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# TalentLens
import os
from io import BytesIO
import streamlit as st
import fitz # PyMuPDF
import requests
from dotenv import load_dotenv
from config import supabase, HF_API_TOKEN, HF_HEADERS, HF_MODELS
from utils.parser import parse_resume, extract_email, summarize_resume
from utils.hybrid_extractor import extract_resume_sections
from utils.builder import build_resume_from_data
from utils.screening import evaluate_resumes
from utils.reporting import generate_pdf_report, generate_interview_questions_from_summaries
# ------------------------- Main App Function -------------------------
def main():
st.set_page_config(
page_title="TalentLens.AI",
layout="centered",
initial_sidebar_state="collapsed"
)
# Hide sidebar completely with CSS
st.markdown("""
<style>
.css-1d391kg {display: none}
.css-1rs6os {display: none}
.css-17ziqus {display: none}
[data-testid="stSidebar"] {display: none}
[data-testid="collapsedControl"] {display: none}
.css-1lcbmhc {display: none}
.css-1outpf7 {display: none}
.sidebar .sidebar-content {display: none}
</style>
""", unsafe_allow_html=True)
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)
# Upload resumes (limit: 10 files)
uploaded_files = st.file_uploader(
"Upload Resumes (PDF Only, Max: 10)",
accept_multiple_files=True,
type=["pdf"]
)
if uploaded_files and len(uploaded_files) > 10:
st.error("⚠️ You can upload a maximum of 10 resumes at a time.")
return
# Input job description
job_description = st.text_area("Enter Job Description")
# Main action buttons
col1, col2 = st.columns(2)
with col1:
# Evaluation trigger
evaluate_clicked = st.button("📊 Evaluate Resumes", type="primary", use_container_width=True)
with col2:
# Format Resume redirect button
format_clicked = st.button("📄 Format Resume", use_container_width=True)
# Handle Format Resume redirect
if format_clicked:
st.switch_page("pages/Template.py")
# Handle Evaluate Resumes
if evaluate_clicked:
if not job_description:
st.error("⚠️ Please enter a job description.")
return
if not uploaded_files:
st.error("⚠️ Please upload at least one resume.")
return
st.write("### 📊 Evaluating Resumes...")
# Resume Evaluation
shortlisted, removed_candidates = evaluate_resumes(uploaded_files, job_description)
if not shortlisted:
st.warning("⚠️ No resumes matched the required keywords.")
else:
st.subheader("✅ Shortlisted Candidates:")
for candidate in shortlisted:
st.write(f"**{candidate['name']}**")
# Generate Interview Questions
questions = generate_interview_questions_from_summaries(shortlisted)
st.subheader("🧠 Suggested Interview Questions:")
for idx, q in enumerate(questions, 1):
st.markdown(f"{q}")
# Downloadable PDF Report
pdf_report = generate_pdf_report(shortlisted, questions)
st.download_button("Download Shortlist Report", pdf_report, "shortlist.pdf")
# Removed Candidates Info
if removed_candidates:
st.subheader("❌ Resumes Removed:")
for removed in removed_candidates:
st.write(f"**{removed['name']}** - {removed['reason']}")
# ------------------------- Run the App -------------------------
if __name__ == "__main__":
main() |