_input("Enter the number of questions", min_value=1, max_value=10, value=3)
        quiz_type = st.selectbox("Select the type of Question", ["multiple-choice", "true-false", "open-ended", "fill-in-the-blank", "mixed"])
        expertise = st.text_input("Enter the domain of the questions to be generated.")

        if st.button("Generate Questions"):
            if quiz_type == "multiple-choice":
                prompt_template = create_multiple_choice_prompt(num_questions, text, expertise)
            elif quiz_type == "true-false":
                prompt_template = create_true_false_prompt(num_questions, text, expertise)
            elif quiz_type == "open-ended":
                prompt_template = create_open_ended_prompt(num_questions, text, expertise)
            elif quiz_type == "fill-in-the-blank":
                prompt_template = create_fill_in_the_blank_prompt(num_questions, text, expertise)
            else:  # mixed
                prompt_template = create_mixed_questions_prompt(num_questions, text, expertise)

            quiz_response = get_gemini_response(text, prompt_template)
            questions, answers = split_questions_answers(quiz_response)
            st.session_state.answers = answers
            st.session_state.questions = questions
            st.write(questions)
    
    if st.button("Show Answers"):
        st.markdown(st.session_state.questions)
        st.write("----")
        st.markdown(st.session_state.answers)

if __name__ == "__main__":
    main()