app(backup).py

import streamlit as st
import openai
import time

# Set your OpenAI API key from Hugging Face Secrets
openai.api_key = st.secrets["OPENAI_API_KEY"]

# Initialize OpenAI client
client = openai.OpenAI(api_key=openai.api_key)

# Function to generate exam questions using OpenAI API with retry logic
def generate_questions_with_retry(knowledge_material, question_type, cognitive_level, extra_instructions, case_based, num_choices=None, max_retries=3):
    # Adjust the number of questions based on the type
    if question_type == "Multiple Choice":
        num_questions = 3
    elif question_type == "Fill in the Blank":
        num_questions = 10
    elif question_type == "True/False":
        num_questions = 5  # Generate 5 true/false questions
    else:  # Open-ended
        num_questions = 3

    # Base prompt
    prompt = f"Generate {num_questions} {question_type.lower()} exam questions based on {cognitive_level.lower()} level from the following material: {knowledge_material}. {extra_instructions}"

    # If case-based medical situation is selected, modify the prompt
    if case_based:
        prompt = f"Generate {num_questions} {question_type.lower()} exam questions based on {cognitive_level.lower()} level from the following medical material: {knowledge_material}. The questions should be based on case-based medical situations, such as patient scenarios. {extra_instructions}"
        if question_type != "Fill in the Blank":
            prompt += " Provide answers with short explanations."

    # Add specific handling for Multiple Choice and True/False
    if question_type == "Multiple Choice" and num_choices:
        prompt += f" Each multiple choice question should have {num_choices} choices."

    if question_type == "True/False":
        prompt += " Provide short explanations for each question based on the given material, without stating True or False explicitly."

    retries = 0
    while retries < max_retries:
        try:
            response = client.chat.completions.create(
                model="gpt-4o-mini",
                messages=[
                    {"role": "system", "content": "You are a helpful assistant for generating exam questions."},
                    {"role": "user", "content": prompt}
                ]
            )
            return response.choices[0].message.content
        except openai.error.APIConnectionError:
            retries += 1
            time.sleep(2)  # Wait for 2 seconds before retrying
            if retries == max_retries:
                st.error("Failed to connect to OpenAI API after several attempts.")
                return None

# Login page
if 'username' not in st.session_state:
    # Show the login form if the username is not set
    st.title("Login")
    username_input = st.text_input("Enter your username:")
    if st.button("Login"):
        if username_input:
            st.session_state['username'] = username_input
            st.success(f"Welcome, {username_input}!")
        else:
            st.warning("Please enter a valid username.")
else:
    # Main App after login
    st.title(f"Welcome, {st.session_state['username']}! Generate your exam questions")

    # Input field for knowledge material (text) with 3,000-word limit
    knowledge_material = st.text_area("Enter knowledge material to generate exam questions:")
    
    # Word count check
    if len(knowledge_material.split()) > 3000:
        st.warning("Please limit the knowledge material to 3,000 words or fewer.")

    # File uploader for PDFs (limited to 5 MB)
    uploaded_file = st.file_uploader("Upload a file (PDF)", type="pdf")
    
    if uploaded_file is not None:
        if uploaded_file.size > 5 * 1024 * 1024:  # 5 MB limit
            st.warning("File size exceeds 5 MB. Please upload a smaller file.")
        else:
            # Here you can add code to extract text from the PDF if needed
            # For simplicity, we're focusing on the text input for now
            st.success("File uploaded successfully! (Text extraction not implemented yet.)")

    # Select question type
    question_type = st.selectbox("Select question type:", 
                                 ["Multiple Choice", "Fill in the Blank", "Open-ended", "True/False"])

    # For multiple choice, let users select the number of choices
    num_choices = None
    if question_type == "Multiple Choice":
        num_choices = st.selectbox("Select the number of choices for each question:", [3, 4, 5])

    # Select cognitive level
    cognitive_level = st.selectbox("Select cognitive level:", 
                                   ["Recall", "Understanding", "Application", "Analysis", "Synthesis", "Evaluation"])

    # Checkbox for Case-Based Medical Situations
    case_based = st.checkbox("Generate case-based medical exam questions")

    # Extra input field for additional instructions (placed below cognitive level)
    extra_instructions = st.text_area("Enter additional instructions (e.g., how you want the questions to be phrased):")

    # Generate questions button
    if 'previous_questions' not in st.session_state:
        st.session_state['previous_questions'] = []

    if st.button("Generate Questions"):
        if len(knowledge_material.split()) <= 3000:
            # Generate questions with retry logic
            questions = generate_questions_with_retry(
                knowledge_material, 
                question_type, 
                cognitive_level, 
                extra_instructions, 
                case_based, 
                num_choices
            )
            
            if questions:
                st.write("Generated Exam Questions:")
                st.write(questions)

                # Avoid showing repeated content in future requests
                st.session_state['previous_questions'].append(questions)

                # Option to download the questions as a text file
                st.download_button(
                    label="Download Questions",
                    data=questions,
                    file_name='generated_questions.txt',
                    mime='text/plain'
                )
        else:
            st.warning("Please reduce the word count to 3,000 or fewer.")

    # Button to generate more questions based on the same material
    if st.button("Generate More Questions"):
        if len(knowledge_material.split()) <= 3000:
            # Regenerate new questions, trying to avoid repeated content
            questions = generate_questions_with_retry(
                knowledge_material, 
                question_type, 
                cognitive_level, 
                extra_instructions, 
                case_based, 
                num_choices
            )

            # Check if the new set of questions is not the same as the previous set
            if questions and questions not in st.session_state['previous_questions']:
                st.write("Generated More Exam Questions:")
                st.write(questions)

                # Append the new questions to the session state
                st.session_state['previous_questions'].append(questions)

                # Option to download the new set of questions
                st.download_button(
                    label="Download More Questions",
                    data=questions,
                    file_name='more_generated_questions.txt',
                    mime='text/plain'
                )
            else:
                st.warning("New questions seem to overlap with the previous ones. Try adjusting the instructions.")
        else:
            st.warning("Please reduce the word count to 3,000 or fewer.")