import PyPDF2
import nltk
import random
import streamlit as st
from openai import OpenAI
from dotenv import load_dotenv
import os
from openai import ChatCompletion

# Download NLTK data (if not already downloaded)
nltk.download('punkt')

# load the environment variables into the python script
load_dotenv() 
# fetching the openai_api_key environment variable
openai_api_key = os.getenv('OPENAI_API_KEY')

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, topic)
        mcqs.append(chatgpt_question)

    return mcqs

def generate_question_with_chatgpt(context, topic):
    # 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",
        "temperature": 0.7,
        "max_tokens": 1024,
        "messages": [
            {"role": "system", "content": "You are a helpful assistant."},
            {"role": "user", "content": f"What is the question on {topic} for the following? {context}"},
        ],
    }

    response = ChatCompletion.create(data)
    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()