import streamlit as st

# ✅ Set page config (must be the first Streamlit command)
st.set_page_config(page_title="AI-Powered Coding Question Generator", layout="centered")

import os
import subprocess
import sqlite3
import random
from fpdf import FPDF
from transformers import pipeline

# ✅ Force install missing dependencies
missing_packages = ["transformers", "torch", "sentence-transformers", "fpdf"]
for package in missing_packages:
    try:
        __import__(package)
    except ImportError:
        subprocess.call(["pip", "install", package])

# ✅ Create database
def create_database():
    conn = sqlite3.connect("questions.db")
    cursor = conn.cursor()
    cursor.execute("""
        CREATE TABLE IF NOT EXISTS questions (
            id INTEGER PRIMARY KEY AUTOINCREMENT,
            subject TEXT,
            topic TEXT,
            question TEXT
        )
    """)
    conn.commit()
    conn.close()

# ✅ Insert question into database
def insert_question(subject, topic, question):
    conn = sqlite3.connect("questions.db")
    cursor = conn.cursor()
    cursor.execute("INSERT INTO questions (subject, topic, question) VALUES (?, ?, ?)", (subject, topic, question))
    conn.commit()
    conn.close()

# ✅ Retrieve stored questions
def get_questions(subject, topic, num):
    conn = sqlite3.connect("questions.db")
    cursor = conn.cursor()
    cursor.execute("SELECT question FROM questions WHERE subject = ? AND topic = ? ORDER BY RANDOM() LIMIT ?", (subject, topic, num))
    questions = [q[0] for q in cursor.fetchall()]
    conn.close()
    return questions

# ✅ Load AI Model for Question Generation
@st.cache_resource
def load_model():
    try:
        model = pipeline("text-generation", model="microsoft/CodeGPT-small-py")
        return model
    except Exception as e:
        st.error(f"❌ Error loading AI Model: {e}")
        return None

model = load_model()

# ✅ Generate AI Questions
def generate_ai_questions(subject, topic, num):
    if not model:
        return ["❌ AI Model not loaded. Try restarting the app."]
    
    try:
        prompt = f"Generate {num} coding-related questions specifically about {topic} in {subject}. Ensure the questions are clear and relevant to programming."
        generated = model(prompt, max_length=100, num_return_sequences=num)
        return [q["generated_text"].strip() for q in generated]
    except Exception as e:
        return [f"❌ Error generating questions: {e}"]

# ✅ Generate PDF
def generate_pdf(subject, topic, questions):
    pdf = FPDF()
    pdf.set_auto_page_break(auto=True, margin=15)
    pdf.add_page()
    pdf.set_font("Arial", style='B', size=16)
    pdf.cell(200, 10, f"{subject} - {topic} Questions", ln=True, align='C')
    pdf.ln(10)
    pdf.set_font("Arial", size=12)
    
    for i, question in enumerate(questions, 1):
        pdf.multi_cell(0, 10, f"{i}. {question}")
        pdf.ln(5)
    
    pdf.output("generated_questions.pdf")
    return "generated_questions.pdf"

# ✅ Main Application
def main():
    st.title("💻 AI-Based Coding Question Generator")
    
    st.sidebar.header("📌 Settings")
    subject = st.sidebar.selectbox("Select Subject", ["DSA", "Python", "Java", "DBMS"])
    topic = st.sidebar.text_input("Enter a topic (e.g., 'Recursion', 'SQL Joins')")
    num = st.sidebar.slider("Number of Questions:", 1, 5, 2)
    
    if st.sidebar.button("🔍 Generate Questions"):
        if topic.strip():
            questions = get_questions(subject, topic, num)
            if not questions:
                questions = generate_ai_questions(subject, topic, num)
                for q in questions:
                    insert_question(subject, topic, q)
            
            st.subheader(f"📌 {subject} - {topic} Questions")
            for i, q in enumerate(questions, 1):
                st.write(f"{i}. {q}")
            
            if st.button("📥 Download as PDF"):
                pdf_path = generate_pdf(subject, topic, questions)
                with open(pdf_path, "rb") as f:
                    st.download_button("📥 Download PDF", f, file_name="questions.pdf", mime="application/pdf")
        else:
            st.warning("⚠️ Please enter a valid topic!")

if __name__ == "__main__":
    create_database()
    main()