app(backup2).py

import streamlit as st
import openai
from openai import OpenAI
import time
import gspread
from oauth2client.service_account import ServiceAccountCredentials
import PyPDF2
import io

# Set up OpenAI client
client = OpenAI(api_key=st.secrets["OPENAI_API_KEY"])

# Constants
WORD_LIMIT = 8000

# Google Sheets setup remains the same
scope = ["https://spreadsheets.google.com/feeds", "https://www.googleapis.com/auth/drive"]
creds = ServiceAccountCredentials.from_json_keyfile_name("genexam-2c8c645ecc0d.json", scope)
client_gs = gspread.authorize(creds)
sheet = client_gs.open("GeneXam user").sheet1

def check_user_in_sheet(username):
    try:
        users_list = sheet.col_values(1)
        if username in users_list:
            return True
        return False
    except Exception as e:
        st.error(f"Error checking user: {str(e)}")
        return False

def update_api_usage(username):
    try:
        users_list = sheet.col_values(1)
        row_number = users_list.index(username) + 1
        api_usage = int(sheet.cell(row_number, 2).value)
        api_usage += 1
        sheet.update_cell(row_number, 2, api_usage)
    except Exception as e:
        st.error(f"Error updating API usage: {str(e)}")

def extract_text_from_pdf(pdf_file):
    """Simple PDF text extraction with word limit check"""
    try:
        pdf_reader = PyPDF2.PdfReader(io.BytesIO(pdf_file.read()))
        text_content = ""
        for page in pdf_reader.pages:
            text_content += page.extract_text() + "\n"
        
        word_count = len(text_content.split())
        if word_count > WORD_LIMIT:
            return None, f"PDF content exceeds {WORD_LIMIT:,} words (contains {word_count:,} words). Please use a shorter document."
        return text_content, None
    except Exception as e:
        return None, f"Error processing PDF: {str(e)}"

def generate_questions_with_retry(knowledge_material, question_type, cognitive_level, extra_instructions, case_based, num_choices=None, max_retries=3):
    # Adjust number of questions based on type
    if question_type == "Multiple Choice":
        num_questions = 3
        format_instructions = f"""
        For each multiple choice question:
        1. Present the question clearly
        2. Provide {num_choices} choices labeled with A, B, C{', D' if num_choices > 3 else ''}{', E' if num_choices > 4 else ''} after get new line from question
        3. After all questions, provide an ANSWER KEY section with:
           - The correct answer letter for each question
           - A brief explanation of why this is the correct answer
           - Why other options are incorrect
        """
    elif question_type == "Fill in the Blank":
        num_questions = 10
        format_instructions = """
        For each fill-in-the-blank question:
        1. Present the question with a clear blank space indicated by _____
        2. After all questions, provide an ANSWER KEY section with:
           - The correct answer for each blank
           - A brief explanation of why this answer is correct
           - Any alternative acceptable answers if applicable
        """
    elif question_type == "True/False":
        num_questions = 5
        format_instructions = """
        For each true/false question:
        1. Present the statement clearly
        2. After all questions, provide an ANSWER KEY section with:
           - Whether the statement is True or False
           - A detailed explanation of why the statement is true or false
           - The specific part of the source material that supports this answer
        """
    else:  # Open-ended
        num_questions = 3
        format_instructions = """
        For each open-ended question:
        1. Present the question clearly
        2. After all questions, provide an ANSWER KEY section with:
           - A structured scoring checklist of key points (minimum 3-5 points per question)
           - Each key point should be worth a specific number of marks
           - Total marks available for each question
           - Sample answer that would receive full marks
           - Common points that students might miss
        """

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

{knowledge_material}

{format_instructions}

{extra_instructions}

Please format the output clearly with:
1. Questions section (numbered 1, 2, 3, etc.)
2. Answer Key section (clearly separated from questions)
3. Each answer should include explanation for better understanding

Make sure all questions and answers are directly related to the provided material."""

    # Modify prompt for case-based medical situations
    if case_based:
        prompt = f"""Generate {num_questions} {question_type.lower()} case-based medical exam questions based on {cognitive_level.lower()} level.

Use this material as the medical knowledge base:
{knowledge_material}

Each question should:
1. Start with a medical case scenario/patient presentation
2. Include relevant clinical details
3. Ask about diagnosis, treatment, or management
4. Be at {cognitive_level.lower()} cognitive level

{format_instructions}

{extra_instructions}

Please format the output with:
1. Cases and Questions (numbered 1, 2, 3, etc.)
2. Detailed Answer Key section including:
   - Correct answers
   - Clinical reasoning
   - Key diagnostic or treatment considerations
   - Common pitfalls to avoid"""

    retries = 0
    while retries < max_retries:
        try:
            response = client.chat.completions.create(
                model="gpt-4o-mini",
                messages=[
                    {"role": "system", "content": "You are an expert exam question generator with deep knowledge in medical education. Create clear, well-structured questions with detailed answer keys and explanations."},
                    {"role": "user", "content": prompt}
                ],
                temperature=0.7,
                max_tokens=3000  # Increased to accommodate answers and explanations
            )
            return response.choices[0].message.content
        except Exception as e:
            retries += 1
            st.warning(f"Attempt {retries} failed. Retrying... Error: {str(e)}")
            if retries == max_retries:
                st.error(f"Failed to generate questions after {max_retries} attempts. Error: {str(e)}")
                return None
            time.sleep(2)

# ระบบ login
# Main Streamlit interface
if 'username' not in st.session_state:
    st.title("Login")
    username_input = st.text_input("Enter your username:")
    if st.button("Login"):
        if username_input:
            if check_user_in_sheet(username_input):
                st.session_state['username'] = username_input
                st.success(f"Welcome, {username_input}!")
                update_api_usage(username_input)
            else:
                st.warning("Username not found. Please try again.")
        else:
            st.warning("Please enter a valid username.")
else:
    st.title(f"Welcome, {st.session_state['username']}! Generate your exam questions")
    
    # Create tabs for input methods
    tab1, tab2 = st.tabs(["Text Input", "PDF Upload"])
    
    with tab1:
        knowledge_material = st.text_area("Enter knowledge material to generate exam questions:")
        word_count = len(knowledge_material.split())
        if word_count > WORD_LIMIT:
            st.error(f"Text exceeds {WORD_LIMIT:,} words. Please shorten your content.")
    
    with tab2:
        st.info(f"Maximum content length: {WORD_LIMIT:,} words")
        uploaded_file = st.file_uploader("Upload a PDF file", type="pdf")
        
        if uploaded_file is not None:
            pdf_content, error = extract_text_from_pdf(uploaded_file)
            if error:
                st.error(error)
            else:
                st.success("PDF processed successfully!")
                knowledge_material = pdf_content

    # Question generation options
    col1, col2 = st.columns(2)
    
    with col1:
        question_type = st.selectbox(
            "Select question type:",
            ["Multiple Choice", "Fill in the Blank", "Open-ended", "True/False"]
        )
        
        if question_type == "Multiple Choice":
            num_choices = st.selectbox("Select number of choices:", [3, 4, 5])
        
        cognitive_level = st.selectbox(
            "Select cognitive level:",
            ["Recall", "Understanding", "Application", "Analysis", "Synthesis", "Evaluation"]
        )
    
    with col2:
        case_based = st.checkbox("Generate case-based medical exam questions")
        extra_instructions = st.text_area("Additional instructions (optional):")

    # Generate questions button
    if st.button("Generate Questions"):
        if 'knowledge_material' in locals() and knowledge_material.strip():
            with st.spinner("Generating questions..."):
                # Your existing generate_questions_with_retry function call here
                questions = generate_questions_with_retry(
                    knowledge_material,
                    question_type,
                    cognitive_level,
                    extra_instructions,
                    case_based,
                    num_choices if question_type == "Multiple Choice" else None
                )
                
                if questions:
                    st.write("### Generated Exam Questions:")
                    st.write(questions)
                    
                    # Download button
                    st.download_button(
                        label="Download Questions",
                        data=questions,
                        file_name='generated_questions.txt',
                        mime='text/plain'
                    )
        else:
            st.warning("Please enter knowledge material or upload a PDF file first.")