import streamlit as st
from utils import evaluate_resumes, generate_pdf_report, store_in_supabase, score_candidate, extract_email, parse_resume
from config import supabase
from config import HF_API_TOKEN, HF_HEADERS, HF_MODELS
import fitz  # PyMuPDF
from io import BytesIO
from dotenv import load_dotenv
import os
import requests

def main():
    st.set_page_config(page_title="TalentLens.AI", layout="centered")
    st.markdown(
        "<h1 style='text-align: center;'>TalentLens.AI</h1>", 
        unsafe_allow_html=True
    )
    st.divider()
    st.markdown(
        "<h3 style='text-align: center;'>AI-Powered Intelligent Resume Screening</h3>", 
        unsafe_allow_html=True
    )
    uploaded_files = st.file_uploader("Upload Resumes (PDF Only)", accept_multiple_files=True, type=["pdf"])
    job_description = st.text_area("Enter Job Description")
    
    if st.button("Evaluate Resumes"):
        shortlisted = evaluate_resumes(uploaded_files, job_description)
        for candidate in shortlisted:
            st.write(f"**{candidate['name']}** - Score: {candidate['score']}")
        
        # Generate PDF Report
        pdf_report = generate_pdf_report(shortlisted)
        st.download_button("Download Shortlist Report", pdf_report, "shortlist.pdf")

if __name__ == "__main__":
    main()